MIT Open Access Articles

Transcriptome-wide mapping reveals a diverse dihydrouridine landscape including mRNA

Tue, 24 May 2022 00:00:00 GMT

Transcriptome-wide mapping reveals a diverse dihydrouridine landscape including mRNA Draycott, Austin S; Schaening-Burgos, Cassandra; Rojas-Duran, Maria F; Wilson, Loren; Schärfen, Leonard; Neugebauer, Karla M; Nachtergaele, Sigrid; Gilbert, Wendy V Dihydrouridine is a modified nucleotide universally present in tRNAs, but the complete dihydrouridine landscape is unknown in any organism. We introduce dihydrouridine sequencing (D-seq) for transcriptome-wide mapping of D with single-nucleotide resolution and use it to uncover novel classes of dihydrouridine-containing RNA in yeast which include mRNA and small nucleolar RNA (snoRNA). The novel D sites are concentrated in conserved stem-loop regions consistent with a role for D in folding many functional RNA structures. We demonstrate dihydrouridine synthase (DUS)-dependent changes in splicing of a D-containing pre-mRNA in cells and show that D-modified mRNAs can be efficiently translated by eukaryotic ribosomes in vitro. This work establishes D as a new functional component of the mRNA epitranscriptome and paves the way for identifying the RNA targets of multiple DUS enzymes that are dysregulated in human disease.

SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort

Thu, 10 Feb 2022 00:00:00 GMT

SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort Finch, Emilie; Lowe, Rachel; Fischinger, Stephanie; de St Aubin, Michael; Siddiqui, Sameed M; Dayal, Diana; Loesche, Michael A; Rhee, Justin; Beger, Samuel; Hu, Yiyuan; Gluck, Matthew J; Mormann, Benjamin; Hasdianda, Mohammad A; Musk, Elon R; Alter, Galit; Menon, Anil S; Nilles, Eric J; Kucharski, Adam J Identifying the potential for SARS-CoV-2 reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders and the choice of baseline time point, and show how to account for both in reinfection analysis.

Persona2vec: a flexible multi-role representations learning framework for graphs

Tue, 30 Mar 2021 00:00:00 GMT

Persona2vec: a flexible multi-role representations learning framework for graphs Yoon, Jisung; Yang, Kai-Cheng; Jung, Woo-Sung; Ahn, Yong-Yeol Graph embedding techniques, which learn low-dimensional representations of a graph, are achieving state-of-the-art performance in many graph mining tasks. Most existing embedding algorithms assign a single vector to each node, implicitly assuming that a single representation is enough to capture all characteristics of the node. However, across many domains, it is common to observe pervasively overlapping community structure, where most nodes belong to multiple communities, playing different roles depending on the contexts. Here, we propose persona2vec, a graph embedding framework that efficiently learns multiple representations of nodes based on their structural contexts. Using link prediction-based evaluation, we show that our framework is significantly faster than the existing state-of-the-art model while achieving better performance.

Chemically induced reprogramming to reverse cellular aging

Wed, 12 Jul 2023 00:00:00 GMT

Chemically induced reprogramming to reverse cellular aging Yang, Jae-Hyun; Petty, Christopher A; Dixon-McDougall, Thomas; Lopez, Maria Vina; Tyshkovskiy, Alexander; Maybury-Lewis, Sun; Tian, Xiao; Ibrahim, Nabilah; Chen, Zhili; Griffin, Patrick T; Arnold, Matthew; Li, Jien; Martinez, Oswaldo A; Behn, Alexander; Rogers-Hammond, Ryan; Angeli, Suzanne; Gladyshev, Vadim N; Sinclair, David A A hallmark of eukaryotic aging is a loss of epigenetic information, a process that can be reversed. We have previously shown that the ectopic induction of the Yamanaka factors OCT4, SOX2, and KLF4 (OSK) in mammals can restore youthful DNA methylation patterns, transcript profiles, and tissue function, without erasing cellular identity, a process that requires active DNA demethylation. To screen for molecules that reverse cellular aging and rejuvenate human cells without altering the genome, we developed high-throughput cell-based assays that distinguish young from old and senescent cells, including transcription-based aging clocks and a real-time nucleocytoplasmic compartmentalization (NCC) assay. We identify six chemical cocktails, which, in less than a week and without compromising cellular identity, restore a youthful genome-wide transcript profile and reverse transcriptomic age. Thus, rejuvenation by age reversal can be achieved, not only by genetic, but also chemical means.

High-Level Expression and Biochemical Properties of A Thermo-Alkaline Pectate Lyase From Bacillus sp. RN1 in Pichia pastoris With Potential in Ramie Degumming

Fri, 24 Jul 2020 00:00:00 GMT

High-Level Expression and Biochemical Properties of A Thermo-Alkaline Pectate Lyase From Bacillus sp. RN1 in Pichia pastoris With Potential in Ramie Degumming Zheng, Xueyun; Zhang, Yimin; Liu, Xiaoxiao; Li, Cheng; Lin, Ying; Liang, Shuli Pectate lyases play an essential role in textiles, animal feed, and oil extraction industries. Pichia pastoris can be an ideal platform for pectate lyases production, and BspPel (a thermo-alkaline pectate lyase from Bacillus sp. RN1) was overexpressed by combined strategies, reaching 1859 U/mL in a 50 L fermentator. It displayed the highest activity at 80°C, and maintained more than 60% of the activity between 30 and 70°C for 1 h. It showed an optimal pH of 10.0, and exhibited remarkable stability over a wider pH range (3.0-11.0), retaining more than 80.0% of enzyme activity for 4 h. The Km and kcat of BspPel on PGA (polygalacturonic acid) was 2.19 g L–1 and 116.1 s–1, respectively. The activity was significantly enhanced by Ca2+, Mn2+, and Cu2+, and a slight increase was observed with the addition of Ba2+ and Mg2+. Scanning electron microscope was used to show the degumming efficiency of BspPel on ramie fibers. The loss weight was 9.2% when treated with crude enzyme supernatant and 20.8% when treated with the enzyme-chemical method, which was higher than the 14.2% weight loss in the positive control treated with 0.5% (w/v) NaOH alone. In conclusion, BspPel could be a good candidate for the ramie degumming industry.

Growth Factor Engineering Strategies for Regenerative Medicine Applications

Tue, 21 Jan 2020 00:00:00 GMT

Growth Factor Engineering Strategies for Regenerative Medicine Applications Ren, Xiaochen; Zhao, Moyuan; Lash, Blake; Martino, Mikaël M; Julier, Ziad Growth factors are critical molecules for tissue repair and regeneration. Therefore, recombinant growth factors have raised a lot of hope for regenerative medicine applications. While using growth factors to promote tissue healing has widely shown promising results in pre-clinical settings, their success in the clinic is not a forgone conclusion. Indeed, translation of growth factors is often limited by their short half-life, rapid diffusion from the delivery site, and low cost-effectiveness. Trying to circumvent those limitations by the use of supraphysiological doses has led to serious side-effects in many cases and therefore innovative technologies are required to improve growth factor-based regenerative strategies. In this review, we present protein engineering approaches seeking to improve growth factor delivery and efficacy while reducing doses and side effects. We focus on engineering strategies seeking to improve affinity of growth factors for biomaterials or the endogenous extracellular matrix. Then, we discuss some examples of increasing growth factor stability and bioactivity, and propose new lines of research that the field of growth factor engineering for regenerative medicine may adopt in the future.

Quantification of muscle fiber malformations using edge detection to investigate chronic muscle pressure ulcers

Mon, 21 Oct 2024 00:00:00 GMT

Quantification of muscle fiber malformations using edge detection to investigate chronic muscle pressure ulcers Ong, Charlene ZL; Nasir, N Jannah M; Welsch, Roy E; Tucker-Kellogg, Lisa; Rajapakse, Jagath C Background: Microscopy of regenerated tissue shows different morphologies between the healing of acute wounds and chronic wounds. This difference can be seen manually by biologists, but computational methods are needed to automate the characterization of morphology and regenerative quality in regenerated muscle tissue. Results: From the detected edge segments, we computed several imaging biomarkers of interest, such as median tortuosity, number of edge segments normalized by area, median edge segment distance and interquartile range of orientation angles of edge segments of the microscope images of successful and unsuccessful muscle regeneration. We observed that muscle fibers in saline-treated pressure ulcers had a larger interquartile range of orientation angles of the edge segments (p = 0.05) and shorter edge segment distances (p = 0.003) compared to those of acute cardiotoxin injuries. Conclusion: Our edge detection method was able to identify statistically significant differences in some of the imaging biomarkers between saline-treated pressure ulcers and cardiotoxin injuries, suggesting that chronic pressure ulcers have increased muscle fiber malformations compared to cardiotoxin injuries.

Fast and Fourier: extreme mass ratio inspiral waveforms in the frequency domain

Fri, 12 Jan 2024 00:00:00 GMT

Fast and Fourier: extreme mass ratio inspiral waveforms in the frequency domain Speri, Lorenzo; Katz, Michael L; Chua, Alvin JK; Hughes, Scott A; Warburton, Niels; Thompson, Jonathan E; Chapman-Bird, Christian EA; Gair, Jonathan R Extreme Mass Ratio Inspirals (EMRIs) are one of the key sources for future spacebased gravitational wave interferometers. Measurements of EMRI gravitational waves are expected to determine the characteristics of their sources with subpercent precision. However, their waveform generation is challenging due to the long duration of the signal and the high harmonic content. Here, we present the first ready-to-use Schwarzschild eccentric EMRI waveform implementation in the frequency domain for use with either graphics processing units (GPUs) or central processing units (CPUs). We present the overall waveform implementation and test the accuracy and performance of the frequency domain waveforms against the time domain implementation. On GPUs, the frequency domain waveform takes in median 0.044 s to generate and is twice as fast to compute as its time domain counterpart when considering massive black hole masses ≥ 2 × 106 M⊙ and initial eccentricities e0 > 0.2. On CPUs, the median waveform evaluation time is 5 s, and it is five times faster in the frequency domain than in the time domain. Using a sparser frequency array can further speed up the waveform generation, reaching up to 0.3 s. This enables us to perform, for the first time, EMRI parameter inference with fully relativistic waveforms on CPUs. Future EMRI models, which encompass wider source characteristics (particularly black hole spin and generic orbit geometries), will require significantly more harmonics. Frequency domain models will be essential analysis tools for these astrophysically realistic and important signals.

Eigenvalue lower bounds and splitting for modified Ricci flow

Fri, 08 Mar 2024 00:00:00 GMT

Eigenvalue lower bounds and splitting for modified Ricci flow Colding, Tobias Holck; Minicozzi II, William P We prove sharp lower bounds for eigenvalues of the drift Laplacian for a modified Ricci flow. The modified Ricci flow is a system of coupled equations for a metric and weighted volume that plays an important role in Ricci flow. We will also show that there is a splitting theorem in the case of equality.

Propagation of symmetries for Ricci shrinkers

Tue, 13 Jun 2023 00:00:00 GMT

Propagation of symmetries for Ricci shrinkers Colding, Tobias Holck; Minicozzi II, William P We will show that if a gradient shrinking Ricci soliton has an approximate symmetry on one scale, this symmetry propagates to larger scales. This is an example of the shrinker principle which roughly states that information radiates outwards for shrinking solitons.

The effects of morphology, mobility size, and secondary organic aerosol (SOA) material coating on the ice nucleation activity of black carbon in the cirrus regime

Thu, 19 Nov 2020 00:00:00 GMT

The effects of morphology, mobility size, and secondary organic aerosol (SOA) material coating on the ice nucleation activity of black carbon in the cirrus regime Zhang, Cuiqi; Zhang, Yue; Wolf, Martin J; Nichman, Leonid; Shen, Chuanyang; Onasch, Timothy B; Chen, Longfei; Cziczo, Daniel J There is evidence that black carbon (BC) particles may affect cirrus formation and, hence, global climate by acting as potential ice nucleating particles (INPs) in the troposphere. Nevertheless, the ice nucleation (IN) ability of bare BC and BC coated with secondary organic aerosol (SOA) material remains uncertain. We have systematically examined the IN ability of 100–400 nm size-selected BC particles with different morphologies and different SOA coatings representative of anthropogenic (toluene and n-dodecane) and biogenic (β-caryophyllene) sources in the cirrus regime (−46 to −38 ∘C). Several BC proxies were selected to represent different particle morphologies and oxidation levels. Atmospheric aging was further replicated with the exposure of SOA-coated BC to OH. The results demonstrate that the 400 nm hydrophobic BC types nucleate ice only at or near the homogeneous freezing threshold. Ice formation at cirrus temperatures below homogeneous freezing thresholds, as opposed to purely homogeneous freezing, was observed to occur for some BC types between 100 and 200 nm within the investigated temperature range. More fractal BC particles did not consistently act as superior INPs over more spherical ones. SOA coating generated by oxidizing β-caryophyllene with O3 did not seem to affect BC IN ability, probably due to an SOA-phase state transition. However, SOA coatings generated from OH oxidation of various organic species did exhibit higher IN-onset supersaturation ratio with respect to ice (SSi), compared with bare BC particles, with the toluene-SOA coating showing an increase in SSi of 0.1–0.15 while still below the homogeneous freezing threshold. Slightly oxidized toluene SOA coating seemed to have a stronger deactivation effect on BC IN ability than highly oxidized toluene SOA, which might be caused by oligomer formation and the phase state transition of toluene SOA under different oxidation levels. n-dodecane and β-caryophyllene-derived SOA-coated BC only froze in the homogeneous regime. We attribute the inhibition of IN ability to the filling of the pores on the BC surface by the SOA material coating. OH exposure levels of n-dodecane and β-caryophyllene SOA coating experiments, from an equivalent atmospheric exposure time from 10 to 90 d, did not render significant differences in the IN potential. Our study of selected BC types and sizes suggests that increases in diameter, compactness, and/or surface oxidation of BC particles lead to more efficient IN via the pore condensation freezing (PCF) pathway, and that coatings of common SOA materials can inhibit the formation of ice.

A machine learning examination of hydroxyl radical differences among model simulations for CCMI-1

Wed, 05 Feb 2020 00:00:00 GMT

A machine learning examination of hydroxyl radical differences among model simulations for CCMI-1 Nicely, Julie M; Duncan, Bryan N; Hanisco, Thomas F; Wolfe, Glenn M; Salawitch, Ross J; Deushi, Makoto; Haslerud, Amund S; Jöckel, Patrick; Josse, Béatrice; Kinnison, Douglas E; Klekociuk, Andrew; Manyin, Michael E; Marécal, Virginie; Morgenstern, Olaf; Murray, Lee T; Myhre, Gunnar; Oman, Luke D; Pitari, Giovanni; Pozzer, Andrea; Quaglia, Ilaria; Revell, Laura E; Rozanov, Eugene; Stenke, Andrea; Stone, Kane; Strahan, Susan; Tilmes, Simone; Tost, Holger; Westervelt, Daniel M; Zeng, Guang The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH4), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime (τCH4 ), both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of τCH4 differences among 10 models are the flux of UV light to the troposphere (indicated by the photolysis frequency JO 1D), the mixing ratio of tropospheric ozone (O3), the abundance of nitrogen oxides (NOx ≡ NO + NO2), and details of the various chemical mechanisms that drive OH. Water vapour, carbon monoxide (CO), the ratio of NO : NOx , and formaldehyde (HCHO) explain moderate differences in τCH4 , while isoprene, methane, the photolysis frequency of NO2 by visible light (JNO2), overhead ozone column, and temperature account for little to no model variation in τCH4 . We also apply the NNs to analysis of temporal trends in OH from 1980 to 2015. All models that participated in the specified dynamics historical simulation for CCMI demonstrate a decline in τCH4 during the analysed timeframe. The significant contributors to this trend, in order of importance, are tropospheric O3, JO 1D, NOx , and H2O, with CO also causing substantial interannual variability in OH burden. Finally, the identified trends in τCH4 are compared to calculated trends in the tropospheric mean OH concentration from previous work, based on analysis of observations. The comparison reveals a robust result for the effect of rising water vapour on OH and τCH4 , imparting an increasing and decreasing trend of about 0.5 % decade−1 , respectively. The responses due to NOx , ozone column, and temperature are also in reasonably good agreement between the two studies.

High-Resolution OCT Reveals Age-Associated Variation in the Region Posterior to the External Limiting Membrane

Wed, 15 Jan 2025 00:00:00 GMT

High-Resolution OCT Reveals Age-Associated Variation in the Region Posterior to the External Limiting Membrane Jamil, Muhammad Usman; Won, Jungeun; Ploner, Stefan B; Marmalidou, Anna; Takahashi, Hiroyuki; Kaiser, Stephanie; Hwang, Yunchan; Abu-Qamar, Omar; Yaghy, Antonio; Witkin, Andre J; Zhao, Peter Y; Desai, Shilpa; Duker, Jay S; Maier, Andreas; Fujimoto, James G; Waheed, Nadia K Purpose: To evaluate visibility of a sub-band posterior to the external limiting membrane (ELM) and assess its age-associated variation. Methods: In a retrospective cross-sectional study, normal eyes were imaged using a high-resolution spectral-domain optical coherence tomography (SD-OCT) prototype (2.7-µm axial resolution). Volume fusion of six sequential scans (each 500 × 500 A-scans over 6 mm × 6 mm) was performed in the motion correction and volume reconstruction in OCT (MoReOCT) framework to enhance feature visibility in OCT. The subjects were divided into three groups: young (21-40 years old), middle (41-60 years old), and older (>60 years old). Three expert graders assessed the visibility of the sub-band on B-scans, and its A-scan intensity relative to ELM intensity (peak intensity ratio) was measured. Results: Forty-four eyes of 44 subjects were imaged. The sub-band, tentatively attributed to the photoreceptor myoid, can be visualized under high-resolution OCT. The B-scan gradings showed that sub-band visibility increased with age (visible in 16.7%, 47.2%, and 66.7% of the young, middle, and older age groups, respectively). The gradings were statistically different among age groups at 1 mm and 2 mm nasal and 1 mm and 2 mm temporal (P < 0.04) from the foveal center. Similarly, the mean peak intensity ratios of the sub-band to the ELM were 71.6%, 77.5%, and 85.2% in the young, middle, and older age groups, respectively, and were positively correlated with age at 1 mm temporal (P = 0.012) and 2 mm temporal (P < 0.001). Conclusions: High-resolution OCT, combined with advanced volume fusion, enables visualization of the photoreceptor myoid and investigation of its age-associated variations. Translational Relevance: Investigating the sub-band can advance our understanding of photoreceptors and their association with aging and disease pathogenesis.

Topographic Measurement of the Subretinal Pigment Epithelium Space in Normal Aging and Age-Related Macular Degeneration Using High-Resolution OCT

Fri, 09 Aug 2024 00:00:00 GMT

Topographic Measurement of the Subretinal Pigment Epithelium Space in Normal Aging and Age-Related Macular Degeneration Using High-Resolution OCT Won, Jungeun; Takahashi, Hiroyuki; Ploner, Stefan B; Karbole, Wenke; Abu-Qamar, Omar; Yaghy, Antonio; Marmalidou, Anna; Kaiser, Stephanie; Hwang, Yunchan; Lin, Junhong; Witkin, Andre; Desai, Shilpa; Baumal, Caroline R; Maier, Andreas; Curcio, Christine A; Waheed, Nadia K; Fujimoto, James G Purpose: A micrometer scale hyporeflective band within the retinal pigment epithelium basal lamina - Bruch's membrane complex (RPE-BL-BrM) was topographically measured in aging and age-related macular degeneration (AMD). Methods: In a prospective cross-sectional study, 90 normal eyes from 76 subjects (range = 23-90 years) and 53 dry AMD eyes from 47 subjects (range = 62-91 years) were enrolled. Isotropic volume raster scans over 6 mm × 6 mm (500 × 500 A-scans) were acquired using a high-resolution (2.7 µm axial resolution) spectral-domain optical coherence tomography (SD-OCT) prototype instrument. Six consecutive optical coherence tomography (OCT) volumes were computationally motion-corrected and fused to improve feature visibility. A boundary regression neural network was developed to measure hyporeflective band thickness. Topographic dependence was evaluated over a 6-mm-diameter Early Treatment Diabetic Retinopathy Study (ETDRS) grid. Results: The hyporeflective band thickness map (median of 4.3 µm and 7.8 µm in normal and AMD eyes, respectively) is thicker below and radially symmetric around the fovea. In normal eyes, age-associated differences occur within 0.7 to 2.3 mm from the foveal center (P < 0.05). In AMD eyes, the hyporeflective band is hypothesized to be basal laminar deposits (BLamDs) and is thicker within the 3-mm ETDRS circle (P < 0.0002) compared with normal eyes. The inner ring is the most sensitive location to detect age versus AMD-associated changes within the RPE-BL-BrM. AMD eyes with subretinal drusenoid deposits (SDDs) have a significantly thicker hyporeflective band (P < 0.001) than those without SDDs. Conclusions: The hyporeflective band is a quantifiable biomarker which differentiates AMD from aging. Longitudinal studies are warranted. The hyporeflective band may be a useful biomarker for risk stratification and disease progression.

Assessment of Choriocapillaris Flow Prior to Nascent Geographic Atrophy Development Using Optical Coherence Tomography Angiography

Thu, 18 Jan 2024 00:00:00 GMT

Assessment of Choriocapillaris Flow Prior to Nascent Geographic Atrophy Development Using Optical Coherence Tomography Angiography Greig, Eugenia Custo; Moult, Eric M; Despotovic, Ivana N; Hodgson, Lauren AB; Pramil, Varsha; Fujimoto, James G; Waheed, Nadia K; Guymer, Robyn H; Wu, Zhichao Purpose: To assess the relationship between choriocapillaris (CC) loss and the development of nascent geographic atrophy (nGA) using optical coherence tomography angiography (OCTA) imaging. Methods: In total, 105 from 62 participants with bilateral large drusen, without late age-related macular degeneration (AMD) or nGA at baseline, were included in this prospective, longitudinal, observational study. Participants underwent swept-source OCTA imaging at 6-month intervals. CC flow deficit percentage (FD%) and drusen volume measurements were determined for the visit prior to nGA development or the second-to-last visit if nGA did not develop. Global and local analyses, the latter based on analyses within superpixels (120 × 120-µm regions), were performed to examine the association between CC FD% and future nGA development. Results: A total of 15 (14%) eyes from 12 (19%) participants developed nGA. There was no significant difference in global CC FD% at the visit prior to nGA development between eyes that developed nGA and those that did not (P = 0.399). In contrast, CC FD% was significantly higher in superpixels that subsequently developed nGA compared to those that did not (P < 0.001), and a model utilizing CC FD% was significantly better at predicting foci of future nGA development at the superpixel level than a model using drusen volume alone (P ≤ 0.040). Conclusions: This study showed that significant impairments in CC blood flow could be detected locally prior to the development of nGA. These findings add to our understanding of the pathophysiologic changes that occur with atrophy development in AMD.

Stochastic Network Utility Maximization in Strategic Queueing Systems: A Game-Theoretic Approach

Thu, 26 Mar 2026 00:00:00 GMT

Stochastic Network Utility Maximization in Strategic Queueing Systems: A Game-Theoretic Approach Nguyen, Quang Minh; Berry, Randall; Modiano, Eytan Stochastic Network Utility Maximization (NUM) has been a dominant framework for many queueing network resource allocation and control problems. Its original model seeks to optimize social welfare, which usually takes the form of the sum of local utilities of participating entities. However, such a centralized utility maximization approach is unsuitable for many modern multi-agent systems, in which each agent may selfishly optimize its local utility without regard to the overall utility. In this paper, we formulate the stochastic NUM problem in strategic queueing systems as a repeated game with queue stability constraints. In particular, the agents repeatedly make decisions to satisfy both their local constraints and global constraints, shared among them, while maintaining queue stability. The goal is to design a policy that constitutes a generalized Nash equilibrium (GNE) for the game. We first derive the fluid model characterization of the strategic queueing NUM problem via a static one-shot game formulation. This characterization motivates a primal-dual algorithm that constitutes an approximate GNE by ensuring last-iterate convergence to a solution of the regularized static one-shot game. However, similar to primal-dual methods developed for the classical NUM problem, this approach does not leverage real-time queue lengths in decision making, leading to suboptimal queueing delay in practice, and has no explicit performance guarantees. To this end, we propose the Strategic Drift-plus-Penalty (SDP) algorithm and show that it constitutes an $\varepsilon$-GNE and has a uniformly bounded expected queue length of order $O\big(\frac{1}{\varepsilon^3} \big)$ for any $\varepsilon > 0$. Under an additional mild assumption that holds for a wide class of problems, we show that our algorithms achieve long-term average social welfare arbitrarily close to that of a welfare-maximizing GNE policy. Simulations validate our theory and demonstrate the favorable performance of our algorithms.

Pop-Up Encounters with Spot: Shaping Public Perceptions of Robots through Hands-On Experience

Mon, 16 Mar 2026 00:00:00 GMT

Pop-Up Encounters with Spot: Shaping Public Perceptions of Robots through Hands-On Experience Park, Hae Won; Van de Zande, Georgia D.; Zhang, Xiajie; Wendell, Dawn; Hodgins, Jessica Public attitudes toward robots are often shaped by indirect exposure (e.g., media, staged demos), leaving open how direct, hands-on experience influences acceptance. In this study, we investigate how interacting with Boston Dynamics’ Spot, an agile, state-of-the-art quadruped robot, in a public pop-up booth affects perceptions of comfort and suitability across everyday and high-stakes environments. In a walk-up, 10-week pop-up booth, participants (N=753) completed pre–post surveys before and after driving Spot within curated Drive Scenes (Factory, Home, Hospital, Outdoor/Disaster). Measures captured comfort encountering robots and perceived suitability across Rated Contexts (RCs), affective reactions, and open-ended reflections. Hands-on control significantly increased comfort across all RCs, with the largest gains in Outdoor/Disaster, and increased perceived suitability—most in Home/Office/Hospital where baselines were lower. Improvements generalized beyond the experienced Drive Scene to other contexts. Age, gender, and prior familiarity moderated baseline levels and some changes, but hands-on exposure raised scores for all groups and attenuated several gaps. Thematic analysis showed memorable moments tied to locomotion, terrain adaptation, and expressive tilt; imagined roles consistently emphasized domestic assistance (e.g., cleaning, mobility), with entertainment/play and companionship emerging post-interaction. Together, these results demonstrate that brief, agency-granting encounters with a high-capability quadruped can broaden where people see robots as appropriate and diversify envisioned roles, offering a scalable model for public-facing HRI that fosters comfort, enthusiasm, and acceptance. HRI ’26, Edinburgh, Scotland, UK

Who’s the Boss? Children Negotiate Robot Control across Role and Context

Mon, 16 Mar 2026 00:00:00 GMT

Who’s the Boss? Children Negotiate Robot Control across Role and Context Pu, Isabella; Rogers, Kantwon; Dinh, Linh Dieu; Alghowinem, Sharifa; Breazeal, Cynthia Children regularly negotiate questions of authority and control in home and school life, but little is known about how they believe robots should fit into these dynamics. We conducted a 75-minute design session with 17 children (ages 6-9) to examine when robots should take, share, or defer control, and how expectations shift when robots are framed as teachers, classmates, or mentees. Children resisted robot control, particularly in adult-regulated domains and areas tied to personal skill or self-expression. They were more open to robot control in domains where they felt less competent, or where robots, perceived as less legitimate authorities than humans, could substitute for adult control. Role framing further shaped expectations: teacher robots were granted autonomy, classmate robots were expected to act as peers, and mentee robots were expected to defer. These findings show that children apply context- and role-sensitive rules when negotiating control with robots. We conclude with design considerations for robots in children's everyday lives that respect children's agency, calibrate autonomy by domain, and align behavior with children's context-sensitive expectations. HRI ’26, Edinburgh, Scotland, UK

WiReSens Toolkit: An Open-source Platform towards Accessible Wireless Tactile Sensing

Sat, 07 Mar 2026 00:00:00 GMT

WiReSens Toolkit: An Open-source Platform towards Accessible Wireless Tactile Sensing Murphy, Devin; Zhu, Junyi; Gadre, Akshay; Torralba, Antonio; Liang, Paul Pu; Matusik, Wojciech; Luo, Yiyue Past research has widely explored the design and fabrication of resistive matrix-based tactile sensors for creating touch-sensitive devices. However, real-world deployment of resistive tactile sensing systems remains difficult for individuals with limited prior experience in embedded sensing due to challenges of portability, adaptivity, and efficiency. We introduce the WiReSens Toolkit, an accessible, open-source platform to bridge this gap. Central to our approach is adaptive hardware for interfacing with resistive sensors and a web-based GUI that streamlines access to advanced features for building scalable tactile sensing systems, including multi-device programming and wireless visualization across three communication protocols, autocalibration for adaptive sensitivity, and intermittent data transmission for low-power use. We validated the toolkit’s usability through a user study with 11 novice participants, who, on average, configured a tactile sensor with over 95% accuracy in under five minutes, calibrated sensors 10× faster than baseline methods, and showed improved sense-making of tactile data. TEI ’26, Chicago, IL, USA

PixBric: Precision Morphological Control of Pre-Stretched Fabrics Through Tessellated Primitive Geometries

Sat, 07 Mar 2026 00:00:00 GMT

PixBric: Precision Morphological Control of Pre-Stretched Fabrics Through Tessellated Primitive Geometries Youn, Hye Jun; Choe, Jun Kyu; Ahn, SooYeon; Tania, Marcello; Sara, Serena Xin Wei; Ishii, Hiroshi 3D printing onto pre-stretched fabrics has emerged as a promising technique for fabricating self-shaping textiles. However, resulting morphing behaviors are often dictated by heuristics or arbitrarily selected parameters. We present PixBric, a pixel-based design framework that enables precise morphological control through tessellated primitive geometries printed onto biaxially stretched fabrics. Upon release, these units buckle into programmed 3D forms including undulations, curling, and bistable snapping. PixBric integrates parametric modeling, mechanical simulation, and empirical evaluation to map geometric parameters to deformation outcomes. We demonstrate applications spanning morphable typography, wearable rings, and reconfigurable surfaces. PixBric bridges digital simulation (tide) with the mechanical constraints of elastic substrates (tied), transforming complex material behaviors into accessible tools for learning, experimentation, and creative fabrication. TEI ’26, Chicago, IL, USA

ChromoLCD: LCD-based Compact Reprogrammer for On-the-fly High-Resolution Images on Photochromic Surfaces

Sat, 07 Mar 2026 00:00:00 GMT

ChromoLCD: LCD-based Compact Reprogrammer for On-the-fly High-Resolution Images on Photochromic Surfaces Zhu, Yunyi; Li, Qingyuan; Yan, Katherine; Guan, Emily; Luchianov, Alexandru; Hen, Eden; Mueller, Stefanie Color-changing materials, such as photochromic pigments, allow objects to have reprogrammable multicolor surface images. Existing systems that reprogram these images are based on projectors and LEDs, each with advantages and limitations in device portability and image resolution. In this paper, we present ChromoLCD, a surface reprogrammer that uses a liquid crystal display (LCD) to achieve a compact handheld device without sacrificing image resolution. ChromoLCD consists of an LCD panel with a custom backlight containing R,G,B and UV LEDs, forming high-resolution light patterns with the required wavelengths. The compact form factor of ChromoLCD enables on-the-fly reprogramming of everyday surfaces. Our technical evaluation shows that ChromoLCD achieves a resolution of 25 ppi, which is 8 times better than the prior work. We demonstrate ChromoLCD with three applications, including the stamping of reprogrammable AR markers on a kitchen counter, on-the-fly designs on personal accessories, and reference pictures on a whiteboard. TEI ’26, Chicago, IL, USA

Natural Convection Heat Transfer from an Inclined Cylinder

Tue, 17 Mar 2026 00:00:00 GMT

Natural Convection Heat Transfer from an Inclined Cylinder Jaffer, Aubrey Based on Jaffer’s (2023) heat engine analysis of natural convection, this investigation mathematically derives a novel, comprehensive formula predicting the natural convective heat transfer from an inclined cylinder given its length, diameter, angle, and Rayleigh number and the fluid’s Prandtl number and thermal conductivity. The present formula was tested with 93 inclined cylinder measurements having length-to-diameter ratios between 1.48 and 104 in nine data-sets from three peer-reviewed studies, yielding (data-set) root-mean-squared relative error values between 1.9% and 4.7%.

Stability and Reactivity of Cyclopentane Nucleoside Analogs in 98% w/w Sulfuric Acid

Tue, 17 Mar 2026 00:00:00 GMT

Stability and Reactivity of Cyclopentane Nucleoside Analogs in 98% w/w Sulfuric Acid Seager, Sara; Seager, Maxwell D.; Visser, Ton; Marinus, Nittert; Poizat, Mael; van Wiltenburg, Jim; Poelert, Martin; Petkowski, Janusz J. We synthesized seven carbocyclic nucleoside analogs featuring a cyclopentane ring in place of the (deoxy)ribose sugar, which serves as a linker in DNA/RNA nucleosides. We assessed the stability of cyclopentane nucleosides in 98% w/w sulfuric acid at room temperature via 1H and 13C NMR spectroscopy. We observe that adenine (A1, A4), guanine (G1) and thymine (T1) cyclopentane nucleoside analogs remain stable for at least two weeks at room temperature, with only minor (~4%) degradation in A1. In contrast, the cytosine analog (C1) rapidly degrades to release a soluble cytosine. Methyl-substituted adenine analogs mimicking polymer backbone attachments at positions prone to tertiary carbocation formation (A2, A3) prove unstable and release soluble adenine. Only the 3,3-dimethylcyclopentyl adenine analog (A4) exhibits sufficient stability. Our findings reveal that cyclopentane serves as a viable stable linker in concentrated sulfuric acid for select nucleic acid bases, provided that the backbone connections avoid tertiary carbons susceptible to carbocation-mediated cleavage. We thus identify one potential key structural feature for engineering examples of genetic-like polymers that could potentially persist in Venus’s concentrated sulfuric acid cloud environment.

Operation of a Modular 3D-Pixelated Liquid Argon Time-Projection Chamber in a Neutrino Beam

Tue, 17 Mar 2026 00:00:00 GMT

Operation of a Modular 3D-Pixelated Liquid Argon Time-Projection Chamber in a Neutrino Beam Abbaslu, S.; Abud, A. Abed; Acciarri, R.; Accorsi, L. P.; Acero, M. A.; Adames, M. R.; Adamov, G.; Adamowski, M.; Adriano, C.; Akbar, F.; Alemanno, F.; Alex, N. S.; Allison, K.; Alrashed, M.; Alton, A.; Alvarez, R.; Alves, T.; Aman, A.; Amar, H.; Amedo, P. The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events.

Accelerated Full Waveform Inversion by Deep Compressed Learning

Fri, 13 Mar 2026 00:00:00 GMT

Accelerated Full Waveform Inversion by Deep Compressed Learning Gelboim, Maayan; Adler, Amir; Araya-Polo, Mauricio We propose and test a method to reduce the dimensionality of Full Waveform Inversion (FWI) inputs as a computational cost mitigation approach. Given modern seismic acquisition systems, the data (as an input for FWI) required for an industrial-strength case is in the teraflop level of storage; therefore, solving complex subsurface cases or exploring multiple scenarios with FWI becomes prohibitive. The proposed method utilizes a deep neural network with a binarized sensing layer that learns by compressed learning seismic acquisition layouts from a large corpus of subsurface models. Thus, given a large seismic data set to invert, the trained network selects a smaller subset of the data, then by using representation learning, an autoencoder computes latent representations of the shot gathers, followed by K-means clustering of the latent representations to further select the most relevant shot gathers for FWI. This approach can effectively be seen as a hierarchical selection. The proposed approach consistently outperforms random data sampling, even when utilizing only 10% of the data for 2D FWI, and these results pave the way to accelerating FWI in large scale 3D inversion.

A Time-Symmetric and Retrocausal Resolution of the EPR Paradox

Thu, 12 Mar 2026 00:00:00 GMT

A Time-Symmetric and Retrocausal Resolution of the EPR Paradox Heaney, Michael B. The Copenhagen Interpretation of quantum mechanics explains the Einstein, Podolsky, and Rosen (EPR) experiments with “spooky action at a distance” and nonlocal wavefunction collapse. A time-symmetric and retrocausal interpretation of quantum mechanics explains the same experiments without spooky action at a distance or nonlocal wavefunction collapse. An experiment that can distinguish between the Copenhagen and Time-Symmetric Interpretations is described.

Ionic Liquid Biospheres

Tue, 03 Mar 2026 00:00:00 GMT

Ionic Liquid Biospheres Seager, Sara; Bains, William; Iakubivskyi, Iaroslav; Agrawal, Rachana; Jenkins, John; Shinde, Pranav; Petkowski, Janusz J. Liquid is a fundamental requirement for life as we understand it, but whether that liquid has to be water is not known. We propose the hypothesis that ionic liquids (ILs) and deep eutectic solvents (DES) constitute a class of non-aqueous planetary liquids capable of persisting on a wide range of bodies where stable liquid water cannot exist. This hypothesis is motivated by key physical properties of ILs and DES. Many exhibit vapor pressures orders of magnitude lower than that of water and remain liquid across exceptionally wide temperature ranges, from cryogenic to well above terrestrial temperatures. These properties permit stable liquids to exist where liquid water would rapidly evaporate or freeze and outside of bulk phases as persistent microscale reservoirs—such as thin films and pore-filling droplets. In other words, ILs and DES can persist in environments without requiring oceans, thick atmospheres, or narrowly regulated climate conditions. We further hypothesize that ILs and DES could act as solvents for non-Earth-like life, based on their polar nature and the demonstrated stability and functionality of proteins and other biomolecules in ionic liquids. More speculatively, our hypothesis extends to the idea that ILs and DES could enable prebiotic chemistry by providing long-lived, protective liquid environments for complex organic molecules on bodies such as comets and asteroids, where liquid water is absent. Additionally, based on the occurrence of DES-like mixtures as protective intracellular liquids in desiccation-tolerant plants, we propose that ILs and DES might be solvents that life elsewhere purposefully evolves. We review protein and other biomolecule studies in ILs and DES and outline planetary environments in which ILs and DES might occur by discussing available anions and cations. We present strategies to advance the IL/DES solvent hypothesis using laboratory studies, computational chemistry, planetary missions, analysis of existing spectroscopic datasets, and modeling of liquid microniches and chemical survival on small bodies.

Nomenclatural Recommendations for Genera Assigned to the Arcobacteraceae from the Subcommittee on the Taxonomy of Campylobacter and Related Bacteria

Mon, 02 Feb 2026 00:00:00 GMT

Nomenclatural Recommendations for Genera Assigned to the Arcobacteraceae from the Subcommittee on the Taxonomy of Campylobacter and Related Bacteria On, Stephen L. W.; Figueras, Maria J.; Fox, James G.; Houf, Kurt; Mégraud, Francis; Miller, William G.; Stolz, John; Takai, Ken; Vandamme, Peter The taxonomy of the genus Arcobacter has been subject to substantive turmoil in recent years following a proposal to subdivide the genus into six genera. This proposal has been challenged by a number of multidisciplinary studies employing phenotypic, genomic, and phylogenetic analyses. Following several discussions among members of the International Committee on Systematics of Prokaryotes (ICSP) subcommittee on the taxonomy of Campylobacter and related bacteria, this group now unanimously recommends the use of the genus term Arcobacter to refer to these species.

Local Geographic Atrophy Growth Rates Not Influenced by Close Proximity to Non-Exudative Type 1 Macular Neovascularization

Fri, 14 Jan 2022 00:00:00 GMT

Local Geographic Atrophy Growth Rates Not Influenced by Close Proximity to Non-Exudative Type 1 Macular Neovascularization Trivizki, Omer; Moult, Eric M; Wang, Liang; Iyer, Prashanth; Shi, Yingying; Gregori, Giovanni; Feuer, William; Fujimoto, James G; Rosenfeld, Philip J Purpose: The local growth rates of geographic atrophy (GA) adjacent to non-exudative type 1 macular neovascularization (MNV) were investigated to determine if MNV influenced GA growth. Methods: Eyes with GA and non-exudative type 1 MNV were followed for at least 1 year. Both GA and the MNV were imaged and measured using swept-source optical coherence tomography angiography (SS-OCTA) scans. Pearson correlations were computed between local growth rates of GA, which were estimated using a biophysical GA growth model, and local distances-to-MNV. Corresponding P values for the null hypothesis of no Pearson correlation were computed using a Monte Carlo approach that adjusts for spatial autocorrelations. Results: Nine eyes were included in this study. There were positive correlations (Pearson's r > 0) between distance-to-MNV and local GA growth in eight (89%) of the eyes; however, in all but one eye (11%), correlations were relatively weak and statistically nonsignificant after Bonferroni correction (corrected P > 0.05). Conclusions: SS-OCTA imaging combined with GA growth modeling and spatial statistical analysis enabled quantitative assessment of correlations between local GA growth rates and local distances-to-MNV. Our results are not consistent with non-exudative type 1 MNV having a strong inhibitory effect on local GA growth rates.

Optical trapping of SrOH molecules for dark matter and T-violation searches

Thu, 29 Jan 2026 00:00:00 GMT

Optical trapping of SrOH molecules for dark matter and T-violation searches Sawaoka, Hiromitsu; Nasir, Abdullah; Lunstad, Annika; Li, Mingda; Mango, Jack; Lasner, Zack D; Doyle, John M We report an optical dipole trap of strontium monohydroxide (SrOH) with 1400(300) trapped molecules. Through optical pumping, we access vibrational states that are proposed for improved probes of the electron’s electric dipole moment (eEDM) and ultralight dark matter (UDM). For each of these states, the lifetime of trapped molecules is measured and found to be consistent with spontaneous radiative decay and blackbody excitation limits, making this platform viable for these eEDM and UDM searches.

Drosophila Fog/Cta and T48 pathways have overlapping and distinct contributions to mesoderm invagination

Wed, 01 May 2024 00:00:00 GMT

Drosophila Fog/Cta and T48 pathways have overlapping and distinct contributions to mesoderm invagination Horo, Uzuki; Clarke, D Nathaniel; Martin, Adam C The regulation of the cytoskeleton by multiple signaling pathways, sometimes in parallel, is a common principle of morphogenesis. A classic example of regulation by parallel pathways is Drosophila gastrulation, where the inputs from the Folded gastrulation (Fog)/Concertina (Cta) and the T48 pathways induce apical constriction and mesoderm invagination. Whether there are distinct roles for these separate pathways in regulating the complex spatial and temporal patterns of cytoskeletal activity that accompany early embryo development is still poorly understood. We investigated the roles of the Fog/Cta and T48 pathways and found that, by themselves, the Cta and T48 pathways both promote timely mesoderm invagination and apical myosin II accumulation, with Cta being required for timely cell shape change ahead of mitotic cell division. We also identified distinct functions of T48 and Cta in regulating cellularization and the uniformity of the apical myosin II network, respectively. Our results demonstrate that both redundant and distinct functions for the Fog/Cta and T48 pathways exist.

Tools for live-cell imaging of cytoskeletal and nuclear behavior in the unconventional yeast, Aureobasidium pullulans

Mon, 01 Apr 2024 00:00:00 GMT

Tools for live-cell imaging of cytoskeletal and nuclear behavior in the unconventional yeast, Aureobasidium pullulans Petrucco, Claudia A; Crocker, Alex W; D’Alessandro, Alec; Medina, Edgar M; Gorman, Olivia; McNeill, Jessica; Gladfelter, Amy S; Lew, Daniel J Aureobasidium pullulans is a ubiquitous fungus with a wide variety of morphologies and growth modes including “typical” single-budding yeast, and interestingly, larger multinucleate yeast than can make multiple buds in a single cell cycle. The study of A. pullulans promises to uncover novel cell biology, but currently tools are lacking to achieve this goal. Here, we describe initial components of a cell biology toolkit for A. pullulans, which is used to express and image fluorescent probes for nuclei as well as components of the cytoskeleton. These tools allowed live-cell imaging of the multinucleate and multibudding cycles, revealing highly synchronous mitoses in multinucleate yeast that occur in a semiopen manner with an intact but permeable nuclear envelope. These findings open the door to using this ubiquitous polyextremotolerant fungus as a model for evolutionary cell biology.

Tracking the Spatio‐Temporal Evolution of Foreshocks Preceding the Mw 6.1 2009 L’Aquila Earthquake

Mon, 07 Mar 2022 00:00:00 GMT

Tracking the Spatio‐Temporal Evolution of Foreshocks Preceding the Mw 6.1 2009 L’Aquila Earthquake Cabrera, Leoncio; Poli, Piero; Frank, William B How faulting processes lead to a large earthquake is a fundamental question in seismology. To better constrain this pre‐seismic stage, we create a dense seismic catalog via template matching to analyze the precursory phase of the Mw 6.1 L’Aquila earthquake that occurred in central Italy in 2009. We estimate several physical parameters in time, such as the coefficient of variation, the seismic moment release, the effective stress drop, and analyze spatio‐temporal patterns to study the evolution of the sequence and the earthquake interactions. We observe that the precursory phase experiences multiple accelerations of the seismicity rate that we divide into two main sequences with different signatures and features: the first part exhibits weak earthquake interactions, quasi‐continuous moment release, slow spatial migration patterns, and a lower effective stress drop, pointing to aseismic processes. The second sequence exhibits strong temporal clustering, fast seismicity expansion, and a larger effective stress drop typical of a stress transfer process. We interpret the differences in seismicity behaviors between the two sequences as distinct physical mechanisms that are controlled by different physical properties of the fault system. We conclude that the L’Aquila earthquake is preceded by a complex preparation, made up of different physical processes over different time scales on faults with different physical properties.

A High‐Resolution Atlas of the Eastern Tropical Pacific Oxygen Deficient Zones

Mon, 27 Dec 2021 00:00:00 GMT

A High‐Resolution Atlas of the Eastern Tropical Pacific Oxygen Deficient Zones Kwiecinski, Jarek V; Babbin, Andrew R Oxygen deficient zones (ODZs) are important biogeochemical provinces of the global oceans wherein standing dissolved oxygen concentrations decrease to nanomolar levels. Despite their confinement, these regions are disproportionally important to the ocean's role in modulating Earth's climate through the interactions between the marine nitrogen cycle and that of carbon. Moreover, the spatial domain of low oxygen regions of the ocean is predicted to change as a consequence of ocean warming, increased stratification, and changes in circulation and productivity. However, the expanse of the modern ODZs is poorly resolved due to a dearth of direct sampling compounded with errors that arise in the processing and gridding of the sparse measurements that do exist. Here, we take a novel approach to map the horizontal and vertical extent of the two major ODZs of the eastern tropical Pacific via analysis of meter-scale resolution electrode sensors from both ship casts and Argo profiles, rather than from discretized bottle measurements. The resulting three-dimensional data product is based on a compendium of nearly 15 million measurements taken across three decades and provides the precise locations of low oxygen water, elucidating the ODZs' three-dimensional structures. It can be utilized by researchers to validate models, plan cruise occupations, and as a comparison for future change. Calculations made with this high-resolution atlas also provide the volumes, layers of maximal areal extent, and other descriptive statistics for both Pacific ODZs. Finally, the atlas reveals fine-scale features of oxygenated water mass intrusions and regional differences across these anoxic zones.

Orbital‐ and Millennial‐Scale Variability in Northwest African Dust Emissions Over the Past 67,000 years

Tue, 07 Dec 2021 00:00:00 GMT

Orbital‐ and Millennial‐Scale Variability in Northwest African Dust Emissions Over the Past 67,000 years Kinsley, Christopher W; Bradtmiller, Louisa I; McGee, David; Galgay, Michael; Stuut, Jan‐Berend; Tjallingii, Rik; Winckler, Gisela; deMenocal, Peter B Reconstructions of aeolian dust flux to West African margin sediments can be used to explore changing atmospheric circulation and hydroclimate over North Africa on millennial to orbital timescales. Here, we extend West African margin dust flux records back to 37 ka in a transect of sites from 19° to 27°N, and back to 67 ka at Ocean Drilling Program (ODP) Hole 658C, in order to explore the interplay of orbital and high-latitude forcings on North African climate and make quantitative estimates of dust flux during the core of the Last Glacial Maximum (LGM). The ODP 658C record shows a Green Sahara interval from 60 to 50 ka during a time of high Northern Hemisphere summer insolation, with dust fluxes similar to levels during the early Holocene African Humid Period, and an abrupt peak in flux during Heinrich event 5a (H5a). Dust fluxes increase from 50 to 35 ka while the high-latitude Northern Hemisphere cools, with peaks in dust flux associated with North Atlantic cool events. From 35 ka through the LGM dust deposition decreases in all cores, and little response is observed to low-latitude insolation changes. Dust fluxes at sites from 21° to 27°N were near late Holocene levels during the LGM time slice, suggesting a more muted LGM response than observed from mid-latitude dust sources. Records along the northwest African margin suggest important differences in wind responses during different stadials, with maximum dust flux anomalies centered south of 20°N during H1 and north of 20°N during the Younger Dryas.

Methyl Chloroform Continues to Constrain the Hydroxyl (OH) Variability in the Troposphere

Sat, 27 Feb 2021 00:00:00 GMT

Methyl Chloroform Continues to Constrain the Hydroxyl (OH) Variability in the Troposphere Patra, PK; Krol, MC; Prinn, RG; Takigawa, M; Mühle, J; Montzka, SA; Lal, S; Yamashita, Y; Naus, S; Chandra, N; Weiss, RF; Krummel, PB; Fraser, PJ; O'Doherty, S; Elkins, JW Trends and variability in tropospheric hydroxyl (OH) radicals influence budgets of many greenhouse gases, air pollutant species, and ozone depleting substances. Estimations of tropospheric OH trends and variability based on budget analysis of methyl chloroform (CH3CCl3) and process-based chemistry transport models often produce conflicting results. Here we use a previously tested transport model to simulate atmospheric CH3CCl3 for the period 1985–2018. Based on mismatches between model output and observations, we derive consistent anomalies in the inverse lifetime of CH3CCl3 (KG) using measurements from two independent observational networks (National Oceanic and Atmospheric Administration and Advanced Global Atmospheric Gases Experiment). Our method allows a separation between “physical” (transport, temperature) and “chemical” (i.e., abundance) influences on OH + CH3CCl3 reaction rate in the atmosphere. Small increases in KG due to “physical” influences are mostly driven by increases in the temperature-dependent reaction between OH and CH3CCl3 and resulted in a smoothly varying increase of 0.80% decade−1. Chemical effects on KG, linked to global changes in OH sources and sinks, show larger year-to-year variations (∼2%–3%), and have a negative correlation with the El Niño Southern Oscillation. A significant positive trend in KG can be derived after 2001, but it persists only through 2015 and only if we assume that CH3CCl3 emissions decayed more slowly over time than our best estimate suggests. If global CH3CCl3 emissions dropped below 3 Gg year−1 after 2015, recent CH3CCl3 measurements indicate that the 2015–2018 loss rate of CH3CCl3 due to reaction with OH is comparable to its value 2 decades ago.

InterCarb: A Community Effort to Improve Interlaboratory Standardization of the Carbonate Clumped Isotope Thermometer Using Carbonate Standards

Tue, 13 Apr 2021 00:00:00 GMT

InterCarb: A Community Effort to Improve Interlaboratory Standardization of the Carbonate Clumped Isotope Thermometer Using Carbonate Standards Increased use and improved methodology of carbonate clumped isotope thermometry has greatly enhanced our ability to interrogate a suite of Earth-system processes. However, interlaboratory discrepancies in quantifying carbonate clumped isotope (Δ47) measurements persist, and their specific sources remain unclear. To address interlaboratory differences, we first provide consensus values from the clumped isotope community for four carbonate standards relative to heated and equilibrated gases with 1,819 individual analyses from 10 laboratories. Then we analyzed the four carbonate standards along with three additional standards, spanning a broad range of δ47 and Δ47 values, for a total of 5,329 analyses on 25 individual mass spectrometers from 22 different laboratories. Treating three of the materials as known standards and the other four as unknowns, we find that the use of carbonate reference materials is a robust method for standardization that yields interlaboratory discrepancies entirely consistent with intralaboratory analytical uncertainties. Carbonate reference materials, along with measurement and data processing practices described herein, provide the carbonate clumped isotope community with a robust approach to achieve interlaboratory agreement as we continue to use and improve this powerful geochemical tool. We propose that carbonate clumped isotope data normalized to the carbonate reference materials described in this publication should be reported as Δ47 (I-CDES) values for Intercarb-Carbon Dioxide Equilibrium Scale.

Age Set versus Kin: Culture and Financial Ties in east Africa

Sun, 01 Sep 2024 00:00:00 GMT

Age Set versus Kin: Culture and Financial Ties in east Africa Moscona, Jacob; Seck, Awa Ambra We study how social organization shapes patterns of economic interaction and the effects of national policy, focusing on the distinction between age-based and kin-based groups in sub-Saharan Africa. Motivated by ethnographic accounts suggesting that this distinction affects redistribution, we analyze a cash transfer program in Kenya and find that in age-based societies there are consumption spillovers within the age cohort, but not the extended family, while in kin-based societies we find the opposite. Next, we document that social structure shapes the impact of policy by showing that Uganda’s pension program had positive effects on child nutrition only in kin-based societies. (JEL H23, I12, I38, J13, O15, Z13).

Social Media and Mental Health

Tue, 01 Nov 2022 00:00:00 GMT

Social Media and Mental Health Braghieri, Luca; Levy, Ro’ee; Makarin, Alexey We provide quasi-experimental estimates of the impact of social media on mental health by leveraging a unique natural experiment: the staggered introduction of Facebook across US colleges. Our analysis couples data on student mental health around the years of Facebook’s expansion with a generalized difference-in-differences empirical strategy. We find that the rollout of Facebook at a college had a negative impact on student mental health. It also increased the likelihood with which students reported experiencing impairments to academic performance due to poor mental health. Additional evidence on mechanisms suggests the results are due to Facebook fostering unfavorable social comparisons. (JEL D91, I12, I23, L82)

Is Journalistic Truth Dead? Measuring How Informed Voters Are about Political News

Mon, 01 Apr 2024 00:00:00 GMT

Is Journalistic Truth Dead? Measuring How Informed Voters Are about Political News Angelucci, Charles; Prat, Andrea To investigate general patterns in news information in the United States, we combine a protocol for identifying major political news stories, 11 monthly surveys with 15,000 participants, and a model of news discernment. When confronted with a true and a fake news story, 47 percent of subjects confidently choose the true story, 3 percent confidently choose the fake story, and the remaining half are uncertain. Socioeconomic differences are associated with large variations in the probability of selecting the true news story. Partisan congruence between an individual and a news story matters, but its impact is up to an order of magnitude smaller. (JEL D72, D83, L82).

How Merchant Towns Shaped Parliaments: From the Norman Conquest of England to the Great Reform Act

Sat, 01 Oct 2022 00:00:00 GMT

How Merchant Towns Shaped Parliaments: From the Norman Conquest of England to the Great Reform Act Angelucci, Charles; Meraglia, Simone; Voigtländer, Nico We study the emergence of urban self-governance in the late medieval period. We focus on England after the Norman Conquest of 1066, building a novel comprehensive dataset of 554 medieval towns. During the Commercial Revolution (twelfth to thirteenth centuries), many merchant towns obtained Farm Grants: the right of self-governed tax collection and law enforcement. Self-governance, in turn, was a stepping stone for parliamentary representation: Farm Grant towns were much more likely to be summoned directly to the medieval English Parliament than otherwise similar towns. We also show that self-governed towns strengthened the role of Parliament and shaped national institutions over the subsequent centuries. (JEL D02, D72, D73, K11, K34, N43, N93).

Shock response of periodic interpenetrating phase composites

Tue, 22 Nov 2022 00:00:00 GMT

Shock response of periodic interpenetrating phase composites Taylor, Spencer V; Gonzales, Manny; Cordero, Zachary C In this work, we examine the macroscale and fine-scale shock responses of interpenetrating phase composites comprising a body-centered cubic steel lattice embedded in an aluminum matrix. Through plate impact simulations, we find that the complex mesoscale geometry reduces shock velocity relative to monolithic constituents, slowing and spreading the shock front via reflection and redirection. The periodicity of the mesoscale composite geometry is also reflected by quasi-steady-wave behavior. On the fine-scale, we can predict several aspects of the oscillatory pressure and longitudinal velocity responses by tracking internal wave reflections. We also observe that the post-shock maximum temperature increases with structural openness and temperature hotspots form at interfaces parallel to the shock direction. The findings in this work provide novel structure–property linkages in the dynamic response of architectured interpenetrating phase composites.

ℏ2 expansion of the transmission probability through a barrier

Fri, 19 Aug 2022 00:00:00 GMT

ℏ2 expansion of the transmission probability through a barrier Pollak, Eli; Cao, Jianshu Ninety years ago, Wigner derived the leading order expansion term in ℏ2 for the tunneling rate through a symmetric barrier. His derivation included two contributions: one came from the parabolic barrier, but a second term involved the fourth-order derivative of the potential at the barrier top. He left us with a challenge, which is answered in this paper, to derive the same but for an asymmetric barrier. A crucial element of the derivation is obtaining the ℏ2 expansion term for the projection operator, which appears in the flux-side expression for the rate. It is also reassuring that an analytical calculation of semiclassical transition state theory (TST) reproduces the anharmonic corrections to the leading order of ℏ2. The efficacy of the resulting expression is demonstrated for an Eckart barrier, leading to the conclusion that especially when considering heavy atom tunneling, one should use the expansion derived in this paper, rather than the parabolic barrier approximation. The rate expression derived here reveals how the classical TST limit is approached as a function of ℏ and, thus, provides critical insights to understand the validity of popular approximate theories, such as the classical Wigner, centroid molecular dynamics, and ring polymer molecular dynamics methods.

Nonlinear exceptional-point lasing with ab initio Maxwell– Bloch theory

Thu, 15 Dec 2022 00:00:00 GMT

Nonlinear exceptional-point lasing with ab initio Maxwell– Bloch theory Benzaouia, Mohammed; Stone, AD; Johnson, Steven G We present a general analysis for finding and characterizing nonlinear exceptional point (EP) lasers above threshold using steady-state ab initio Maxwell–Bloch equations. For a system of coupled slabs, we show that a nonlinear EP is obtained for a given ratio between the external pumps in each resonator and that it is associated with a kink in the output power and lasing frequency, confirming coupled-mode theory predictions. Through numerical linear stability analysis, we confirm that the EP laser can be stable for a large enough inversion relaxation rate. We further show that the EP laser can be characterized by scattering a weak signal off the lasing cavity so that the scattering frequency spectrum exhibits a quartic divergence. Our approach can be applied to arbitrary scatterers with multi-level gain media.

The impact of semiconductor surface states on vacuum field emission

Wed, 26 Oct 2022 00:00:00 GMT

The impact of semiconductor surface states on vacuum field emission Kim, Taeyoung; Joishi, Chandan; Shih, Pao-Chuan; Palacios, Tomás; Rajan, Siddharth This work presents a theoretical analysis of the impact of surface states on vacuum field emission currents in semiconductors. In wide and ultra-wide bandgap semiconductors such as GaN and AlGaN, low electron affinity has been proposed as a benefit for field emission into vacuum. However, in these materials, the surface Fermi level at the surface is pinned well below the conduction band, and the surface depletion barriers due to the surface Fermi level pinning can be comparable to or higher than the electron affinity. Therefore, analysis of field emission requires consideration of not only the vacuum potential barrier set by electron affinity, but also the depletion region near the semiconductor surface. In this paper, we develop analytical models to predict field emission currents with careful consideration of the impact of surface states on the energy band alignment. The results are used to provide guidelines for design of field emitters that could benefit from the low electron affinity of semiconductors such as Al(Ga)N.

A robust computational approach to Lees–Dorodnitsyn laminar hypersonic boundary layers with temperature-dependent properties

Mon, 03 Oct 2022 00:00:00 GMT

A robust computational approach to Lees–Dorodnitsyn laminar hypersonic boundary layers with temperature-dependent properties Onyeador, CN; Hodge, A; Harris, W The Lees–Dorodnitsyn (L–D) boundary layer equations for two-dimensional, non-reactive, laminar, hypersonic, boundary layer flows, and an assumption of an isentropic external flow are examined. They are applied to various geometries for which the Thin Shear Layer assumptions are valid. This study expands on previous work to develop a novel and robust methodology for computing high-temperature hypersonic flows using a uniform and compact computational stencil implemented through a computational tool, the Bulk-property Boundary Layer (BuBL) solver. In particular, we explore the impact of treating high-temperature effects present in hypersonic flows, namely, treating air as a thermally perfect gas with temperature-variable properties. The ability to solve these flows computationally using second-order finite difference methods is evaluated as are various models for viscosity, Prandtl number, and specific heat. The methodology for solving the external flow properties in the transformed L–D computational domain is also discussed. It is shown that the L–D equations evaluated using the “box” computational stencil are an effective means for evaluating laminar hypersonic boundary layer flows. Solutions for displacement and momentum thicknesses, skin friction, and Stanton number variations are obtained as a function of Prandtl number, specific heat model, and Mach number. Verification and validation measures are performed for the code. Excellent agreement is found in comparisons between BuBL and other computational fluid dynamics and experimental results, thus demonstrating the utility of the proposed methodology.

Plasmas for in situ resource utilization on Mars: Fuels, life support, and agriculture

Tue, 16 Aug 2022 00:00:00 GMT

Plasmas for in situ resource utilization on Mars: Fuels, life support, and agriculture Guerra, V; Silva, T; Pinhão, N; Guaitella, O; Guerra-Garcia, C; Peeters, FJJ; Tsampas, MN; van de Sanden, MCM This work discusses the potential of combining non-thermal plasmas and conducting membranes for in situ resource utilization (ISRU) on Mars. By converting different molecules directly from the Martian atmosphere, plasmas can create the necessary feed-stock and base chemicals for processing fuels, breathing oxygen, building materials, and fertilizers. Different plasma sources operate according to different principles and are associated with distinct dominant physicochemical mechanisms. This diversity allows exploring different energy transfer pathways leading to CO2 dissociation, including direct electron-impact processes, plasma chemistry mediated by vibrationally and electronically excited states, and thermally driven dissociation. The coupling of plasmas with membranes is still a technology under development, but a synergistic effect between plasma decomposition and oxygen permeation across conducting membranes is anticipated. The emerging technology is versatile, scalable, and has the potential to deliver high rates of production of molecules per kilogram of instrumentation sent to space. Therefore, it will likely play a very relevant role in future ISRU strategies.

Bridging the gap between H- and J-aggregates: Classification and supramolecular tunability for excitonic band structures in two-dimensional molecular aggregates

Thu, 23 Jun 2022 00:00:00 GMT

Bridging the gap between H- and J-aggregates: Classification and supramolecular tunability for excitonic band structures in two-dimensional molecular aggregates Deshmukh, Arundhati P; Geue, Niklas; Bradbury, Nadine C; Atallah, Timothy L; Chuang, Chern; Pengshung, Monica; Cao, Jianshu; Sletten, Ellen M; Neuhauser, Daniel; Caram, Justin R Molecular aggregates with long-range excitonic couplings have drastically different photophysical properties compared to their monomer counterparts. From Kasha's model for one-dimensional systems, positive or negative excitonic couplings lead to blue or red-shifted optical spectra with respect to the monomers, labeled H-and J-aggregates, respectively. The overall excitonic couplings in higher dimensional systems are much more complicated and cannot be simply classified from their spectral shifts alone. Here, we provide a unified classification for extended 2D aggregates using temperature dependent peak shifts, thermal broadening, and quantum yields. We discuss the examples of six 2D aggregates with J-like absorption spectra but quite drastic changes in quantum yields and superradiance. We find the origin of the differences is, in fact, a different excitonic band structure where the bright state is lower energy than the monomer but still away from the band edge. We call this an “I-aggregate.” Our results provide a description of the complex excitonic behaviors that cannot be explained solely on Kasha's model. Furthermore, such properties can be tuned with the packing geometries within the aggregates providing supramolecular pathways for controlling them. This will allow for precise optimizations of aggregate properties in their applications across the areas of optoelectronics, photonics, excitonic energy transfer, and shortwave infrared technologies.

Design and construction of a compact, high-repetition-rate ultrafast electron diffraction instrument

Tue, 30 May 2023 00:00:00 GMT

Design and construction of a compact, high-repetition-rate ultrafast electron diffraction instrument Freelon, Byron; Rohwer, Timm; Zong, Alfred; Kogar, Anshul; Zhou, Hengyun; Wong, Liang Jie; Ergeçen, Emre; Gedik, Nuh We present the design and performance of a compact ultrafast electron diffraction instrument. The diffractometer provides a means of examining time-resolved ultrafast dynamical properties of solids. The system’s utilization is discussed in terms of instrument parameters and diffraction data from selected condensed matter samples. The difractometer’s performance is highlighted in terms of detection sensitivity, instrumental temporal resolution, and the electron beam transverse coherence length. Following specific details of the construction, we present a practical discussion of parameters such as repetition rate and provide advice on general construction approaches for laboratory-based, keV ultrafast electron diffractometers. In addition, design guidance for constructing a compact electron gun source that is well-suited for studying diffraction from hard condensed matter is given. A unique data acquisition scheme, utilizing high laser repetition rates, is presented.

EXPANSE: A time-of-flight EXPanded Angle Neutron Spin Echo spectrometer at the Second Target Station of the Spallation Neutron Source

Mon, 11 Jul 2022 00:00:00 GMT

EXPANSE: A time-of-flight EXPanded Angle Neutron Spin Echo spectrometer at the Second Target Station of the Spallation Neutron Source Do, Changwoo; Ashkar, Rana; Boone, Cristina; Chen, Wei-Ren; Ehlers, Georg; Falus, Peter; Faraone, Antonio; Gardner, Jason S; Graves, Van; Huegle, Thomas; Katsumata, Reika; Kent, Darian; Lin, Jiao YY; McHargue, Bill; Olsen, Bradley; Wang, Yangyang; Wilson, Danielle; Z, Y EXPANSE, an EXPanded Angle Neutron Spin Echo instrument, has been proposed and selected as one of the first suite of instruments to be built at the Second Target Station of the Spallation Neutron Source at the Oak Ridge National Laboratory. This instrument is designed to address scientific problems that involve high-energy resolution (neV–μeV) of dynamic processes in a wide range of materials. The wide-angle detector banks of EXPANSE provide coverage of nearly two orders of magnitude in scattering wavenumbers, and the wide wavelength band affords approximately four orders of magnitude in Fourier times. This instrument will offer unique capabilities that are not available in the currently existing neutron scattering instruments in the United States. Specifically, EXPANSE will enable direct measurements of slow dynamics in the time domain over wide Q-ranges simultaneously and will also enable time-resolved spectroscopic studies. The instrument is expected to contribute to a diverse range of science areas, including soft matter, polymers, biological materials, liquids and glasses, energy materials, unconventional magnets, and quantum materials.

Thermal diffusivity in ion-irradiated single-crystal iron, chromium, vanadium, and tungsten measured using transient grating spectroscopy

Fri, 22 Jul 2022 00:00:00 GMT

Thermal diffusivity in ion-irradiated single-crystal iron, chromium, vanadium, and tungsten measured using transient grating spectroscopy Wylie, APC; Woller, KB; Al Dajani, SAA; Dacus, BR; Pickering, EJ; Preuss, M; Short, MP The speed-up of radiation science development with the advent of ion-irradiation experiments has, until recently, been omitted in the post-irradiation examination technique. This paper reports the results of transient grating spectroscopy—a rapid, non-destructive, in situ photothermal surface technique—of ion-irradiated single-crystals of iron, chromium, vanadium, and tungsten at room temperature. Thermal diffusivity was used to track damage development throughout irradiation, with 5 MeV self-ion irradiated iron, chromium, and vanadium showing little to no change up to damages of the order of 1 dpa. 5 MeV Si3+-ion irradiated tungsten exhibits a reduction of thermal diffusivity from 0.78(7) to 0.29(2) cm2 s−1 with logarithmically increasing dose over a similar damage range. A comparison to literature of transient grating spectroscopy thermal diffusivity values past and present shows good agreement; radiation-induced change can be clearly distinguished from differences between mono- and poly-crystalline tungsten.

Thickness and temperature dependence of the atomic-scale structure of SrRuO3 thin films

Wed, 11 May 2022 00:00:00 GMT

Thickness and temperature dependence of the atomic-scale structure of SrRuO3 thin films Zhang, Xuanyi; Penn, Aubrey N; Wysocki, Lena; Zhang, Zhan; van Loosdrecht, Paul HM; Kornblum, Lior; LeBeau, James M; Lindfors-Vrejoiu, Ionela; Kumah, Divine P The temperature-dependent layer-resolved structure of 3 to 44 unit cell thick SrRuO3 (SRO) films grown on Nb-doped SrTiO3 substrates is investigated using a combination of high-resolution synchrotron x-ray diffraction and high-resolution electron microscopy to understand the role that structural distortions play in suppressing ferromagnetism in ultra-thin SRO films. The oxygen octahedral tilts and rotations and Sr displacements characteristic of the bulk orthorhombic phase are found to be strongly dependent on temperature, the film thickness, and the distance away from the film–substrate interface. For thicknesses, t, above the critical thickness for ferromagnetism (t > 3 uc), the orthorhombic distortions decrease with increasing temperature above TC. Below TC, the structure of the films remains constant due to the magneto-structural coupling observed in bulk SRO. The orthorhombic distortions are found to be suppressed in the 2–3 interfacial layers due to structural coupling with the SrTiO3 substrate and correlate with the critical thickness for ferromagnetism in uncapped SRO films.

Hyperbolic phonon polaritons with positive and negative phase velocities in suspended α -MoO3

Mon, 14 Mar 2022 00:00:00 GMT

Hyperbolic phonon polaritons with positive and negative phase velocities in suspended α -MoO3 Shen, Jialiang; Zheng, Zhiren; Dinh, Thao; Wang, Chuanyu; Chen, Mingyuan; Chen, Pengyu; Ma, Qiong; Jarillo-Herrero, Pablo; Kang, Lixing; Dai, Siyuan Sample suspension is a valuable method to improve the mechanical, thermal, electronic, and optical properties of low-dimensional materials. In terms of confined light-matter waves—the polaritons, sample suspension can elongate the wavelength of polaritons with a positive phase velocity. Previous work demonstrates a wavelength elongation of ∼10% for hyperbolic phonon polaritons (HPPs) in uniaxial crystals of hexagonal boron nitride (hBN). In this work, we report the alteration of HPPs in biaxial α-phase molybdenum trioxide (α-MoO3) by sample suspension. Our combined infrared nano-imaging experiments and electromagnetic theory reveal a wavelength elongation > 60% and a propagation length increase > 140%, due to the simultaneous wavelength elongation and dissipation elimination in the suspended specimen. We have also examined HPPs in α-MoO3 with a negative phase velocity. The sample suspension shortens the HPP wavelength and simultaneously reduces the dissipation due to the unique permittivity tensor. The HPPs with improved figures of merits in the suspended specimen may be developed for nano-polaritonic circuits, biochemical sensing, emission engineering, and energy transfer.

Hole opening from growing interfacial voids: A possible mechanism of solid state dewetting

Thu, 03 Mar 2022 00:00:00 GMT

Hole opening from growing interfacial voids: A possible mechanism of solid state dewetting Curiotto, Stefano; Chame, Anna; Müller, Pierre; Thompson, Carl V; Pierre-Louis, Olivier Vacancies at interfaces between a film and a substrate can affect material properties and could play a role in solid state dewetting. Using kinetic Monte Carlo simulations, we show that interfacial mono-vacancies diffuse and coalesce to form vacancy clusters and voids. The film/substrate excess energy ES, which is related to the apparent contact angle, controls the mechanisms of coalescence. Depending on ES, voids emerging at the film surface form a hole that can be filled by the film or can lead to dewetting of the film from the substrate.

2D materials-enabled optical modulators: From visible to terahertz spectral range

Tue, 19 Apr 2022 00:00:00 GMT

2D materials-enabled optical modulators: From visible to terahertz spectral range Gan, Xuetao; Englund, Dirk; Van Thourhout, Dries; Zhao, Jianlin Two-dimensional (2D) materials with layered structures have a variety of exceptional electronic and optical attributes for potentially developing basic functions of light wave technology from light-emitting to -modulating and -sensing. Here, we present state-of-the-art 2D materials-enabled optical intensity modulators according to their operation spectral ranges, which are mainly determined by the optical bandgaps of the 2D materials. Leveraging rich electronic structures from different 2D materials and the governed unique light–matter interactions, the working mechanisms and device architectures for the enabled modulators at specific wavelength ranges are discussed. For instance, the tunable excitonic effect in monolayer transition metal dichalcogenides allows the modulation of visible light. Electro-absorptive and electro-refractive graphene modulators could be operated in the telecom-band relying on their linear dispersion of the massless Dirac fermions. The bendable electronic band edge of the narrow bandgap in few-layer black phosphorus promises the modulation of mid-infrared light via the quantum-confined Franz–Keldysh or Burstein–Moss shift effect. Electrically and magnetically tunable optical conductivity in graphene also supports the realizations of terahertz modulators. While these modulators were demonstrated as proof of concept devices, part of them have great potential for future realistic applications, as discussed with their wavelength coverage, modulation depth, insertion loss, dynamic response speed, etc. Specifically, benefiting from the well-developed technologies of photonic chips and optical fibers in telecom and datacom, the 2D materials-based modulators integrated on these photonic structures are expected to find applications in fiber and chip optical communications. The free-space mid-infrared and terahertz modulators based on 2D materials can expect application in chemical bond spectroscopy, free-space communications, and environment/health sensing.

Current-induced switching of a ferromagnetic Weyl semimetal Co2MnGa

Wed, 24 Nov 2021 00:00:00 GMT

Current-induced switching of a ferromagnetic Weyl semimetal Co2MnGa Han, Jiahao; McGoldrick, Brooke C; Chou, Chung-Tao; Safi, Taqiyyah S; Hou, Justin T; Liu, Luqiao The introduction of magnetic moments to topological materials provides rich opportunities for studying the interplay among magnetism, electron correlation, and topological orders, which can give rise to exotic magnetoelectric effects and allow one to manipulate the topological band structure via spintronic approaches. Here, we report current-induced switching in a thin film of ferromagnetic Weyl semimetal Co2MnGa with perpendicular magnetic anisotropy, via the spin–orbit torque from a neighboring heavy metal Pt. The reversal of the large anomalous Hall signal indicates an effective electrical control of the Berry curvatures associated with the Weyl nodes in the topological band structure. The efficiency of the spin–orbit torque switching is calibrated to be comparable to that in conventional ferromagnets. Given the compatibility of Co2MnGa films with various spintronic devices and techniques, our work represents an essential step toward memory and computing devices built by topological ferromagnetic materials.

Super-resolved second harmonic generation imaging by coherent image scanning microscopy

Fri, 18 Feb 2022 00:00:00 GMT

Super-resolved second harmonic generation imaging by coherent image scanning microscopy Raanan, Dekel; Song, Man Suk; Tisdale, William A; Oron, Dan We extend image scanning microscopy to second harmonic generation (SHG) by extracting the complex field amplitude of the second-harmonic beam. While the theory behind coherent image scanning microscopy (ISM) is known, an experimental demonstration was not yet established. The main reason is that the naive intensity-reassignment procedure cannot be used for coherent scattering as the point spread function is now defined for the field amplitude rather than for the intensity. We use an inline interferometer to demonstrate super-resolved phase-sensitive SHG microscopy by applying the ISM reassignment machinery on the resolved field. This scheme can be easily extended to third harmonic generation and stimulated Raman microscopy schemes.

Sub-50 cm/s surface recombination velocity in InGaAsP/InP ridges

Mon, 08 Nov 2021 00:00:00 GMT

Sub-50 cm/s surface recombination velocity in InGaAsP/InP ridges Andrade, Nicolas M; Hooten, Sean; Kim, Yunjo; Kim, Jeehwan; Yablonovitch, Eli; Wu, Ming C The III–V InP/InGaAsP/InGaAs material family is important for photonic devices due to its optical emission and absorption in the 1.55 and 1.3 lm telecommunication bands for optical interconnects. However, InGaAsP/InGaAs generally suffer from relatively high surface recombination velocity—compared to Si [Das et al., in 2020 47th IEEE Photovoltaic Specialists Conference (PVSC) (IEEE, Calgary, AB, 2020), pp. 1167–1170] and InP [Joyce et al., Nano Lett. 12, 5325–5330 (2012)], which reduces the efficiency and can increase the noise in nanophotonic devices. Here, we demonstrate an efficient method to passivate the surface using a combination of sulfur-saturated ammonium sulfide and atomic layer deposition. After annealing, the surface passivation led to a surface recombination velocity as low as 45 cm/s, corresponding to a >180 increase in the photoluminesence of a nanoscale light-emitting device with 200 nm width.

Emerging GaN technologies for power, RF, digital, and quantum computing applications: Recent advances and prospects

Fri, 29 Oct 2021 00:00:00 GMT

Emerging GaN technologies for power, RF, digital, and quantum computing applications: Recent advances and prospects Hoo Teo, Koon; Zhang, Yuhao; Chowdhury, Nadim; Rakheja, Shaloo; Ma, Rui; Xie, Qingyun; Yagyu, Eiji; Yamanaka, Koji; Li, Kexin; Palacios, Tomás GaN technology is not only gaining traction in power and RF electronics but is also rapidly expanding into other application areas including digital and quantum computing electronics. This paper provides a glimpse of future GaN device technologies and advanced modeling approaches that can push the boundaries of these applications in terms of performance and reliability. While GaN power devices have recently been commercialized in the 15–900 V classes, new GaN devices are greatly desirable to explore both higher-voltage and ultra-low-voltage power applications. Moving into the RF domain, ultra-high frequency GaN devices are being used to implement digitized power amplifier circuits, and further advances using the hardware–software co-design approach can be expected. On the horizon is the GaN CMOS technology, a key missing piece to realize the full-GaN platform with integrated digital, power, and RF electronics technologies. Although currently a challenge, high-performance p-type GaN technology will be crucial to realize high-performance GaN CMOS circuits. Due to its excellent transport characteristics and ability to generate free carriers via polarization doping, GaN is expected to be an important technology for ultra-low temperature and quantum computing electronics. Finally, given the increasing cost of hardware prototyping of new devices and circuits, the use of high-fidelity device models and data-driven modeling approaches for technology-circuit co-design are projected to be the trends of the future. In this regard, physically inspired, mathematically robust, less computationally taxing, and predictive modeling approaches are indispensable. With all these and future efforts, we envision GaN to become the next Si for electronics.

Underscreening and hidden ion structures in large scale simulations of concentrated electrolytes

Fri, 01 Oct 2021 00:00:00 GMT

Underscreening and hidden ion structures in large scale simulations of concentrated electrolytes Krucker-Velasquez, Emily; Swan, James W The electrostatic screening length predicted by Debye–Hückel theory decreases with increasing ionic strength, but recent experiments have found that the screening length can instead increase in concentrated electrolytes. This phenomenon, referred to as underscreening, is believed to result from ion–ion correlations and short-range forces such as excluded volume interactions among ions. We use Brownian Dynamics to simulate a version of the Restrictive Primitive Model for electrolytes over a wide range of ion concentrations, ionic strengths, and ion excluded volume radii for binary electrolytes. We measure the decay of the charge–charge correlation among ions in the bulk and compare it against scaling trends found experimentally and determined in certain weak coupling theories of ion–ion correlation. Moreover, we find that additional large scale ion structures emerge at high concentrations. In this regime, the frequency of oscillations computed from the charge–charge correlation function is not dominated by electrostatic interactions but rather by excluded volume interactions and with oscillation periods on the order of the ion diameter. We also find the nearest neighbor correlation of ions sharing the same charge transitions from negative at small concentrations to positive at high concentrations, representing the formation of small, like-charge ion clusters. We conclude that the increase in local charge density due to the formation of these clusters and the topological constraints of macroscopic charged surfaces can help explain the degree of underscreening observed experimentally.

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs

Mon, 22 Nov 2021 00:00:00 GMT

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.

A deep learning augmented genetic algorithm approach to polycrystalline 2D material fracture discovery and design

Fri, 10 Dec 2021 00:00:00 GMT

A deep learning augmented genetic algorithm approach to polycrystalline 2D material fracture discovery and design Lew, Andrew J; Buehler, Markus J The gestalt of computational methods including physics-based molecular dynamics simulations, data-driven machine learning (ML) models, and biologically-inspired genetic algorithms affords a powerful toolbox for tackling materials mechanism discovery and design problems. Here, we leverage these methods to investigate the complex multidimensional problem of polycrystalline 2D material fracture. We focus first on graphene and in doing so, demonstrate a practical workflow for exploring the structural dependencies of fracture energy. Despite training our ML model on exclusively single crystal fracture in increments of 10° orientations, we can identify a crack branching mechanism responsible for high bicrystal toughness centered at initial crystal orientation angles of 19° and 41°. These high peaks span only a few degrees in range and are completely overlooked by a search with stride 10°. Furthermore, we can discover qualitative physical phenomena such as collective fracture branch termination and extract quantitative trends relating angular dispersion and mis-orientation angles of crystal grains to fracture energy. None of these complex polycrystalline behaviors were presented in the training data, and the predictive power of the model ultimately allows us to expeditiously generate polycrystalline graphene structures with bespoke fracture paths, a task with great implications in industrial design applications and mechanism discovery. Furthermore, the approach is not limited to graphene specifically, as we demonstrate by retraining the model for another more complex 2D material—MoS2—and achieve polycrystalline fracture predictions of comparable accuracy.

Estimating the task content of work: workforce design for AI-driven human-robot collaboration in intralogistics

Sun, 22 Mar 2026 00:00:00 GMT

Estimating the task content of work: workforce design for AI-driven human-robot collaboration in intralogistics Bouquet, Pierre; Bagnoli, Nicolò Piergiovanni; Sheffi, Yossi This paper addresses the challenge of strategic workforce planning for AI-driven human-robot collaboration (AI-HRC) in intralogistics. We ask two questions: how can task-level full-time equivalent (FTE) estimates be constructed from existing labour statistics, and how can these estimates, combined with AI exposure metrics, inform strategic AI-HRC design and workforce planning? Drawing on U.S. Bureau of Labor Statistics employment data, O∗NET occupational profiles, and task-level AI exposure scores, we develop a stochastic task-time framework that decomposes occupations into tasks and models task frequencies as probability vectors on the simplex. A covariance-completion procedure reconstructs task covariance matrices consistent with survey standard errors, enabling the translation of occupational data into task-level and detailed work activity (DWA)-level FTE estimates with uncertainty bounds. Applying the framework to the U.S. intralogistics workforce, we find that approximately 370,000 FTEs (about 17% of workers) are concentrated in the top 15% most AIexposed DWAs. These results provide task-specific insight into AI-driven automation and support scenario-based workforce planning by linking alternative AI-HRC adoption paths to task-level FTE impacts, uncertainty bands, and upskilling priorities, thereby offering an analytical foundation for resilient, human-centered AI-HRC systems.

The stress in a dispersion of mutually polarizable spheres

Thu, 01 Jul 2021 00:00:00 GMT

The stress in a dispersion of mutually polarizable spheres Reed, KM; Swan, JW Dispersions of dielectric and paramagnetic nanoparticles polarize in response to an external electric or magnetic field and can form chains or other ordered structures depending on the strength of the applied field. The mechanical properties of these materials are of interest for a variety of applications; however, computational studies in this area have so far been limited. In this work, we derive expressions for two important properties for dispersions of polarizable spherical particles with dipoles induced by a uniform external field—the isothermal stress tensor and the pressure. Numerical calculations of these quantities, evaluated using a spectrally accurate Ewald summation method, are validated using thermodynamic integration. We also compare the stress obtained using the mutual dipole model, which accounts for the mutual polarization of particles, to the stress expected from calculations using a fixed dipole model, which neglects mutual polarization. We find that as the conductivity of the particles increases relative to the surrounding medium, the fixed dipole model does not accurately describe the dipolar contribution to the stress. The thermodynamic pressure, calculated from the trace of the stress tensor, is compared to the virial expression for the pressure, which is simpler to calculate but inexact. We find that the virial pressure and the thermodynamic pressure differ, especially in suspensions with a high volume fraction of particles.

Wind farm yaw control set-point optimization under model parameter uncertainty

Wed, 21 Jul 2021 00:00:00 GMT

Wind farm yaw control set-point optimization under model parameter uncertainty Howland, Michael F Wake steering, the intentional yaw misalignment of certain turbines in an array, has demonstrated potential as a wind farm control approach to increase collective power. Existing algorithms optimize the yaw misalignment angle set-points using steady-state wake models and either deterministic frameworks or optimizers that account for wind direction and yaw misalignment variability and uncertainty. Wake models rely on parameterizations of physical phenomena in the mean flow field, such as the wake spreading rate. The wake model parameters are uncertain and vary in time at a wind farm depending on the atmospheric conditions, including turbulence intensity, stability, shear, veer, and other atmospheric features. In this study, we develop a yaw set-point optimization approach that includes model parameter uncertainty in addition to wind condition variability and uncertainty. To enable computationally efficient online set-point optimization under model parameter uncertainty, a simplified, approximate parameter distribution estimation method is used. The optimization is tested in open-loop control numerical experiments using utility-scale wind farm operational data for which the set-point optimization framework with parametric uncertainty has a statistically significant impact on the wind farm power production for certain wind turbine layouts at low turbulence intensity, but the results are not significant for all layouts considered nor at higher turbulence intensity. The set-point optimizer is also tested for closed-loop wake steering control of a model wind farm in large eddy simulations of a convective atmospheric boundary layer (ABL). The yaw set-point optimization with model parameter uncertainty reduced the sensitivity of the closed-loop wake steering control to increases in the yaw controller update frequency. Increases in wind farm power production were not statistically significant due to the high ambient power variability in the turbulent, convective ABL.

Native oxide reconstructions on AlN and GaN (0001) surfaces

Wed, 19 May 2021 00:00:00 GMT

Native oxide reconstructions on AlN and GaN (0001) surfaces Mirrielees, Kelsey J; Dycus, J Houston; Baker, Jonathon N; Reddy, Pramod; Collazo, Ramón; Sitar, Zlatko; LeBeau, James M; Irving, Douglas L Properties of AlN/GaN surfaces are important for realizing the tunability of devices, as the presence of surface states contributes to Fermi level pinning. This pinning can influence the performance of high electron mobility transistors and is also important for passivation of the surface when developing high-power electronic devices. It is widely understood that both AlN and GaN surfaces oxidize. Since there are many possible reconstructions for each surface, it is a challenge to identify the relevant surface reconstructions in advance of a detailed simulation. Because of this, different approaches are often employed to down select initial structures to reduce the computational load. These approaches usually rely on either electron counting rules or oxide stoichiometry, as both of these models tend to lead to structures that are energetically favorable. Here we explore models from these approaches but also explore a reconstruction of the (0001) surface directly observed using scanning transmission electron microscopy with predictive density functional theory simulations. Two compositions of the observed surface reconstruction—one which obeys oxide stoichiometry and one which is cation deficient and obeys electron counting—are compared to reconstructions from the previous work. Furthermore, surface states are directly calculated using hybrid exchange-correlation functionals that correct for the underestimation of the bandgaps in AlN and GaN and improve the predicted positions of surface states within the gap. It is found that cation deficiency in the observed reconstruction yields surface states consistent with the experiment. Based on all of these results, we provide insight into the observed properties of oxidized AlGaN surfaces.

Chemical kinetic mechanisms and scaling of two-dimensional polymers via irreversible solution-phase reactions

Mon, 17 May 2021 00:00:00 GMT

Chemical kinetic mechanisms and scaling of two-dimensional polymers via irreversible solution-phase reactions Zhang, Ge; Zeng, Yuwen; Gordiichuk, Pavlo; Strano, Michael S Two-dimensional (2D) polymers are extended networks of multi-functional repeating units that are covalently linked together but confined to a single plane. The past decade has witnessed a surge in interest and effort toward producing and utilizing 2D polymers. However, facile synthesis schemes suitable for mass production are yet to be realized. In addition, unifying theories to describe the 2D polymerization process, such as those for linear polymers, have not yet been established. Herein, we perform a chemical kinetic simulation to study the recent synthesis of 2D polymers in homogeneous solution with irreversible chemistry. We show that reaction sites for polymerization in 2D always scale unfavorably compared to 3D, growing as molecular weight to the 1/2 power vs 2/3 power for 3D. However, certain mechanisms can effectively suppress out-of-plane defect formation and subsequent 3D growth. We consider two such mechanisms, which we call bond-planarity and templated autocatalysis. In the first, although single bonds can easily rotate out-of-plane to render polymerization in 3D, some double-bond linkages prefer a planar configuration. In the second mechanism, stacked 2D plates may act as van der Waals templates for each other to enhance growth, which leads to an autocatalysis. When linkage reactions possess a 1000:1 selectivity (γ) for staying in plane vs rotating, solution-synthesized 2D polymers can have comparable size and yield with those synthesized from confined polymerization on a surface. Autocatalysis could achieve similar effects when self-templating accelerates 2D growth by a factor β of 106. A combined strategy relaxes the requirement of both mechanisms by over one order of magnitude. We map the dependence of molecular weight and yield for the 2D polymer on the reaction parameters, allowing experimental results to be used to estimate β and γ. Our calculations show for the first time from theory the feasibility of producing two-dimensional polymers from irreversible polymerization in solution.

Ionic thermoelectric materials for near ambient temperature energy harvesting

Mon, 11 Jan 2021 00:00:00 GMT

Ionic thermoelectric materials for near ambient temperature energy harvesting Liu, Weishu; Qian, Xin; Han, Cheng-Gong; Li, Qikai; Chen, Gang Ionic thermoelectric (i-TE) materials, using ions as the energy carrier, can generate a voltage under a temperature difference, bearing similarities to the Seebeck effect of electrons and holes in solid-state materials. Recent experiments have demonstrated large thermopower of quasi-solid-state i-TE materials, which are attractive for harvesting ambient heat as large enough voltage can be generated under a small temperature difference to match the voltage input needs of sensors for internet-of-things applications. In this perspective article, we discuss similarities and differences of i-TE materials from electronic-based thermoelectric materials and also different i-TE thermoelectric effects including the thermodiffusion (Soret) effect and the thermogalvanic effect, in which the latter includes redox reaction entropy and the Soret effect. Strategies to improve performances of materials and devices are elaborated, together with needs for future research in understanding microscopic origins of different effects.

Ultrafast low-temperature metal–insulator interface phonon dynamics and heat transport in a Pt/Gd3Fe5O12 heterostructure

Mon, 24 Nov 2025 00:00:00 GMT

Ultrafast low-temperature metal–insulator interface phonon dynamics and heat transport in a Pt/Gd3Fe5O12 heterostructure Sri Gyan, Deepankar; Li, Ni; Chen, Zhantao; Geprägs, Stephan; Dietlein, Maxim; Gross, Rudolf; Sato, Takahiro; Sun, Yanwen; Hoffmann, Matthias C; Zhu, Diling; Haskel, Daniel; Strempfer, Jörg; Li, Mingda; Mannix, Danny; Evans, Paul G Interfacial thermal and acoustic phenomena have an important role in quantum science and technology, including in spintronic and spincaloritronic materials and devices. Simultaneous measurements of the low-temperature thermal and acoustic properties of a metal/insulator heterostructure reveal distinct dynamics in the characteristic phonon frequency ranges of acoustic and thermal transport. The measurements probed a heterostructure consisting of a thin film of Pt on the ferrimagnetic insulator gadolinium iron garnet (Gd3Fe5O12, GdIG) grown epitaxially on a gadolinium gallium garnet substrate. Ultrafast structural dynamics within the Pt layer were tracked using time-resolved ultrafast x-ray diffraction and analyzed to probe interfacial acoustic and thermal properties. The rapid heating of the Pt layer by a 400 nm wavelength femtosecond-duration optical pulse produced transient structural changes that provided the stimulus for these measurements. Rapid heating produced a broadband acoustic pulse that was partially reflected by the Pt/GdIG interface. Temporal frequencies up to 740 GHz, corresponding to angular frequencies of several THz, were detected in a wavelet analysis of the acoustic oscillations of the strain in the Pt layer. The structural results were analyzed to determine (i) the acoustic damping coefficient and phonon mean free path in Pt at frequencies of hundreds of GHz and (ii) the Grüneisen anharmonicity parameter. The thermal conductance of the Pt/GdIG interface was tracked using the slower, tens-of-picosecond-scale, dynamics of the initial cooling of the heated Pt layer. Analysis using a model based on the Boltzmann transport equation shows that the phonon transmission is lower at the phonon frequencies relevant to thermal transport than for subterahertz regime acoustics.

Two-dimensional electron gases as non-Newtonian fluids

Mon, 30 Oct 2023 00:00:00 GMT

Two-dimensional electron gases as non-Newtonian fluids Kryhin, Serhii; Levitov, Leonid Two-dimensional electron systems offer an appealing platform to explore long-lived excitations arising due to collinear carrier scattering enabled by phase-space constraints at the Fermi surface. Recently it was found that these effects can boost excitation lifetimes over the fundamental bound set by Landau’s Fermi-liquid theory by a factor as large as (TF/T)α with α≈2. Long-lived degrees of freedom possess the capability to amplify the response to weak perturbations, producing lasting collective memory effects. This leads to non-Newtonian hydrodynamics in 2D electron fluids driven by multiple viscous modes with scale-dependent viscosity. We describe these modes as Fermi surface modulations of odd parity evolving in space and time, and discuss their implications for experimental studies of electron hydrodynamics.

Humpback whale (Megaptera novaeangliae) breathing sound characteristics from simultaneous above and underwater measurements

Tue, 01 Apr 2025 00:00:00 GMT

Humpback whale (Megaptera novaeangliae) breathing sound characteristics from simultaneous above and underwater measurements Radermacher, Max K; Schinault, Matthew E; Seri, Sai Geetha; Mohebbi-Kalkhoran, Hamed; Makris, Nicholas C; Ratilal, Purnima Humpback whale breathing-related sounds were recorded on elements of a coherent hydrophone array subaperture deployed vertically at the Great South Channel on the US Northeastern continental shelf in Fall 2021, where half of the hydrophones were in-air and the rest submerged underwater. In-air hydrophones recorded breathing sounds with approximately 2.5 s duration, but smaller bandwidths compared to underwater hydrophones where signal energies extended beyond 50 kHz, and a mean underwater source level of 161 ± 4 dB re 1 μPa at 1 m, based on measurements at 22.9 m. The underwater recorded humpback whale breathing sound spectra displayed a broadband dip centered at 15.7 kHz, with approximately 400 Hz half-power bandwidth, likely caused by attenuation from propagation through pulsating air bubbles. The air bubble radius for natural frequency of oscillations at 15.7 kHz is estimated to be 0.205–0.21 mm. These bubbles are capable of removing energy from the forward propagated humpback breathing sounds via resonance absorption most pronounced at and near bubble natural oscillation frequency. Humpback whale distances from the vertically deployed hydrophones are estimated and tracked by matching the curved nonlinear travel-time wavefront of its breathing sounds, since the whale was in the near-field of the subarray.

Estimation of the spatial variability of the New England Mud Patch geoacoustic properties using a distributed array of hydrophones and deep learning

Fri, 06 Dec 2024 00:00:00 GMT

Estimation of the spatial variability of the New England Mud Patch geoacoustic properties using a distributed array of hydrophones and deep learning Vardi, Ariel; Dahl, Peter H; Dall'Osto, David; Knobles, David; Wilson, Preston; Leonard, John; Bonnel, Julien This article presents a spatial environmental inversion scheme using broadband impulse signals with deep learning (DL) to model a single spatially-varying sediment layer over a fixed basement. The method is applied to data from the Seabed Characterization Experiment 2022 (SBCEX22) in the New England Mud-Patch (NEMP). Signal Underwater Sound (SUS) explosive charges generated impulsive signals recorded by a distributed array of bottom-moored hydrophones. The inversion scheme is first validated on a range-dependent synthetic test set simulating SBCEX22 conditions, then applied to experimental data to predict the lateral spatial structure of sediment sound speed and its ratio with the interfacial water sound speed. Traditional geoacoustic inversion requires significant computational resources. Here, a neural network enables rapid single-signal inversion, allowing the processing of 1836 signals along 722 tracks. The method is applied to both synthetic and experimental data. Results from experimental data suggest an increase in both absolute compressional sound speed and sound speed ratio from southwest to northeast in the NEMP, consistent with published coring surveys and geoacoustic inversion results. This approach demonstrates the potential of DL for efficient spatial geoacoustic inversion in shallow water environments.

The JIBO Kids Corpus: A speech dataset of child-robot interactions in a classroom environment

Fri, 01 Nov 2024 00:00:00 GMT

The JIBO Kids Corpus: A speech dataset of child-robot interactions in a classroom environment Shankar, Natarajan Balaji; Afshan, Amber; Johnson, Alexander; Mahapatra, Aurosweta; Martin, Alejandra; Ni, Haolun; Park, Hae Won; Perez, Marlen Quintero; Yeung, Gary; Bailey, Alison; Breazeal, Cynthia; Alwan, Abeer This paper describes an original dataset of children's speech, collected through the use of JIBO, a social robot. The dataset encompasses recordings from 110 children, aged 4–7 years old, who participated in a letter and digit identification task and extended oral discourse tasks requiring explanation skills, totaling 21 h of session data. Spanning a 2-year collection period, this dataset contains a longitudinal component with a subset of participants returning for repeat recordings. The dataset, with session recordings and transcriptions, is publicly available, providing researchers with a valuable resource to advance investigations into child language development.

Range-dynamical low-rank split-step Fourier method for the parabolic wave equation

Wed, 30 Oct 2024 00:00:00 GMT

Range-dynamical low-rank split-step Fourier method for the parabolic wave equation Charous, Aaron; Lermusiaux, Pierre FJ Numerical solutions to the parabolic wave equation are plagued by the curse of dimensionality coupled with the Nyquist criterion. As a remedy, a new range-dynamical low-rank split-step Fourier method is developed. The integration scheme scales sub-linearly with the number of classical degrees of freedom in the transverse directions. It is orders of magnitude faster than the classic full-rank split-step Fourier algorithm and saves copious amounts of storage space. This enables numerical solutions of the parabolic wave equation at higher frequencies and on larger domains, and simulations may be performed on laptops rather than high-performance computing clusters. Using a rank-adaptive scheme to optimize the low-rank equations further ensures the approximate solution is highly accurate and efficient. The methodology and algorithms are demonstrated on realistic high-resolution data-assimilative ocean fields in Massachusetts Bay for two three-dimensional acoustic configurations with different source locations and frequencies. The acoustic pressure, transmission loss, and phase solutions are analyzed in the two geometries with seamounts and canyons across and along Stellwagen Bank. The convergence with the rank of the subspace and the properties of the rank-adaptive scheme are demonstrated, and all results are successfully compared with those of the full-rank method when feasible.

Replayed reef sounds induce settlement of Favia fragum coral larvae in aquaria and field environments

Mon, 21 Oct 2024 00:00:00 GMT

Replayed reef sounds induce settlement of Favia fragum coral larvae in aquaria and field environments Aoki, Nadège; Weiss, Benjamin; Jézéquel, Youenn; Apprill, Amy; Mooney, T Aran Acoustic cues of healthy reefs are known to support critical settlement behaviors for one reef-building coral, but acoustic responses have not been demonstrated in additional species. Settlement of Favia fragum larvae in response to replayed coral reef soundscapes were observed by exposing larvae in aquaria and reef settings to playback sound treatments for 24–72 h. Settlement increased under 24 h sound treatments in both experiments. The results add to growing knowledge that acoustically mediated settlement may be widespread among stony corals with species-specific attributes, suggesting sound could be one tool employed to rehabilitate and build resilience within imperiled reef communities.

A deep learning method for reflective boundary estimation

Mon, 01 Jul 2024 00:00:00 GMT

A deep learning method for reflective boundary estimation Arikan, Toros; Weiss, Amir; Vishnu, Hari; Deane, Grant B; Singer, Andrew C; Wornell, Gregory W Environment estimation is a challenging task in reverberant settings such as the underwater and indoor acoustic domains. The locations of reflective boundaries, for example, can be estimated using acoustic echoes and leveraged for subsequent, more accurate localization and mapping. Current boundary estimation methods are constrained to high signal-to-noise ratios or are customized to specific environments. Existing methods also often require a correct assignment of echoes to boundaries, which is difficult if spurious echoes are detected. To evade these limitations, a convolutional neural network (NN) method is developed for robust two-dimensional boundary estimation, given known emitter and receiver locations. A Hough transform-inspired algorithm is leveraged to transform echo times of arrival into images, which are amenable to multi-resolution regression by NNs. The same architecture is trained on transform images of different resolutions to obtain diverse NNs, deployed sequentially for increasingly refined boundary estimation. A correct echo labeling solution is not required, and the method is robust to reverberation. The proposed method is tested in simulation and for real data from a water tank, where it outperforms state-of-the-art alternatives. These results are encouraging for the future development of data-driven three-dimensional environment estimation with high practical value in underwater acoustic detection and tracking.

Dynamically orthogonal narrow-angle parabolic equations for stochastic underwater sound propagation. Part I: Theory and schemes

Thu, 25 Jan 2024 00:00:00 GMT

Dynamically orthogonal narrow-angle parabolic equations for stochastic underwater sound propagation. Part I: Theory and schemes Ali, Wael H; Lermusiaux, Pierre FJ Robust informative acoustic predictions require precise knowledge of ocean physics, bathymetry, seabed, and acoustic parameters. However, in realistic applications, this information is uncertain due to sparse and heterogeneous measurements and complex ocean physics. Efficient techniques are thus needed to quantify these uncertainties and predict the stochastic acoustic wave fields. In this work, we derive and implement new stochastic differential equations that predict the acoustic pressure fields and their probability distributions. We start from the stochastic acoustic parabolic equation (PE) and employ the instantaneously-optimal Dynamically Orthogonal (DO) equations theory. We derive stochastic DO-PEs that dynamically reduce and march the dominant multi-dimensional uncertainties respecting the nonlinear governing equations and non-Gaussian statistics. We develop the dynamical reduced-order DO-PEs theory for the Narrow-Angle parabolic equation and implement numerical schemes for discretizing and integrating the stochastic acoustic fields.

Dynamically orthogonal narrow-angle parabolic equations for stochastic underwater sound propagation. Part II: Applications

Thu, 25 Jan 2024 00:00:00 GMT

Dynamically orthogonal narrow-angle parabolic equations for stochastic underwater sound propagation. Part II: Applications The stochastic dynamically orthogonal (DO) narrow-angle parabolic equations (NAPEs) are exemplified and their properties and capabilities are described using three new two-dimensional stochastic range-independent and range-dependent test cases with uncertain sound speed field, bathymetry, and source location. We validate results against ground-truth deterministic analytical solutions and direct Monte Carlo (MC) predictions of acoustic pressure and transmission loss fields. We verify the stochastic convergence and computational advantages of the DO-NAPEs and discuss the differences with normal mode approaches. Results show that a single DO-NAPE simulation can accurately predict stochastic range-dependent acoustic fields and their non-Gaussian probability distributions, with computational savings of several orders of magnitude when compared to direct MC methods. With their coupling properties and their adaptation in range to the dominant uncertainties, the DO-NAPEs are shown to predict accurate statistics, from mean and variance to multiple modes and full probability distributions, and to provide excellent reconstructed realizations, from amplitudes and phases to other specific properties of complex realization fields.

Weird A.I.

Wed, 18 Mar 2026 00:00:00 GMT

Weird A.I. Lindquist, Benjamin This essay sketches out what I call “weird AI”: probabilistic, associative systems that behave as if they feel. It shows how midcentury architects of artificial neural networks deliberately courted the uncanny as they engineered space for intuition, emotion, and nonrational thought, even as standard histories cast computing as an Enlightenment project of calculation and control. To make sense of artificial intelligence’s past and present, historians must move beyond an information-centric framework and reckon with the affective undercurrents that have shaped the field from its start.

Vibrotactile stimulation at gamma frequency mitigates pathology related to neurodegeneration and improves motor function

Thu, 18 May 2023 00:00:00 GMT

Vibrotactile stimulation at gamma frequency mitigates pathology related to neurodegeneration and improves motor function Suk, Ho-Jun; Buie, Nicole; Xu, Guojie; Banerjee, Arit; Boyden, Edward S; Tsai, Li-Huei The risk for neurodegenerative diseases increases with aging, with various pathological conditions and functional deficits accompanying these diseases. We have previously demonstrated that non-invasive visual stimulation using 40 Hz light flicker ameliorated pathology and modified cognitive function in mouse models of neurodegeneration, but whether 40 Hz stimulation using another sensory modality can impact neurodegeneration and motor function has not been studied. Here, we show that whole-body vibrotactile stimulation at 40 Hz leads to increased neural activity in the primary somatosensory cortex (SSp) and primary motor cortex (MOp). In two different mouse models of neurodegeneration, Tau P301S and CK-p25 mice, daily exposure to 40 Hz vibrotactile stimulation across multiple weeks also led to decreased brain pathology in SSp and MOp. Furthermore, both Tau P301S and CK-p25 mice showed improved motor performance after multiple weeks of daily 40 Hz vibrotactile stimulation. Vibrotactile stimulation at 40 Hz may thus be considered as a promising therapeutic strategy for neurodegenerative diseases with motor deficits.

Traffic management protocols for advanced air mobility

Wed, 17 May 2023 00:00:00 GMT

Traffic management protocols for advanced air mobility Chin, Christopher; Qin, Victor; Gopalakrishnan, Karthik; Balakrishnan, Hamsa The demand for advanced air mobility (AAM) operations is expected to be at a much larger scale than conventional aviation. Additionally, AAM flight operators are likely to compete in providing a range of on-demand services in congested airspaces, with varying operational costs. These characteristics motivate the need for the development of new traffic management algorithms for advanced air mobility. In this paper, we explore the use of traffic management protocols (“rules-of-the-road” for airspace access) to enable efficient and fair operations. First, we show that it is possible to avoid gridlock and improve efficiency by leveraging the concepts of cycle detection and backpressure. We then develop a cost-aware traffic management protocol based on the second-price auction. Using simulations of representative advanced air mobility scenarios, we demonstrate that our traffic management protocols can help balance efficiency and fairness, in both the operational and the economic contexts.

If blockchain is the solution, robot security is the problem

Tue, 16 May 2023 00:00:00 GMT

If blockchain is the solution, robot security is the problem Ferrer, Eduardo Castelló Robotics systems of all types are revolutionizing a wide variety of industries—transportation, manufacturing, and even healthcare—and yet, many essential ingredients for robotics systems in the real world are not technologically ready for deployment. Currently, robots lack the protocols and standards required to be safe and secure outside factories. In an attempt to close this gap, recent research has demonstrated the security benefits of combining robotics systems with blockchain-based and related technologies (e.g., smart contracts, zero-knowledge proofs, Merkle trees). In this perspective article, I argue that blockchain-based robotics is starting to provide innovative solutions (e.g., secure data sharing, consensus mechanisms, and new interaction methods) to urgent problems of robot security. I list the most important takeaways so far from this emerging field of research that I helped establish together with a growing community. I close the article by discussing the implications of the security challenges that the robotics research community is facing, and possible ways for us to move forward.

Quantification of heat vulnerability using system dynamics

Tue, 04 Apr 2023 00:00:00 GMT

Quantification of heat vulnerability using system dynamics Bayomi, Norhan; Fernandez, John E One of the major climate threats is extreme heat events, as they pose significant risks to public health that are well documented in the epidemiologic literature. The effects of extreme heat events have been evident over the past years by several extreme heat events worldwide. With the growing concerns of future heat exposure, numerous studies in the literature have developed heat vulnerability indices based on determinants that have heat-related impacts. However, there has been limited guidance on heat vulnerability assessment that accounts for the impacts of the characteristics of the built environment and changes in population dynamics over time. This paper focuses on developing the methodology for heat vulnerability assessment in urban areas using System Dynamics (SD) based on integrating three levels of the physical urban environment: the urban level, the building level, and the human adaptive capacity to heat exposure. We examine the viability of using SD modeling as an approach to examine the key drivers in heat vulnerability assessment in urban areas. Thus, the paper assesses the dynamic relationship between heat vulnerability components, namely, Susceptibility, Exposure, Coping Capacity, and Adaptive Capacity, and their effect on increased or decreased vulnerability under extreme heat events. The paper concludes with an applied case study in Cairo, Egypt, to test the use of the SD approach in assessing heat vulnerability in urban settings. Results from the proposed SD model confirm the underlying hypothesis that vulnerability from heat exposure is dynamically linked to the coping and adaptive capacity of the surrounding built environment with the urban population’s socioeconomic characteristics. The main contribution of this approach is that it allows for parallel examination of the effect of the human system that simulation models cannot include and the performance of the built environment system that epidemic heat vulnerability studies cannot capture.

Predicting one-year left ventricular mass index regression following transcatheter aortic valve replacement in patients with severe aortic stenosis: A new era is coming

Tue, 04 Apr 2023 00:00:00 GMT

Predicting one-year left ventricular mass index regression following transcatheter aortic valve replacement in patients with severe aortic stenosis: A new era is coming Asheghan, Mohammad Mostafa; Javadikasgari, Hoda; Attary, Taraneh; Rouhollahi, Amir; Straughan, Ross; Willi, James Noel; Awal, Rabina; Sabe, Ashraf; de la Cruz, Kim I; Nezami, Farhad R Aortic stenosis (AS) is the most common valvular heart disease in the western world, particularly worrisome with an ever-aging population wherein postoperative outcome for aortic valve replacement is strongly related to the timing of surgery in the natural course of disease. Yet, guidelines for therapy planning overlook insightful, quantified measures from medical imaging to educate clinical decisions. Herein, we leverage statistical shape analysis (SSA) techniques combined with customized machine learning methods to extract latent information from segmented left ventricle (LV) shapes. This enabled us to predict left ventricular mass index (LVMI) regression a year after transcatheter aortic valve replacement (TAVR). LVMI regression is an expected phenomena in patients undergone aortic valve replacement reported to be tightly correlated with survival one and five year after the intervention. In brief, LV geometries were extracted from medical images of a cohort of AS patients using deep learning tools, and then analyzed to create a set of statistical shape models (SSMs). Then, the supervised shape features were extracted to feed a support vector regression (SVR) model to predict the LVMI regression. The average accuracy of the predictions was validated against clinical measurements calculating root mean square error and R2 score which yielded the satisfactory values of 0.28 and 0.67, respectively, on test data. Our work reveals the promising capability of advanced mathematical and bioinformatics approaches such as SSA and machine learning to improve medical output prediction and treatment planning.

Aesthetic chills cause an emotional drift in valence and arousal

Tue, 07 Mar 2023 00:00:00 GMT

Aesthetic chills cause an emotional drift in valence and arousal Jain, Abhinandan; Schoeller, Felix; Horowitz, Adam; Hu, Xiaoxiao; Yan, Grace; Salomon, Roy; Maes, Pattie Aesthetic chills are an embodied peak emotional experience induced by stimuli such as music, films, and speeches and characterized by dopaminergic release. The emotional consequences of chills in terms of valence and arousal are still debated and the existing empirical data is conflicting. In this study, we tested the effects of ChillsDB, an open-source repository of chills-inducing stimuli, on the emotional ratings of 600+ participants. We found that participants experiencing chills reported significantly more positive valence and greater arousal during the experience, compared to participants who did not experience chills. This suggests that the embodied experience of chills may influence one’s perception and affective evaluation of the context, in favor of theoretical models emphasizing the role of interoceptive signals such as chills in the process of perception and decision-making. We also found an interesting pattern in the valence ratings of participants, which tended to harmonize toward a similar mean after the experiment, though initially disparately distributed. We discuss the significance of these results for the diagnosis and treatment of dopaminergic disorders such as Parkinson’s, schizophrenia, and depression.

On projection and the shadow of [wh]

Thu, 01 Jan 2026 00:00:00 GMT

On projection and the shadow of [wh] Newman, Elise Much work has shown that wh-movement is subject to several kinds of locality restrictions cross-linguistically. I propose that these restrictions arise when [wh] projects past the maximal projection that it came from. When this happens, it intervenes for whmovement, trapping the wh-element in its base position, unless it can escape through other means. The need to escape the domain of [wh] is proposed to capture the distribution of successive-cyclic movement and interactions with Voice in different languages. Different locality conditions in different languages are captured by different distributions of the same features and probes.

Discussion of “Experimental Design and Modeling for Forward-Inverse Maps” by R. Barton & M. Morris, appearing in Technometrics

Tue, 20 May 2025 00:00:00 GMT

Discussion of “Experimental Design and Modeling for Forward-Inverse Maps” by R. Barton & M. Morris, appearing in Technometrics Marzouk, Youssef M. Inverse design—essentially the problem of finding system parameter values that achieve a given performance metric—is an enormously important problem across a wide range of engineering fields. Typical methods for inverse design employ a forward model for example, a complex computer simulation mapping design parameters to performance metrics, and embed it in an optimization loop. If the forward model is a black box, for which direct evaluation of gradients is intractable, then one must resort to derivative-free or so-called “zeroth order” optimization approaches (e.g., Močkus Citation1975; Jones, Schonlau, and Welch Citation1998; Conn, Scheinberg, and Vicente Citation2009; Larson, Menickelly, and Wild Citation2019). Most of these approaches iteratively construct a metamodel for the forward map during optimization. Barton and Morris (henceforth “the authors” or “BM”) propose instead to build an inverse metamodel, that is, a computationally inexpensive approximation of the performance metric-to-parameter map. The promise of such an inverse metamodel is that it makes inverse design much faster and more direct, bypassing the need for explicit optimization.

Where Are All the CFOs?

Tue, 03 Mar 2026 00:00:00 GMT

Where Are All the CFOs? Wright, Randall S. In my 38 years with MIT’s Office of Corporate Relations, where I worked with and advised executives, I saw chief executive officers (CEOs), company presidents, managing directors, general managers, chief information officers (CIOs), chief technology officers (CTOs), vice presidents, chief scientists, chief counsels, directors of innovation hubs, managers of strategic alliances, technology entrepreneurs, managers of supply chains, presidents of European Trade Commissions, scientific attachés, senior NATO officers, ministers of economics, speakers of parliaments, chancellors, governors, Members of Congress . . .

An Alternative to Probability Tables for Modeling Unresolved Resonance Behavior

Wed, 17 Dec 2025 00:00:00 GMT

An Alternative to Probability Tables for Modeling Unresolved Resonance Behavior Ridley, Gavin; Forget, Benoit We first review the requirements of Monte Carlo neutron transport codes to accurately model the phenomena associated with the unresolved resonance regime and present the first rigorous justification for the modeling assumption employed by probability tables for unresolved resonances. We present a new method named AURA (analytic unresolved resonance algorithm) for modeling unresolved resonance cross-sections with the normal inverse Gaussian distribution. The new method accurately models temperature dependence in the unresolved resonance region (URR), requires fewer data than previous methods, and outperforms the conventional URR treatment on GPUs.

Direct Sampling of the Egelstaff-Schofield Scattering Law and the Phonon Sampling Method for Liquids

Mon, 15 Dec 2025 00:00:00 GMT

Direct Sampling of the Egelstaff-Schofield Scattering Law and the Phonon Sampling Method for Liquids Ridley, Gavin; Forget, Benoit The phonon sampling method (PSM) enables accurate and efficient simulation of thermal neutron scattering from solids; it obviates a substantial degree of discretization, enabling continuous representations of scattering law behavior across a variety of conditions. Despite these strengths, the PSM relies on the phonon expansion, which only applies to solid materials. To remove this limitation, we demonstrate an efficient sampling algorithm for the nonsymmetric translational 𝒮⁡(𝛼,𝛽) distribution of Egelstaff and Schofield, and show how this can be used to extend the PSM for the simulation of thermal neutron scattering in materials exhibiting mixed translational and vibrational behavior, such as water or molten salts. We demonstrate the correctness of the method with example results for scattering from room temperature water at a few incident neutron energies.

Preliminary Verification of Fixed-Source Sensitivity Analysis in OpenMC

Fri, 02 Jan 2026 00:00:00 GMT

Preliminary Verification of Fixed-Source Sensitivity Analysis in OpenMC Ebiwonjumi, Bamidele; Forget, Benoit; Peterson, Ethan Sensitivity analysis capabilities have yet to find extensive use in fusion reactor design applications where they can help understand the impact of nuclear data uncertainties on the tritium breeding ratio (TBR), shutdown dose rates, and nuclear heating. Significant uncertainty exists in nuclear data for fusion applications, and the goal of this work is to explore whether adjoint- and perturbation theory–based eigenvalue and generalized response sensitivity methods recently developed within the OpenMC Monte Carlo code can be extended to fixed-source Monte Carlo radiation transport simulations. This paper presents a derivation for the extended sensitivity analysis method. The adjoint-based sensitivity coefficients are compared with Monte Carlo SERPENT sensitivity coefficients for a TBR calculation in a simplified ARC-class tokamak. Further verification with the Monte Carlo MCSEN and deterministic ASUSD sensitivity coefficients for the tritium production rate in the Frascati neutron generator helium-cooled pebble bed test blanket module mock-up experiment was performed. The OpenMC sensitivity coefficients were found to agree with the other code systems. The use of the sensitivity coefficients with nuclear data covariance within the sandwich rule for cross-section uncertainty propagation also showed good agreement with the reference total Monte Carlo nuclear data uncertainty.

Supply chain mapping through retrieval-augmented generation: applications to the electronics industry

Fri, 19 Dec 2025 00:00:00 GMT

Supply chain mapping through retrieval-augmented generation: applications to the electronics industry Jackson, Ilya; Saénz, Maria Jesus; Ivanov, Dmitry; Ma, Benedict Jun This paper presents a novel methodology for automated multi-tier supply chain mapping, leveraging Retrieval-Augmented Generation (RAG) and network science techniques. We developed an RAG-based approach that extracts supplier-customer relationships from unstructured public data sources, including SEC 10-K filings and earnings calls. The extracted entities are structured into a directed supply chain graph and analysed using network science metrics such as centrality, modularity, and path length. The case study focuses on three of the largest contract manufacturers in the electronics industry: Hon Hai Precision Industry (Foxconn), Flex Ltd., and Jabil Inc. Our findings demonstrate that Generative AI (GAI), specifically LLMs enhanced with RAG, can construct scalable and comprehensive supply chain graphs. The proof of concept is successful, as evidenced by the construction of a directed supply chain graph encompassing 4,644 nodes and 8,341 edges, covering three of the largest contract manufacturers in the electronics industry.

Quantifying Flash Flood Inundation and Assessing Damage Using Satellite Earth Observations: The Case of 2022 Flash Flood in Bangladesh

Fri, 02 Jan 2026 00:00:00 GMT

Quantifying Flash Flood Inundation and Assessing Damage Using Satellite Earth Observations: The Case of 2022 Flash Flood in Bangladesh Sariful, Md; Mitra, Juthi Rani; Rahman, Munshi Khaledur Floods pose significant threats to Bangladesh, frequently causing the loss of lives, properties, infrastructure, and livelihoods. This study examines the spatial and temporal dynamics of the 2022 Sylhet flood by integrating Sentinel-1 Synthetic Aperture Radar (SAR) imagery with socioeconomic datasets. Otsu thresholding method was used to estimate water extent before, during, and after the 2022 flood event in the Sylhet region. Results suggest that over 1,600 km² of land in Sylhet division was inundated, with Habiganj district experiencing the highest surge. More than half a million people were directly impacted, alongside significant damage to cropland and urban areas. Furthermore, the study highlighted substantial impacts on urban built-up areas and cropland across districts. Cumulative cropland damage increased from 3376.30 km² in June to 4701.30 km² in July, indicating severe consequences for agricultural productivity. Concurrently, the affected built-up areas were found to be 40.9 km², emphasizing the impact on human settlements. By providing a detailed assessment of flood extent and damage, this study provides valuable insights for policymakers, planners, and disaster management authorities. The findings support the development of targeted strategies for flood risk reduction, agricultural resilience, and the mitigation of future disaster impacts in vulnerable regions of Bangladesh.

GeoXCP: uncertainty quantification of spatial explanations in explainable AI

Fri, 10 Oct 2025 00:00:00 GMT

GeoXCP: uncertainty quantification of spatial explanations in explainable AI Lou, Xiayin; Luo, Peng; Li, Ziqi; Gao, Song; Meng, Liqiu Understanding and explaining complex geographic phenomena—ranging from climate change to socioeconomic disparities—is a central focus in both geography and the broader scientific community. Various methods have been developed to elucidate relationships between variables, from coefficient estimates in linear regression models to the increasingly dominant use of feature attribution scores in Explainable AI (XAI) techniques. However, explanations generated by XAI methods often carry uncertainty, stemming from the model itself and the data used to train the model. Despite the critical importance of accounting for such uncertainty, this issue remains largely overlooked in the geospatial domain. In this study, we developed an uncertainty quantification framework for XAI explanations based on conformal prediction, termed Geospatial eXplanation Conformal Prediction (GeoXCP). By incorporating spatial dependence into the modeling process, GeoXCP produced spatially adaptive explanations with calibrated uncertainty estimates. We validated the effectiveness of GeoXCP through extensive simulation experiments and real-world datasets. The results demonstrated that GeoXCP provided reliable explanations while effectively quantifying uncertainty across diverse geospatial scenarios. Our approach represented a significant advancement in explainable geospatial machine learning, enabling decision-makers to better assess the trustworthiness of model-driven insights. The proposed framework was implemented in a python package, named GeoXCP.

Rapidly innovating firms: patent lifecycle and support for trade and IP enforcement

Wed, 04 Mar 2026 00:00:00 GMT

Rapidly innovating firms: patent lifecycle and support for trade and IP enforcement Cha, Sujin; Lee, Jieun; Osgood, Iain; Park, Sojun The rate of technological innovation and the speed with which old technologies are discarded are fundamental features of industries in the modern economy. How do these factors shape the politics of trade and trade agreements? We describe two potential channels. In one, rapid innovators support trade agreements and trade liberalization because of their privileged competitive position at the cutting edge of innovation. In the other, rapid innovators support trade agreements and intellectual property (IP) enforcement due to their particular need for speed in patent approval and enforcement. By matching data on patent lifecycles to data on United States (US) tariffs and corporate support for trade agreements and IP enforcement, we test these two theoretical accounts. We find evidence consistent with both. We conclude that rapidly innovating firms are strong supporters of globalization, though their political successes have also contributed to contention over the contemporary international order, both at home and abroad.

Grounding infrastructure: community ownership of an international cooperation project in Kibera, Nairobi

Fri, 06 Feb 2026 00:00:00 GMT

Grounding infrastructure: community ownership of an international cooperation project in Kibera, Nairobi Williams, Sarah; Carolini, Gabriella International infrastructure projects are deeply ensconced in debates about power, intentions, and imaginaries of progress that also stir debate about what it means to decolonize international relations and projects that nominally build improvements in low-income environments. Traditional prioritization of technical expertise, the criticality of contextual knowledge, and the dynamics of uneven partnerships involved are all central elements of these pronounced tensions in the practice of international infrastructure development. This paper instead describes an international infrastructure project that is centred on community stewardship and co-design. The infrastructure project Living Data Hubs (LDH), highlighted here, is a small-scale information and communication technology (ICT) and data management project in the informal settlement of Kibera in Nairobi, Kenya. In its development, equal attention was afforded to technical, conceptual, and procedural knowledge production, ensuring that both universal and contextual elements of the ICT infrastructure and data management were explicitly discussed and valued. We argue that international partnerships like LDH that give space to technical, conceptual, and procedural capacity building alike can produce community stewarded infrastructure that is sustainable and puts forward a pathway for diminishing uneven power relations and enhancing community well-being.

Writing revolutions:1 From Haiti to MIT to Palestine through the lenses of linguistics and history for decolonization and liberation

Writing revolutions:1 From Haiti to MIT to Palestine through the lenses of linguistics and history for decolonization and liberation DeGraff, Michel In this reflexive essay, I explore, through historical and linguistic lenses, the similarities between the freedom struggles of Haitians and Palestinians. One of my goals is to uncover certain pervasive mechanisms of oppression and resistance. As I do so, I reflect on my personal and professional journey as a Haitian scholar–activist at MIT, highlighting the political repression I have faced after proposing an elective “Special Topics” seminar on language and linguistics for decolonization and liberation in Haiti, Palestine and Israel. Employing distinct yet complementary analytical approaches, I dissect the complex interplay between language and history in the Haitian and Palestinian struggles. By integrating historical perspectives with linguistic analysis, I illustrate how these elements collectively contribute to forging paths toward decolonization and liberation, at both the individual and collective levels.

Advancing Pedestrian Models: A Comparative Review and Vision for the Future

Mon, 23 Feb 2026 00:00:00 GMT

Advancing Pedestrian Models: A Comparative Review and Vision for the Future Zafri, Niaz Mahmud; Sevtsuk, Andres Problem, research strategy, and findings Pedestrian mobility is essential for creating sustainable, healthy, and equitable cities, yet pedestrian modeling remains underdeveloped compared with vehicle-centric approaches. To advance the state of the art, we critically review four available pedestrian modeling frameworks—urban network analysis (UNA), multi-agent transport simulation (MATSim), model of pedestrian demand (MoPeD), and spatial design network analysis (sDNA)—through the lens of the traditional four-step transportation modeling framework. We assess their methodological foundations, capabilities, practical applications, and limitations and outline future directions for improving modeling practice. UNA and sDNA offer high-resolution, trip-based network analyses; MATSim supports agent- and activity-based multimodal simulations; and MoPeD estimates grid-level pedestrian demand. Despite these strengths, several key gaps remain: Most models focus predominantly on utilitarian walking, neglect leisure and social activities, typically assume homogeneous pedestrian behavior by overlooking sociodemographic variations, face shortcomings with mode choice estimation, and are rarely applied in informal urban contexts. Furthermore, limited availability of pedestrian count data continues to constrain effective model calibration and validation. Takeaway for practice We propose that researchers and planners adopt a human-centered, inclusive, and policy-aligned modeling agenda, emphasizing simple yet intuitive metrics that capture the full spectrum of walking benefits, supporting early-stage planning even in data-scarce contexts, fostering stronger collaboration with practitioners, and promoting a modular, adaptable modeling ecosystem. Ultimately, reorienting pedestrian models as flexible decision support tools—rather than narrowly focused forecasting instruments—can meaningfully support the development of more walkable cities.

Reasons for Non-Agents

Mon, 16 Sep 2024 00:00:00 GMT

Reasons for Non-Agents Watkins, Eliot According to a standard picture, normative reasons do not extend beyond the boundaries of agency. If something isn’t an agent, then there can’t be normative reasons for it to do one thing rather than another. This paper argues that the standard picture is false. There are reasons for smoke detectors to alarm when exposed to smoke, and for Venus Flytraps to close around their prey when stimulated. I argue that the collapse of the standard picture has important implications for philosophical debates about reasons, and especially serious consequences for theories that analyse normative reasons in terms of the standards of good practical reasoning.

Fully 3D-Printed Electric Motor Manufactured via Multi-Modal, Multi-Material Extrusion

Fri, 02 Jan 2026 00:00:00 GMT

Fully 3D-Printed Electric Motor Manufactured via Multi-Modal, Multi-Material Extrusion Cañada, Jorge; Bigelow, Zoey; Velásquez-García, Luis Fernando Material extrusion additive manufacturing can process a wide variety of functional materials including electrically conductive, magnetic, and mechanically compliant polymer composites. While filaments developed for 3D printing often exhibit limited functionality, highly loaded functional composites originally formulated for specialised manufacturing processes can be processed via material extrusion. In this work, a commercial multi-material extrusion 3D printer was modified to process conductive inks, soft and hard magnetic composite pellets, and rigid and compliant polymeric filaments. Using this system, solenoids, hard magnets, and springs were fabricated. These components were combined through straightforward assembly to demonstrate the first fully 3D-printed electric motor — a linear actuator composed of five distinct functional materials: dielectric, electrically conductive, soft magnetic, hard magnetic, and flexible. The solenoids produced up to 2.03 mT magnetic fields, the magnets generated up to 71 mT magnetic fields, and the linear actuator attained a maximum displacement of 318 μm at its resonant frequency (41.6 Hz). This study demonstrates the capability of multi-modal, multi-material extrusion 3D printing to fabricate all critical components of electrical machines, with magnetisation of the hard magnets being the only post-printing step. This milestone advances multi-material, multi-functional 3D printing towards implementing in-situ, customised, low-waste, and low-cost functional hardware.

Partial Identification of Individual-Level Parameters Using Aggregate Data in a Nonparametric Model

Mon, 08 Dec 2025 00:00:00 GMT

Partial Identification of Individual-Level Parameters Using Aggregate Data in a Nonparametric Model Moon, Sarah I develop a methodology to partially identify linear combinations of conditional mean outcomes when the researcher only has access to aggregate data. Unlike the existing literature, I only allow for marginal, not joint, distributions of covariates in my model of aggregate data. Bounds are obtained by solving an optimization program and can easily accommodate additional polyhedral shape restrictions. I provide a procedure to construct confidence intervals on the identified set and demonstrate the performance of my method in a simulation study. In an empirical illustration of the method using Rhode Island standardized exam data, I find that conditional pass rates vary across student subgroups and across counties.

Shaping suburbia: the one-and-a-half-century evolution of setback regulations in American neighbourhood development

Thu, 15 Jan 2026 00:00:00 GMT

Shaping suburbia: the one-and-a-half-century evolution of setback regulations in American neighbourhood development Zhu, Chenhao; Ben-Joseph, Eran A comprehensive understanding of setback regulations is vital to American neighbourhood development and ongoing zoning reform efforts; however, the topic remains underexplored. By examining zoning codes, historical documents, norms, and development plans, this study traces the evolution of setback regulations from the 19th century to the present. The results map out the historical trajectory of setback regulations, highlight their evolving roles in shaping neighbourhood development, and synthesize the regulatory and dimensional trends. Building on the findings, insights are offered into the multifaceted roles of setbacks, the implications of identified historical periods, and recommendations for innovating future setback regulations.

The European Union’s CBAM: averting emissions leakage or promoting the diffusion of carbon pricing?

Thu, 13 Nov 2025 00:00:00 GMT

The European Union’s CBAM: averting emissions leakage or promoting the diffusion of carbon pricing? Mehling, Michael A.; Dolphin, Geoffroy; Ritz, Robert A. Adopted in 2023, the Carbon Border Adjustment Mechanism (CBAM) is a significant component of the European Union’s ambitious decarbonization strategy under the European Green Deal. This article questions the output effectiveness of the CBAM in achieving its stated objective, prevention of carbon leakage, while demonstrating its impact effectiveness as an instrument for advancing the global diffusion of carbon pricing. Empirical evidence for carbon leakage remains sparse, and implementation challenges might limit the capacity of the CBAM to counteract leakage even where it occurs. Nonetheless, the CBAM has already demonstrated a powerful spillover effect by incentivizing the acceleration of carbon pricing roadmaps across EU trade partners, suggesting that trade-related climate measures can effectively encourage global climate action. As the EU navigates the complexities of operationalizing the CBAM, it must balance several tradeoffs to maintain this important spillover effect. If successful, the CBAM could catalyze a virtuous cycle of carbon pricing adoption, reinforcing its potentially pivotal role in the EU’s toolbox to manage the environment-trade nexus.

Shadow players of the eviction crisis: identifying and characterizing professional evicting attorneys in Massachusetts

Mon, 17 Nov 2025 00:00:00 GMT

Shadow players of the eviction crisis: identifying and characterizing professional evicting attorneys in Massachusetts Aizman, Asya; Huntley, Eric Robsky This paper examines an under-studied class of actors in the housing system: attorneys representing landlords. We use a cluster-detection algorithm to identify salient clusters of attorneys based on their scale of operations. We then characterize these groups—what we call professional, active, less active, and least active evicting and tenant attorneys—using metrics related to the geographic scope of their practice, their prevalence in eviction court, case outcomes, and client base. We find that there are large differences between the practices of professional and less active landlord attorneys: professional attorneys’ cases are resolved more quickly, more regularly result in executions, affect more varied geographies, and have a greater proportion of institutional clients. Placed in a growing body of literature on eviction and advocacy for tenants’ Right to Counsel, we argue that professional evicting attorneys—most of whom are named or founding principal—are not neutral actors, but are contributing to the worsening eviction crisis in class solidarity with landlords.

Adaptive Digital Twin Modeling with Control: Integration of Extended Kalman Filter-Based Recursive Sparse Nonlinear Identification with Model Predictive Control

Mon, 09 Mar 2026 00:00:00 GMT

Adaptive Digital Twin Modeling with Control: Integration of Extended Kalman Filter-Based Recursive Sparse Nonlinear Identification with Model Predictive Control Wang, Jingyi; Cao, Liang; Cao, Yankai; Gopaluni, Bhushan The adoption of digital twins has revolutionized industrial process simulation, monitoring, and control effectiveness. However, practical implementations of digital twins are hindered by substantial challenges, including extended development time, diminishing model accuracy, and restricted interactive capabilities. Addressing these critical issues, this paper proposes a comprehensive digital twin development framework that integrates digital twin identification, real-time model updating, and advanced process control. The proposed approach first identifies the offline digital twin model through the sparse identification of a nonlinear dynamics algorithm, reducing the digital twin development time while maintaining model fidelity. Then, the identified model is updated by the extended Kalman filter to mitigate the problem of diminishing accuracy. Finally, incorporating the latest updated model into the model predictive control facilitates the control inputs optimization and enhances the interactive capacity of digital twins. Through one industrial case study and two simulation examples, the advantages of the proposed algorithm are demonstrated.

FastComposer: Tuning-Free Multi-subject Image Generation with Localized Attention

Thu, 19 Sep 2024 00:00:00 GMT

FastComposer: Tuning-Free Multi-subject Image Generation with Localized Attention Xiao, Guangxuan; Yin, Tianwei; Freeman, William T.; Durand, Frédo; Han, Song Diffusion models excel at text-to-image generation, especially in subject-driven generation for personalized images. However, existing methods are inefficient due to the subject-specific fine-tuning, which is computationally intensive and hampers efficient deployment. Moreover, existing methods struggle with multi-subject generation as they often blend identity among subjects. We present FastComposer which enables efficient, personalized, multi-subject text-to-image generation without fine-tuning. FastComposer uses subject embeddings extracted by an image encoder to augment the generic text conditioning in diffusion models, enabling personalized image generation based on subject images and textual instructions with only forward passes. To address the identity blending problem in the multi-subject generation, FastComposer proposes cross-attention localization supervision during training, enforcing the attention of reference subjects localized to the correct regions in the target images. Naively conditioning on subject embeddings results in subject overfitting. FastComposer proposes delayed subject conditioning in the denoising step to maintain both identity and editability in subject-driven image generation. FastComposer generates images of multiple unseen individuals with different styles, actions, and contexts. It achieves 300 $$\times $$ × –2500 $$\times $$ × speedup compared to fine-tuning-based methods and requires zero extra storage for new subjects. FastComposer paves the way for efficient, personalized, and high-quality multi-subject image creation. Code, model, and dataset are available here ( https://github.com/mit-han-lab/fastcomposer ).

Molecular Mechanisms of Liver Metastasis: Connecting Biology, Biomarkers, and Outcomes

Thu, 05 Mar 2026 00:00:00 GMT

Molecular Mechanisms of Liver Metastasis: Connecting Biology, Biomarkers, and Outcomes Wagner, Doris; Balzer, Felix; Margonis, Georgios Antonios In our Special Issue titled “Molecular Mechanisms of Liver Metastases,” we aimed to attract articles that connect metastasis mechanisms and biomarkers with clinical disease characteristics and patient outcomes. Starting with the review paper by the Ohio State group, the authors provide valuable insight into the complex, multi-step molecular mechanisms underpinning liver metastasis [1]. Moving from pathogenesis to the prognostic and predictive role of clinically actionable proxies of tumor biology, the University of California, San Francisco (UCSF) group reviews current evidence on the prognostic and predictive relevance of key alterations—including RAS, BRAF, mismatch repair (MMR) genes, TP53, and SMAD4—in surgically treated colorectal liver metastases (CRLMs) [2]. For RAS and BRAF in particular—given the breadth of existing evidence—the authors emphasize the largest and/or the most recently published studies to provide the most robust and contemporary overview for readers.

Stability and Reactivity of Alternative Nucleobases in Concentrated Sulfuric Acid

Tue, 03 Mar 2026 00:00:00 GMT

Stability and Reactivity of Alternative Nucleobases in Concentrated Sulfuric Acid Huang, Jingcheng; Seager, Sara; Seager, Maxwell D.; Petkowski, Janusz J. Recent findings demonstrate that concentrated sulfuric acid supports rich organic chemistry, including the stability of the canonical DNA bases adenine, thymine, guanine and cytosine. Yet, due to full protonation in concentrated sulfuric acid, these bases may not pair as effectively as they do in water. We are therefore motivated to study nucleic acid bases that pair via hydrophobic and van der Waals interactions instead of canonical hydrogen bonding. Here, we investigate the stability of 14 selected, commercially available alternative nucleobases in concentrated sulfuric acid to evaluate their potential for forming DNA-like polymers in this solvent. The reactivity of compounds 1–14 have not been previously investigated in concentrated sulfuric acid. We incubate the selected compounds in 98% and 81% w/w sulfuric acid and monitor their stability using 1H and 13C NMR spectroscopy over 3 weeks at room temperature. In 98% w/w sulfuric acid, six bases—benzo[c][1,2,5]thiadiazole (1), 2,2′-bipyridine (2), 1,1′-biphenyl (3), 1-methoxy-3-methylbenzene (MMO2) (7) and 1-chloro-3-methoxybenzene (ClMO) (13), and 2,4-difluorotoluene (14)—remain soluble and stable with no detectable degradation. A few compounds show non-destructive reactivity, like sulfonation (compound 3) or H/D exchange (compounds 7, 13, 14). The other compounds react rapidly or are insoluble in 98% w/w sulfuric acid. In 81% w/w sulfuric acid, only compounds 1 and 2 remain stable and soluble, while other selected compounds are insoluble or unstable. Our findings identify a subset of alternative bases stable in concentrated sulfuric acid, advancing efforts towards the design of an example genetic-like polymer in this unusual solvent. Our work further highlights sulfuric acid’s potential for supporting complex organic chemistry, with implications for astrobiology, planetary science of Venus and synthetic biology.

Examining the Uptake and Effectiveness of the Climate Justice Instructional Toolkit

Tue, 24 Feb 2026 00:00:00 GMT

Examining the Uptake and Effectiveness of the Climate Justice Instructional Toolkit Rabe, Chris; Schlegel, Madeline; Mitchell, Pearl Climate justice is an accelerating global movement in which education plays a vital role in building awareness, understanding and catalyzing action. Yet, many institutions of higher education face persistent barriers to integrating climate justice across disciplines, including limited institutional focus, lack of faculty expertise, and, more recently, heightened political constraints. In response, climate justice educators have proposed a range of strategies—such as conducting faculty workshops, hosting events, offering incentives, increasing funding, and developing curricular tools—though few studies have examined how curricular resources themselves can advance climate justice education. The Climate Justice Instructional Toolkit (CJIT) was developed to address this gap by providing accessible, adaptable materials to help instructors, even those with limited prior experience, incorporate climate and environmental justice into diverse disciplines. Using a novel survey tool across multiple educational contexts, this study used a mixed methods approach to analyze 76 survey responses to evaluate the CJIT’s effectiveness and user experiences among postsecondary instructors, K–12 teachers, and students. The findings showed broad positive feedback regarding the toolkit’s adaptability and utility while underscoring the need for stronger inclusion of Indigenous perspectives, greater socioeconomic accountability, and more attention to solutions and resilience. Respondents also emphasized that inclusive design, community engagement, and institutional support are critical for advancing climate justice integration and empowering educators in this work.

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems

Tue, 22 Apr 2025 00:00:00 GMT

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems Wu, Xinyi; Loveland, Donald; Chen, Runjin; Liu, Yozen; Chen, Xin; Neves, Leonardo; Jadbabaie, Ali; Ju, Mingxuan; Shah, Neil; Zhao, Tong Deep recommender systems rely heavily on large embedding tables to handle high-cardinality categorical features such as user/item identifiers, and face significant memory constraints at scale. To tackle this challenge, hashing techniques are often employed to map multiple entities to the same embedding and thus reduce the size of the embedding tables. Concurrently, graph-based collaborative signals have emerged as powerful tools in recommender systems, yet their potential for optimizing embedding table reduction remains unexplored. This paper introduces GraphHash, the first graph-based approach that leverages modularity-based bipartite graph clustering on user-item interaction graphs to reduce embedding table sizes. We demonstrate that the modularity objective has a theoretical connection to message-passing, which provides a foundation for our method. By employing fast clustering algorithms, GraphHash serves as a computationally efficient proxy for message-passing during preprocessing and a plug-and-play graph-based alternative to traditional ID hashing. Extensive experiments show that GraphHash substantially outperforms diverse hashing baselines on both retrieval and click-through-rate prediction tasks. In particular, GraphHash achieves on average a 101.52% improvement in recall when reducing the embedding table size by more than 75%, highlighting the value of graph-based collaborative information for model reduction. Our code is available at https://github.com/snap-research/GraphHash. WWW ’25, April 28-May 2, 2025, Sydney, NSW, Australia

Mindful young brains and minds: a systematic review of the neural correlates of mindfulness-based interventions in youth

Mon, 03 Mar 2025 00:00:00 GMT

Mindful young brains and minds: a systematic review of the neural correlates of mindfulness-based interventions in youth Jande, Jovan; Treves, Isaac N.; Ely, Samantha L.; Gowatch, Leah C.; Carpenter, Carmen; Shampine, MacKenna; Webb, Christian A.; Sacchet, Matthew D.; Gabrielli, John D. E.; Marusak, Hilary A. This systematic narrative review examines neuroimaging studies that investigated the neural correlates of mindfulness-based interventions in youth (ages 0–18). We extracted 13 studies with a total of 467 participants aged 5–18 years from the MEDLINE database on February 21st, 2024. These studies included both typically developing youth and those at risk of developing or recovering from neuropsychiatric disorders. Most studies (76.9%) utilized a pre-post intervention design, with resting-state functional magnetic resonance imaging (fMRI) being the most common imaging modality (46.1%), followed by task-based fMRI (38.4%), diffusion-weighted imaging (15.4%), and structural MRI (7.7%). Despite substantial heterogeneity across study designs and findings, several consistent patterns emerged. Resting-state fMRI studies generally reported increased functional connectivity within and between networks, notably involving the salience network, frontoparietal network, and default mode network. Studies using diffusion-weighted imaging indicated enhancements in white matter microstructural properties, supporting overall connectivity improvements. Several task-based fMRI studies identified decreased activation of the default mode network and heightened reactivity of the salience network during or after mindfulness practice, with real-time neurofeedback further amplifying these effects. While preliminary, the reviewed studies suggest that mindfulness interventions may alter both functional and structural connectivity and activity in youth, potentially bolstering self-regulation and cognitive control. Nonetheless, the variability in methodologies and small sample sizes restricts the generalizability of these results. Future research should prioritize larger and more diverse samples, and standardized mindfulness-based interventions to deepen our understanding of the neural mechanisms underlying mindfulness-based interventions in youth and to optimize their efficacy.

Theory Instead of Experiment (TIE): A Creator Valuation System at Tencent

Sun, 03 Aug 2025 00:00:00 GMT

Theory Instead of Experiment (TIE): A Creator Valuation System at Tencent Huang, Lei; Zhang, Juanjuan Experiments are informative but should be used judiciously as a costly resource. Well-constructed theory may serve as a substitute. We develop a ''Theory Instead of Experiment'' (TIE) framework and, in collaboration with Tencent, apply the framework to assess how much value (e.g., user clicks) each creator contributes to its WeChat Official Accounts Platform. This TIE application models content demand and supply upon the counterfactual departure of a creator. The demand model predicts user clicks based on estimated user preferences, while the supply model captures the platform's content distribution response. Together, they predict how each creator influences user engagement through the platform's content distribution strategy. We test the predictions of the TIE system with 168 experiments, each examining a different mix of creators and involving more than 9 million unique users. The TIE system and the experiments demonstrate a 97% correlation on the key performance metric (change in user clicks). Based on its low costs, high accuracy, granular output, and minimal latency, Tencent has deployed the TIE system as the default approach to creator valuation, assessing tens of millions of creators each day while avoiding a 2.5% user click loss associated with a typical experiment. KDD ’25, Toronto, ON, Canada

The Seasonal Cycle of Atmospheric Heating and Temperature

Mon, 15 Jul 2013 00:00:00 GMT

The Seasonal Cycle of Atmospheric Heating and Temperature Donohoe, Aaron; Battisti, David S The seasonal cycle of the heating of the atmosphere is divided into a component due to direct solar absorption in the atmosphere and a component due to the flux of energy from the surface to the atmosphere via latent, sensible, and radiative heat fluxes. Both observations and coupled climate models are analyzed. The vast majority of the seasonal heating of the northern extratropics (78% in the observations and 67% in the model average) is due to atmospheric shortwave absorption. In the southern extratropics, the seasonal heating of the atmosphere is entirely due to atmospheric shortwave absorption in both the observations and the models, and the surface heat flux opposes the seasonal heating of the atmosphere. The seasonal cycle of atmospheric temperature is surface amplified in the northern extratropics and nearly barotropic in the Southern Hemisphere; in both cases, the vertical profile of temperature reflects the source of the seasonal heating. In the northern extratropics, the seasonal cycle of atmospheric heating over land differs markedly from that over the ocean. Over the land, the surface energy fluxes complement the driving absorbed shortwave flux; over the ocean, they oppose the absorbed shortwave flux. This gives rise to large seasonal differences in the temperature of the atmosphere over land and ocean. Downgradient temperature advection by the mean westerly winds damps the seasonal cycle of heating of the atmosphere over the land and amplifies it over the ocean. The seasonal cycle in the zonal energy transport is 4.1 PW. Finally, the authors examine the change in the seasonal cycle of atmospheric heating in 11 models from phase 3 of the Coupled Model Intercomparison Project (CMIP3) due to a doubling of atmospheric carbon dioxide from preindustrial concentrations. The seasonal heating of the troposphere is everywhere enhanced by increased shortwave absorption by water vapor; it is reduced where sea ice has been replaced by ocean, which increases the effective heat storage reservoir of the climate system and thereby reduces the seasonal magnitude of energy fluxes between the surface and the atmosphere. As a result, the seasonal amplitude of temperature increases in the upper troposphere (where atmospheric shortwave absorption increases) and decreases at the surface (where the ice melts).

Mechanistic modeling explains the production dynamics of recombinant adeno-associated virus with the baculovirus expression vector system

Thu, 14 Sep 2023 00:00:00 GMT

Mechanistic modeling explains the production dynamics of recombinant adeno-associated virus with the baculovirus expression vector system Destro, Francesco; Joseph, John; Srinivasan, Prasanna; Kanter, Joshua M; Neufeld, Caleb; Wolfrum, Jacqueline M; Barone, Paul W; Springs, Stacy L; Sinskey, Anthony J; Cecchini, Sylvain; Kotin, Robert M; Braatz, Richard D Current manufacturing processes for recombinant adeno-associated viruses (rAAVs) have less-than-desired yields and produce significant amounts of empty capsids. The increasing demand and the high cost of goods for rAAV-based gene therapies motivate development of more efficient manufacturing processes. Recently, the US Food and Drug Administration (FDA) approved the first rAAV-based gene therapy product manufactured in the baculovirus expression vector system (BEVS), a technology that demonstrated production of high titers of full capsids. This work presents a first mechanistic model describing the key extracellular and intracellular phenomena occurring during baculovirus infection and rAAV maturation in the BEVS. The model predictions are successfully validated for in-house and literature experimental measurements of the vector genome and of structural and non-structural proteins collected during rAAV manufacturing in the BEVS with the TwoBac and ThreeBac constructs. A model-based analysis of the process is carried out to identify the bottlenecks that limit full capsid formation. Vector genome amplification is found to be the limiting step for rAAV production in Sf9 cells using either the TwoBac or ThreeBac system. In turn, vector genome amplification is hindered by limiting Rep78 levels. Transgene and non-essential baculovirus protein expression in the insect cell during rAAV manufacturing also negatively influences the rAAV production yields.

PixBric: Precision Morphological Control of Pre-Stretched Fabrics Through Tessellated Primitive Geometries

Sat, 27 Sep 2025 00:00:00 GMT

PixBric: Precision Morphological Control of Pre-Stretched Fabrics Through Tessellated Primitive Geometries Youn, Hye Jun; Sara, Serena; Ishii, Hiroshi 3D printing patterns onto pre-stretched fabrics has emerged as a promising method for the rapid fabrication of self-shaping textiles. However, the influence of design parameters on morphing behavior remains insufficiently explored, often resulting in heuristic-driven decisions. This study introduces PixBric, a pixel-based textile methodology composed of primitive geometries designed to induce controlled morphing behaviors—such as undulation and bending—and mechanical properties including multistability. By parametrically adjusting geometry, thickness, and inter-pixel spacing, PixBric enables precise morphing outcomes. The framework includes a morphing simulation tool and a design chart linking geometric variables to deformation results. We also propose a streamlined fabrication protocol using biaxial pre-stretching with magnetic framing. These contributions establish a systematic design approach for the functional and interactive deployment of self-shaping textile structures. UIST Adjunct ’25, Busan, Republic of Korea

Cellular anatomy of the mouse primary motor cortex

Wed, 06 Oct 2021 00:00:00 GMT

Cellular anatomy of the mouse primary motor cortex An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input–output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture.

Pair Crossing Number, Cutwidth, and Good Drawings on Arbitrary Point Sets

Wed, 22 Jan 2025 00:00:00 GMT

Pair Crossing Number, Cutwidth, and Good Drawings on Arbitrary Point Sets Pi, Oriol S. Determining whether there exists a graph such that its crossing number and pair crossing number are distinct is an important open problem in geometric graph theory. We show that cr ( G ) = O ( pcr ( G ) 3 / 2 ) for every graph G, improving the previous best bound by a logarithmic factor. Answering a question of Pach and Tóth, we prove that the bisection width (and, in fact, the cutwidth as well) of a graph G with degree sequence d 1 , d 2 , ⋯ , d n satisfies bw ( G ) = O ( pcr ( G ) + ∑ k = 1 n d k 2 ) . Then we show that there is a constant C ≥ 1 such that the following holds: For any graph G of order n and any set S of at least n C points in general position on the plane, G admits a straight-line drawing which maps the vertices to points of S and has no more than O log n · pcr ( G ) + ∑ k = 1 n d k 2 crossings. Our proofs rely on a slightly modified version of a separator theorem for string graphs by Lee, which might be of independent interest.

Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY

Fri, 03 Feb 2023 00:00:00 GMT

Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY Kim, Colin Y; Mitchell, Andrew J; Kastner, David W; Albright, Claire E; Gutierrez, Michael A; Glinkerman, Christopher M; Kulik, Heather J; Weng, Jing-Ke Plants contain rapidly evolving specialized enzymes that support the biosynthesis of functionally diverse natural products. In coumarin biosynthesis, a BAHD acyltransferase-family enzyme COSY was recently discovered to accelerate coumarin formation as the only known BAHD enzyme to catalyze an intramolecular acyl transfer reaction. Here we investigate the structural and mechanistic basis for COSY’s coumarin synthase activity. Our structural analyses reveal an unconventional active-site configuration adapted to COSY’s specialized activity. Through mutagenesis studies and deuterium exchange experiments, we identify a unique proton exchange mechanism at the α-carbon of the o-hydroxylated trans-hydroxycinnamoyl-CoA substrates during the catalytic cycle of COSY. Quantum mechanical cluster modeling and molecular dynamics further support this key mechanism for lowering the activation energy of the rate-limiting trans-to-cis isomerization step in coumarin production. This study unveils an unconventional catalytic mechanism mediated by a BAHD-family enzyme, and sheds light on COSY’s evolutionary origin and its recruitment to coumarin biosynthesis in eudicots.

Identification and Validation of Cyclic Peptides with Mucin-Selective, Location-Specific Binding in the Gastrointestinal Tract

Fri, 11 Apr 2025 00:00:00 GMT

Identification and Validation of Cyclic Peptides with Mucin-Selective, Location-Specific Binding in the Gastrointestinal Tract Subramanian, Deepak A; Chin, Austin; Shi, Yunhua; Liu, Gary W; Langer, Robert; Traverso, Giovanni Oral drug delivery is a widely preferred method of drug administration due to its ease of use and convenience for patients. Localization of drug release in the gastrointestinal (GI) tract is important to treat localized diseases and maximize drug absorption. However, achieving drug localization in the dynamic GI tract is challenging. To address this challenge, we leveraged the geographic diversity of the GI tract by targeting its mucus layers, which coat the epithelial surfaces. These layers, composed of mucin glycoproteins, are synthesized with unique chemical compositions and expressed in different regions, making them ideal targets for drug localization. In this article, we identify cyclic peptides that bind selectively to MUC2 (in the intestines) and MUC5AC (in the stomach), serving as targeting ligands to these regions of the GI tract. We demonstrate the effectiveness of these peptides through in vitro, ex vivo, and in vivo experiments, showing that incorporating these targeting ligands can increase binding and selectivity 2-fold to the desired regions, thus potentially overcoming challenges with localizing drug distribution in oral delivery. These results indicate that cyclic peptides can be used to localize drug cargoes at certain sites in the body compared to free drugs.

Pd-Catalyzed Amination of Base-Sensitive Five-Membered Heteroaryl Halides with Aliphatic Amines

Tue, 31 Jan 2023 00:00:00 GMT

Pd-Catalyzed Amination of Base-Sensitive Five-Membered Heteroaryl Halides with Aliphatic Amines Reichert, Elaine C; Feng, Kaibo; Sather, Aaron C; Buchwald, Stephen L We report a versatile and functional-group-tolerant method for the Pd-catalyzed C–N cross-coupling of five-membered heteroaryl halides with primary and secondary amines, an important but underexplored transformation. Coupling reactions of challenging, pharmaceutically relevant heteroarenes, such as 2-H-1,3-azoles, are reported in good-to-excellent yields. High-yielding coupling reactions of a wide set of five-membered heteroaryl halides with sterically demanding α-branched cyclic amines and acyclic secondary amines are reported for the first time. The key to the broad applicability of this method is the synergistic combination of (1) the moderate-strength base NaOTMS, which limits base-mediated decomposition of sensitive five-membered heteroarenes that ultimately leads to catalyst deactivation, and (2) the use of a GPhos-supported Pd catalyst, which effectively resists heteroarene-induced catalyst deactivation while promoting efficient coupling, even for challenging and sterically demanding amines. Cross-coupling reactions between a wide variety of five-membered heteroaryl halides and amines are demonstrated, including eight examples involving densely functionalized medicinal chemistry building blocks.

Abiotic peptides as carriers of information for the encoding of small-molecule library synthesis

Thu, 02 Mar 2023 00:00:00 GMT

Abiotic peptides as carriers of information for the encoding of small-molecule library synthesis Rössler, Simon L; Grob, Nathalie M; Buchwald, Stephen L; Pentelute, Bradley L Encoding small-molecule information in DNA has been leveraged to accelerate the discovery of ligands for therapeutic targets such as proteins. However, oligonucleotide-based encoding is hampered by inherent limitations of information stability and density. In this study, we establish abiotic peptides for next-generation information storage and apply them for the encoding of diverse small-molecule synthesis. The chemical stability of the peptide-based tag allows the use of palladium-mediated reactions to efficiently synthesize peptide-encoded libraries (PELs) with broad chemical diversity and high purity. We demonstrate the successful de novo discovery of small-molecule protein ligands from PELs by affinity selection against carbonic anhydrase IX and the oncogenic protein targets BRD4(1) and MDM2. Collectively, this work establishes abiotic peptides as carriers of information for the encoding of small-molecule synthesis, leveraged herein for the discovery of protein ligands.

Studying Regioisomer Formation in the Pd‐Catalyzed Fluorination of Cyclic Vinyl Triflates: Evidence for in situ Ligand Modification

Sun, 12 Feb 2023 00:00:00 GMT

Studying Regioisomer Formation in the Pd‐Catalyzed Fluorination of Cyclic Vinyl Triflates: Evidence for in situ Ligand Modification Ye, Yuxuan; Kim, Seoung‐Tae; King, Ryan P; Baik, Mu‐Hyun; Buchwald, Stephen L Pd-catalyzed nucleophilic fluorination reactions are important methods for the synthesis of fluoroarenes and fluoroalkenes. However, these reactions can generate a mixture of regioisomeric products that are often difficult to separate. While investigating the Pd-catalyzed fluorination of cyclic vinyl triflates, we observed that the addition of a substoichiometric quantity of TESCF3 significantly improved the regioselectivity of the reaction. Herein, we report a combined experimental and computational study on the mechanism of this transformation focusing on the role of TESCF3. The poor regioselectivity of the reaction in the absence of additives results from the formation of LPd-cyclohexyne complexes (L=biaryl monophosphine ligand). When TESCF3 is added to the reaction mixture, the generation of the Pd-cyclohexyne complexes is diminished by an unexpected pathway involving the dearomatization of the ligand by nucleophilic attack from a trifluoromethyl anion (CF3−).

Room-Temperature Cu-Catalyzed Amination of Aryl Bromides Enabled by DFT-Guided Ligand Design

Thu, 16 Mar 2023 00:00:00 GMT

Room-Temperature Cu-Catalyzed Amination of Aryl Bromides Enabled by DFT-Guided Ligand Design Kim, Seoung-Tae; Strauss, Michael J; Cabré, Albert; Buchwald, Stephen L Ullmann-type C–N coupling reactions represent an important alternative to well-established Pd-catalyzed approaches due to the differing reactivity and the lower cost of Cu. While the design of anionic Cu ligands, particularly those by Ma, has enabled the coupling of various classes of aryl halides and alkyl amines, most methods require conditions that can limit their utility on complex substrates. Herein, we disclose the development of anionic N1,N2-diarylbenzene-1,2-diamine ligands that promote the Cu-catalyzed amination of aryl bromides under mild conditions. Guided by DFT calculations, these ligands were designed to (1) increase the electron density on Cu, thereby increasing the rate of oxidative addition of aryl bromides, and (2) stabilize the active anionic CuI complex via a π-interaction. Under optimized conditions, structurally diverse aryl and heteroaryl bromides and a broad range of alkyl amine nucleophiles, including pharmaceuticals bearing multiple functional groups, were efficiently coupled at room temperature. Combined computational and experimental studies support a mechanism of C–N bond formation that follows a catalytic cycle akin to the well-explored Pd-catalyzed variants. Modification of the ligand structure to include a naphthyl residue resulted in a lower energy barrier to oxidative addition, providing a 30-fold rate increase relative to what is seen with other ligands. Collectively, these results establish a new class of anionic ligands for Cu-catalyzed C–N couplings, which we anticipate may be extended to other Cu-catalyzed C–heteroatom and C–C bond-forming reactions.

Stereoselective Synthesis of Trisubstituted Alkenes via Copper Hydride-Catalyzed Alkyne Hydroalkylation

Fri, 04 Aug 2023 00:00:00 GMT

Stereoselective Synthesis of Trisubstituted Alkenes via Copper Hydride-Catalyzed Alkyne Hydroalkylation Kutateladze, Dennis A; Mai, Binh Khanh; Dong, Yuyang; Zhang, Yu; Liu, Peng; Buchwald, Stephen L Alkenes are ubiquitous in organic chemistry, yet many classes of alkenes remain challenging to access by current synthetic methodology. Herein, we report a copper hydride-catalyzed approach for the synthesis of Z-configured trisubstituted alkenes with high stereo- and regioselectivity via alkyne hydroalkylation. A DTBM-dppf-supported Cu catalyst was found to be optimal, providing a substantial increase in product yield compared to reactions conducted with dppf as the ligand. DFT calculations show that the DTBM substitution leads to the acceleration of alkyne hydrocupration through combined ground and transition state effects related to preventing catalyst dimerization and enhancing catalyst–substrate dispersion interactions, respectively. Alkyne hydroalkylation was successfully demonstrated with methyl and larger alkyl tosylate electrophiles to produce a variety of (hetero)aryl-substituted alkenes in moderate to high yields with complete selectivity for the Z stereochemically configured products. In the formation of the key C–C bond, computational studies revealed a direct SN2 pathway for alkylation of the vinylcopper intermediate with in situ-formed alkyl iodides.

Room‐Temperature Copper‐Catalyzed Etherification of Aryl Bromides

Thu, 15 Feb 2024 00:00:00 GMT

Room‐Temperature Copper‐Catalyzed Etherification of Aryl Bromides Strauss, Michael J; Greaves, Megan E; Kim, Seoung‐Tae; Teijaro, Christiana N; Schmidt, Michael A; Scola, Paul M; Buchwald, Stephen L We disclose the development of a Cu-catalyzed C−O coupling method utilizing a new N1,N2-diarylbenzene-1,2-diamine ligand, L8. Under optimized reaction conditions, structurally diverse aryl and heteroaryl bromides underwent efficient coupling with a variety of alcohols at room temperature using an L8-based catalyst. Notably, the L8-derived catalyst exhibited enhanced activity when compared to the L4-based system previously disclosed for C−N coupling, namely the ability to functionalize aryl bromides containing acidic functional groups. Mechanistic studies demonstrate that C−O coupling utilizing L8 ⋅ Cu involves rate-limiting alkoxide transmetallation, resulting in a mechanism of C−O bond formation that is distinct from previously described Pd-, Cu-, or Ni-based systems. This lower energy pathway leads to rapid C−O bond formation; a 7-fold increase relative to what is seen with other ligands. The results presented in this report overcome limitations in previously described C−O coupling methods and introduce a new ligand that we anticipate may be useful in other Cu-catalyzed C-heteroatom bond-forming reactions.

CuH-Catalyzed Regio- and Enantioselective Formal Hydroformylation of Vinyl Arenes

Thu, 09 May 2024 00:00:00 GMT

CuH-Catalyzed Regio- and Enantioselective Formal Hydroformylation of Vinyl Arenes Garhwal, Subhash; Dong, Yuyang; Mai, Binh Khanh; Liu, Peng; Buchwald, Stephen L A highly enantioselective formal hydroformylation of vinyl arenes enabled by copper hydride (CuH) catalysis is reported. Key to the success of the method was the use of the mild Lewis acid zinc triflate to promote the formation of oxocarbenium electrophiles through the activation of diethoxymethyl acetate. Using the newly developed protocol, a broad range of vinyl arene substrates underwent efficient hydroacetalization reactions to provide access to highly enantioenriched α-aryl acetal products in good yields with exclusively branched regioselectivity. The acetal products could be converted to the corresponding aldehydes, alcohols, and amines with full preservation of the enantiomeric purity. Density functional theory studies support that the key C–C bond-forming event between the alkyl copper intermediate and the oxocarbenium electrophile takes place with inversion of configuration of the Cu–C bond in a backside SE2-type mechanism.

Cu-Catalyzed Amination of Base-Sensitive Aryl Bromides and the Chemoselective N- and O-Arylation of Amino Alcohols

Wed, 26 Jun 2024 00:00:00 GMT

Cu-Catalyzed Amination of Base-Sensitive Aryl Bromides and the Chemoselective N- and O-Arylation of Amino Alcohols Strauss, Michael J; Liu, Kaylee X; Greaves, Megan E; Dahl, Jakob C; Kim, Seoung-Tae; Wu, Yong-Jin; Schmidt, Michael A; Scola, Paul M; Buchwald, Stephen L We report a general and functional-group-tolerant method for the Cu-catalyzed amination of base-sensitive aryl bromides including substrates possessing acidic functional groups and small five-membered heteroarenes. The results presented herein substantially expand the scope of Cu-catalyzed C–N coupling reactions. The combination of L8, an anionic N1,N2-diarylbenzene-1,2-diamine ligand, along with the mild base NaOTMS leads to the formation of a stable yet reactive catalyst that resists deactivation from coordination to heterocycles or charged intermediates. This system enables the use of low catalyst and ligand loadings. Exploiting the differences in nucleophile deprotonation in C–O and C–N coupling reactions catalyzed by Cu·L8 we developed a method to chemoselectively N- and O-arylate a variety of amino alcohol substrates. Employing NaOt-Bu as the base resulted exclusively in C–O coupling when the amino alcohols featured primary alcohols and more hindered amines or aniline groups. Utilizing NaOTMS enabled the ability to override the steric-based selectivity of these reactions completely and exclusively promoted C–N coupling regardless of the structure of the amino alcohol. The ability to invert the observed chemoselectivity is distinct from previously described methods that require protecting group manipulations or rely entirely on steric effects to control reactivity. These results substantially improve the scope of Cu-catalyzed C–N coupling reactions using N1,N2-diarylbenzene-1,2-diamine ligands and introduce a new chemoselective method to arylate amino alcohols.

Copper-Catalyzed Amination of Aryl Chlorides under Mild Reaction Conditions

Mon, 16 Sep 2024 00:00:00 GMT

Copper-Catalyzed Amination of Aryl Chlorides under Mild Reaction Conditions Ai, Han-Jun; Kim, Seoung-Tae; Liu, Cecilia; Buchwald, Stephen L We report a mild method for the copper-catalyzed amination of aryl chlorides. Key to the success of the method was the use of highly sterically encumbered N¹,N²-diaryl diamine ligands which resist catalyst deactivation, allowing reactions to proceed at significantly lower temperatures and with a broader scope than current protocols. A sequence of highly chemoselective C-N and C-O cross-coupling reactions were demonstrated, and mechanistic studies indicate that oxidative addition of the Cu catalyst to the aryl chlorides is rate-limiting. We anticipate that the design principles disclosed herein will help motivate further advances in Cu-catalyzed transformations of aryl chlorides.

Development of a Deactivation-Resistant Dialkylbiarylphosphine Ligand for Pd-Catalyzed Arylation of Secondary Amines

Tue, 17 Sep 2024 00:00:00 GMT

Development of a Deactivation-Resistant Dialkylbiarylphosphine Ligand for Pd-Catalyzed Arylation of Secondary Amines Feng, Kaibo; Raguram, Elaine Reichert; Howard, James R; Peters, Ellyn; Liu, Cecilia; Sigman, Matthew S; Buchwald, Stephen L Despite the prevalence of N-heteroarenes in small-molecule pharmaceuticals, Pd-catalyzed C-N cross-coupling reactions of aryl halides and amines containing these rings remain challenging due to their ability to displace the supporting ligand via coordination to the metal center. To address this limitation, we report the development of a highly robust Pd catalyst supported by a new dialkylbiarylphosphine ligand, FPhos. The FPhos-supported catalyst effectively resists N-heteroarene-mediated catalyst deactivation to readily promote C-N coupling between a wide variety of Lewis-basic aryl halides and secondary amines, including densely functionalized pharmaceuticals. Mechanistic and structural investigations, as well as principal component analysis and density functional theory, elucidated two key design features that enable FPhos to overcome the limitations of previous ligands. First, the ligated Pd complex is stabilized through its conformational preference for the O-bound isomer, which likely resists coordination by N-heteroarenes. Second, 3',5'-disubstitution on the non-phosphorus-containing ring of FPhos creates the ideal steric environment around the Pd center, which facilitates binding by larger secondary amines while mitigating the formation of off-cycle palladacycle species.

Kinetic Modeling Enables Understanding of Off-Cycle Processes in Pd-Catalyzed Amination of Five-Membered Heteroaryl Halides

Wed, 20 Nov 2024 00:00:00 GMT

Kinetic Modeling Enables Understanding of Off-Cycle Processes in Pd-Catalyzed Amination of Five-Membered Heteroaryl Halides Raguram, Elaine Reichert; Dahl, Jakob C; Jensen, Klavs F; Buchwald, Stephen L The mechanism of Pd-catalyzed amination of five-membered heteroaryl halides was investigated by integrating experimental kinetic analysis with kinetic modeling through predictive testing and likelihood ratio analysis, revealing an atypical productive coupling pathway and multiple off-cycle events. The GPhos-supported Pd catalyst, along with the moderate-strength base NaOTMS, was previously found to promote efficient coupling between five-membered heteroaryl halides and secondary amines. However, slight deviations from the optimal concentration, temperature, and/or solvent resulted in significantly lower yields, contrary to typical reaction optimization trends. We found that the coupling of 4-bromothiazole with piperidine proceeds through an uncommon mechanism in which the NaOTMS base, rather than the amine, binds first to the oxidative addition complex; the resulting OTMS-bound Pd species is the resting state. Formation of the Pd-amido complex via base/amine exchange was identified as the turnover-limiting step, unlike other reported catalyst systems for which reductive elimination is turnover-limiting. We determined that the amine-bound Pd complex, usually an on-cycle intermediate, is instead a reversibly generated off-cycle species, and that base-mediated decomposition of 4-bromothiazole is the primary irreversible catalyst deactivation pathway. Predictive testing and kinetic modeling were key to the identification of these off-cycle processes, providing insight into minor mechanistic pathways that are difficult to observe experimentally. Collectively, this report reveals the unique enabling features of the Pd-GPhos/NaOTMS system, implementing mechanistic insights to improve the yields of particularly challenging coupling reactions. Moreover, these findings highlight the utility of applying predictive tests to kinetic models for the rapid evaluation of mechanistic possibilities in small-molecule catalytic systems.

Characterization of the response of radiochromic film to quasi-monoenergetic x rays through a cross-calibration with image plates

Fri, 20 Sep 2024 00:00:00 GMT

Characterization of the response of radiochromic film to quasi-monoenergetic x rays through a cross-calibration with image plates Buschmann, BI; Cufari, M; Vanderloo, N; Vargas, J; Foo, BC; DeVault, A; Dannhoff, SG; Evans, TE; Johnson, TM; Kunimune, JH; Lawrence, Y; Pearcy, JA; Reichelt, BL; Wink, CW; Russell, L; Gatu Johnson, M; Petrasso, RD; Frenje, JA Radiochromic film (RCF) and image plates (IPs) are both commonly used detectors in diagnostics fielded at inertial confinement fusion (ICF) and high-energy-density physics (HEDP) research facilities. Due to the intense x-ray background in all ICF/HEDP experiments, accurately calibrating the optical density of RCF as a function of x-ray dose, and the photostimulated luminescence per photon of IPs as a function of x-ray energy, is necessary for interpreting experimental results. Various measurements of the sensitivity curve of different IPs to x rays have been performed [Izumi et al., Proc. SPIE 8850, 885006 (2013) and Rosenberg et al., Rev. Sci. Instrum. 90(1), 013506 (2019)]; however, calibrating RCF is a tedious process that depends on factors such as the orientation in which the RCF is scanned in the film scanner and the batch of RCF used. These issues can be mitigated by cross-calibrating RCF with IPs to enable the use of IPs for the determination of dose on the RCF without scanning the RCF. Here, the first cross-calibration of RCF with IPs to quasi-monoenergetic titanium, copper, and molybdenum K-line x rays is presented. It is found that the IP-inferred dose rates on the RCF for the Ti and Mo x rays agree well with the measured dose rates, while the IP-inferred dose rate for the Cu x rays is larger than the measured dose rate by ∼2×. Explanations for this discrepancy and plans for future work are discussed.

Determination of the response for the National Ignition Facility particle time of flight (PTOF) detector using single particle counting

Wed, 02 Oct 2024 00:00:00 GMT

Determination of the response for the National Ignition Facility particle time of flight (PTOF) detector using single particle counting Lawrence, Y; Reichelt, BL; Wink, CW; Rigon, G; Johnson, M Gatu; Li, CK; Frenje, JA The Particle Time of Flight (PTOF) detector is a chemical vapor deposition diamond-based detector used to measure bang times in low-yield (≲ 1015 neutrons) experiments at the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory (LLNL). Historically, the impulse response for PTOF diamond detectors has been obtained from x-ray timing shots on the NIF and shots on the MegaRay pulsed electron accelerator at LLNL. The impulse response may alternatively be obtained using single particle interactions with the detector, at substantially less cost and higher frequency compared to NIF timing shots, which typically occur months apart. Here, the response of a PTOF detector setup is characterized by statistically averaging a large number of single particle waveforms. A high fidelity instrument response function can be constructed in this way. This is confirmed by comparison of the single particle counting-constructed response to the impulse response function measured for the same detector at LLNL’s MegaRay facility.

Development of a compact magnetic spectrometer for use at the OMEGA Laser Facility and the National Ignition Facility

Thu, 03 Oct 2024 00:00:00 GMT

Development of a compact magnetic spectrometer for use at the OMEGA Laser Facility and the National Ignition Facility Pearcy, JA; Russell, L; Kabadi, NV; Johnson, TM; Adrian, PA; Gatu-Johnson, M; Casco, E; Palmisano, K; Gates, G; Burgett, T; Scott, M; Petrasso, RD; Li, CK; Frenje, J Measurement of proton spectra is an important diagnostic for a variety of high energy density physics experiments. Current diagnostics are either not designed to capture the spectrum of low-energy protons or are unsuitable for high debris experiments. To bridge the gap, a new CR-39 based compact magnetic spectrometer (MagSpec) has been developed to measure proton spectra in the 1–20 MeV energy range, with a particular focus on the low-energy (1–6 MeV) spectrum, for use in experiments at the OMEGA Laser Facility and the National Ignition Facility (NIF). In the MagSpec diagnostic, protons of different energies are dispersed as they pass through a magnetic field before impinging on a differentially filtered CR-39 surface, resulting in a spatial distribution of CR-39 tracks that corresponds to the energy spectrum. In this paper, we discuss details of the design and implementation of MagSpec on the NIF and OMEGA.

Temperature stabilization of a lab space at 10 mK-level over a day

Fri, 27 Sep 2024 00:00:00 GMT

Temperature stabilization of a lab space at 10 mK-level over a day Fife, Dylan; Shin, Dong-Chel; Sudhir, Vivishek Temperature fluctuations over long time scales (≳ 1 h) are an insidious problem for precision measurements. In optical laboratories, the primary effect of temperature fluctuations is drifts in optical circuits over spatial scales of a few meters and temporal scales extending beyond a few minutes. We present a lab-scale environment temperature control system approaching 10 mK-level temperature instability across a lab for integration times above an hour and extending to a day. This is achieved by passive isolation of the laboratory space from the building walls using a circulating air gap and an active control system feeding back to heating coils at the outlet of the laboratory’s Heating-Ventilation-Air-Conditioning (HVAC) unit. These techniques together result in 20 dB suppression of the temperature power spectrum across the lab at 10−4 Hz—approaching the limit set by statistical coherence of the temperature field—and 10 mK Allan deviation around 15 °C after an hour of averaging, which is an order of magnitude better than any previous report for a full laboratory.

Incentives to Comply with the Minimum Wage in the United States and the United Kingdom

Wed, 01 Jan 2025 00:00:00 GMT

Incentives to Comply with the Minimum Wage in the United States and the United Kingdom Stansbury, Anna There is substantial evidence of minimum wage non-compliance in the United States and the United Kingdom. In this article, the author compiles new, comprehensive data on the costs that minimum wage violators incur when non-compliance is detected. In both countries, the costs violators face are often little more than the money they saved by underpaying. To have an incentive to comply under existing penalty regimes, typical US firms would thus have to expect a 47% to 83% probability of detection by the Department of Labor (DOL), or a 25% probability of a successful Fair Labor Standards Act (FLSA) suit. In the United Kingdom, typical firms would have to expect a 44% to 56% probability of detection. Actual probabilities of detection are substantially lower than this for many firms and would likely remain so even with realistic increases in enforcement capacity. Improved enforcement alone is thus insufficient: Expected penalties must also substantially increase to ensure that most firms have an incentive to comply.

Non-Euclidean motion planning with graphs of geodesically convex sets

Mon, 01 Sep 2025 00:00:00 GMT

Non-Euclidean motion planning with graphs of geodesically convex sets Cohn, Thomas; Petersen, Mark; Simchowitz, Max; Tedrake, Russ Computing optimal, collision-free trajectories for high-dimensional systems is a challenging and important problem. Sampling-based planners struggle with the dimensionality, whereas trajectory optimizers may get stuck in local minima due to inherent nonconvexities in the optimization landscape. The use of mixed-integer programming to encapsulate these nonconvexities and find globally optimal trajectories has recently shown great promise, thanks in part to tight convex relaxations and efficient approximation strategies that greatly reduce runtimes. These approaches were previously limited to Euclidean configuration spaces, precluding their use with mobile bases or continuous revolute joints. In this paper, we handle such scenarios by modeling configuration spaces as Riemannian manifolds, and we describe a reduction procedure for the zero-curvature case to a mixed-integer convex optimization problem. We further present a method for obtaining approximate solutions via piecewise-linear approximations that is applicable to manifolds of arbitrary curvature. We demonstrate our results on various robot platforms, including producing efficient collision-free trajectories for a PR2 bimanual mobile manipulator.

Extended state infrastructure power in an age of networked competition: The cases of Thailand and Taiwan

Sun, 17 Nov 2024 00:00:00 GMT

Extended state infrastructure power in an age of networked competition: The cases of Thailand and Taiwan Stokols, Andrew; Kollar, Justin Scholars have highlighted the emergence of infrastructure as a key domain in the struggle over network centrality in what some call the ‘Second Cold War’ between the U.S. and China. We qualify this ‘infrastructural turn’ by drawing attention to the contingent nature of state infrastructural power as depending on key domestic firms that often serve as intermediaries between domestic infrastructure and global supply chains or international partners. Utilising empirical case studies based on field research conducted between 2021 and 2023 in Thailand and Taiwan, we analyse the ways in which state infrastructure power is exercised through strategic negotiation between national politics of the state and territorial investment decisions of multinational and major domestic firms within global supply chains. The study highlights how outcomes of state projects to foster connectivity or centrality in networks are shaped by contingent and sometimes ad-hoc coalitions between state agencies and domestic and multinational companies with their own interests and agency. In the case of Taiwan, the centrality of Taiwan Semiconductor Manufacturing Company (TSMC) to global supply chains makes it an important player amidst continued U.S.-China tension. In Thailand, CP Group’s connections to China have afforded it a role as an interlocutor between Thailand and China, allowing it to obtain state infrastructure contracts. Through comparative case studies the paper complicates both ‘globalist’ and methodologically nationalist perspectives on the ‘infrastructural turn’, and introduces the concept of ‘extended state infrastructural power’ to account for this complex, networked exercise of state authority.

Uncovering Patterns in Overdose Deaths: An Analysis of Spike Identification in Fatal Drug Overdose Data in Massachusetts, 2017-2023

Thu, 01 Jan 2026 00:00:00 GMT

Uncovering Patterns in Overdose Deaths: An Analysis of Spike Identification in Fatal Drug Overdose Data in Massachusetts, 2017-2023 Lee, Hannah; Otero-Leon, Daniel; Dong, Huiru; Stringfellow, Erin J; Jalali, Mohammad S Objectives: Yearly rolling aggregate trends or rates are commonly used to analyze trends in overdose deaths, but focusing on long-term trends can obscure short-term fluctuations (eg, daily spikes). We analyzed data on spikes in daily fatal overdoses and how various spike detection thresholds influence the identification of spikes. Materials and Methods: We used a spike detection algorithm to identify spikes among 16 660 drug-related overdose deaths (from any drug) reported in Massachusetts’ vital statistics from 2017 through 2023. We adjusted the parameters of the algorithm to define spikes in 3 distinct scenarios: deaths exceeding 2 adjusted moving SDs above the 7-, 30-, and 90-day adjusted moving average. Results: Our results confirmed the on-the-ground observation that there are days when many more people die of overdoses than would be expected based on fluctuations due to differences among people alone. We identified spikes on 5.8% to 20.6% of the days across the 3 scenarios, annually, constituting 11.1% to 31.6% of all overdose deaths. The absolute difference in percentage points of days identified as spikes varied from 5.2 to 11.5 between 7- and 30-day lags and from 0 to 4.6 between 30- and 90-day lags across years. When compared with the adjusted moving average across the 3 scenarios, in 2017 an average of 3.9 to 5.5 additional deaths occurred on spike days, while in 2023 the range was 3.7 to 6.0. Practice Implications: A substantial percentage of deaths occurred annually on spike days, highlighting the need for effectively monitoring short-term overdose trends. Moreover, our study serves as a foundational analysis for future research into exogenous events that may contribute to spikes in overdose deaths, aiming to prevent future deaths.

Experiential learning amid disequilibrium: Attuning to student emotions

Thu, 09 Jan 2025 00:00:00 GMT

Experiential learning amid disequilibrium: Attuning to student emotions O’Flanagan, Sinead E; Y Jester, Michellana Educators recognize the significant role emotions play in experiential learning (EL), particularly in how they support students through the inherent emotion work. However, the traditional design of experiential learning theory (ELT) in higher education (HE) often presupposes a stable environment, which overlooks the impact of unpredictable external factors on students’ emotions and learning. Despite its critical importance, emotion work in EL remains underexplored, with emotional dynamics often obscured or dismissed as isolated incidents. This study sheds light on the heightened emotional challenges that arise during periods of sustained disequilibrium, such as the COVID-19-induced restrictions. It provides novel insights into the dynamic interplay of emotions and learning progression within EL frameworks, drawing on perspectives from EL educators, advisors, and students. The research underscores the importance of emotion-focused dialogue, educator-student connection, and assimilating autonomy needs in EL amid disequilibrium. It also identifies often-neglected elements in EL frameworks, such as students “sharing struggles” or “valuing work efforts,” alongside educator strategies like “personal anchoring.” The findings contribute to ELT by proposing adaptive strategies that integrate emotion work into pedagogical frameworks, enhancing reflection and conceptualization practices, and extending ELT’s applicability across diverse educational and work-based management learning settings.

Insulin Delivery Pumps for Human Spaceflight: Steps Toward an Accessible Space Future

Mon, 01 Sep 2025 00:00:00 GMT

Insulin Delivery Pumps for Human Spaceflight: Steps Toward an Accessible Space Future Horn, Kyle J; Hoffman, Jeffrey A Commercially available insulin pumps for treatment of diabetes mellitus are currently not qualified to operate in the space environment. This work rigorously tested the fluid delivery performance of a Tandem t:slim X2 insulin pump in both micro- and hypergravity during a parabolic microgravity research flight. The parabolic research flight environment serves as an analogue to the types of transient gravitational loadings experienced during human-led missions, which provides a foundation to expand testing to suborbital and orbital flights in addition to other extreme environmental tests for wilderness dependency. The results of the flight data showed no significant difference between fluid delivery performance at 0, 1, and 2g acceleration regimes, nor at the transitions between gravity environments. Recommendations are made for further experimentation and qualification tests before use in future spaceflight missions.

On the nonlinear Eshelby inclusion problem and its isomorphic growth limit

Thu, 01 Jan 2026 00:00:00 GMT

On the nonlinear Eshelby inclusion problem and its isomorphic growth limit Bonavia, Joseph E; Chockalingam, S; Cohen, Tal In the late 1950s, Eshelby’s linear solutions for the deformation field inside an ellipsoidal inclusion and, subsequently, the infinite matrix in which it is embedded were published. The solutions’ ability to capture the behavior of an orthotropically symmetric shaped inclusion made it invaluable in efforts to understand the behavior of defects within, and the micromechanics of, metals and other stiff materials throughout the rest of the 20th century. Over half a century later, we wish to understand the analogous effects of microstructure on the behavior of soft materials, both organic and synthetic, but in order to do so, we must venture beyond the linear limit, far into the nonlinear regime. However, no solutions to these analogous problems currently exist for non-spherical inclusions. In this work, we present an accurate semi-inverse solution for the elastic field in an isotropically growing spheroidal inclusion embedded in an infinite matrix, both made of the same incompressible neo-Hookean material. We also investigate the behavior of such an inclusion as it grows infinitely large, demonstrating the existence of a non-spherical asymptotic shape and an associated asymptotic pressure. We call this the isomorphic limit, and the associated pressure the isomorphic pressure.

Evaluating Risk for Astronaut Involvement in In-Space Manufacturing: Analog Field Testing and Future Planetary Surface Procedures

Sat, 29 Mar 2025 00:00:00 GMT

Evaluating Risk for Astronaut Involvement in In-Space Manufacturing: Analog Field Testing and Future Planetary Surface Procedures MacRobbie, Madelyn; Patel, Palak B. Introduction A key objective of the NASA Artemis program is to establish a sustained human presence on the Moon, along with its international and commercial partners. NASA aims to establish a lunar economy, increasing the need for infrastructure to support human habitation and facilitate growth. In-space manufacturing (ISM) coupled with in situ resource utilization (ISRU) can reduce launch mass and reduce the dependency on Earth resupply for long-term habitation, enabling rapid expansion. However, the space environment introduces unique challenges compared to Earth, such as the absence of an atmosphere, reduced gravity levels, and high consequences of human-machine interactions given the barrier to evacuating an astronaut injured in a manufacturing accident on the Moon, necessitating new safety standards for ISM processes. Methods This study proposes the application of a modified analytical hierarchy process (AHP) to identify high-risk aspects of crew procedures in molten regolith electrolysis (MRE) for both Earth-based analog testing and lunar production. Results The modified AHP assists in pinpointing areas needing hazard mitigation to protect crew members, enabling the improvement of safety standards for MRE in both environments. Conclusion Findings will inform the development of robust safety protocols for ISM, crucial for the success of NASA's Artemis missions and the broader goal of sustained human presence on the Moon and Mars.

Origins of Face Responses in the Human Cortex: fNIRS and fMRI Evidence From Infants

Wed, 01 Oct 2025 00:00:00 GMT

Origins of Face Responses in the Human Cortex: fNIRS and fMRI Evidence From Infants Saxe, Rebecca; Kosakowski, Heather L In adults, cortical regions in the fusiform face area (FFA), superior temporal sulcus (STS), and medial prefrontal cortex (MPFC) respond selectively to faces but underlie distinct perceptual and social processes. When do each of these regions, and their distinctive functions, develop? We reviewed recent studies of awake human infants’ cortical responses to faces using functional near-infrared spectroscopy (fNIRS) and functional MRI (fMRI). The results converged and do not support a slow, sequential posterior-to-anterior development of face-selective responses. Instead, cortical face-selective responses arise very early and simultaneously in infancy and may reflect distinctively social processes from the start.

The Effect of Basketball Analytics Investment on National Basketball Association (NBA) Team Performance

Fri, 01 Aug 2025 00:00:00 GMT

The Effect of Basketball Analytics Investment on National Basketball Association (NBA) Team Performance Wang, Henry; Sarker, Arnab; Hosoi, Anette In the National Basketball Association (NBA), basketball data and analytics is an area of significant financial investment for all 30 franchises, despite there being little quantitative evidence demonstrating analytics adoption actually improves team-level performance. This study seeks to measure the return on investment of analytics on NBA team success in a time of great demand for analytical front office personnel. Using a two-way fixed effects modeling approach, we identify the causal effect of analytics department headcounts on regular season wins using 12 years of season-level data for each team. We find a positive and statistically significant effect, suggesting clubs that invest more in analytics tend to outperform competitors when controlling for roster characteristics, injuries, difficulty of schedule, and team-specific and time-specific effects. This research contributes to the body of literature affirming the value of data analytics for organizational performance and supports current investments in analytics being made by NBA teams.

Workshop on Noninvasive Glucose Monitoring 2024

Tue, 01 Jul 2025 00:00:00 GMT

Workshop on Noninvasive Glucose Monitoring 2024 Kang, Jeon Woong; Arnold, Mark A; Steenkamp, Devin; Tapsak, Mark A; Mäntele, Werner; Khang, Yoonho; Jue, Miyeon; So, Peter TC This first workshop on noninvasive glucose monitoring (NIGM) was held at the Massachusetts Institute of Technology (MIT) on October 30, 2024. Six invited speakers, representing industry, academia, and clinics, gave presentations that covered (1) an overview of the NIGM technologies, (2) the state of the art in NIGM technologies, such as near-infrared (NIR), mid-infrared (IR), photoacoustic, and Raman spectroscopies, (3) minimally invasive implantable continuous glucose monitoring (CGM) sensors, and (4) a clinician’s perspective on the impact of the current CGM devices for patient care.

The community test tube of American civilization: Burt and Ethel Aginsky’s Social Science Field Laboratory, 1939–47

Mon, 30 Jun 2025 00:00:00 GMT

The community test tube of American civilization: Burt and Ethel Aginsky’s Social Science Field Laboratory, 1939–47 Kapsalakis, Lauren The Social Science Field Laboratory (SSFL, 1939–47), a field school in the Ukiah Valley that trained students in social scientific and anthropological methodology, sheds light on a period in anthropology when methods were shifting from objective empiricism to meaningful participation. As analytic tools for framing the study of society failed to keep pace with social change, sociopolitical trends inside and outside anthropology situated a valley in northern California as the opportune place to gather a sample of ‘American history in vitro’. Founded by Columbia-trained anthropologists Burt and Ethel Aginsky, the SSFL responded to trends inside and outside anthropology. As the Great Depression directed anthropologists’ attention to the study of practical, modern problems in complex American communities—such as race relations, immigration, modernization, and urbanization—funding agencies strengthened the relations between sociology and anthropology and encouraged the development of interdisciplinary approaches. The Aginskys conceived of the Ukiah Valley as a ‘community test-tube of American civilization’, where scientists from all disciplines ‘can come for a convenient sample of the United States, past and present’. In teaching students how to collect data in the field, the Aginskys pierced the widely held notion that ethnographic technique cannot be taught but must be experienced by the lone individual in the field.

Exploring How Organizational Actors Experience Evaluation and Its Influence: A Q-Methodological Study

Wed, 23 Apr 2025 00:00:00 GMT

Exploring How Organizational Actors Experience Evaluation and Its Influence: A Q-Methodological Study Kelly, Catherine This article contributes to research on evaluation by examining how organizational actors respond to and use evaluation imposed on them within an evaluation system. Drawing on Henry and Mark's theory of evaluation influence, this study uses Q-methodology to explore how staff within English higher education providers experience evaluation and its influence on their widening participation practice and strategy decision-making. The experiences of organizational actors are examined and classified into four types: strategic practitioners, pragmatic practitioners, staff with indirect involvement in widening participation, and evaluation enthusiasts. Through analyzing these experiences, the findings illustrate the diverse ways organizational actors are influenced by evaluation within evaluation systems. To deepen our understanding of evaluation influence in the contexts of evaluation systems, this article recommends explicitly embedding organizational theories into future theories of evaluation influence and provides suggestions for future research on the topic.

Mapping the Caregiver Experience: Predicting Dimensions of Caregiver Strain Through Task-Based Profiles

Thu, 01 Jan 2026 00:00:00 GMT

Mapping the Caregiver Experience: Predicting Dimensions of Caregiver Strain Through Task-Based Profiles Brady, Samantha; Ashebir, Sophia; D’Ambrosio, Lisa; Balmuth, Alexa; Felts, Adam; Lee, Chaiwoo Objective: Family caregiving is a prevalent, diverse, and often challenging experience. We develop caregiving activity profiles to better understand how sets of care-tasks contribute to various aspects of strain. Methods: Using diary data from a survey of 213 family caregivers in the U.S., we perform latent class analysis to group commonly occurring care-related tasks into activity profiles. We then use these classifications to predict physical, financial, and emotional strain. Main Findings: We identified 4 unique activity profiles based on a set of 36 daily caregiving activities performed. Activity profiles varied significantly across the three analyzed strain dimensions. Conclusion: Activity profiles present opportunities to better understand how caregiving tasks are related to specific types kinds of caregiving strain.

Your home is not a school: The limits of homeschooling as a political practice

Fri, 18 Apr 2025 00:00:00 GMT

Your home is not a school: The limits of homeschooling as a political practice Pavel, Sonia Maria; Cynamon, Jeremy Kingston Homeschooling is on the rise. It appeals to very different perspectives and ideologies that tend not to have common ground, from classical conservative to radical progressive. But the justifications for the practice are weak. In this paper, we build a case against the “home school” as a political practice using the existing commitments of liberal, conservative, and democratic theories of education. Whether education should aim at the cultivation of children's autonomy, their formation as members of cultural communities, or their training as democratic citizens, there are reasons to doubt that the practice of homeschooling can fulfill our educational goals. As such, we argue that liberals, conservatives, and democrats each have their own motivations to oppose homeschooling as an institutional alternative to traditional schools. Through our critiques, we also advance a metatheoretical argument in favor of centering the aims of education in our philosophical and political debates.

Qualitative Assessment of Terrestrial Care Settings to Inform Self-sufficient Spaceflight Medical Care

Mon, 01 Sep 2025 00:00:00 GMT

Qualitative Assessment of Terrestrial Care Settings to Inform Self-sufficient Spaceflight Medical Care Porter, Allison; Arquilla, Katya; Stankovic, Aleksandra Introduction Long communication latencies in exploration spaceflight will necessitate in situ resolution to medical problems. Integrating automation into the care paradigm can address challenges posed by resource gaps inherent to spaceflight operations. However, it is not clear what aspects of exploration care are most well suited for automation integration. Methods To probe the potential role of automation in spaceflight medicine, we began by decomposing the human-automation system to first characterize the work domain(s) of the human tasks. Using the lens of point-of-care ultrasound, we leveraged existing analogous Earth medical domains to conduct in situ observations in a hospital emergency department to understand how clinicians process contextual information to provide urgent care using ultrasound and semistructured interviews with specialists to identify key procedural information components for automation. Results This investigation allowed us to characterize the dynamic system surrounding a task that does not exist in its intended—currently inaccessible—use case (ie, point-of-care ultrasound on Mars) to guide future human-automation systems development. Conclusion We conclude that specific aspects of the care environment that influence the result of a task or process (“mediating factors”) from candidate work domains call for distinct, targeted guidance for automation support and are valuable in providing system developers with tunable automation level and implementation guidelines within and/or between those work domains. Such evidence-based design practice is directly translatable to automation assistance for medical providers in resource-limited environments as well as to any situation where a person's sensory processing, perception, decision making, or response selection could be aided by automation to accomplish a task.

Solutions and Challenges for Addressing Misinformation

Tue, 10 Jun 2025 00:00:00 GMT

Solutions and Challenges for Addressing Misinformation Martel, Cameron; Rand, David G Research on mitigating the effects of misinformation has contributed to the development of multiple feasible interventions designed to reduce belief in, and sharing of, falsehoods. The authors review these interventions and discuss challenges and open questions for future research. First, they provide an overview of content-neutral and content-based interventions. Next, they discuss two practical challenges to deploying and assessing these interventions in the field: scalability and pushback against content moderation efforts due to perceived political bias. Finally, they highlight several open theoretical questions and common pitfalls of research on misinformation. In particular, they argue for critical evaluation of how interventions may be effective across different types of misinformative content, different key subpopulations, and different media and environmental contexts.

Atomic Transactions

Sat, 01 Jan 1994 00:00:00 GMT

Atomic Transactions Lynch, Nancy; Merritt, Michael; Weihl, William; Fekete, Alan

Recirculation through western boundary currents varies nonlinearly with the ocean basin's aspect ratio

Tue, 17 Sep 2024 00:00:00 GMT

Recirculation through western boundary currents varies nonlinearly with the ocean basin's aspect ratio Gianchandani, Kaushal Recirculation gyres adjacent to western boundary currents (WBCs) in the ocean enhance the poleward transport of these currents. While it is well-established that the WBC in a barotropic ocean strengthens with increase in basin's aspect ratio (the meridional-to-zonal extent ratio), how intensity of the recirculation through the western boundary layer varies with this parameter remains unexplored. I address this using the non-dimensional form of the nonlinear, wind-driven Stommel–Munk model of westward intensification that comprises three parameters—the aspect ratio (δ), the damping coefficient (ϵ), and the β-Rossby number (Rβ). Here, ϵ is set by the ratio of Rayleigh friction coefficient (or eddy viscosity) to the meridional gradient of the Coriolis frequency and the basin's zonal dimension, while Rβ is proportional to wind stress amplitude and quantifies the strength of nonlinearity. In the weak-to-moderate nonlinearity limit (Rβ<∼ϵ), perturbation analysis reveals that recirculation varies concavely with aspect ratio, suggesting existence of an optimal aspect ratio (δopt) for which the recirculation is maximum and for typical values of ϵ (10−3−10−2), δopt follows the power-law relation δopt=4.3ϵ. Numerical simulations further validate the existence of δopt. For large ϵ (>5×10−3), the power-law predicts δopt for the numerical solutions rather accurately, but does not hold for smaller ϵ (2×10−3) due to increased importance of nonlinear terms. Nevertheless, the nonlinear variation in recirculation through the western boundary layer with aspect ratio is observed for all ϵ values and may contribute to the heterogeneous increase in the WBC's transport across different ocean basins in a warming climate.

Streamlining Physics Problem Generation to Support Physics Teachers in Using Generative Artificial Intelligence

Tue, 01 Oct 2024 00:00:00 GMT

Streamlining Physics Problem Generation to Support Physics Teachers in Using Generative Artificial Intelligence El-Adawy, Shams; Liao, Isaac; Lad, Vedang; Abdelhafez, Mohamed; Dourmashkin, Peter The rapid advancement of large language models (LLMs) presents a unique opportunity for educators to find ways to include artificial intelligence (AI) in physics course design. By critically engaging with LLMs to help with the task of generating problems, physics teachers can not only model a potentially effective way to use LLMs for other teachers, but also showcase to students ways to productively engage with LLMs. This article presents a workflow with two different starting points to generate physics problems using ChatGPT 3.5. The first initialization involves interacting with ChatGPT in a conversational manner, guiding iterative problem creation by breaking tasks into smaller tasks. The second initialization harnesses ChatGPT’s generative abilities, aligning problem generation with established problem styles by instructing the model to emulate contexts from question banks. We discuss the implications of this workflow for other physics instructors exploring productive ways to incorporate the use of AI in their own course design.

Ion optical design of the magnetic proton recoil neutron spectrometer for the SPARC tokamak

Tue, 01 Oct 2024 00:00:00 GMT

Ion optical design of the magnetic proton recoil neutron spectrometer for the SPARC tokamak Mackie, S; Wink, CW; Dalla Rosa, M; Berg, GPA; Ball, JL; Wang, X; Carmichael, J; Tinguely, RA; Rigamonti, D; Tardocchi, M; Raj, P; Frenje, J; Rice, J A magnetic proton recoil (MPR) neutron spectrometer is being designed for SPARC, a high magnetic field (BT = 12 T), compact (R0 = 1.85 m, a = 0.57 m) tokamak currently under construction in Devens, MA, USA. MPR neutron spectrometers are versatile tools for making high fidelity ab initio calibrated measurements of fusion neutron flux spectra and have been used to infer fusion power, ion temperature, fuel ion ratio, and suprathermal fuel populations at several high performance fusion experiments. The performance of an MPR neutron spectrometer is in large part determined by the design of the magnetic field, which disperses and focuses recoil protons. This article details the ion optical design of a high-resolution MPR neutron spectrometer, including the amelioration of image aberrations due to nonlinear effects. An optimized design is presented that achieves ion optical energy resolution δE/E < 1% and focal plane properties that enable straightforward integration with the hodoscope detector array.

Performance predictions of the SPARC x-ray crystal spectrometers for ion temperature and toroidal rotation measurements

Tue, 27 Aug 2024 00:00:00 GMT

Performance predictions of the SPARC x-ray crystal spectrometers for ion temperature and toroidal rotation measurements Perks, C; Vezinet, D; Rice, JE; Reinke, ML SPARC will be outfitted with three systems of x-ray crystal spectrometer arrays. Two of these are designed using cylindrically bent crystals to achieve high spectral-resolution for ion temperature and toroidal velocity measurements via imaging He-like Kr and Ne-like Xe. The last acts as a spectral survey system to monitor Ne-like W and nearby H- and He-like emission from Cr, Fe, Co, Ni, and Cu. Line radiation intensities are calculated using the Flexible Atomic Code for atomic data and ColRadPy for collisional-radiative modeling, then convoluted with a Voigt line shape. Free–free, free-bound, and two-photon continuum radiation is also included. The ToFu code is used to perform volume-of-sight integration to produce synthetic detector images. In addition, presented is cross-validation performed using the XICSRT Monte Carlo ray-tracing code. Ion temperature and toroidal velocity profiles are reconstructed using ToFu via tomographic inversion.

Edge scanning reflectometry for density profile measurement on the SPARC tokamak

Wed, 21 Aug 2024 00:00:00 GMT

Edge scanning reflectometry for density profile measurement on the SPARC tokamak Lin, Y; Nikolaeva, V; Hachmeister, D; Kowalski, E; Reinke, ML Edge scanning reflectometry (ESRL) on the SPARC tokamak aims to measure the electron density profile from the far scrape-off layer to the top of the typical H-mode pedestal and provide real-time data for plasma control. ESRL uses a standard frequency-modulated continuous wave technique from 18 to 90 GHz. By implementing both the O-mode and left-hand-cutoff X-mode, it covers densities from ∼4 × 1018 to ∼4 × 1020 m−3 at B0 ∼12 T. A voltage-controlled oscillator acts as the frequency sweep source. Phase-locked dielectric resonator oscillators and bandpass filters generate base signals ∼9–15 GHz. The signals are then frequency multiplied and amplified to reach the K (18–26 GHz), Ka (26–40 GHz), U (40–60 GHz), and E (60–90 GHz) bands. Multi-band signals are combined via the quasi-optical technique. ESRL plans to use oversized waveguides (∼20 m one-way) and a bi-static arrangement to minimize signal losses and distortions while allowing system flexibility. A COMSOL Multiphysics RF model in 2D has been set up to simulate the reflectometry process and help decide the layout of the horn antennas. Engineering analyses of the key parts of the system have been carried out in support of its preliminary design.

Neutronics simulations for the design of neutron flux monitors in SPARC

Fri, 30 Aug 2024 00:00:00 GMT

Neutronics simulations for the design of neutron flux monitors in SPARC Wang, X; Gocht, R; Ball, J; Mackie, S; Panontin, E; Tinguely, RA; Raj, P; Holmes, I; Saltos, AA; Johnson, A; Grieve, A This paper presents the development and application of high-fidelity neutronic models of the SPARC tokamak for the design of neutron flux monitors (NFM) for application during plasma operations. NFMs measure the neutron flux in the tokamak hall, which is related to fusion power via calibration. We have explored Boron-10 gamma-compensated ionization chambers (ICs) and parallel-plate Uranium-238 fission chambers (FCs). We plan for all NFMs to be located by the wall in the tokamak hall and directly exposed to neutrons streaming through a shielded opening in a midplane port. Our simulations primarily use a constructive solid geometry-based OpenMC model based on the true SPARC geometry. The OpenMC model is benchmarked against a detailed CAD-based MCNP6 model. The B10 ICs are equipped with high-density polyethylene (HDPE) sleeves, borated HDPE housings, and borated aluminum covers to shield out scattered neutrons, optimize detector response levels, and make calibration robust against changes in the tokamak hall. The B10 neutron absorption branching ratio may cause the detectors’ responses to be non-linear to neutron flux >200 keV. However, our simulations unveil that, in the SPARC environment and with the proposed housings and sleeves, >99% of the detector responses are induced by <100 keV neutrons. U238’s insensitivity to slow neutrons makes this FC a promising candidate for direct fusion neutron measurements. Along with a borated HDPE sleeve, about 60% of the FCs’ responses are induced by direct neutrons.

Image plate multi-scan response to fusion protons in the range of 1–14 MeV

Tue, 24 Sep 2024 00:00:00 GMT

Image plate multi-scan response to fusion protons in the range of 1–14 MeV Vanderloo, N; Cufari, M; Russell, L; Johnson, TM; Vargas, J; Foo, BC; Buschmann, BI; Dannhoff, SG; DeVault, A; Evans, TE; Kunimune, JH; Lawrence, Y; Pearcy, JA; Reichelt, BL; Wink, CW; Gatu Johnson, M; Petrasso, RD; Frenje, JA; Li, CK Image plates (IPs) are a quickly recoverable and reusable radiation detector often used to measure proton and x-ray fluence in laser-driven experiments. Recently, IPs have been used in a proton radiography detector stack on the OMEGA laser, a diagnostic historically implemented with CR-39, or radiochromic film. The IPs used in this and other diagnostics detect charged particles, neutrons, and x-rays indiscriminately. IPs detect radiation using a photo-stimulated luminescence (PSL) material, often phosphor, in which electrons are excited to metastable states by ionizing radiation. Protons at MeV energies deposit energy deeper into the IP compared with x rays below ∼20 keV due to the Bragg peak present for protons. This property is exploited to discriminate between radiation types. Doses of mono-energetic protons between 1.7 and 14 MeV are applied to IPs using the MIT linear electrostatic ion accelerator. This paper presents the results from consecutive scans of IPs irradiated with different proton energies. The PSL ratios between subsequent scans are shown to depend on proton energy, with higher energy protons having lower PSL ratios for each scan. This finding is separate from the known energy dependence in the absolute sensitivity of IPs. The results can be compared to complimentary work on x rays, showing a difference between protons and x rays, forging a path to discriminate between proton and x-ray fluence in mixed radiation environments.

A compact and portable gamma-ray spectrometer (GRASP) for inertial confinement fusion and basic science experiments

Mon, 05 Aug 2024 00:00:00 GMT

A compact and portable gamma-ray spectrometer (GRASP) for inertial confinement fusion and basic science experiments Dannhoff, SG; Wink, CW; Mackie, S; Berg, GPA; Frenje, JA A compact and portable gamma-ray spectrometer has been designed to diagnose different components of the inertial confinement fusionrelevant γ-ray spectrum with energies between ∼3.7–17.9 MeV. The system is designed to be as compact as possible for convenient transportation and fielding in diagnostic ports on the OMEGA laser, the National Ignition Facility, and other photon-source facilities. The system consists of a conversion foil for Compton scattering in front of four magnetic spectrometer “arms,” each covering a different energy range and constructed out of cylindrical permanent magnet Halbach arrays. Monte Carlo simulations have been used to optimize and assess the performance of the conversion foil, and COSY INFINITY ion-optical simulations have been used to optimize the spectrometer magnets. The performance of the design is assessed for a simulated direct-drive γ-ray spectrum. Spanning its total γ-ray energy bandwidth and using a 1.7 mm thick boron conversion foil, the system’s total energy resolution and efficiency are ∼15.8%–4.5% and 5.4 × 10−7 –3.7 × 10−7 e − /γ, respectively, with room for improvement. Spectral γ-ray measurements will provide guidance to the inertial confinement fusion program toward achieving high-energy gain relevant to inertial fusion energy and enable new measurement capabilities for basic discovery science.

Characterization of the image plate multi-scan response to mono-energetic x-rays

Tue, 24 Sep 2024 00:00:00 GMT

Characterization of the image plate multi-scan response to mono-energetic x-rays Cufari, M; Vanderloo, N; Buschmann, BI; DeVault, A; Foo, BC; Vargas, J; Dannhoff, SG; Evans, TE; Johnson, TM; Kunimune, J; Lawrence, Y; Pearcy, JA; Reichelt, BL; Russell, L; Wink, CW; Gatu Johnson, M; Petrasso, RD; Frenje, JA Image plates (IPs), or phosphor storage screens, are a technology employed frequently in inertial confinement fusion (ICF) and high energy density plasma (HEDP) diagnostics because of their sensitivity to many types of radiation, including, x rays, protons, alphas, beta particles, and neutrons. Prior studies characterizing IPs are predicated on the signal level remaining below the scanner saturation threshold. Since the scanning process removes some signal from the IP via photostimulated luminescence, repeatedly scanning an IP can bring the signal level below the scanner saturation threshold. This process, in turn, raises concerns about the signal response of IPs after an arbitrary number of scans and whether such a process yields, for example, a constant ratio of signal between the nth and n + 1st scan. Here, the sensitivity of IPs is investigated when scanned multiple times. It is demonstrated that the ratio of signal decay is not a constant with the number of scans and that the signal decay depends on the x-ray energy. As such, repeatedly scanning an IP with a mixture of signal types (e.g., x ray, neutron, and protons) enables ICF and HEDP diagnostics employing IPs to better isolate a particular signal type.

Microbially-enhanced dissolution of calcite in sinking marine particles

Mon, 09 Mar 2026 00:00:00 GMT

Microbially-enhanced dissolution of calcite in sinking marine particles Borer, Benedict; Subhas, Adam V.; Hayden, Matthew G.; Woosley, Ryan J.; Babbin, Andrew R. Evidence for the shallow cycling of calcium carbonate in the global ocean is mounting, but the mechanisms driving the dissolution of thermodynamically stable polymorphs, like aragonite and calcite, in the surface ocean remain unconstrained. Here, we quantify how microbial metabolism creates acidic microenvironments in marine particles that enhance the local dissolution of calcite despite supersaturated conditions in bulk waters. A temporal decoupling of particle deoxygenation and acidification suggests that respiration-derived carbon dioxide is not the sole driver of the observed undersaturation. Rapid dissolution occurs in particles exhibiting bacterial growth, with rates exceeding abiotic dissolution at the same bulk saturation by more than an order of magnitude. We observe the highest particle-associated dissolution rates at intermediate settling velocities, indicating that a trade-off between elevated mass transfer due to settling and bacterial respiration governs the ensuing dissolution rates. Translation of our experiments to the water column suggests that microbially driven undersaturation in marine particles may dissolve sufficient calcite in the mesopelagic ocean to extend particle transit times by eliminating this vital ballast mineral, reducing the efficiency of organic carbon sequestration.

Process cost analysis of performance challenges and their mitigations in sodium-ion battery cathode materials

Wed, 21 May 2025 00:00:00 GMT

Process cost analysis of performance challenges and their mitigations in sodium-ion battery cathode materials Munjal, Mrigi; Prein, Thorben; Ramadan, Mahmoud M.; Smith, Hugh B.; Venugopal, Vineeth; Rupp, Jennifer L.M.; Abate, Iwnetim I.; Olivetti, Elsa A.; Huang, Kevin J. The success of sodium-ion batteries (SIBs) hinges on mitigating underperformance in ways that are cost effective, manufacturable, and scalable. This work investigates interfacial, morphological, and bulk interventions to enhance the performance of layered metal oxide cathode active materials (CAMs) for SIBs. We mapped the full space of literature-reported SIB CAM challenges and their mitigations. We then estimated the manufacturing costs for a diverse and representative set of mitigation approaches. Adding sacrificial salts can be cost effective, given low materials costs and minimal process changes. By contrast, many methods are reported to tune CAM morphology. Several are likely challenging at scale due to process throughput and yield limitations. Finally, bulk modifications can mitigate the moisture sensitivity of some CAMs, a likely less costly route than expanding stringent atmosphere controls during manufacturing. We end by discussing the limits and promise of process cost analysis, given the current state of battery reporting in the literature.

Design of a diamond-based in-vessel soft x-ray detector for the SPARC tokamak

Tue, 24 Sep 2024 00:00:00 GMT

Design of a diamond-based in-vessel soft x-ray detector for the SPARC tokamak Normile, S; Vezinet, D; Perks, C; Bombarda, F; Verona-Rinati, G; Rice, JE; Verona, C; Raso, AM; Angelone, M The in-vessel silicon diode arrays that are used for soft x-ray detection in many tokamaks are sensitive to neutron damage, making them unsuitable for burning plasma devices such as SPARC. In such a device, the silicon diodes would need to be placed far from the plasma—limiting their field of view—or an alternative detector could be used. Here, we present the design of a camera containing an array of chemical vapor deposition single-crystal diamonds, which will be placed in the upper and lower port plugs of the SPARC tokamak with a large enough view of the poloidal cross section to enable tomographic inversion. The camera design presented here is optimized to provide a wide field of view of the poloidal cross section. Simulated plasma conditions are used to estimate the x-ray signal that this detector array will receive and to fine-tune the camera placement within the tokamak.

Development of the prototype for the SPARC hard X-ray monitor

Mon, 05 Aug 2024 00:00:00 GMT

Development of the prototype for the SPARC hard X-ray monitor Panontin, E; Tinguely, RA; Hartwig, ZS; Saltos, AA; Vezinet, D; Rice, J The SPARC tokamak will be equipped with a hard X-ray (HXR) monitor system capable of measuring the bremsstrahlung emission from runaway electrons with photon energies in excess of about 100 keV. This diagnostic will detect the formation of runaway electron beams during plasma start-up and inform the plasma control system to terminate the discharge early to protect the machine. In this work, we present a 0D estimate of the HXR emission in SPARC during plasma start-up. Then we discuss the characterization of a prototype of the HXR monitor. The detector mounts a 1 × 1-in.2 LaBr3 inorganic scintillator coupled with a photomultiplier tube and has been tested with γ-ray sources to find its dynamic range. Finally, two possible modes of operation for spectroscopic and current mode measurements on SPARC are proposed.

Perspectives on pilot-wave hydrodynamics

Mon, 15 Jul 2024 00:00:00 GMT

Perspectives on pilot-wave hydrodynamics Bush, John WM; Frumkin, Valeri; Sáenz, Pedro J We present a number of fresh perspectives on pilot-wave hydrodynamics, the field initiated in 2005 by Couder and Fort's discovery that millimetric droplets self-propelling along the surface of a vibrating bath can capture certain features of quantum systems. A recurring theme will be that pilot-wave hydrodynamics furnishes a classical framework for reproducing many quantum phenomena and allows one to rationalize such phenomena mechanistically, from a local realist perspective, obviating the need to appeal to quantum nonlocality. The distinction is drawn between hydrodynamic pilot-wave theory and its quantum counterparts, Bohmian mechanics, the Bohm–Vigier stochastic pilot-wave theory, and de Broglie's theory of the double-solution. Each of these quantum predecessors provide a valuable touchstone as we take the physical picture engendered in the walking droplets and extend it into the quantum realm via theoretical modeling. Emphasis is given to recent developments in the field, both experimental and conceptual, and to forecasting potentially fruitful new directions.

Automated transient grating spectroscopy mapping and signal control for large samples

Wed, 10 Jul 2024 00:00:00 GMT

Automated transient grating spectroscopy mapping and signal control for large samples Weaver, Colin; Stapelberg, Myles; Short, Michael P; Wylie, Angus; Artalejo, Elena Botica We present developments for the mapping of large areas using transient grating spectroscopy (TGS) that allow for smoother, larger, autonomous measurements of material samples. The addition of a precise linear stage in the direction parallel to laser sampling coupled with signal optimizing control allows for hands free, self-correcting measurements. In addition, the simplification of the sample holding design to a form that is small enough to mount directly to the linear stage exhibits a straightforward, low-cost solution for automated TGS applications. This capability is demonstrated by taking large uninterrupted maps of gradient wafers, and the results are validated on calibrated tungsten samples and control TGS samples from gradient wafers.

Manipulating the duration of picoinjection controls the injected volume of individual droplets

Tue, 02 Jul 2024 00:00:00 GMT

Manipulating the duration of picoinjection controls the injected volume of individual droplets Thakur, R.; Weitz, D. The ability to add reagents into droplets is required in many microfluidic workflows. Picoinjection can address this need; however, it is unable to control the injection volume for each individual droplet. Here, we present an improved picoinjection method that can inject controlled volumes into individual droplets. We achieve this by adjusting the injection duration for each picoinjection event. This improved picoinjection method can be used to create complex microfluidic workflows that are able to control the biochemical composition of individual droplets.

Multitask methods for predicting molecular properties from heterogeneous data

Wed, 03 Jul 2024 00:00:00 GMT

Multitask methods for predicting molecular properties from heterogeneous data Fisher, KE; Herbst, MF; Marzouk, YM Data generation remains a bottleneck in training surrogate models to predict molecular properties. We demonstrate that multitask Gaussian process regression overcomes this limitation by leveraging both expensive and cheap data sources. In particular, we consider training sets constructed from coupled-cluster (CC) and density functional theory (DFT) data. We report that multitask surrogates can predict at CC-level accuracy with a reduction in data generation cost by over an order of magnitude. Of note, our approach allows the training set to include DFT data generated by a heterogeneous mix of exchange–correlation functionals without imposing any artificial hierarchy on functional accuracy. More generally, the multitask framework can accommodate a wider range of training set structures—including the full disparity between the different levels of fidelity—than existing kernel approaches based on Δ-learning although we show that the accuracy of the two approaches can be similar. Consequently, multitask regression can be a tool for reducing data generation costs even further by opportunistically exploiting existing data sources.

Automated Flow Synthesis of Artificial Heme Enzymes for Enantiodivergent Biocatalysis

Wed, 22 Jan 2025 00:00:00 GMT

Automated Flow Synthesis of Artificial Heme Enzymes for Enantiodivergent Biocatalysis Fittolani, Giulio; Kutateladze, Dennis A; Loas, Andrei; Buchwald, Stephen L; Pentelute, Bradley L The remarkable efficiency with which enzymes catalyze small-molecule reactions has driven their widespread application in organic chemistry. Here, we employ automated fast-flow solid-phase synthesis to access catalytically active full-length enzymes without restrictions on the number and structure of noncanonical amino acids incorporated. We demonstrate the total syntheses of iron-dependent Bacillus subtilis myoglobin (BsMb) and sperm whale myoglobin (SwMb). The synthetic enzymes displayed excellent enantioselectivity and yield in carbene transfer reactions. Absolute control over enantioselectivity in styrene cyclopropanation was achieved using synthetic L- and D-BsMb mutants, which delivered each enantiomer of cyclopropane product in identical and opposite enantiomeric enrichment. BsMb mutants outfitted with noncanonical amino acids were used to facilitate detailed structure–activity relationship studies, revealing a previously unrecognized hydrogen-bonding interaction as the primary driver of enantioselectivity in styrene cyclopropanation. We anticipate that our approach will advance biocatalysis by providing reliable and rapid access to fully synthetic enzymes possessing noncanonical amino acids.

Development of a Ligand for Cu-Catalyzed Amination of Base-Sensitive (Hetero)aryl Chlorides

Mon, 13 Oct 2025 00:00:00 GMT

Development of a Ligand for Cu-Catalyzed Amination of Base-Sensitive (Hetero)aryl Chlorides Ai, Han-Jun; Mai, Binh Khanh; Liu, Cecilia; Liu, Peng; Buchwald, Stephen L We report a new N1,N2-diarylbenzene-1,2-diamine ligand, L6, that supports a copper catalyst capable of coupling base-sensitive aryl chlorides and amines that were previously unsuccessful substrates for Cu-catalyzed C–N coupling. A detailed structure–activity relationship study, combined with density functional theory (DFT) calculations, was used to uncover two key structural features that contribute to the efficacy of the catalyst derived from L6. First, steric repulsion caused by a methyl substituent induces a conformational change that opens up additional space for ligand deprotonation and oxidative addition. Second, the trifluoromethyl groups create electrostatic interactions between the ligand and aryl chloride substrates that facilitate oxidative addition via through-space ligand–substrate interaction.

Ligand Design Enables Cu-Catalyzed Etherification of Aryl Bromides Using Mild Bases

Mon, 05 Jan 2026 00:00:00 GMT

Ligand Design Enables Cu-Catalyzed Etherification of Aryl Bromides Using Mild Bases Strauss, Michael J; Greaves, Megan E; Kim, Seoung-Tae; Schmidt, Michael A; Scola, Paul M; Buchwald, Stephen L We report a Cu-catalyzed method for the efficient coupling of base-sensitive aryl bromides and alcohols utilizing a newly developed N1,N2-diarylbenzene-1,2-diamine ligand, L15. This ligand was developed to increase the Lewis acidity of the Cu center, thereby permitting the use of a substantially milder base (NaOTMS or NaOPh) relative to those required in a previous iteration of this methodology (NaOMe or NaOt-Bu). Under the optimized reaction conditions, several classes of previously incompatible aryl bromides were efficiently transformed, including base-sensitive heterocycles and those containing acidic functional groups. Kinetic analyses support that C–O coupling proceeds via a mechanism involving binding/deprotonation of alcohol nucleophiles, that the pKa of the base influences the overall rate law, and that substoichiometric quantities of strong base can be utilized to accelerate ligand activation and thereby increase the overall rate of the transformation.

Time-Resolved Line Shapes of Single Quantum Emitters via Machine Learned Photon Correlations

Fri, 04 Aug 2023 00:00:00 GMT

Time-Resolved Line Shapes of Single Quantum Emitters via Machine Learned Photon Correlations Proppe, Andrew H; Lee, Kin Long Kelvin; Kaplan, Alexander EK; Ginterseder, Matthias; Krajewska, Chantalle J; Bawendi, Moungi G Solid-state single-photon emitters (SPEs) are quantum light sources that combine atomlike optical properties with solid-state integration and fabrication capabilities. SPEs are hindered by spectral diffusion, where the emitter's surrounding environment induces random energy fluctuations. Timescales of spectral diffusion span nanoseconds to minutes and require probing single emitters to remove ensemble averaging. Photon correlation Fourier spectroscopy (PCFS) can be used to measure time-resolved single emitter line shapes, but is hindered by poor signal-to-noise ratio in the measured correlation functions at early times due to low photon counts. Here, we develop a framework to simulate PCFS correlation functions directly from diffusing spectra that match well with experimental data for single colloidal quantum dots. We use these simulated datasets to train a deep ensemble autoencoder machine learning model that outputs accurate, noiseless, and probabilistic reconstructions of the noisy correlations. Using this model, we obtain reconstructed time-resolved single dot emission line shapes at timescales as low as 10 ns, which are otherwise completely obscured by noise. This enables PCFS to extract optical coherence times on the same timescales as Hong-Ou-Mandel two-photon interference, but with the advantage of providing spectral information in addition to estimates of photon indistinguishability. Our machine learning approach is broadly applicable to different photon correlation spectroscopy techniques and SPE systems, offering an enhanced tool for probing single emitter line shapes on previously inaccessible timescales.

Uncovering temperature-dependent exciton-polariton relaxation mechanisms in hybrid organic-inorganic perovskites

Thu, 27 Apr 2023 00:00:00 GMT

Uncovering temperature-dependent exciton-polariton relaxation mechanisms in hybrid organic-inorganic perovskites Laitz, Madeleine; Kaplan, Alexander EK; Deschamps, Jude; Barotov, Ulugbek; Proppe, Andrew H; García-Benito, Inés; Osherov, Anna; Grancini, Giulia; deQuilettes, Dane W; Nelson, Keith A; Bawendi, Moungi G; Bulović, Vladimir Hybrid perovskites have emerged as a promising material candidate for exciton-polariton (polariton) optoelectronics. Thermodynamically, lowthreshold Bose-Einstein condensation requires efficient scattering to the polariton energy dispersion minimum, and many applications demand precise control of polariton interactions. Thus far, the primary mechanisms by which polaritons relax in perovskites remains unclear. In this work, we perform temperature-dependent measurements of polaritons in low-dimensional perovskite wedged microcavities achieving a Rabi splitting of _ΩRabi = 260 ± 5 meV. We change the Hopfield coefficients by moving the optical excitation along the cavity wedge and thus tune the strength of the primary polariton relaxation mechanisms in this material. We observe the polariton bottleneck regime and show that it can be overcome by harnessing the interplay between the different excitonic species whose corresponding dynamics are modified by strong coupling. This work provides an understanding of polariton relaxation in perovskites benefiting from efficient, material-specific relaxation pathways and intracavity pumping schemes from thermally brightened excitonic species. Springer Science and Business Media LLC

A Self-Directed, Home-Like XR System for Sustained Intangible Cultural Heritage Practice: An Ikebana Case Study

Thu, 05 Feb 2026 00:00:00 GMT

A Self-Directed, Home-Like XR System for Sustained Intangible Cultural Heritage Practice: An Ikebana Case Study Wu, Yu; Li, Manxueying; Mai, Gelei Sustained Intangible Cultural Heritage (ICH) practices for novices depend more on curiosity and creative agency than on procedural training. Yet, most extended reality (XR) systems for ICH emphasize guided instruction or exhibitions, limiting self-direction and continuity beyond the device. Using Ikebana as a case study, we present a self-directed, home-like virtual reality (VR) experience built with 3D Gaussian Splatting (3D GS) and natural hand tracking, complemented by an augmented reality (AR) revisiting feature that exports creations for real-world placement and sharing. In a study with 11 novices, pre-post questionnaires showed gains in interest, likelihood to continue offline, and understanding (p ≤.01). Interviews indicated that domestic realism reduced intimidation, natural gestures supported immersion, and AR revisiting extended reflection and engagement. We contribute (1) a home-like, self-directed XR design for ICH practice and (2) evidence that approachability, autonomy, and cross-reality continuity enhance motivation beyond the virtual world. VRCAI ’25, Macau, China

CS Ed. in Prisons and Jails: Evidence of Computer Programming Self-Efficacy Growth Across Multiple Course Offerings

Tue, 17 Feb 2026 00:00:00 GMT

CS Ed. in Prisons and Jails: Evidence of Computer Programming Self-Efficacy Growth Across Multiple Course Offerings Fishberg, Andrew; Gaetz, Marisa; Nisser, Martin; Cafferty, Carole; Perlman, Lee; Soicher, Raechel N.; Long, Joshua Incarcerated students enrolled in education programs in prisons and jails experience a range of benefits, from reduced recidivism to improved psychosocial well-being. With respect to computer science education, little is still known about how courses impact incarcerated students' experiences, though recent work has explored fears and confidence of incarcerated students enrolled in computer science courses. Our work investigates incarcerated students' changes in self-efficacy over multiple iterations of four different classes. Our findings showed that all subscales of computer programming self-efficacy (algorithm, control, cooperation, debugging, and logic), but not generalized self-efficacy, were statistically significantly increased at the end of the courses relative to the beginning (p < 0.001, n = 36). A similar pattern of results across the full sample (n = 188) adds additional support for the veracity of the effects found in the subset of paired data. Additionally, we share students' qualitative data to add nuance to our findings and emphasize the importance of these educational experiences for incarcerated students' personal and professional development.

HyProf: A Profiler for Programming Students that Offers Hypotheses about Performance Bugs

Tue, 17 Feb 2026 00:00:00 GMT

HyProf: A Profiler for Programming Students that Offers Hypotheses about Performance Bugs Dargan, Hope; Hartz, Adam; Miller, Robert Programming students often struggle to find and fix performance bugs in their code. To provide students additional performance debugging support, as well as expose them to profiling tools, we developed Hypothesis Profiler (HyProf). HyProf automatically profiles a slow student submission and produces a profile visualization suitable for learners. In addition to showing individual function and line times, HyProf shows details about the call graph, lines that made recursive calls or did not execute, and hypotheses about possible causes of slow performance, formulated by comparing the slow profile against fast submissions from other students. We deployed HyProf in a 400-student Python course and evaluated it through web logs, office hour observations, and surveys, which showed that 75% of respondents successfully used HyProf to find or fix a performance issue and 85% would recommend it to others. SIGCSE TS 2026, St. Louis, MO, USA

KANELÉ: Kolmogorov–Arnold Networks for Efficient LUT-based Evaluation

Sat, 21 Feb 2026 00:00:00 GMT

KANELÉ: Kolmogorov–Arnold Networks for Efficient LUT-based Evaluation Hoang, Duc; Gupta, Aarush; Harris, Philip C Low-latency, resource-efficient neural network inference on FPGAs is essential for applications demanding real-time capability and low power. Lookup table (LUT)-based neural networks are a common solution, combining strong representational power with efficient FPGA implementation. In this work, we introduce KANELÉ, a framework that exploits the unique properties of Kolmogorov–Arnold Networks (KANs) for FPGA deployment. Unlike traditional multilayer perceptrons (MLPs), KANs employ learnable one-dimensional splines with fixed domains as edge activations, a structure naturally suited to discretization and efficient LUT mapping. We present the first systematic design flow for implementing KANs on FPGAs, co-optimizing training with quantization and pruning to enable compact, high-throughput, and low-latency KAN architectures. Our results demonstrate up to a 2700x speedup and orders of magnitude resource savings compared to prior KAN-on-FPGA approaches. Moreover, KANELÉ matches or surpasses other LUT-based architectures on widely used benchmarks, particularly for tasks involving symbolic or physical formulas, while balancing resource usage across FPGA hardware. Finally, we showcase the versatility of the framework by extending it to real-time, power-efficient control systems. FPGA ’26, Seaside, CA, USA

AI Séance: Recounts from designing artificial intelligence for transcendence, interpretive lenses and chance

Thu, 17 Jul 2025 00:00:00 GMT

AI Séance: Recounts from designing artificial intelligence for transcendence, interpretive lenses and chance Schroeder, Hope; Smith, Amy; Epstein, Ziv As AI becomes a prism through which we reflect, see, and make sense of the world, the way we create creative, transcendent experiences around AI can shape our relationship to it. Drawing inspiration from the ritual structures of Spiritualist séances and creative art-making séances of Hilma af Klint, we present reflections from a series of participatory experiments we called AI Séances. These gatherings brought together artists, technologists, and spiritual practitioners to engage with generative models in contexts shaped by ritual, randomness, and collaborative interpretation. We found that creative production with AI can yield transcendent user experiences (TUX), different communities bring distinct interpretive lenses to AI outputs, and increased technical control can paradoxically diminish serendipity and transcendence. Through our experiences, we suggest that reclaiming interpretive agency over AI outputs in the creative and spiritual context, rather than treating models as machines that produce answers, opens up new avenues for critical and creative engagement with these technologies and is critical to preserving our humanity. The AI Séance offers a model for human-centered interaction with generative systems where magic lies not in the machine’s capabilities, but in our collective ability to create meaning.

NeuSE: Neural SE(3)-equivariant embedding for long-term object-based simultaneous localization and mapping

Thu, 01 Jan 2026 00:00:00 GMT

NeuSE: Neural SE(3)-equivariant embedding for long-term object-based simultaneous localization and mapping Fu, Jiahui; Du, Yilun; Singh, Kurran; Tenenbaum, Joshua B; Leonard, John J We present NeuSE, a novel Neural SE(3)-Equivariant Embedding for objects, and illustrate how it supports object-based Simultaneous Localization and Mapping (SLAM) for consistent spatial understanding with long-term scene changes. NeuSE is a set of latent object embeddings created from partial object observations. It serves as a compact point cloud surrogate for complete object models, encoding the full shape, scale, and transform information about an object. In addition, the inferred latent code is both SE(3) and scale equivariant, enabling strong generalization to objects of both unseen sizes and different SE(3) poses. This makes NeuSE particularly effective in real-world scenarios where objects may vary in size or spatial configuration. With NeuSE, relative frame transforms can be directly derived from inferred latent codes. Our proposed SLAM paradigm, using NeuSE for object shape, size, and pose characterization, can operate independently or in conjunction with typical SLAM systems. It directly infers SE(3) camera pose constraints that are compatible with general SLAM pose graph optimization, while maintaining a lightweight, object-centric map that adapts to real-world changes. Our evaluation is conducted on synthetic and real-world sequences with changes in both controlled and uncontrolled settings, featuring multi-category objects of various shapes and sizes. Our approach demonstrates improved localization capability and change-aware mapping consistency when working either independently or as a complement to common SLAM pipelines.

TravelAgent: Generative agents in the built environment

Sun, 01 Feb 2026 00:00:00 GMT

TravelAgent: Generative agents in the built environment Noyman, Ariel; Hu, Kai; Larson, Kent Understanding human behavior in the built environment is critical for designing highly-functional, human-centered urban spaces. Traditional approaches, such as manual observations, surveys, and simple simulations, often struggle to capture the complexity and nuance of real-world human behavior and experience. Here we introduce TravelAgent, a novel agentic simulation platform that models pedestrian navigation, activity, and human-like decision-making in the built environment. TravelAgent is proposed to help design teams and decision-makers understand how different users might experience diverse built environments under varying environmental conditions. TravelAgent integrates Generative Agents, multi-modal sensory inputs, and virtual environments, enabling agents to perceive, navigate, and interact with their surroundings, with tasks ranging from goal-oriented navigation to free exploration. We share analysis from 200 simulations with 3364 decision points and task completion rate of ∼80%, across diverse spatial layouts and agent archetypes. We present spatial, linguistic, and sentiment analysis, and show how agents react and experience their surroundings. Finally, we suggest TravelAgent as a new paradigm for designing, simulating, and understanding human experiences in urban environments.

Cleaning a dark matter detector: A case of ontological and normative elusiveness

Sat, 30 Aug 2025 00:00:00 GMT

Cleaning a dark matter detector: A case of ontological and normative elusiveness de Swart, Jaco; Mol, Annemarie Laboratory sciences crucially depend on the cleanliness of experiments. But what is clean? In this article, we show that the salience of the valuation clean emerges through its relation to a particular ontological repertoire. Our case is the XENONnT experiment in the Gran Sasso Mountains of Italy, designed to detect dark matter in the form of hypothetical WIMPs (Weakly Interacting Massive Particles). In this experiment, dirt presents a significant disruption, as contaminations can mimic the signals of WIMPs, and electronegative molecules risk erasing such signals. The ideosyncratic cleanliness required makes the practice of cleaning the XENONnT detector exceedingly difficult. So far, the ontological question ‘do WIMPs exist?’ remains open, which means that the normative question ‘is the detector clean enough?’ cannot be answered either. In addition, more cleaning will make the detector sensitive to a background of unremovable neutrinos—hence irredeemably dirty. With the normative goal of a ‘clean detector’ out of reach, the ontological question ‘do WIMPs exist?’ is bound to remain open as well. Alternative experiments therefore hunt for different hypothetical dark matter candidates, with different equipment, requiring different kinds of cleanliness. At the same time, the XENONnT experiment must navigate tensions between its own cleanliness goals and rules meant to ensure the environmental cleanliness of the Gran Sasso National Park. Cleaning turns out to be dirty. This leads us to ask: Which goods deserve to be cherished, and, intertwined with that, which realities deserve to be cared for?

Multi-fidelity reinforcement learning for time-optimal quadrotor re-planning

Fri, 22 Aug 2025 00:00:00 GMT

Multi-fidelity reinforcement learning for time-optimal quadrotor re-planning Ryou, Gilhyun; Wang, Geoffrey; Karaman, Sertac High-speed online trajectory planning for UAVs poses a significant challenge due to the need for precise modeling of complex dynamics while also being constrained by computational limitations. This paper presents a multi-fidelity reinforcement learning method (MFRL) that aims to effectively create a realistic dynamics model and simultaneously train a planning policy that can be readily deployed in real-time applications. The proposed method involves the co-training of a planning policy and a reward estimator; the latter predicts the performance of the policy’s output and is trained efficiently through multi-fidelity Bayesian optimization. This optimization approach models the correlation between different fidelity levels, thereby constructing a high-fidelity model based on a low-fidelity foundation, which enables the accurate development of the reward model with limited high-fidelity experiments. The framework is further extended to include real-world flight experiments in reinforcement learning training, allowing the reward model to precisely reflect real-world constraints and broadening the policy’s applicability to real-world scenarios. We present rigorous evaluations by training and testing the planning policy in both simulated and real-world environments. The resulting trained policy not only generates faster and more reliable trajectories compared to the baseline snap minimization method, but it also achieves trajectory updates in 2 ms on average, while the baseline method takes several minutes.

Designing Distribution Network Tariffs in the US with an Application to Increased Electric Vehicle Adoption

Sat, 01 Nov 2025 00:00:00 GMT

Designing Distribution Network Tariffs in the US with an Application to Increased Electric Vehicle Adoption Turk, Graham; Schittekatte, Tim; Duenas-Martinez, Pablo; Joskow, Paul L; Schmalensee, Richard Time-of-use (TOU) tariffs that vary the cost per kWh to reflect wide variations in generation and wholesale market costs give incentives to shift all electric vehicle (EV) charging to low-price periods. As EV penetration increases, such tariffs would substantially raise the local kW demand in those low-priced periods, which eventually would lead to increasing network expansion costs. A straightforward way to mitigate this problem is to separate energy charges from network charges, with appropriate rate designs for each. This paper uses a realistic case study to investigate the implications of combining TOU energy charges with various network tariff designs in the face of increased EV penetration. Our results provide support for the adoption in the US of ex-ante subscribed capacity tariffs (subscription charges), which give consumers incentives to reduce their peak kW demands. Reducing costs of EV ownership (a priority for many US states) need not be pursued at the expense of broader affordability goals. JEL classification: L51, L94, L97, Q41, D40

Geopolitical ecologies of cloud capitalism: Territorial restructuring and the making of national computing power in the U.S. and China

Mon, 15 Sep 2025 00:00:00 GMT

Geopolitical ecologies of cloud capitalism: Territorial restructuring and the making of national computing power in the U.S. and China Kollar, Justin; Stokols, Andrew As computing power becomes central to geopolitical rivalry, cloud infrastructure is increasingly framed as critical to national security, economic resilience and technological sovereignty. Current debates often focus on global competition – especially between the U.S. and China – highlighting strategic investments, export controls and infrastructure diplomacy abroad. Yet far less attention has been paid to the domestic territorial transformations that make such geopolitical projection possible. This paper argues that national strategies for AI and cloud dominance depend on the reorganization of land, energy and regulatory systems to sustain large-scale computation. Using a geopolitical ecology framework, we examine how the U.S. and China build national computing power as a strategic economic and military resource. In the U.S., cloud firms operate as state-aligned actors, drawing on fragmented regulatory authority, public subsidies and national security discourse to expand into rural and peri-urban regions. China pursues a more centralized strategy through its East Data, West Computing initiative, redistributing infrastructure to inland provinces under state-led development goals. Through comparative regional analysis, we show how domestic infrastructural expansion underpins geopolitical rivalry, producing new forms of territorial governance and socio-environmental inequality. Far from immaterial, the cloud is grounded in enclosure, extraction and the spatial foundations of techno-industrial power.

Unlikely Organizers: The Rise of Tech Worker Labor Activism

Thu, 09 Oct 2025 00:00:00 GMT

Unlikely Organizers: The Rise of Tech Worker Labor Activism Tan, JS; Luka, Natalia; Mazo, Emily Tech workers—professionals in the technology industry, such as software engineers, product managers, and UX designers—are not normally associated with labor activism. Yet, since 2017, there has been a significant rise in workplace activism over “bread-and-butter” issues among this group. Using an original data set, the authors demonstrate how, in the case of tech workers, periods of intense workplace social activism preceded later periods of heightened labor activism. Regression analysis confirms that participation in social activism increases the likelihood of labor activism six months to one year later at the same company. Extending Rick Fantasia’s cultures of solidarity to professional workers, the authors highlight a new mechanism by which professionals engage in labor organizing: First, tech workers, guided by their professional interest in socially beneficial work, engage in workplace social activism. This action generates solidarity among employee-participants but also creates conflict with management and leads to the emergence of labor activism among professionals.

Fast detection of liver fibrosis with collagen-binding single-nanometer iron oxide nanoparticles via T1-weighted MRI

Mon, 24 Apr 2023 00:00:00 GMT

Fast detection of liver fibrosis with collagen-binding single-nanometer iron oxide nanoparticles via T1-weighted MRI Zhang, Juanye; Ning, Yingying; Zhu, Hua; Rotile, Nicholas J; Wei, He; Diyabalanage, Himashinie; Hansen, Eric C; Zhou, Iris Y; Barrett, Stephen C; Sojoodi, Mozhdeh; Tanabe, Kenneth K; Humblet, Valerie; Jasanoff, Alan; Caravan, Peter; Bawendi, Moungi G SNIO–CBP, a single-nanometer iron oxide (SNIO) nanoparticle functionalized with a type I collagen-binding peptide (CBP), was developed as a T1-weighted MRI contrast agent with only endogenous elements for fast and noninvasive detection of liver fibrosis. SNIO–CBP exhibits 6.7-fold higher relaxivity compared to a molecular gadolinium-based collagen-binding contrast agent CM-101 on a per CBP basis at 4.7 T. Unlike most iron oxide nanoparticles, SNIO–CBP exhibits fast elimination from the bloodstream with a 5.7 min half-life, high renal clearance, and low, transient liver enhancement in healthy mice. We show that a dose of SNIO–CBP that is 2.5-fold lower than that for CM-101 has comparable imaging efficacy in rapid (within 15 min following intravenous injection) detection of hepatotoxin-induced liver fibrosis using T1-weighted MRI in a carbon tetrachloride–induced mouse liver injury model. We further demonstrate the applicability of SNIO–CBP in detecting liver fibrosis in choline-deficient L-amino acid-defined high-fat diet mouse model of nonalcoholic steatohepatitis. These results provide a platform with potential for the development of high relaxivity, gadolinium-free molecular MRI probes for characterizing chronic liver disease.

Quantum Shell in a Shell: Engineering Colloidal Nanocrystals for a High-Intensity Excitation Regime

Tue, 06 Jun 2023 00:00:00 GMT

Quantum Shell in a Shell: Engineering Colloidal Nanocrystals for a High-Intensity Excitation Regime Harankahage, Dulanjan; Cassidy, James; Beavon, Jacob; Huang, Jiamin; Brown, Niamh; Berkinsky, David B; Marder, Andrew; Kayira, Barbra; Montemurri, Michael; Anzenbacher, Pavel; Schaller, Richard D; Sun, Liangfeng; Bawendi, Moungi G; Malko, Anton V; Diroll, Benjamin T; Zamkov, Mikhail Many optoelectronic processes in colloidal semiconductor nanocrystals (NCs) suffer an efficiency decline under high-intensity excitation. This issue is caused by Auger recombination of multiple excitons, which converts the NC energy into excess heat, reducing the efficiency and life span of NC-based devices, including photodetectors, X-ray scintillators, lasers, and high-brightness light-emitting diodes (LEDs). Recently, semiconductor quantum shells (QSs) have emerged as a promising NC geometry for the suppression of Auger decay; however, their optoelectronic performance has been hindered by surface-related carrier losses. Here, we address this issue by introducing quantum shells with a CdS-CdSe-CdS-ZnS core-shell-shell-shell multilayer structure. The ZnS barrier inhibits the surface carrier decay, which increases the photoluminescence (PL) quantum yield (QY) to 90% while retaining a high biexciton emission QY of 79%. The improved QS morphology allows demonstrating one of the longest Auger lifetimes reported for colloidal NCs to date. The reduction of nonradiative losses in QSs also leads to suppressed blinking in single nanoparticles and low-threshold amplified spontaneous emission. We expect that ZnS-encapsulated quantum shells will benefit many applications exploiting high-power optical or electrical excitation regimes.

Synthesis of Zwitterionic CsPbBr3 Nanocrystals with Controlled Anisotropy using Surface-Selective Ligand Pairs

Mon, 24 Jul 2023 00:00:00 GMT

Synthesis of Zwitterionic CsPbBr3 Nanocrystals with Controlled Anisotropy using Surface-Selective Ligand Pairs Zhu, Hua; Kick, Matthias; Ginterseder, Matthias; Krajewska, Chantalle J; Šverko, Tara; Li, Ruipeng; Lu, Yongli; Shih, Meng‐Chen; Van Voorhis, Troy; Bawendi, Moungi G Mechanistic studies of the morphology of lead halide perovskite nanocrystals (LHP‐NCs) are hampered by a lack of generalizable suitable synthetic strategies and ligand systems. Here, the synthesis of zwitterionic CsPbBr3 NCs is presented with controlled anisotropy using a proposed “surface‐selective ligand pairs” strategy. Such a strategy provides a platform to systematically study the binding affinity of capping ligand pairs and the resulting LHP morphologies. By using zwitterionic ligands (ZwL) with varying structures, majority ZwL‐capped LHP NCs with controlled morphology are obtained, including anisotropic nanoplatelets and nanorods, for the first time. Combining experiments with density functional theory calculations, factors that govern the ligand binding on the different surface facets of LHP‐NCs are revealed, including the steric bulkiness of the ligand, the number of binding sites, and the charge distance between binding moieties. This study provides guidance for the further exploration of anisotropic LHP‐NCs.

Theory of Photoluminescence Spectral Line Shapes of Semiconductor Nanocrystals

Tue, 08 Aug 2023 00:00:00 GMT

Theory of Photoluminescence Spectral Line Shapes of Semiconductor Nanocrystals Lin, Kailai; Jasrasaria, Dipti; Yoo, Jason J; Bawendi, Moungi; Utzat, Hendrik; Rabani, Eran Single-molecule photoluminescence (PL) spectroscopy of semiconductor nanocrystals (NCs) reveals the nature of exciton-phonon interactions in NCs. Understanding the homogeneous spectral line shapes and their temperature dependence remains an open problem. Here, we develop an atomistic model to describe the PL spectrum of NCs, accounting for excitonic effects, phonon dispersion relations, and exciton-phonon couplings. We validate our model using single-NC measurements on CdSe/CdS NCs from T = 4 to 290 K, and we find that the slightly asymmetric main peak at low temperatures is comprised of a narrow zero-phonon line (ZPL) and acoustic phonon sidebands. Furthermore, we identify the specific phonon modes that give rise to the optical phonon sidebands. At temperatures above 200 K, the spectral line width shows a stronger dependence upon the temperature, which we demonstrate to be correlated with higher order exciton-phonon couplings. We also identify the line width dependence upon reorganization energy, NC core sizes, and shell thicknesses.

Ultrafast dense DNA functionalization of quantum dots and rods for scalable 2D array fabrication with nanoscale precision

Fri, 11 Aug 2023 00:00:00 GMT

Ultrafast dense DNA functionalization of quantum dots and rods for scalable 2D array fabrication with nanoscale precision Chen, Chi; Luo, Xin; Kaplan, Alexander EK; Bawendi, Moungi G; Macfarlane, Robert J; Bathe, Mark Scalable fabrication of two-dimensional (2D) arrays of quantum dots (QDs) and quantum rods (QRs) with nanoscale precision is required for numerous device applications. However, self-assembly–based fabrication of such arrays using DNA origami typically suffers from low yield due to inefficient QD and QR DNA functionalization. In addition, it is challenging to organize solution-assembled DNA origami arrays on 2D device substrates while maintaining their structural fidelity. Here, we reduced manufacturing time from a few days to a few minutes by preparing high-density DNA-conjugated QDs/QRs from organic solution using a dehydration and rehydration process. We used a surface-assisted large-scale assembly (SALSA) method to construct 2D origami lattices directly on solid substrates to template QD and QR 2D arrays with orientational control, with overall loading yields exceeding 90%. Our fabrication approach enables the scalable, high fidelity manufacturing of 2D addressable QDs and QRs with nanoscale orientational and spacing control for functional 2D photonic devices.

Rational Design of a Chemical Bath Deposition Based Tin Oxide Electron‐Transport Layer for Perovskite Photovoltaics

Tue, 18 Jul 2023 00:00:00 GMT

Rational Design of a Chemical Bath Deposition Based Tin Oxide Electron‐Transport Layer for Perovskite Photovoltaics Lu, Yongli; Shih, Meng‐Chen; Tan, Shaun; Grotevent, Matthias J; Wang, Lili; Zhu, Hua; Zhang, Ruiqi; Lee, Joo‐Hong; Lee, Jin‐Wook; Bulović, Vladimir; Bawendi, Moungi G Chemical bath deposition (CBD) is widely used to deposit tin oxide (SnOx) as an electron-transport layer in perovskite solar cells (PSCs). The conventional recipe uses thioglycolic acid (TGA) to facilitate attachments of SnOx particles onto the substrate. However, nonvolatile TGA is reported to harm the operational stability of PSCs. In this work, a volatile oxalic acid (OA) is introduced as an alternative to TGA. OA, a dicarboxylic acid, functions as a chemical linker for the nucleation and attachment of particles to the substrate in the chemical bath. Moreover, OA can be readily removed through thermal annealing followed by a mild H2O2 treatment, as shown by FTIR measurements. Synergistically, the mild H2O2 treatment selectively oxidizes the surface of the SnOx layer, minimizing nonradiative interface carrier recombination. EELS (electron-energy-loss spectroscopy) confirms that the SnOx surface is dominated by Sn4+, while the bulk is a mixture of Sn2+ and Sn4+. This rational design of a CBD SnOx layer leads to devices with T85 ≈1500 h, a significant improvement over the TGA-based device with T80 ≈250 h. The champion device reached a power conversion efficiency of 24.6%. This work offers a rationale for optimizing the complex parameter space of CBD SnOx to achieve efficient and stable PSCs.

Reduced recombination via tunable surface fields in perovskite thin films

Wed, 28 Feb 2024 00:00:00 GMT

Reduced recombination via tunable surface fields in perovskite thin films deQuilettes, Dane W; Yoo, Jason J; Brenes, Roberto; Kosasih, Felix Utama; Laitz, Madeleine; Dou, Benjia Dak; Graham, Daniel J; Ho, Kevin; Shi, Yangwei; Shin, Seong Sik; Ducati, Caterina; Bawendi, Moungi G; Bulović, Vladimir The ability to reduce energy loss at semiconductor surfaces through passivation or surface field engineering is an essential step in the manufacturing of efficient photovoltaic (PV) and optoelectronic devices. Similarly, surface modification of emerging halide perovskites with quasi-two-dimensional (2D) heterostructures is now ubiquitous to achieve PV power conversion efficiencies (PCEs) >25%, yet a fundamental understanding to how these treatments function is still generally lacking. Here we use a unique combination of depth-sensitive nanoscale characterization techniques to uncover a tunable passivation strategy and mechanism found in perovskite PV devices that were the first to reach the >25% PCE milestone. Namely, treatment with hexylammonium bromide leads to the simultaneous formation of an iodide-rich 2D layer along with a Br halide gradient that extends from defective surfaces and grain boundaries into the bulk three-dimensional (3D) layer. This interface can be optimized to extend the charge carrier lifetime to record values >30 μs and to reduce interfacial recombination velocities to values as low as <7 cm s−1.

Solution-phase sample-averaged single-particle spectroscopy of quantum emitters with femtosecond resolution

Mon, 08 Apr 2024 00:00:00 GMT

Solution-phase sample-averaged single-particle spectroscopy of quantum emitters with femtosecond resolution Shi, Jiaojian; Shen, Yuejun; Pan, Feng; Sun, Weiwei; Mangu, Anudeep; Shi, Cindy; McKeown-Green, Amy; Moradifar, Parivash; Bawendi, Moungi G; Moerner, WE; Dionne, Jennifer A; Liu, Fang; Lindenberg, Aaron M The development of many quantum optical technologies depends on the availability of single quantum emitters with near-perfect coherence. Systematic improvement is limited by a lack of understanding of the microscopic energy flow at the single-emitter level and ultrafast timescales. Here we utilize a combination of fluorescence correlation spectroscopy and ultrafast spectroscopy to capture the sample-averaged dynamics of defects with single-particle sensitivity. We employ this approach to study heterogeneous emitters in two-dimensional hexagonal boron nitride. From milliseconds to nanoseconds, the translational, shelving, rotational and antibunching features are disentangled in time, which quantifies the normalized two-photon emission quantum yield. Leveraging the femtosecond resolution of this technique, we visualize electron–phonon coupling and discover the acceleration of polaronic formation on multi-electron excitation. Corroborated with theory, this translates to the photon fidelity characterization of cascaded emission efficiency and decoherence time. Our work provides a framework for ultrafast spectroscopy in heterogeneous emitters, opening new avenues of extreme-scale characterization for quantum applications.

Additive‐Free Oxidized Spiro‐MeOTAD Hole Transport Layer Significantly Improves Thermal Solar Cell Stability

Thu, 06 Jun 2024 00:00:00 GMT

Additive‐Free Oxidized Spiro‐MeOTAD Hole Transport Layer Significantly Improves Thermal Solar Cell Stability Grotevent, Matthias J; Lu, Yongli; Šverko, Tara; Shih, Meng‐Chen; Tan, Shaun; Zhu, Hua; Dang, Tong; Mwaura, Jeremiah K; Swartwout, Richard; Beiglböck, Finn; Kothe, Linda; Bulović, Vladimir; Bawendi, Moungi G Perovskite solar cells are among the most promising new solar technologies, already surpassing polycrystalline silicon solar cell efficiencies. The stability of the highest efficiency devices at elevated temperature is, however, poor. These cells typically use Spiro‐MeOTAD as the hole transporting layer. It is generally believed that additives, required for enhancing electrical conductivity and optimizing energy level alignment, are responsible for the reduced stability—inferring that Spiro‐MeOTAD based hole transporting layers are intrinsically unstable. Here, a reliable noble metal free synthesis of Spiro‐MeOTAD (bis(trifluoromethane)sulfonimide)4 is presented which is used as the oxidizing agent. No additives are added to the partially oxidized Spiro‐MeOTAD hole‐transporting layer. Device efficiencies up to 24.2% are achieved. Electrical conductivity is largely developed by the first 1% oxidation. Further oxidation shifts the energy levels away from the vacuum level, which allows tuning of the energy level alignment without the use of additives—contradicting the current understanding of this system. Without additives, devices demonstrate significant improvement in stability at elevated temperatures up to 85 °C under one sun over 1400 h continuous illumination. The remaining degradation is pinpointed to ion migration and reactions in the perovskite layer which may be further suppressed with compositional engineering and adequate ion barrier layers.

Bright and Fast Emission from Robust Supramolecular J-Aggregate Nanostructures through Silica-Encapsulation

Wed, 24 Jul 2024 00:00:00 GMT

Bright and Fast Emission from Robust Supramolecular J-Aggregate Nanostructures through Silica-Encapsulation Thanippuli Arachchi, Dimuthu H; Barotov, Ulugbek; Perkinson, Collin F; Šverko, Tara; Kaplan, Alexander EK; Bawendi, Moungi G We introduce a two-step silica-encapsulation procedure to optimize both the optical efficiency and structural robustness of 5,5',6,6'-tetrachloro-1,1'-diethyl-3,3'-di(4-sulfobutyl)-benzimidazolocarbocyanine (TDBC), a two-dimensional sheet-like J-aggregate. We report a fluorescence quantum yield of ∼98%, the highest quantum yield recorded for any J-aggregate structure at room temperature, and a fast, emissive lifetime of 234 ps. Silica, as an encapsulating matrix, provides optical transparency, chemical inertness, and robustness to dilution, while rigidifying the J-aggregate structure. Our in situ encapsulation process preserves the excitonic structure in TDBC J-aggregates, maintaining their light absorption and emission properties. The homogeneous silica coating has an average thickness of 0.5-1 nm around J-aggregate sheets. Silica encapsulation permits extensive dilutions of J-aggregates without significant disintegration into monomers. The narrow absorbance and emission line widths exhibit further narrowing upon cooling to 79 K, which is consistent with J-type coupling in the encapsulated aggregates. This silica TDBC J-aggregate construct signifies (1) a bright, fast, and robust fluorophore system, (2) a platform for further manipulation of J-aggregates as building blocks for integration with other optical materials and structures, and (3) a system for fundamental studies of exciton delocalization, transport, and emission dynamics within a rigid matrix.

Toward biophysical markers of depression vulnerability

Tue, 18 Oct 2022 00:00:00 GMT

Toward biophysical markers of depression vulnerability Pinotsis, DA; Fitzgerald, S; See, C; Sementsova, A; Widge, AS A major difficulty with treating psychiatric disorders is their heterogeneity: different neural causes can lead to the same phenotype. To address this, we propose describing the underlying pathophysiology in terms of interpretable, biophysical parameters of a neural model derived from the electroencephalogram. We analyzed data from a small patient cohort of patients with depression and controls. Using DCM, we constructed biophysical models that describe neural dynamics in a cortical network activated during a task that is used to assess depression state. We show that biophysical model parameters are biomarkers, that is, variables that allow subtyping of depression at a biological level. They yield a low dimensional, interpretable feature space that allowed description of differences between individual patients with depressive symptoms. They could capture internal heterogeneity/variance of depression state and achieve significantly better classification than commonly used EEG features. Our work is a proof of concept that a combination of biophysical models and machine learning may outperform earlier approaches based on classical statistics and raw brain data.

Understanding Robustness and Generalization of Artificial Neural Networks Through Fourier Masks

Tue, 12 Jul 2022 00:00:00 GMT

Understanding Robustness and Generalization of Artificial Neural Networks Through Fourier Masks Karantzas, Nikos; Besier, Emma; Ortega Caro, Josue; Pitkow, Xaq; Tolias, Andreas S.; Patel, Ankit B.; Anselmi, Fabio Despite the enormous success of artificial neural networks (ANNs) in many disciplines, the characterization of their computations and the origin of key properties such as generalization and robustness remain open questions. Recent literature suggests that robust networks with good generalization properties tend to be biased toward processing low frequencies in images. To explore the frequency bias hypothesis further, we develop an algorithm that allows us to learn modulatory masks highlighting the essential input frequencies needed for preserving a trained network's performance. We achieve this by imposing invariance in the loss with respect to such modulations in the input frequencies. We first use our method to test the low-frequency preference hypothesis of adversarially trained or data-augmented networks. Our results suggest that adversarially robust networks indeed exhibit a low-frequency bias but we find this bias is also dependent on directions in frequency space. However, this is not necessarily true for other types of data augmentation. Our results also indicate that the essential frequencies in question are effectively the ones used to achieve generalization in the first place. Surprisingly, images seen through these modulatory masks are not recognizable and resemble texture-like patterns.

Enhancement of Cyanobacterial Bloom Monitoring in Lake Taihu Using Dual Red-Edge Bands of GF-6/WFV: Multi-Dimensional Feature Combination and Extraction Accuracy Analysis

Fri, 20 Feb 2026 00:00:00 GMT

Enhancement of Cyanobacterial Bloom Monitoring in Lake Taihu Using Dual Red-Edge Bands of GF-6/WFV: Multi-Dimensional Feature Combination and Extraction Accuracy Analysis Sun, Yunxiao; Zhang, Ruolin; Zhao, Chunhong; Meng, Qingyan; Sun, Zhenhui; Wang, Jialong; Wu, Jun; Wang, Yao; Gao, Decai; Guan, Huyi Cyanobacterial blooms pose a serious threat to freshwater ecosystems, necessitating accurate remote sensing monitoring. Although red-edge bands show potential in terrestrial monitoring, their multi-dimensional features (i.e., spectral, textural, and index-based characteristics) remain underutilized for aquatic blooms. This study leverages the dual red-edge bands (710 nm and 750 nm) of GF-6/WFV to enhance cyanobacterial bloom identification in Lake Taihu. Multi-temporal images from 2019–2023 were used to construct red-edge features in three dimensions: spectral (evaluated via adaptive band selection method) and Jeffries–Matusita–Bhattacharyya distance), texture (based on Gray Level Co-occurrence Matrix and principal component analysis), and indices (nine vegetation indices ranked by Random Forest importance). Twelve feature-combination schemes were designed and implemented with a Random Forest classifier. Results show that red-edge features consistently improve identification accuracy. Quantitatively, compared to the basic four-band (RGBN) combination, the 710 nm band improved spectral separability by an average of 9.63%, whereas the 750 nm band yielded a lower average improvement of 5.69%. Red-edge indices, especially the modified chlorophyll absorption reflectance index 1 (MCARI1) and normalized difference red-edge index (NDRE), exhibited higher importance than non-red-edge indices. All schemes incorporating red-edge features achieved mean overall accuracies of 92.8–94.9% and Kappa coefficients of 0.86–0.94, surpassing the basic four-band scheme. Among these features, red-edge indices contributed most significantly to accuracy gains, increasing the overall accuracy by an average of 0.36–6.06% and the Kappa coefficient by up to 0.06. The enhancement effect of the red-edge 710 nm band features was superior to that of the 750 nm band. This study demonstrates that multi-dimensional red-edge features effectively enhance the identification accuracy of cyanobacterial blooms and provides a methodological reference for operational GF-6 applications in water quality monitoring.

Biological Activity of Metal Complexes

Tue, 17 Feb 2026 00:00:00 GMT

Biological Activity of Metal Complexes Sharma, Vinay K. Metal complexes play a fundamental role in biological systems and continue to attract sustained interest due to their remarkable potential in therapeutic, diagnostic, and biotechnological applications [1–8]. In recent years, the field of bioinorganic chemistry has advanced rapidly, driven by progress in coordination chemistry, spectroscopy, nanotechnology, and molecular biology [9–22]. These developments have enabled a deeper understanding of how metal ions and complexes interact with biomolecular targets and have opened new avenues for the rational design of metal-based agents for cancer therapy, antimicrobial treatment, imaging, and the study of metal-mediated biochemical processes [23–30].

Single Parameter Model for Galaxy Rotation Curves

Sun, 15 Feb 2026 00:00:00 GMT

Single Parameter Model for Galaxy Rotation Curves Cisneros, Sophia N.; Ott, Rich; Crowley, Meagan; Roberts, Amy; Paz, Marcus One key piece of evidence for dark matter is the rotation-curve problem: the disagreement between measured galactic rotation curves and their luminous mass. A novel solution to this problem is presented here, in a model that predicts observed Doppler-shifted spectra based only on the luminous matter estimates and one free model parameter 𝛼. This model is applied to fit the rotation curves of the SPARC sample of 175 galaxies, yielding mass-to-light ratios, goodness of fit measurements, and 𝛼. The measured average 𝜒2 𝑟 =2.24 compares favorably with the Navarro-Frenk-White dark matter model’s average of 𝜒2 𝑟 =4.19 for the same data, and more galaxies are successfully fit by this model. The model provides a useful formulation linking luminous matter to the observed rotation curves, with the dark matter contribution to galaxies encoded in two transformation terms of the luminous mass. It also offers a lower-parameter characterization of the rotation curve problem, and a power law relationship between 𝛼 and galactic photometric quantities is observed, potentially removing the need for the free parameter.

Non-Clinical Safety of GRAd Vector-Based COVID-19 and HIV Vaccines Supports a Platform Regulatory Approach

Fri, 06 Feb 2026 00:00:00 GMT

Non-Clinical Safety of GRAd Vector-Based COVID-19 and HIV Vaccines Supports a Platform Regulatory Approach Paalangara, Reji; Gohin, Stephanie; Menard, Alexis; Amy, Charlotte; Berrabah, Wahiba; Rogue, Alexandra; Getz, Matthew A.; Alrubayyi, Aljawharah; Battella, Simone; Raggioli, Angelo; Gentile, Michela; Di Rita, Anthea; Noto, Alessia; Miselli, Giuseppina; Grazioli, Fabiana; Napolitano, Federico; Sowcik, Dhurata; Soriani, Marco; Chmielewski, Benjamin; Molife, Lebohang Background/Objectives: The rapid development of safe and efficacious vaccines is often hindered by extensive, mandated non-clinical safety evaluations in animals. With the aim to provide scientific evidence supporting a “vaccine platform approach”, here we present the complete non-clinical studies for two investigational vaccines, GRAd-COV2 and GRAdHIVNE1, based on GRAd, a gorilla-derived group C adenoviral vector. Methods: The biodistribution of GRAd genomes following the intramuscular administration of the vaccines was assessed in rats by a sensitive qPCR method. Local tolerance and systemic toxic effects were evaluated in single- and repeated-dose toxicity studies in rabbits. Results: GRAd-COV2 and GRAdHIVNE1 were well-tolerated. Distribution was highly confined to the injection site and draining lymph nodes, and toxicity profile consisted of transient, non-adverse inflammatory responses, while the expected immune responses to the encoded antigens were successfully induced. Notably, both vaccines demonstrated a consistent safety profile despite transgene and backbone differences, comparable to other replication-defective adenoviral vectors. Conclusions: The established non-clinical safety profile of the GRAd platform provides a robust foundation for a more efficient and streamlined regulatory pathway. By leveraging this prior knowledge, future GRAd-based vaccines can achieve accelerated clinical development while fully adhering to the ethical principles of replacement, reduction, and refinement of animal use in research.

Design and User-Centered Field Evaluation of an Accessible Precision Irrigation Tool and Its Human–Machine Interaction on a Jordanian Farm

Wed, 04 Feb 2026 00:00:00 GMT

Design and User-Centered Field Evaluation of an Accessible Precision Irrigation Tool and Its Human–Machine Interaction on a Jordanian Farm Van de Zande, Georgia D.; Sheline, Carolyn; Pratt, Shane R.; Winter V, Amos G. This work aims to demonstrate the successful, long-term human use of an automatic scheduling-manual operation (AS-MO) precision irrigation tool by farmers on a medium-scale Jordanian farm. Innovation in low-cost, accessible, and water-efficient irrigation technologies is critical as water resources become scarce, especially on resource-constrained farms in the drought-prone Middle East and North Africa (MENA) region. Prior work has shown that a proposed AS-MO decision support tool could bridge the gap between fully manual irrigation—a common practice on many MENA farms—and existing precision agriculture solutions, which are often too expensive or complex for medium-scale farmers to adopt. Recent developments have also demonstrated that the scheduling theory behind the proposed AS-MO tool uses up to 44% less water compared to fully manual irrigation. However, a functional design of the AS-MO tool has not been realized nor has it been demonstrated on a farm with farmer users. This work documents the detailed design of an AS-MO tool’s human–machine interaction (HMI) and validates the human execution of the tool in context. Through an 11-week case study conducted on a Jordanian farm, we show that farmers used a functional prototype of the AS-MO tool as intended. The functional tool prototype was designed to deliver a long-term AS-MO user experience to study participants. The prototype monitored local weather conditions, generated water-efficient schedules using an existing scheduling theory, and notified users’ phones when they should manually open or close valves. The irrigation practices of participants using the AS-MO prototype were measured, and participants demonstrated successful use of the tool. Users correctly confirmed 93% of the scheduled events using the tool’s HMI. Despite manual operation, a majority of confirmed irrigation event durations fell within 15% of the automatically scheduled durations; relative to the length of scheduled irrigation event durations, the medians of confirmed and scheduled durations were 102% and 88%, respectively. These results demonstrate the success of the tool’s decision support ability. Feedback from study participants can support the AS-MO tool’s next design iteration and can inform the development of other decision support systems designed for resource-constrained, medium-scale farms. This work presents an important step towards developing a precision irrigation tool that, if adopted at scale, could increase the adoption of water-efficient irrigation practices on resource-constrained farms that are not served by existing technology, improving sustainable agriculture in MENA.

The Effect of Genipin Matrix Augmentation on the Retention of Glycosaminoglycans in the Intervertebral Disc—A Pilot Study

Mon, 02 Feb 2026 00:00:00 GMT

The Effect of Genipin Matrix Augmentation on the Retention of Glycosaminoglycans in the Intervertebral Disc—A Pilot Study Hedman, Thomas; Brown, Matthew; Slusarewicz, Pawel The degradation of intervertebral disc proteoglycans, including the loss or shortening of their hydrophilic glycosaminoglycan chains, causes a loss of disc hydration, leading to an increase in solid matrix stresses. This illustrates one aspect of the complex multifactorial relationship between tissue degradation and the resulting mechanical dysfunction. Genipin matrix augmentation has previously been evaluated with regard to its ability to improve mechanical properties of the disc, increasing joint stability and permeability. The study aim was to evaluate the ability of genipin augmentation to increase retention of glycosaminoglycans in disc specimens subjected to free swelling. Three different models were utilized: whole bovine caudal discs, partial annulus specimens from bovine, and human thoracic discs. Total glycosaminoglycan release to a surrounding bath was quantified using a modified dimethyl-methylene blue assay. Genipin solution injections reduced glycosaminoglycan loss by 44.0% in intact bovine discs compared to buffer-only controls (p = 0.027), by 75.8% in partial bovine annulus specimens (p = 0.0004), and by 51.9% in human annulus specimens (p = 0.017). The combination of increased permeability and glycosaminoglycans retention may produce beneficial effects on nutritional flow, diurnal irrigation, and reduction of matrix solid phase stress. Combining these effects with the ability to improve joint stability and augment tissue mechanical properties suggests this nano-scale device may be capable of arresting ongoing degeneration.

A Novel Recurrent Neural Network Framework for Prediction and Treatment of Oncogenic Mutation Progression

Mon, 02 Feb 2026 00:00:00 GMT

A Novel Recurrent Neural Network Framework for Prediction and Treatment of Oncogenic Mutation Progression Parthasarathy, Rishab; Bhowmik, Achintya K. Despite significant medical advancements, cancer remains the second leading cause of death in the US, causing over 600,000 deaths per year. One emerging field, pathway analysis, is promising but still relies on manually derived wet lab data, which is time-consuming to acquire. This work proposes an efficient, effective, end-to-end framework for Artificial Intelligence (AI)-based pathway analysis that predicts both cancer severity and mutation progression in order to recommend possible treatments. The proposed technique involves a novel combination of time-series machine learning models and pathway analysis. First, mutation sequences were isolated from The Cancer Genome Atlas (TCGA) Database. Then, a novel preprocessing algorithm was used to filter key mutations by mutation frequency. This data was fed into a Recurrent Neural Network (RNN) that predicted cancer severity. The model probabilistically used the RNN predictions, information from the preprocessing algorithm, and multiple drug-target databases to predict future mutations and recommend possible treatments. This framework achieved robust results and Receiver Operating Characteristic (ROC) curves (a key statistical metric) with accuracies greater than 60%, similar to existing cancer diagnostics. In addition, preprocessing played a key role in isolating a few hundred key driver mutations per cancer stage, consistent with current research. Heatmaps based on predicted gene frequency were also generated, highlighting key mutations in each cancer. Overall, this work is the first to propose an efficient, cost-effective end-to-end framework for projecting cancer prognosis and providing possible treatments without relying on expensive, time-consuming wet lab work.

All-Pay Auctions with Different Forfeits

Fri, 09 Jan 2026 00:00:00 GMT

All-Pay Auctions with Different Forfeits Kang, Benjamin; Unwin, James In an auction, each party bids a certain amount, and the one who bids the highest is the winner. Interestingly, auctions can also be used as models for other real-world systems. In an all-pay auction all parties must pay a forfeit for bidding. In the most commonly studied all-pay auction, parties forfeit their entire bid, and this has been considered as a model for expenditure on political campaigns. Here, we consider a number of alternative forfeits that might be used as models for different real-world competitions, such as preparing bids for defense or infrastructure contracts.

Spontaneous formation of robust two-dimensional perovskite phases

Thu, 08 May 2025 00:00:00 GMT

Spontaneous formation of robust two-dimensional perovskite phases Tan, Shaun; Shih, Meng-Chen; Lu, Yongli; Choi, Seung-Gu; Dong, Yifan; Lee, Joo-Hong; Yavuz, Ilhan; Larson, Bryon W; Park, So Yeon; Kodalle, Tim; Zhang, Ruiqi; Grotevent, Matthias J; Lin, Yu-Kuan; Zhu, Hua; Bulović, Vladimir; Sutter-Fella, Carolin M; Park, Nam-Gyu; Beard, Matthew C; Lee, Jin-Wook; Zhu, Kai; Bawendi, Moungi G The two-dimensional on three-dimensional (2D/3D) perovskite bilayer heterostructure can improve the stability and performance of perovskite solar cells. We show that the 2D/3D perovskite stack in a device evolves dynamically during its end-of-life decomposition. Initially phase-pure 2D interlayers can evolve differently, resulting in different device stabilities. We show that a robust 2D interlayer can be formed using mixed solvents to regulate its crystallinity and phase purity. The resulting 2D/3D devices achieved 25.9% efficiency and had good durability, retaining 91% of their initial performance after 1074 hours at 85°C using maximum power point tracking.

Third-order photon correlations extract single-nanocrystal multiexciton properties in solution

Mon, 28 Jul 2025 00:00:00 GMT

Third-order photon correlations extract single-nanocrystal multiexciton properties in solution Horowitz, Jonah R; Berkinsky, David B; Bendekgey, Henry C; Tye, Oliver J; Šverko, Tara; Shulenberger, Katherine E; Bawendi, Moungi G Colloidal semiconductor nanocrystals are considered promising materials for high-flux optical applications, including lasing, light-emitting diodes, biological imaging, and quantum optics. In high-flux applications, multiexcitons can significantly contribute to emission, influencing its brightness, spectral purity, and kinetics. As a result, understanding and controlling multiexciton emission in colloidal nanocrystal materials is of the utmost importance. In the past, single-nanocrystal photon correlation methods have been applied to understand biexciton and triexciton efficiencies, lifetimes, and spectra. While powerful, such methods suffer from user selection bias and require stable emission from single nanocrystals. To compensate for this shortcoming, second-order correlation methods were developed to extract sample-averaged biexciton properties from a solution of nanocrystals. Until now, however, the analogous third-order solution photon correlation methods remained unexplored. In this work, we present a pair of third-order photon correlation techniques to obtain the sample-averaged single-nanocrystal triexciton quantum yield and lifetime in a solution-phase experiment. These techniques derive from the relationship between the Poisson probability of nanocrystal photon absorption and the intrinsic probability of nanocrystal photon emission. We validate the theoretical background of these techniques by creating a numerical model to simulate the diffusion and emission of many nanocrystals in solution. Our simulations confirm that the average triexciton quantum yield and triexciton lifetime can be extracted from a solution of nanocrystals. These techniques will enable researchers to gain a better understanding of the fundamental multiexciton properties of colloidal nanocrystals.

Challenges of II‐VI and III‐V Blue Quantum Dot Light‐Emitting Diodes

Mon, 22 Sep 2025 00:00:00 GMT

Challenges of II‐VI and III‐V Blue Quantum Dot Light‐Emitting Diodes Tan, Shaun; Horowitz, Jonah R; Tye, Oliver J; Bawendi, Moungi G Quantum dot light-emitting diodes (QD-LEDs) are electroluminescent devices where the emissive layer consists of inorganic colloidal quantum dots. Recent breakthroughs have enabled the development of bright and efficient blue-emitting QD-LEDs based on heavy metal-free compositions. However, challenges remain that hinder their practical application in electroluminescent displays and lighting technologies. The primary obstacle is their limited operational lifetimes which remain significantly below practical requirement standards, especially in comparison to the red- and green-emitting QD-LEDs. Another important issue is the low color purity and broad spectral linewidths of heavy metal-free blue quantum dot compositions. Additional problems include transient electroluminescent behaviors such as fluorescence intermittency and positive aging effects. This review examines the current understanding of the physical mechanisms underlying these challenges faced by blue QD-LEDs. Often, contradictory explanations are proposed to account for the same phenomenon. Here, potential interpretations are suggested that may help reconcile the conflicting reports. Recent advances are further examined that have contributed to the development of state-of-the-art blue QD-LEDs.

Impact of Processing Environment on Anti-Solvent Free FAPbI3 Films and Solar Cells

Wed, 17 Dec 2025 00:00:00 GMT

Impact of Processing Environment on Anti-Solvent Free FAPbI3 Films and Solar Cells Wall, Elizabeth M; Lin, Yu‐Kuan; Bawendi, Moungi; Burlingame, Quinn C; Loo, Yueh‐Lin As perovskite solar cells approach commercialization, understanding the environmental sensitivities of perovskites during fabrication becomes increasingly important. In this work, the humidity-dependence of each deposition and annealing step in the anti-solvent-free two-step formamidinium lead iodide fabrication process is investigated in air and N2. In-situ grazing-incidence wide-angle X-ray scattering measurements during spin-coating indicate that humidity affects the formation and dynamics of intermediate phases in perovskite precursor films. These differences, and those induced by annealing in humidity, impact the structure, morphology, and composition of resultant perovskite films, though the initial performance of solar cells fabricated using these active layers is relatively insensitive to humidity across the range studied. In contrast, stability is maximized in devices with dry-processed active layers and those terminally annealed in humidity. Spin-coating of PbI2 is most environmentally sensitive—needle-like structures precipitate while spin-coating in 40% relative humidity leading to significantly reduced photovoltaic performance and device stability. Additionally, films and solar cells fabricated in air appear virtually identical to those fabricated in N2. Collectively, these results show that optimal performance and stability of two-step processed formamidinium lead iodide solar cells is achieved when fabricating active layers in a dry atmosphere or with some humidity during the final anneal.

Cognitive Reinforcement: Capturing Tacit Knowledge and Enhancing Expertise with a Biofeedback Interface for Visual Attention

Wed, 04 Mar 2026 00:00:00 GMT

Cognitive Reinforcement: Capturing Tacit Knowledge and Enhancing Expertise with a Biofeedback Interface for Visual Attention Armengol-Urpi, Alexandre; Salazar-Gomez, Andres F.; Sinha, Pawan; Sarma, Sanjay E. Objective. Tacit or implicit knowledge refers to know-how that experts possess but often cannot articulate, codify, or explicitly transfer to others. This can present a significant challenge for learning, skill acquisition, and knowledge transfer across various domains, including those that rely on apprenticeships, craftsmanship, sports, and medical imaging diagnosis. This study explores whether expert tacit knowledge can be accessed and leveraged using an EEG and gaze-informed biofeedback interface to enhance expertise transfer and training. Approach. We designed an image classification task where novices were trained until they implicitly learned to classify images correctly, despite being unaware of which image regions or features guided their decisions. The task involved images with a hidden spatial asymmetry that even trained participants did not explicitly recognize. Using combined eye-tracking and EEG measures, we tracked both overt and covert visual attention to determine whether individuals unconsciously internalized this asymmetry during learning. We then investigated whether providing explicit gaze-informed feedback on their own implicit attention biases could further improve task performance of trained participants. Main Results. Our findings reveal that as participants became trained, their attention patterns —both overt and covert— consistently reflected an unconscious awareness of image asymmetry, with attention biased toward task-relevant image regions. Moreover, trained individuals who received explicit feedback derived from their own gaze behavior showed additional improvements in classification performance compared to an equally trained control group. Significance. These results open the door to novel uses of biofeedback interfaces to facilitate new forms of expertise transfer, training, and collective intelligence. By extracting and conveying tacit expert knowledge—ordinarily difficult to externalize—our interface enables its transmission to novices, trained individuals, or even machine learning systems. We refer to this process as cognitive reinforcement.

Host–Guest Complexation by β-Cyclodextrin Enhances the Solubility of an Esterified Protein

Mon, 29 Aug 2022 00:00:00 GMT

Host–Guest Complexation by β-Cyclodextrin Enhances the Solubility of an Esterified Protein Cheah, Keith M; Jun, Joomyung V; Wittrup, K Dane; Raines, Ronald T The carboxyl groups of a protein can be esterified by reaction with a diazo compound, 2-diazo-2-(p-methylphenyl)-N,N-dimethylacetamide. This esterification enables the entry of the protein into the cytosol of a mammalian cell, where the nascent ester groups are hydrolyzed by endogenous esterases. The low aqueous solubility of the ensuing esterified protein is, however, a major practical challenge. Solubility screening revealed that β-cyclodextrin (β-CD) is an optimal solubilizing agent for esterified green fluorescent protein (est-GFP). Its addition can increase the recovery of est-GFP by 10-fold. α-CD, γ-CD, and cucurbit-7-uril are less effective excipients. 1H NMR titration experiments revealed that β-CD encapsulates the hydrophobic tolyl group of ester conjugates with Ka = 321 M–1. Combining l-arginine and sucrose with β-CD enables the nearly quantitative recovery of est-GFP. Thus, the insolubility of esterified proteins can be overcome with excipients.

Quantifying the Role of Kinematic and Behavioral Features in Driver-Pedestrian Interaction across Environments: An Inverse Reinforcement Learning Approach

Mon, 01 Sep 2025 00:00:00 GMT

Quantifying the Role of Kinematic and Behavioral Features in Driver-Pedestrian Interaction across Environments: An Inverse Reinforcement Learning Approach Noonan, T Zach; Gershon, Pnina; Domeyer, Josh; Mehler, Bruce; Reimer, Bryan This study examined real-world driver-pedestrian encounters to identify key interaction features and assess how the importance of these features is mediated by protection afforded by the environment. Using inverse reinforcement learning, we estimated the utility functions to evaluate the relative importance of different aspects of the interaction for each road user and how they differ between undesignated (e.g., jaywalking) and designated (e.g., zebra crossings) crossings. Pedestrian pausing behavior and dynamic features like acceleration changes and time gaps were important at designated crossings, whereas undesignated crossings relied on distances and bidirectional gaze, highlighting reliance on non-verbal cues. This work builds on previous studies analyzing the role of environmental features on interaction, communication, and negotiation between drivers and pedestrians. Understanding driver-pedestrian communication and identifying the most important interaction features may enhance the design of effective and coordinated driver-pedestrian interaction strategies, especially in the context of automated driving systems.

Preoperative Function, Previous SERM Treatment, and Triple-Negative Tumor Status are Independently Associated With 3-Month Postoperative Function After Surgical Decompression of Metastatic Breast Cancer

Tue, 04 Nov 2025 00:00:00 GMT

Preoperative Function, Previous SERM Treatment, and Triple-Negative Tumor Status are Independently Associated With 3-Month Postoperative Function After Surgical Decompression of Metastatic Breast Cancer Siraj, Layla; Duvall, Julia B.; Massaad, Elie; Fourman, Mitchell S.; Shin, John H. Background: The most common cancer in women worldwide, breast cancer most often metastasizes to the bone. Improved chemo- and radiotherapies and novel molecular therapies have prolonged survival in women with osseous metastatic breast cancer, but spinal metastases often cause cord compression that degrades their functional independence. Purpose: In women with breast cancer metastasized to the spine, we sought to (1) identify independent predictors of a functional deficit 3 months after surgical management and (2) assess the utility of existing metrics at highlighting patients at risk of a postoperative functional deficit. Methods: We performed a single-institution, retrospective analysis of 92 patients meeting our inclusion criteria between 2004 and 2021. Patients were classified by 3-month postoperative Eastern Cooperative Oncology Group (ECOG) scores into good/independent (ECOG 0 to 2) and poor/dependent (ECOG 3 to 5) functional outcome groups. Univariate and multivariate analyses were performed to identify patient and tumor factors associated with good vs. poor 3-month ECOG scores. Results: Preoperative use of selective estrogen receptor modulators (SERMs) was significantly associated with good postoperative functional outcomes. Poor preoperative function, the presence of visceral metastases at the time of surgery, and triple-negative primary or metastatic tumor status were independently associated with poor 3-month postoperative function. Host characteristics, sociodemographic factors, and indicators of surgical complexity, including estimated blood loss, front/back surgery, and corpectomy reconstruction, were not associated with 3-month ECOG score. A multivariate model including these significant univariate associations and normalized for patient demographics identified preoperative SERM use, poor preoperative function (ECOG score), and triple-negative primary or metastatic tumor status as independently associated with functional status 3 months after surgery. Conclusions: Our retrospective analysis found that preoperative SERM use was significantly associated with improved postoperative functional outcomes, while poor preoperative function and triple-negative tumor status were significantly associated with poor function 3 months after surgery. These factors may serve as indicators of function and independence after surgery for patients with metastatic breast cancer to the spine. Level of Evidence: Level IV: Prognostic Study

The Influence of Prior Semantic Knowledge in Noisy Channel Interpretation

Thu, 25 Sep 2025 00:00:00 GMT

The Influence of Prior Semantic Knowledge in Noisy Channel Interpretation Chen, Sihan; Washington, Lia; Gibson, Edward How do comprehenders interpret semantically implausible sentences? Previous studies proposed a noisy-channel framework of sentence comprehension, where communication between a speaker and a comprehender happens in a noisy channel. The comprehender rationally adopts an interpretation of a sentence based on how likely the interpretation is (the semantic prior) and how likely is the interpretation corrupted into the perceived sentence because of noise (the likelihood). The theory predicted that comprehenders would be more likely to adopt a literal interpretation of an implausible sentence if their prior of implausible sentences were higher. To test this hypothesis, Gibson et al. manipulated the proportion of implausible test sentences in two sets of experiments, where participants read a number of sentences and answer a comprehension question following each sentence. Although their results supported the hypothesis, the experiment could be confounded (a) by participants’ adaptation effect (due to different experiment lengths) and (b) by different participants having different strategies to do the task (due to the between-subject design). In our study, we manipulated the semantic prior and controlled for these potential confounds. We found participants exposed to more implausible sentences were indeed more likely to interpret implausible sentences literally. Our results hence offer additional support for the noisy-channel framework.

The Politics of Engagement in Platform Governance

Sun, 01 Sep 2024 00:00:00 GMT

The Politics of Engagement in Platform Governance Lewis, Becca; Christin, Angèle In recent years, the concept of user engagement has dominated debate over the governance of online platforms, and critics use the term to assign crass commercial interests to social media companies. We argue that social media engagement is a multifaceted ideal that serves both economic and ideological functions for platforms. We show how Facebook’s early leadership used the concept to reconcile the competing demands of expansion, revenue generation, and community-building. In doing so, they synthesized three distinct ideas: the Silicon Valley belief that network expansion correlated with network strength, the ad industry’s contention that media should promote emotional investment from viewers, and the academic claim that civic participation is the most important democratic virtue. Even as the contradictions that these claims yield have come to the foreground, the multiple logics of engagement have proven difficult to evade, and it continues to shape discussions of platform governance.

The Impact of Electrification and Partial Automation on Driver Speeding Behavior

Mon, 01 Sep 2025 00:00:00 GMT

The Impact of Electrification and Partial Automation on Driver Speeding Behavior Gershon, Pnina; Noonan, T Zach; Lenneman, John As electric vehicles (EVs) and partial automation systems become increasingly prevalent, their impact on everyday driving behavior remains underexplored. This study utilizes real-world naturalistic data to examine how vehicle type, an electric versus an internal combustion engine (ICE), and the use of partial automation are associated with speeding behavior. Data were collected from 24 drivers over the course of a month each, comparing Tesla Model 3s with Autopilot (EV) and Cadillac CT6s with Super Cruise (ICE), covering about 38,000 miles of driving. Results indicate that EV drivers tended to speed for shorter durations on arterial roads but exhibited higher speeding magnitudes on residential and controlled access roads after their first week of driving. Notably, driving with partial automation, regardless of powertrain, was associated with significantly longer speeding durations and slightly greater speeding magnitudes compared to manual driving. These findings suggest that both electrification and automation contribute to evolving driver behaviors, changing speeding behavior in specific driving contexts. As drivers adapt to new vehicle technologies, understanding how these systems shape behavior is important. Insights from this study may inform the design of future in-vehicle systems and guide driver education strategies to promote safe driving practices in an evolving transportation landscape.

Cloud Capitalism and the AI Transition

Fri, 26 Dec 2025 00:00:00 GMT

Cloud Capitalism and the AI Transition Tan, JS; Thelen, Kathleen This article explores the origins and implications of a new cloud business model that is powering the advance of AI. We document how this model emerged within a handful of the most dominant IT firms whose reach into all corners of the economy makes them a powerful node or “choke point” in the political economy as a whole. We then elaborate how the features of the cloud business model differ from the traditional platform model out of which it grew, as it evolved from asset-light to asset-heavy, from hierarchical organization to semivertical integration, from domination over to collaboration with partner firms, and from embracing consumer- to enterprise-facing strategies. A final section considers the technological, political, and distributional impacts of the rise of this new business model—showing how the current race to artificial general intelligence (AGI) has reinforced and accelerated its underlying dynamics (above all, intensifying the drive for scale and ever-greater asset intensity), analyzing the new techno-nationalist alliance between industry leaders and the state that the model's development has inspired, and considering the new power-distributional dynamics this model has produced.

Hexamethylbenzene Elimination Enables the Generation of Transient, Sterically Unhindered Multiply Bonded Boron Species

Fri, 16 May 2025 00:00:00 GMT

Hexamethylbenzene Elimination Enables the Generation of Transient, Sterically Unhindered Multiply Bonded Boron Species Zhang, Chonghe; Dabringhaus, Philipp; Tra, Bi Youan E.; Gilliard, Robert J. Jr; Cummins, Christopher C. We present a method for the generation of boron-containing unsaturated small molecules via hexamethylbenzene elimination. The fragmentation precursors are obtained through bond insertion into phenyl boranorbornadiene (PhB(C6Me6), 1). Compound 1 undergoes 1,1-insertion with 2,6-xylyl isocyanide, affording a boron-doped bicyclo[2.2.2]octa-2,5-diene 2. Heating 2 in toluene results in the formation of a base-stabilized boraketenimine PhB(CNxyl)2 (i.e., borylene diisocyanide) as an intermediate via retro-Diels–Alder reaction. Surprisingly, PhB(CNxyl)2 dimerizes to give a boron-doped 6-membered ring (PhB)2C4(CNxyl)64. The reaction of 1 with trimethylamine N-oxide and phenyl azide yields triphenyl boroxine and a BN4 ring, respectively, implying the involvement of transient oxoborane (PhB[triple bond, length as m-dash]O) and iminoborane intermediates (PhB[triple bond, length as m-dash]NPh), respectively. Furthermore, boranorbornadiene also undergoes 2,3-insertion with mesityl isocyanate (MesNCO), affording a fused 6/5-membered heterocycle 11. This insertion profile is analogous to the insertion of phenyl azide into 1.

Mechanisms and Scale-up Potential of 3D Solar Interfacial-Evaporators

Thu, 24 Apr 2025 00:00:00 GMT

Mechanisms and Scale-up Potential of 3D Solar Interfacial-Evaporators Zhang, James H.; Mittapally, Rohith; Oluwade, Abimbola; Chen, Gang Evaporation fluxes from porous evaporators under sunlight have been reported to exceed the solar-thermal limit, determined by relating the incoming solar energy to the latent and sensible heat of water, for applications in desalination and brine pond drying. Although flat two-dimensional (2D) evaporators exceeding the solar limit imply a non-thermal process, tall three-dimensional (3D) solar evaporators can exceed it by absorbing additional environmental heat into its cold sidewalls. Through modeling, we explain the physics and identify the critical heights in which a fin transitions from 2D to 3D evaporation and exceeds the solar-thermal limit. Our analyses illustrate that environmental heat absorption in 3D evaporators is determined by the ambient relative humidity and the airflow velocity. The model is then coarse-grained into a large-scale fin array device on the meters scale to analyze their scalability. We identify that these devices are unlikely to scale favorably in closed environment settings such as solar stills. Our modeling clearly illustrates the benefits and limitations of 3D evaporating arrays and pinpoints design choices in previous works that hinder the device's overall performance. This work illustrates the importance in distinguishing 2D from 3D evaporation for mechanisms underlying interfacial evaporation exceeding the solar-thermal limit.

Decarbonization Approaches for Ethylene Production: Comparative Techno-Economic and Life-Cycle Analysis

Tue, 18 Feb 2025 00:00:00 GMT

Decarbonization Approaches for Ethylene Production: Comparative Techno-Economic and Life-Cycle Analysis Shin, Woojae; Lin, Bosong; Lai, Haoxiang; Ibrahima, Gasim; Zang, Guiyan Ethylene, a building block of the chemical industry, significantly contributes to global greenhouse gas (GHG) emissions, prompting interest in decarbonization approaches to align with recent carbon neutrality initiatives. This paper presents a comprehensive techno-economic analysis (TEA) and life cycle analysis (LCA) of GHG emissions, comparing conventional ethane-based ethylene plants with three decarbonization approaches. The study was conducted within the context of the U.S. average, with sensitivity analysis to identify key drivers affecting well-to-gate (WTG) GHG emissions and the levelized cost of ethylene (LCOE). The conventional plant exhibited a GHG emission of 869 kgCO2e per tonne-ethylene and a LCOE of $746 per tonne-ethylene. Substituting external natural gas fuels with grid or renewable electricity decreased the emissions to 806 and 717 kgCO2e per tonne-ethylene, respectively. The emissions of the grid-powered or renewable-powered electrically heated cracker that exports co-produced hydrogen to substitute conventional gray hydrogen were 1031 and −163 kgCO2e per tonne-ethylene, respectively. The application of CCS to purge gas showed 703 and 514 kgCO2e per tonne-ethylene emissions, respectively. The electric cracker showed lower emissions than the conventional plant below 380 kgCO2e per MW h electricity upstream, and at 60 kgCO2e per MW h, it achieved carbon neutrality. Regarding LCOE, when using a grid electricity source, no external natural gas, electric cracker, and adding CCS to purge gas showed $743, 833, and 771 per tonne-ethylene, respectively. When these plants adopt renewable electricity, their LCOEs will be $737, 746 and 757 per tonne-ethylene. Below $41.1 per MW h electricity price, the electric cracker had the lowest value among all cases. With hydrogen prices of $0.5–3.0 per kg-H2, the electric cracker's LCOE ranged from −$45(cost)–128(saving) per tonne-ethylene compared to the conventional concept.

Archerfish: A Retrofitted 3D Printer for High-throughput Combinatorial Experimentation via Continuous Printing

Fri, 31 Jan 2025 00:00:00 GMT

Archerfish: A Retrofitted 3D Printer for High-throughput Combinatorial Experimentation via Continuous Printing Alexander E. Siemenn, Basita Das, Eunice Aissi, Fang Sheng, Lleyton Elliott, Blake Hudspeth, Marilyn Meyers, James Serdy and Tonio Buonassisi The maturation of 3D printing technology has enabled low-cost, rapid prototyping capabilities for mainstreaming accelerated product design. The materials research community has recognized this need, but no universally accepted rapid prototyping technique currently exists for material design. Toward this end, we develop Archerfish, a 3D printer retrofitted to dispense liquid with in situ mixing capabilities for performing high-throughput combinatorial printing (HTCP) of material compositions. Using this HTCP design, we demonstrate continuous printing throughputs of up to 250 unique compositions per minute, 100× faster than similar tools such as Opentrons that utilize stepwise printing with ex situ mixing. We validate the formation of these combinatorial “prototype” material gradients using hyperspectral image analysis and energy-dispersive X-ray spectroscopy. Furthermore, we describe hardware challenges to realizing reproducible, accurate, and precise composition gradients with continuous printing, including those related to precursor dispensing, mixing, and deposition. Despite these limitations, the continuous printing and low-cost design of Archerfish demonstrate promising accelerated materials screening results across a range of materials systems from nanoparticles to perovskites.

Borinine-FLP Ring Expansion: Isolation of Eight-Membered B-P Rings Bridged by µ2 Chalcogenide and Chloronium Ions

Sat, 10 May 2025 00:00:00 GMT

Borinine-FLP Ring Expansion: Isolation of Eight-Membered B-P Rings Bridged by µ2 Chalcogenide and Chloronium Ions Frey, Nathan C.; Sarkar, Samir Kumar; Dickie, Diane A.; Molinoa, Andrew; Gilliard, Robert J. Jr Boron–phosphorus (B–P) frustrated Lewis pairs (FLPs) are an important class of compounds for activating various small molecules. Utilizing the ring expansion reactivity of 9-chloro-9-borafluorene, a borinine-based FLP was synthesized. Various five-membered main-group element heterocycles were obtained via the reaction of the FLP with Me3NO, S8, and Se. Subsequent reduction of these species yielded the ring-expanded compounds, each featuring bridging B–E–B (E = O, S, Se) bonds. Similarly, halide abstraction from the FLP with AgNTf2 led to the formation of a cationic ring-expanded compound with a bridging B–Cl–B motif. This motif constitutes one of the first examples of a boron-stabilized chloronium ion, as verified using in-depth bonding analysis methods. Mechanistic pathways for the reduction- and halide abstraction-mediated ring expansion reactions are proposed with the aid of density functional theory. Electronic structure computations were performed to determine the best representation of bonding interactions in each compound, suggesting phosophorus(V)–chalcogen double bonding and chalcogen–boron(III) dative interactions within the heterocycles.

High-resolution structure of Zn3(HOTP)2 (HOTP = hexaoxidotriphenylene), a three-dimensional conductive MOF

Mon, 02 Jun 2025 00:00:00 GMT

High-resolution structure of Zn3(HOTP)2 (HOTP = hexaoxidotriphenylene), a three-dimensional conductive MOF Zhang, Kimberly J.; Chen, Tianyang; Oppenheim, Julius J.; Yang, Luming; Palatinus, Lukáš; Müller, Peter; Van Voorhisa, Troy; Dincă, Mircea Although two-dimensional (2D) electrically conducting metal–organic frameworks (cMOFs) have become prominent due to their numerous potential applications, their structures are often implied or assumed from rather crude powder X-ray diffraction data. Indeed, exceedingly few examples exist of atomic-level structural details coming from single crystal diffraction experiments. Most widely studied among cMOFs are materials based on triphenylene ligands, in particular M3(HOTP)2 (M = Cu, Zn) and [M3(HOTP)2][M3(HOTP)]2 (M = Mg, Ni, Co; H6HOTP = 2,3,6,7,10,11-hexahydroxytriphenylene), which are invariably described as 2D van der Waals materials with sheets of ligands connected by square planar or octahedral metal ions. Here, we employ electron diffraction to show that, unlike the Mg, Co, Ni, and Cu analogs, Zn3(HOTP)2 crystallizes into a three-dimensional network that is analogous to the structures of the lanthanide-based HOTP MOFs. Moreover, similar to the lanthanide frameworks, Zn3(HOTP)2 exhibits incommensurate modulation, likely originating from a frustration between the preferred π–π stacking distance and the Zn–O bond lengths, or from a Peierls distortion. This work reinforces the importance of employing single crystal diffraction measurements for the characterization of conductive MOFs, especially when trying to correlate electronic properties to structural details.

Intratumoral nanobody–IL-2 fusions that bind the tumor extracellular matrix suppress solid tumor growth in mice

Tue, 01 Nov 2022 00:00:00 GMT

Intratumoral nanobody–IL-2 fusions that bind the tumor extracellular matrix suppress solid tumor growth in mice Lutz, Emi A; Jailkhani, Noor; Momin, Noor; Huang, Ying; Sheen, Allison; Kang, Byong H; Wittrup, K Dane; Hynes, Richard O Confining cytokine exposure to the tumors would greatly enhance cancer immunotherapy safety and efficacy. Immunocytokines, cytokines fused to tumor-targeting antibodies, have been developed with this intention, but without significant clinical success to date. A critical limitation is uptake by receptor-expressing cells in the blood, that decreases the dose at the tumor and engenders toxicity. Small-format immunocytokines, constructed with antibody fragments, are hypothesized to improve tumor specificity due to rapid systemic clearance. However, effective design criteria for small-format immunocytokines need further examination. Here, we engineer small interleukin-2 (IL-2) immunocytokines fused to nanobodies with nanomolar to picomolar affinities for the tumor-specific EIIIB domain of fibronectin (also known as EDB). Upon intravenous delivery into immunocompetent mice, such immunocytokines led to similar tumor growth delay as size-matched untargeted IL-2. Intratumoral (i.t.) delivery imparted improved survival dependent on affinity to EIIIB. I.t. administration offers a promising avenue to deliver small-format immunocytokines, given effective affinity for the tumor microenvironment.

Ablative radiotherapy improves survival but does not cure autochthonous mouse models of prostate and colorectal cancer

Wed, 09 Aug 2023 00:00:00 GMT

Ablative radiotherapy improves survival but does not cure autochthonous mouse models of prostate and colorectal cancer Schmidt, Daniel R; Gramatikov, Iva Monique T; Sheen, Allison; Williams, Christopher L; Hurwitz, Martina; Dodge, Laura E; Holupka, Edward; Kiger, WS; Cornwall-Brady, Milton R; Huang, Wei; Mak, Howard H; Cormier, Kathleen S; Condon, Charlene; Dane Wittrup, K; Yilmaz, Ömer H; Stevenson, Mary Ann; Down, Julian D; Floyd, Scott R; Roper, Jatin; Vander Heiden, Matthew G Background Genetically engineered mouse models (GEMMs) of cancer are powerful tools to study mechanisms of disease progression and therapy response, yet little is known about how these models respond to multimodality therapy used in patients. Radiation therapy (RT) is frequently used to treat localized cancers with curative intent, delay progression of oligometastases, and palliate symptoms of metastatic disease. Methods Here we report the development, testing, and validation of a platform to immobilize and target tumors in mice with stereotactic ablative RT (SART). Xenograft and autochthonous tumor models were treated with hypofractionated ablative doses of radiotherapy. Results We demonstrate that hypofractionated regimens used in clinical practice can be effectively delivered in mouse models. SART alters tumor stroma and the immune environment, improves survival in GEMMs of primary prostate and colorectal cancer, and synergizes with androgen deprivation in prostate cancer. Complete pathologic responses were achieved in xenograft models, but not in GEMMs. Conclusions While SART is capable of fully ablating xenografts, it is unable to completely eradicate disease in GEMMs, arguing that resistance to potentially curative therapy can be modeled in GEMMs. Plain language summary Mice can be used to model the types of cancer seen in people to investigate the effects of cancer therapies, such as radiation. Here, we apply radiation therapy treatments that are able to cure cancer in humans to mice that have cancer of the prostate or colorectum. We show that the mice do not experience many side effects and that the tumours reduce in size, but in some cases show progression after treatment. Our study demonstrates that mice can be used to better understand how human cancers respond to radiation treatment, which can lead to the development of improved treatments and treatment schedules.

Anti–PD-1 and Extended Half-life IL2 Synergize for Treatment of Murine Glioblastoma Independent of Host MHC Class I Expression

Fri, 02 Jun 2023 00:00:00 GMT

Anti–PD-1 and Extended Half-life IL2 Synergize for Treatment of Murine Glioblastoma Independent of Host MHC Class I Expression Tritz, Zachariah P; Ayasoufi, Katayoun; Wolf, Delaney M; Owens, Carley A; Malo, Courtney S; Himes, Benjamin T; Fain, Cori E; Goddery, Emma N; Yokanovich, Lila T; Jin, Fang; Hansen, Michael J; Parney, Ian F; Wang, Chensu; Moynihan, Kelly D; Irvine, Darrell J; Wittrup, K Dane; Diaz Marcano, Rosa M; Vile, Richard G; Johnson, Aaron J Glioblastoma (GBM) is the most common malignant brain tumor in adults, responsible for approximately 225,000 deaths per year. Despite preclinical successes, most interventions have failed to extend patient survival by more than a few months. Treatment with anti—programmed cell death protein 1 (anti–PD-1) immune checkpoint blockade (ICB) monotherapy has been beneficial for malignant tumors such as melanoma and lung cancers but has yet to be effectively employed in GBM. This study aimed to determine whether supplementing anti–PD-1 ICB with engineered extended half-life IL2, a potent lymphoproliferative cytokine, could improve outcomes. This combination therapy, subsequently referred to as enhanced checkpoint blockade (ECB), delivered intraperitoneally, reliably cures approximately 50% of C57BL/6 mice bearing orthotopic GL261 gliomas and extends median survival of the treated cohort. In the CT2A model, characterized as being resistant to CBI, ECB caused a decrease in CT2A tumor volume in half of measured animals similar to what was observed in GL261-bearing mice, promoting a trending survival increase. ECB generates robust immunologic responses, features of which include secondary lymphoid organ enlargement and increased activation status of both CD4 and CD8 T cells. This immunity is durable, with long-term ECB survivors able to resist GL261 rechallenge. Through employment of depletion strategies, ECB's efficacy was shown to be independent of host MHC class I–restricted antigen presentation but reliant on CD4 T cells. These results demonstrate ECB is efficacious against the GL261 glioma model through an MHC class I–independent mechanism and supporting further investigation into IL2-supplemented ICB therapies for tumors of the central nervous system.

Collagen-Anchored Interleukin-2 and Interleukin-12 Safely Reprogram the Tumor Microenvironment in Canine Soft-Tissue Sarcomas

Thu, 01 Jun 2023 00:00:00 GMT

Collagen-Anchored Interleukin-2 and Interleukin-12 Safely Reprogram the Tumor Microenvironment in Canine Soft-Tissue Sarcomas Stinson, Jordan A; Sheen, Allison; Momin, Noor; Hampel, Jordan; Bernstein, Rebecca; Kamerer, Rebecca; Fadl-Alla, Bahaa; Samuelson, Jonathan; Fink, Elizabeth; Fan, Timothy M; Wittrup, K Dane Purpose: Cytokine therapies such as IL2 and IL12 suffer from impractically small therapeutic windows driven by their on-target, off-tumor activity, limiting their clinical potential despite potent antitumor effects. We previously engineered cytokines that bind and anchor to tumor collagen following intratumoral injection, and sought to test their safety and biomarker activity in spontaneous canine soft-tissue sarcomas (STS). Experimental Design: Collagen-binding cytokines were canine-ized to minimize immunogenicity and were used in a rapid dose-escalation study in healthy beagles to identify a maximum tolerated dose. Ten client-owned pet dogs with STS were then enrolled into trial, receiving cytokines at different intervals prior to surgical tumor excision. Tumor tissue was analyzed through IHC and NanoString RNA profiling for dynamic changes within treated tumors. Archived, untreated STS samples were analyzed in parallel as controls. Results: Intratumorally administered collagen-binding IL2 and IL12 were well tolerated by STS-bearing dogs, with only Grade 1/2 adverse events observed (mild fever, thrombocytopenia, neutropenia). IHC revealed enhanced T-cell infiltrates, corroborated by an enhancement in gene expression associated with cytotoxic immune function. We found concordant increases in expression of counter-regulatory genes that we hypothesize would contribute to a transient antitumor effect, and confirmed in mouse models that combination therapy to inhibit this counter-regulation can improve responses to cytokine therapy. Conclusions: These results support the safety and activity of intratumorally delivered, collagen-anchoring cytokines for inflammatory polarization of the canine STS tumor microenvironment. We are further evaluating the efficacy of this approach in additional canine cancers, including oral malignant melanoma. Translational Relevance Successful translation of novel cancer therapies could be accelerated through the inclusion of tumor models that accurately recapitulate natural evolution and malignant transformation processes operative in human tumor development. Spontaneous cancer in pet dogs provides an underutilized opportunity to assess the safety and activity of investigational cancer therapies in tumors that arise following years of immunoediting. Particularly for the evaluation of immunotherapies, canine tumors enable the assessment of clinical potential in the context of an experienced, and often senescent, immune background. Beyond efficacy, such evaluation provides meaningful insight into tumor resistance mechanisms that could influence eventual human clinical success. Herein, we characterize immune activities generated by intratumoral injections of engineered collagen-binding cytokines IL2 and IL12 into naturally occurring canine soft-tissue sarcomas, and demonstrate through comparative assessment in mouse tumors the differential learnings from each model and their combined role in guiding rational design of treatment combinations with greater expected efficacy.

Both intratumoral regulatory T cell depletion and CTLA-4 antagonism are required for maximum efficacy of anti-CTLA-4 antibodies

Mon, 24 Jul 2023 00:00:00 GMT

Both intratumoral regulatory T cell depletion and CTLA-4 antagonism are required for maximum efficacy of anti-CTLA-4 antibodies Lax, Brianna M; Palmeri, Joseph R; Lutz, Emi A; Sheen, Allison; Stinson, Jordan A; Duhamel, Lauren; Santollani, Luciano; Kennedy, Alan; Rothschilds, Adrienne M; Spranger, Stefani; Sansom, David M; Wittrup, K Dane Anti-CTLA-4 antibodies have successfully elicited durable tumor regression in the clinic; however, long-term benefit is limited to a subset of patients for select cancer indications. The incomplete understanding of their mechanism of action has hindered efforts at improvement, with conflicting hypotheses proposing either antagonism of the CTLA-4:B7 axis or Fc effector-mediated regulatory T cell (Treg) depletion governing efficacy. Here, we report the engineering of a nonantagonistic CTLA-4 binding domain (b1s1e2) that depletes intratumoral Tregs as an Fc fusion. Comparison of b1s1e2-Fc to 9d9, an antagonistic anti-CTLA-4 antibody, allowed for interrogation of the separate contributions of CTLA-4 antagonism and Treg depletion to efficacy. Despite equivalent levels of intratumoral Treg depletion, 9d9 achieved more long-term cures than b1s1e2-Fc in MC38 tumors, demonstrating that CTLA-4 antagonism provided additional survival benefit. Consistent with prior reports that CTLA-4 antagonism enhances priming, treatment with 9d9, but not b1s1e2-Fc, increased the percentage of activated T cells in the tumor-draining lymph node (tdLN). Treg depletion with either construct was restricted to the tumor due to insufficient surface CTLA-4 expression on Tregs in other compartments. Through intratumoral administration of diphtheria toxin in Foxp3-DTR mice, we show that depletion of both intratumoral and nodal Tregs provided even greater survival benefit than 9d9, consistent with Treg-driven restraint of priming in the tdLN. Our data demonstrate that anti-CTLA-4 therapies require both CTLA-4 antagonism and intratumoral Treg depletion for maximum efficacy—but that potential future therapies also capable of depleting nodal Tregs could show efficacy in the absence of CTLA-4 antagonism.

Overcoming lung cancer immunotherapy resistance by combining nontoxic variants of IL-12 and IL-2

Tue, 05 Sep 2023 00:00:00 GMT

Overcoming lung cancer immunotherapy resistance by combining nontoxic variants of IL-12 and IL-2 Horton, Brendan L; D’Souza, Alicia D; Zagorulya, Maria; McCreery, Chloe V; Abhiraman, Gita C; Picton, Lora; Sheen, Allison; Agarwal, Yash; Momin, Noor; Wittrup, K Dane; White, Forest M; Garcia, K Christopher; Spranger, Stefani Engineered cytokine-based approaches for immunotherapy of cancer are poised to enter the clinic, with IL-12 being at the forefront. However, little is known about potential mechanisms of resistance to cytokine therapies. We found that orthotopic murine lung tumors were resistant to systemically delivered IL-12 fused to murine serum albumin (MSA, IL12-MSA) because of low IL-12 receptor (IL-12R) expression on tumor-reactive CD8+ T cells. IL2-MSA increased binding of IL12-MSA by tumor-reactive CD8+ T cells, and combined administration of IL12-MSA and IL2-MSA led to enhanced tumor-reactive CD8+ T cell effector differentiation, decreased numbers of tumor-infiltrating CD4+ regulatory T cells, and increased survival of lung tumor-bearing mice. Predictably, the combination of IL-2 and IL-12 at therapeutic doses led to significant dose-limiting toxicity. Administering IL-12 and IL-2 analogs with preferential binding to cells expressing Il12rb1 and CD25, respectively, led to a significant extension of survival in mice with lung tumors while abrogating dose-limiting toxicity. These findings suggest that IL-12 and IL-2 represent a rational approach to combination cytokine therapy whose dose-limiting toxicity can be overcome with engineered cytokine variants.

Intratumoral aluminum hydroxide–anchored IL-12 drives potent antitumor activity by remodeling the tumor microenvironment

Fri, 08 Dec 2023 00:00:00 GMT

Intratumoral aluminum hydroxide–anchored IL-12 drives potent antitumor activity by remodeling the tumor microenvironment Battula, Sailaja; Papastoitsis, Gregory; Kaufman, Howard L; Wittrup, K Dane; Schmidt, Michael M IL-12 is a potent cytokine that can promote innate and adaptive anticancer immunity, but its clinical development has been limited by toxicity when delivered systemically. Intratumoral (i.t.) administration can expand the therapeutic window of IL-12 and other cytokines but is in turn limited by rapid drug clearance from the tumor, which reduces efficacy, necessitates frequent administration, and increases systemic accumulation. To address these limitations, we developed an anchored IL-12 designated ANK-101, composed of an engineered IL-12 variant that forms a stable complex with the FDA-approved vaccine adjuvant aluminum hydroxide (Alhydrogel). Following i.t. administration of murine ANK-101 (mANK-101) in early intervention syngeneic mouse tumors, the complex formed a depot that was locally retained for weeks as measured by IVIS or SPECT/CT imaging, while unanchored protein injected i.t. was cleared within hours. One or 2 i.t. injections of mANK-101 induced single-agent antitumor activity across a diverse range of syngeneic tumors, including models resistant to checkpoint blockade at doses where unanchored IL-12 had no efficacy. Local treatment with mANK-101 further induced regressions of noninjected lesions, especially when combined with systemic checkpoint blockade. Antitumor activity was associated with remodeling of the tumor microenvironment, including prolonged IFN-γ and chemokine expression, recruitment and activation of T and NK cells, M1 myeloid cell skewing, and increased antigen processing and presentation. Subcutaneous administration of ANK-101 in cynomolgus macaques was well tolerated. Together, these data demonstrate that ANK-101 has an enhanced efficacy and safety profile and warrants future clinical development.

CD8+ T cell priming that is required for curative intratumorally anchored anti-4-1BB immunotherapy is constrained by Tregs

Fri, 01 Mar 2024 00:00:00 GMT

CD8+ T cell priming that is required for curative intratumorally anchored anti-4-1BB immunotherapy is constrained by Tregs Palmeri, Joseph R; Lax, Brianna M; Peters, Joshua M; Duhamel, Lauren; Stinson, Jordan A; Santollani, Luciano; Lutz, Emi A; Pinney, William; Bryson, Bryan D; Dane Wittrup, K Although co-stimulation of T cells with agonist antibodies targeting 4-1BB (CD137) improves antitumor immune responses in preclinical studies, clinical success has been limited by on-target, off-tumor activity. Here, we report the development of a tumor-anchored ɑ4-1BB agonist (ɑ4-1BB-LAIR), which consists of a ɑ4-1BB antibody fused to the collagen-binding protein LAIR. While combination treatment with an antitumor antibody (TA99) shows only modest efficacy, simultaneous depletion of CD4+ T cells boosts cure rates to over 90% of mice. Mechanistically, this synergy depends on ɑCD4 eliminating tumor draining lymph node regulatory T cells, resulting in priming and activation of CD8+ T cells which then infiltrate the tumor microenvironment. The cytotoxic program of these newly primed CD8+ T cells is then supported by the combined effect of TA99 and ɑ4-1BB-LAIR. The combination of TA99 and ɑ4-1BB-LAIR with a clinically approved ɑCTLA-4 antibody known for enhancing T cell priming results in equivalent cure rates, which validates the mechanistic principle, while the addition of ɑCTLA-4 also generates robust immunological memory against secondary tumor rechallenge. Thus, our study establishes the proof of principle for a clinically translatable cancer immunotherapy.

Targeting of the CD161 inhibitory receptor enhances T-cell–mediated immunity against hematological malignancies

Thu, 21 Mar 2024 00:00:00 GMT

Targeting of the CD161 inhibitory receptor enhances T-cell–mediated immunity against hematological malignancies Alvarez Calderon, Francesca; Kang, Byong H; Kyrysyuk, Oleksandr; Zheng, Shiwei; Wang, Hao; Mathewson, Nathan D; Luoma, Adrienne M; Ning, Xiaohan; Pyrdol, Jason; Cao, Xuan; Suvà, Mario L; Yuan, Guo-Cheng; Wittrup, K Dane; Wucherpfennig, Kai W The CD161 inhibitory receptor is highly upregulated by tumor-infiltrating T cells in multiple human solid tumor types, and its ligand, CLEC2D, is expressed by both tumor cells and infiltrating myeloid cells. Here, we assessed the role of the CD161 receptor in hematological malignancies. Systematic analysis of CLEC2D expression using the Cancer Cell Line Encyclopedia revealed that CLEC2D messenger RNA was most abundant in hematological malignancies, including B-cell and T-cell lymphomas as well as lymphocytic and myelogenous leukemias. CLEC2D protein was detected by flow cytometry on a panel of cell lines representing a diverse set of hematological malignancies. We, therefore, used yeast display to generate a panel of high-affinity, fully human CD161 monoclonal antibodies (mAbs) that blocked CLEC2D binding. These mAbs were specific for CD161 and had a similar affinity for human and nonhuman primate CD161, a property relevant for clinical translation. A high-affinity CD161 mAb enhanced key aspects of T-cell function, including cytotoxicity, cytokine production, and proliferation, against B-cell lines originating from patients with acute lymphoblastic leukemia, diffuse large B-cell lymphoma, and Burkitt lymphoma. In humanized mouse models, this CD161 mAb enhanced T-cell–mediated immunity, resulting in a significant survival benefit. Single cell RNA-seq data demonstrated that CD161 mAb treatment enhanced expression of cytotoxicity genes by CD4 T cells as well as a tissue-residency program by CD4 and CD8 T cells that is associated with favorable survival outcomes in multiple human cancer types. These fully human mAbs, thus, represent potential immunotherapy agents for hematological malignancies.

Upcycling spent medium-Ni cathodes via novel liquified salts sourcing

Wed, 02 Apr 2025 00:00:00 GMT

Upcycling spent medium-Ni cathodes via novel liquified salts sourcing Yoon, Moonsu; Park, Jin-Sung; Chen, Weiyin; Huang, Yimeng; Dai, Tao; Lee, Yumin; Shin, Jungmin; Lee, Seungmi; Kim, Yongil; Lee, Dongsoo; Shin, Daiha; Cho, Jaephil; Dong, Yanhao; Li, Ju The rapid growth in lithium-ion battery technology underscores the urgent need for sustainable recycling to address the environmental and economic challenges of battery waste. This study introduces a liquified-salts-assisted upcycling approach to transform spent medium-Ni cathodes into high-performance single-crystalline Ni-rich cathodes. Utilizing the LiOH–LiNO3–Ni(NO3)2·6H2O eutectic, this method leverages planetary centrifugal mixing to create a liquid-like environment for accelerated elemental diffusion and microstructural refinement. The in situ liquefaction of these salts ensures seamless precursor integration, achieving compositional uniformity and minimizing impurity formation. Compared to conventional solid-state methods, our method significantly suppresses rock-salt phase formation, and improves electrochemical performance with superior cycling stability and rate capability. The environmental and economic advantages of our approach highlight its potential to reduce greenhouse gas emissions and energy consumption. This scalable, energy-efficient strategy provides a transformative solution for battery waste management, paving the way for the sustainable production of next-generation cathode materials.

CLN-617 Retains IL2 and IL12 in Injected Tumors to Drive Robust and Systemic Immune-Mediated Antitumor Activity

Thu, 01 Aug 2024 00:00:00 GMT

CLN-617 Retains IL2 and IL12 in Injected Tumors to Drive Robust and Systemic Immune-Mediated Antitumor Activity Mehta, Naveen K; Rakhra, Kavya; Meetze, Kristan A; Li, Bochong; Momin, Noor; Chang, Jason YH; Wittrup, K Dane; Baeuerle, Patrick A; Michaelson, Jennifer S Despite clinical evidence of antitumor activity, the development of cytokine therapies has been hampered by a narrow therapeutic window and limited response rates. Two cytokines of high interest for clinical development are interleukin 2 (IL2) and interleukin 12 (IL12), which potently synergize to promote the activation and proliferation of T cells and NK cells. However, the only approved human IL2 therapy, Proleukin, is rarely used in the clinic due to systemic toxicities, and no IL12 product has been approved to date due to severe dose-limiting toxicities. Here, we describe CLN-617, a first-in-class therapeutic for intratumoral (IT) injection that co-delivers IL2 and IL12 on a single molecule in a safe and effective manner. CLN-617 is a single-chain fusion protein comprised of IL2, leukocyte-associated immunoglobulin-like receptor 2 (LAIR2), human serum albumin (HSA), and IL12. LAIR2 and HSA function to retain CLN-617 in the treated tumor by binding collagen and increasing molecular weight, respectively. We found that IT administration of a murine surrogate of CLN-617, mCLN-617, eradicated established treated and untreated tumors in syngeneic models, significantly improved response to anti-PD1 checkpoint therapy, and generated a robust abscopal response dependent on cellular immunity and antigen cross-presentation. CLN-617 is being evaluated in a clinical trial in patients with advanced solid tumors (NCT06035744).

Porous Organic Materials-Based Atomically Dispersed Metal Electrocatalysts

Tue, 25 Mar 2025 00:00:00 GMT

Porous Organic Materials-Based Atomically Dispersed Metal Electrocatalysts Zhang, Hao; Wang, Suwen; Lv, Enmin; Qi, Menghui; He, Chengchao; Dong, Xinglong; Qiu, Jieshan; Wang, Yong; Wen, Zhenhai The transition to renewable energy sources and the need for efficient energy conversion technologies have led to the development of various types of catalysts, among which atomically dispersed metal catalysts (ADMCs) supported by porous organic materials (POMs) have attracted attention for their high catalytic efficiency and stability. This review focuses on the development and application of ADMCs supported by POMs, such as MOFs, COFs, and HOFs, which offer catalytic performance due to their high atomic utilization, stability, and selectivity. This paper systematically explores various strategies for synthesizing ADMCs, including the use of organic linkers, metal nodes, and pore spaces within POMs to stabilize metal atoms and prevent aggregation. Key applications highlighted include energy conversion and storage technologies, such as fuel cells, water splitting, CO2 reduction and nitrogen reduction, where ADMCs demonstrate the potential to replace noble metals. Despite the progress, challenges remain in achieving high metal loading, long-term stability, and cost-effective large-scale production. This study underscores the importance of advanced characterization techniques and computational models to deepen the understanding of ADMCs’ catalytic mechanisms and guide future material design, paving the way for their broader application in sustainable energy technologies.

Quantifying Mining Requirement and Waste for Energy Sustainability

Sun, 13 Apr 2025 00:00:00 GMT

Quantifying Mining Requirement and Waste for Energy Sustainability Ermakova, Dinara; Sen, Drishti; Wainwright, Haruko; Bae, Jin Whan; Chene, Lisha; Vujic, Jasmina This study demonstrates the life-cycle assessment of different energy sources-coal, natural gas, solar, wind, nuclear, and hydro-particularly focused on mining activities and waste per given electricity capacity and generation. It also includes carbon dioxide emissions generated during the transportation of raw materials to build and operate electricity generating systems and their environmental impacts in the US from 2023 to 2050. We identify the raw material and metal requirements for the U.S.-based typical systems in each energy type and synthesize datasets on typical ore fraction and material recycling factors, while taking into account the capacity factor of the power plants. We then compute the total mass and volume of material requirements and waste mass and volume for the front-end (i.e., mining, material needed for construction), operation (i.e., fuel, maintenance), and back-end (i.e., decommissioning) activities. The key findings are that (1) the energy transition from fossil fuel to low-carbon energy sources would reduce mining waste as well as the shipping carbon footprint; (2) the difference in capacity and actual electricity generation is significant for the life-cycle assessment due to low capacity factors of solar and wind energy; (3) several key metals with low abundance or high requirements dominate mining waste, which highlights the need for recycling and establishing a circular economy; (4) mining of critical minerals becomes important during the clean energy transition and (5) nuclear energy generates least waste and contributes least to shipping emissions among the low-carbon sources due to the high energy density and capacity factor and the small mass of materials it requires. Although the waste mass may not necessarily be equal to the environmental impact due to different waste isolation technologies, we aim to highlight the importance of considering mining and decommissioning waste, which are often ignored but important for accounting for the environmental impacts and addressing energy justice issues.

The Scholarly Knowledge Ecosystem: Challenges and Opportunities for the Field of Information

Mon, 31 Jan 2022 00:00:00 GMT

The Scholarly Knowledge Ecosystem: Challenges and Opportunities for the Field of Information Altman, Micah; Cohen, Philip N The scholarly knowledge ecosystem presents an outstanding exemplar of the challenges of understanding, improving, and governing information ecosystems at scale. This article draws upon significant reports on aspects of the ecosystem to characterize the most important research challenges and promising potential approaches. The focus of this review article is the fundamental scientific research challenges related to developing a better understanding of the scholarly knowledge ecosystem. Across a range of disciplines, we identify reports that are conceived broadly, published recently, and written collectively. We extract the critical research questions, summarize these using quantitative text analysis, and use this quantitative analysis to inform a qualitative synthesis. Three broad themes emerge from this analysis: the need for multi-sectoral cooperation and coordination, for mixed methods analysis at multiple levels, and interdisciplinary collaboration. Further, we draw attention to an emerging consensus that scientific research in this area should by a set of core human values.

Investigation of L2/Ln Pragmatic Competence: Its Core and Route Map

Tue, 17 Aug 2021 00:00:00 GMT

Investigation of L2/Ln Pragmatic Competence: Its Core and Route Map Mao, Tiaoyuan How to use language properly and acquire the capacity for language use has become the focus of linguists and philosophers for centuries. Therefore, pragmatic competence underlying language use arouses enormous interests of language acquisition practitioners. This study reveals the core properties of various models or theories of pragmatic competence, such as the communicative componential models, the form-function mapping proposal of the functionalist, the tripartite cognitive model, and the current integrated model of pragmatic competence. The common core includes (but not limited to) integration of thought and communication, one uniform pragmatic mechanism, dynamic form-function mapping, and complementarity between grammatical and pragmatic competences. With the findings as a departure, a brief outline for further investigation of pragmatic competence is proposed finally, including pathological and neurobiological examination of pragmatic competence.

Investigating Structural Biophysical Features for Antigen-Binding Fragment Crystallization via Machine Learning

Fri, 28 Feb 2025 00:00:00 GMT

Investigating Structural Biophysical Features for Antigen-Binding Fragment Crystallization via Machine Learning Chattaraj, Krishna Gopal; Ferreira, Joana; Myerson, Allan S.; Trout, Bernhardt L. Antibody-based therapeutics continue to be an important pharmaceutical development modality. Crystallization of antibodies is important for structural characterization, but in addition has the potential for use as a separation method and for use as a dosage form. Nevertheless, bringing about controlled crystallization of an antibody remains a challenging task due to its large size, high degree of segmental flexibility, and the intricacy of all the occurring interactions (e.g., protein–protein interactions, protein–solvent interactions, etc.). Methods to predict important contact sites could help to develop such crystallization methods. However, limited data and understanding have hitherto not allowed the development of such robust methods. This study employs machine learning combined with in silico modelling of crystal structures using available experimental structures to identify the crucial physicochemical features necessary for successful antibody crystallization in an attempt to remedy that gap. The developed method can with good accuracy distinguish crystal-site residues from non-crystal-site residues. A set of 510 descriptors is utilized to characterize each residue, which is treated as a distinct data point. Moreover, new algorithms have been developed to design novel descriptors that improve the model's predictive capabilities. Fragment antigen-binding (Fab) regions are investigated due to the scarcity of full-length monoclonal antibodies (mAbs) crystal structures. The current findings show that the extreme gradient boosting (XGBoost) algorithm effectively identifies crystal site residues, as evidenced by an AUPRC value that is more than 3-fold higher than that of the baseline model. The top-ranked descriptors indicate that crystal-site residues are primarily characterized by solvent-exposed residues with high spatial aggregation propensity (SAP), signifying hydrophobic patches, and their immediate surface-exposed neighbors. Moreover, these high SAP residues are often surrounded by other solvent-exposed residues that are either polar, charged, or both. In contrast, residues not involved in crystal interfaces generally lack these essential features, though some might be excluded due to specific crystal lattice arrangements. Additionally, reducing the feature set from 510 to the top 15% in the XGBoost model yields similar performance while significantly simplifying the model.

Modeling the Role of Supramolecular Clustering in Multivalent Assembly

Wed, 23 Apr 2025 00:00:00 GMT

Modeling the Role of Supramolecular Clustering in Multivalent Assembly Sbalbi, Nicholas; Petrov, Artem; Sass, Jacob; Ye, Matthew; Alexander-Katz, Alfredo; Macfarlane, Robert J. In self-assembled systems, a combination of multiple weak supramolecular interactions is often utilized to enable strong yet reversible binding. When modeling the behavior of these multivalent interfaces, it is commonly assumed that binding pairs are independent, i.e., the probability of a pair being bound is unaffected by the bound state of neighboring pairs. Inspired by recent experimental work, we report that for a variety of systems this assumption may not hold, leading to the formation of clusters at the binding interface. Through a series of analytical and numerical models of end-functionalized brushes, we reveal the role of cluster size on binding thermodynamics, detail how entropic contributions from polymer chains provide tunable control of cluster size, and provide predictions for cluster size as a function of system architecture. Investigation of these models yields surprising results: within the melting window, the enthalpy of binding of multivalent interfaces is predicted to depend only on cluster size and not on the overall valency of the multivalent system. Moreover, clustering is predicted to be significant even in systems with only weak dipole and dispersion interactions between neighboring groups. Combined, this work brings to light the potential impacts of clustering on multivalent self-assembly, providing theoretical justification for previous experimental observations and paving the way for future work in this area.

Elucidating the effect of Fe substitution on structural and redox stability of Na2Mn3O7

Tue, 11 Mar 2025 00:00:00 GMT

Elucidating the effect of Fe substitution on structural and redox stability of Na2Mn3O7 Smith, Hugh B.; Lee, Gi-Hyeok; Kumar, Bachu Sravan; Penn, Aubrey N.; Venturi, Victor; Gao, Yifan; Davis, Ryan C.; Stone, Kevin Hunter; Hunt, Adrian; Waluyo, Iradwikanari; Stavitski, Eli; Yangb, Wanli; Abate, Iwnetim I. Sodium-ion batteries have the potential to meet the growing demand for energy storage due to their low costs stemming from natural resource abundances, but their cathode energy densities must be improved to be comparable to those of lithium-ion batteries. One strategy is accessing high voltage capacity through high-valent redox reactions. Such reactions usually cause instability in cathode materials, but Na2Mn3O7 (NMO) has demonstrated excellent performance and reversibility in the high-valent regime due to its unique lattice structure with ordered Mn vacancies. This work expands the universality of the ordered vacancy as a design principle and increases the material candidates with such exceptional electrochemical behavior. Our approach involves synergizing cationic ordered vacancies with tunable metal–ligand hybridization through partial metal substitution. In particular, we successfully incorporated Fe3+ for Mn4+ in NMO to make Na2.25Mn2.75Fe0.25O7 and achieved improved high-valent redox behavior. Fe substitution leads to larger specific capacities (171 vs. 159 mA h g−1 first cycle), enhanced cycle stability (97 vs. 60 mA h g−1 after 50 cycles), and superior rate performance. This study lays the foundation for developing new cathode materials with stable high-valent redox through substitution of redox-active transition metals by employing cationic ordered vacancies and partial transition metal substitution as design principles in tandem.

Progress in Computational Methods and Mechanistic Insights on the Growth of Carbon Nanotubes

Wed, 19 Mar 2025 00:00:00 GMT

Progress in Computational Methods and Mechanistic Insights on the Growth of Carbon Nanotubes Wang, Linzheng; Tricard, Nicolas; Chen, Zituo; Deng, Sili Carbon nanotubes (CNTs), as a promising nanomaterial with broad applications across various fields, are continuously attracting significant research attention. Despite substantial progress in understanding their growth mechanisms, synthesis methods, and post-processing techniques, two major goals remain challenging: achieving property-targeted growth and efficient mass production. Recent advancements in computational methods driven by increased computational resources, the development of platforms, and the refinement of theoretical models, have significantly deepened our understanding of the mechanisms underlying CNT growth. This review aims to comprehensively examine the latest computational techniques that shed light on various aspects of CNT synthesis. The first part of this review focuses on progress in computational methods. Beginning with atomistic simulation approaches, we introduce the fundamentals and advancements in density functional theory (DFT), molecular dynamics (MD) simulations, and kinetic Monte Carlo (kMC) simulations. We discuss the applicability and limitations of each method in studying mechanisms of CNT growth. Then, the focus shifts to multiscale modeling approaches, where we demonstrate the coupling of atomic-scale simulations with reactor-scale multiphase flow models. Given that CNT growth inherently spans multiple temporal and spatial scales, the development and application of multiscale modeling techniques are poised to become a central focus of future computational research in this field. Furthermore, this review emphasizes the growing role played by machine learning in CNT growth research. Compared with traditional physics-based simulation methods, data-driven machine learning approaches have rapidly emerged in recent years, revolutionizing research paradigms from molecular simulation to experimental design. In the second part of this review, we highlight the latest advancements in CNT growth mechanisms and synthesis methods achieved through computational techniques. These include novel findings across fundamental growth stages, i.e., from nucleation to elongation and ultimately termination. We also examine the dynamic behaviors of catalyst nanoparticles and chirality-controlled growth processes, emphasizing how these insights contribute to advancing the field. Finally, in the concluding section, we propose future directions for advancements of computational approaches toward deeper understanding of CNT growth mechanisms and better support of CNT manufacturing.

Superthermal Solar Interfacial Evaporation is not due to Reduced Latent Heat of Water

Mon, 13 Jan 2025 00:00:00 GMT

Superthermal Solar Interfacial Evaporation is not due to Reduced Latent Heat of Water Zhang, James H.; Mittapally, Rohith; Lva, Guangxin; Chen, Gang To explain reported solar interfacial-evaporation rates from porous materials beyond an apparent 100% efficiency using the thermal evaporation mechanism, many publications hypothesize that intermediate water inside porous materials has a reduced latent heat. Key supporting evidence is that water-only surfaces have lower natural evaporation rates than porous evaporators, with the ratio of the two rates taken as the latent heat reduction. Through simulations and experiments, we study natural evaporation of water and show that reported differences in evaporation rates between porous materials and water are likely due to experimental error from recessed evaporating surfaces. A few millimeter recession of the water surface relative to the container lip can drop evaporation rates by over 50% due to a stagnant air layer, suggesting that the comparative experiments are prone to error. Furthermore, in the reduced latent heat picture, interfacial cooling must occur at the porous sample–water interface due to the enthalpy difference between bulk water and intermediate water. Our transport modeling shows that reduced latent heat cannot explain superthermal evaporation and that new mechanistic directions need to be pursued.

Generative design and molecular mechanics characterization of silk proteins based on unfolding behavior

Fri, 02 May 2025 00:00:00 GMT

Generative design and molecular mechanics characterization of silk proteins based on unfolding behavior Lu, Wei; Buehler, Markus J. Spider silk exhibits exceptional mechanical properties, biocompatibility, and biodegradability, making it a promising material for bioengineered applications. However, the complexity and diversity of silk proteins, coupled with limited experimental data, have hindered the rational design of silk-based biomaterials. Furthermore, the mechanobiology of these proteins and their impact on silk fiber properties remain underexplored. In this study, we introduce a series of novel silk protein sequences and characterize their nonlinear unfolding behavior and mechanical properties through molecular dynamics (MD) simulations. Focusing on major ampullate spidroin (MaSp) silk proteins, we curate a dataset that integrates experimentally acquired sequences with synthetic sequences generated by SilkomeGPT, a generative model for silk-inspired proteins. Structural predictions are performed using OmegaFold, from which high-fidelity regions are extracted and analyzed. Their unfolding responses are assessed via implicit all-atom MD simulations, enabling characterization of their mechanical behavior. This computationally efficient framework facilitates the rational design of spider silk proteins by linking atomistic and sequence features to larger-scale properties. The developed dataset systematically captures structural uncertainties, while simulations provide atomic-level insights into how protein mechanics contribute to fiber properties, advancing the mechanobiological understanding of spider silk and supporting diverse applications in biomaterials design.

Tumor-Localized Interleukin-2 and Interleukin-12 Combine with Radiation Therapy to Safely Potentiate Regression of Advanced Malignant Melanoma in Pet Dogs

Fri, 13 Sep 2024 00:00:00 GMT

Tumor-Localized Interleukin-2 and Interleukin-12 Combine with Radiation Therapy to Safely Potentiate Regression of Advanced Malignant Melanoma in Pet Dogs Stinson, Jordan A; Barbosa, Matheus Moreno P; Sheen, Allison; Momin, Noor; Fink, Elizabeth; Hampel, Jordan; Selting, Kim A; Kamerer, Rebecca L; Bailey, Keith L; Wittrup, Karl D; Fan, Timothy M Purpose: Cytokines IL2 and IL12 exhibit potent anticancer activity but suffer a narrow therapeutic window due to off-tumor immune cell activation. Engineering cytokines with the ability to bind and associate with tumor collagen after intratumoral injection potentiated response without toxicity in mice and was previously safe in pet dogs with sarcoma. Here, we sought to test the efficacy of this approach in dogs with advanced melanoma. Patients and Methods: This study examined 15 client-owned dogs with histologically or cytologically confirmed malignant melanoma that received a single 9-Gy fraction of radiotherapy, followed by six cycles of combined collagen-anchored IL2 and IL12 therapy every 2 weeks. Cytokine dosing followed a 3 + 3 dose escalation design, with the initial cytokine dose chosen from prior evaluation in canine sarcomas. No exclusion criteria for tumor stage or metastatic burden, age, weight, or neuter status were applied for this trial. Results: Median survival regardless of the tumor stage or dose level was 256 days, and 10/13 (76.9%) dogs that completed treatment had CT-measured tumor regression at the treated lesion. In dogs with metastatic disease, 8/13 (61.5%) had partial responses across their combined lesions, which is evidence of locoregional response. Profiling by NanoString of treatment-resistant dogs revealed that B2m loss was predictive of poor response to this therapy. Conclusions: Collectively, these results confirm the ability of locally administered tumor-anchored cytokines to potentiate responses at regional disease sites when combined with radiation. This evidence supports the clinical translation of this approach and highlights the utility of comparative investigation in canine cancers.

Bivalent target-binding bioPROTACs induce potent degradation of oncogenic SHP2

Sun, 01 Sep 2024 00:00:00 GMT

Bivalent target-binding bioPROTACs induce potent degradation of oncogenic SHP2 Hoffman, Megan; Krum, David; Wittrup, K Dane Targeted protein degradation is an emergent and rapidly evolving therapeutic strategy. In particular, biologics-based targeted degradation modalities (bioPROTACs) are relatively under explored compared to small molecules. Here, we investigate how target affinity, cellular localization, and valency of bioPROTACs impact efficacy of targeted degradation of the oncogenic phosphatase src-homology 2 containing protein tyrosine phosphatase-2 (SHP2). We identify bivalent recruitment of SHP2 by bioPROTACs as a broadly applicable strategy to improve potency. Moreover, we demonstrate that SHP2-targeted bioPROTACs can effectively counteract gain-of-function SHP2 mutants present in cancer, which are otherwise challenging to selectively target with small molecule constructs. Overall, this study demonstrates the utility of bioPROTACs for challenging targets, and further explicates design principles for therapeutic bioPROTACs.

Local delivery of cell surface-targeted immunocytokines programs systemic antitumor immunity

Wed, 07 Aug 2024 00:00:00 GMT

Local delivery of cell surface-targeted immunocytokines programs systemic antitumor immunity Santollani, Luciano; Maiorino, Laura; Zhang, Yiming J; Palmeri, Joseph R; Stinson, Jordan A; Duhamel, Lauren R; Qureshi, Kashif; Suggs, Jack R; Porth, Owen T; Pinney, William; Msari, Riyam Al; Walsh, Agnes A; Wittrup, K Dane; Irvine, Darrell J Systemically administered cytokines are potent immunotherapeutics but can cause severe dose-limiting toxicities. To overcome this challenge, cytokines have been engineered for intratumoral retention after local delivery. However, despite inducing regression of treated lesions, tumor-localized cytokines often elicit only modest responses at distal untreated tumors. In the present study, we report a localized cytokine therapy that safely elicits systemic antitumor immunity by targeting the ubiquitous leukocyte receptor CD45. CD45-targeted immunocytokines have lower internalization rates relative to wild-type counterparts, leading to sustained downstream cis and trans signaling between lymphocytes. A single intratumoral dose of αCD45-interleukin (IL)-12 followed by a single dose of αCD45-IL-15 eradicated treated tumors and untreated distal lesions in multiple syngeneic mouse tumor models without toxicity. Mechanistically, CD45-targeted cytokines reprogrammed tumor-specific CD8+ T cells in the tumor-draining lymph nodes to have an antiviral transcriptional signature. CD45 anchoring represents a broad platform for protein retention by host immune cells for use in immunotherapy.

Tumor Integrin-Targeted Glucose Oxidase Enzyme Promotes ROS-Mediated Cell Death that Combines with Interferon Alpha Therapy for Tumor Control

Thu, 02 Jan 2025 00:00:00 GMT

Tumor Integrin-Targeted Glucose Oxidase Enzyme Promotes ROS-Mediated Cell Death that Combines with Interferon Alpha Therapy for Tumor Control Stinson, Jordan A; Sheen, Allison; Lax, Brianna M; Yang, Grace N; Duhamel, Lauren; Santollani, Luciano; Fink, Elizabeth; Palmeri, Joseph R; Wittrup, Karl Dane Although heightened intratumoral levels of reactive oxygen species (ROS) are typically associated with a suppressive tumor microenvironment, under certain conditions ROS contribute to tumor elimination. Treatment approaches, including some chemotherapy and radiation protocols, increase cancer cell ROS levels that influence their mechanism of cell death and subsequent recognition by the immune system. Furthermore, activated myeloid cells rapidly generate ROS upon encounter with pathogens or infected cells to eliminate disease, and recently, this effector function has been noted in cancer contexts as well. Collectively, ROS-induced cancer cell death may help initiate adaptive antitumor immune responses that could synergize with current approved immunotherapies, for improved control of solid tumors. In this work, we explore the use of glucose oxidase, an enzyme which produces hydrogen peroxide, a type of ROS, to therapeutically mimic the endogenous oxidative burst from myeloid cells to promote antigen generation within the tumor microenvironment. We engineer the enzyme to target pan-tumor-expressed integrins both as a tumor-agnostic therapeutic approach and as a strategy to prolong local enzyme activity following intratumoral administration. We found the targeted enzyme potently induced cancer cell death and enhanced cross-presentation by dendritic cells in vitro and further combined with interferon alpha for long-term tumor control in murine MC38 tumors in vivo. Optimizing the single-dose administration of this enzyme overcomes limitations with immunogenicity noted for other prooxidant enzyme approaches. Overall, our results suggest ROS-induced cell death can be harnessed for tumor control and highlight the potential use of designed enzyme therapies alongside immunotherapy against cancer.

Yeast as a tool for exploring disulfide-rich peptides

Thu, 18 Dec 2025 00:00:00 GMT

Yeast as a tool for exploring disulfide-rich peptides Yap, Kuok; Porth, Owen T; Xie, Jing; Wang, Conan K; Durek, Thomas; Wittrup, K Dane; Craik, David J Cyclic disulfide-rich peptides have become increasingly popular in drug development because their structures enhance molecular stability and allow for mutagenesis to introduce non-native functions. This review focuses on yeast-based platform technologies and their utility in advancing cyclic disulfide-rich peptides as drug modalities and for large-scale biomanufacturing. These technologies include yeast surface display which facilitates the screening of large libraries to develop peptide binders with strong affinity and selectivity for protein targets, while maintaining the innate high stability of the peptide scaffold via protease-based selection pressure. We also describe a recently developed platform that leverages yeast’s ability to secrete correctly folded disulfide-rich peptides while simultaneously displaying peptide or protein tags on their surfaces. In combination with microfluidics technology, the platform creates single-cell yeast-in-droplets reactors, enabling the screening of large libraries based on functional output rather than solely on binding affinity. After identifying cyclic peptide candidates through library-based discovery, these candidates can be produced using a versatile yeast-based bioproduction platform. Traditionally, cyclic disulfide-rich peptides are produced through solid-phase synthesis, a method that generates significant amounts of toxic waste. In contrast, yeast-based bioproduction offers an environmentally sustainable alternative. It has the capability to produce structurally distinct peptides with minimal adjustments and is easily scalable using microbial fermenters, making it an ideal choice for large-scale production.

Aligning supply chain design for boosting resilience

Tue, 01 May 2018 00:00:00 GMT

Aligning supply chain design for boosting resilience Sáenz, María Jesús; Revilla, Elena; Acero, Beatriz Many researchers have analyzed the effect of disruptive events, such as natural disasters and economic and market forces, on global supply chains. However, there is a lack of consensus on delineating a universal collection of supply chain risk management practices that will help companies operate in a global market with large-scale disruptions. In this article, we present an analysis, in conjunction with a worldwide online survey, based on successful global brands and their supply chains. We propose a framework that deploys the dynamics of building supply chain resilience, first linking the design of the supply chain portfolio (local versus global scope, as well as strategic responsiveness versus cost reduction) with supply chain vulnerabilities (external versus internal). We describe the transition between different supply chain structures as a way of coping with disruptions and thus proactively developing resilience. In this article, we introduce both a supply chain risk management approach and the reactive-by-deployment mode, as illustrated by successful global company examples.

Directed evolution-based discovery of ligands for in vivo restimulation of chimeric antigen receptor T cells

Mon, 25 Aug 2025 00:00:00 GMT

Directed evolution-based discovery of ligands for in vivo restimulation of chimeric antigen receptor T cells Grzywa, Tomasz M; Neeser, Alexandra; Ramasubramanian, Ranjani; Romanov, Anna; Tannir, Ryan; Mehta, Naveen K; Cossette, Benjamin; Morgan, Duncan M; Goncalves, Beatriz; Sukaj, Ina; Bergaggio, Elisa; Kadauke, Stephan; Myers, Regina M; Paruzzo, Luca; Ghilardi, Guido; Cozzone, Austin; Schuster, Stephen J; Frey, Noelle; Zhang, Libin; Yousefpour, Parisa; Abraham, Wuhbet; Suh, Heikyung; Ruella, Marco; Grupp, Stephan A; Chiarle, Roberto; Wittrup, K Dane; Ma, Leyuan; Irvine, Darrell J Chimeric antigen receptor (CAR) T cell therapy targeting CD19 elicits remarkable clinical efficacy in B cell malignancies, but many patients relapse owing to failed expansion and/or progressive loss of CAR-T cells. We recently reported a strategy to potently restimulate CAR-T cells in vivo, enhancing their functionality by administration of a vaccine-like stimulus comprised of surrogate peptide ligands for a CAR linked to a lymph node-targeting amphiphilic PEG-lipid (amph-vax). Here we demonstrate a general strategy to discover and optimize peptide mimotopes enabling amph-vax generation for any CAR. We use yeast surface display to identify peptide binders to FMC63 (the scFv used in clinical CD19 CARs), which are then subsequently affinity matured by directed evolution. CAR-T vaccines using these optimized mimotopes triggered marked expansion and memory development of CD19 CAR-T cells in both syngeneic and humanized mouse models of B-acute lymphoblastic leukaemia/lymphoma, and enhanced control of disease progression compared with CD19 CAR-T-only-treated mice. This approach enables amph-vax boosting to be applied to any clinically relevant CAR-T cell product.

Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics

Tue, 25 Jan 2022 00:00:00 GMT

Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics Lai, Pin-Kuang; Gallegos, Austin; Mody, Neil; Sathish, Hasige A; Trout, Bernhardt L Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this study, we measured accelerated aggregation rates at 45°C and viscosity at 150 mg/ml for 20 preclinical and clinical-stage antibodies. Features obtained from molecular dynamics simulations of the full-length antibody and sequences were used for machine learning model construction. We found a k-nearest neighbors regression model with two features, spatial positive charge map on the CDRH2 and solvent-accessible surface area of hydrophobic residues on the variable fragment, gives the best performance for predicting antibody aggregation rates (r = 0.89). For the viscosity classification model, the model with the highest accuracy is a logistic regression model with two features, spatial negative charge map on the heavy chain variable region and spatial negative charge map on the light chain variable region. The accuracy and the area under precision recall curve of the classification model from validation tests are 0.86 and 0.70, respectively. In addition, we combined data from another 27 commercial mAbs to develop a viscosity predictive model. The best model is a logistic regression model with two features, number of hydrophobic residues on the light chain variable region and net charges on the light chain variable region. The accuracy and the area under precision recall curve of the classification model are 0.85 and 0.6, respectively. The aggregation rates and viscosity models can be used to predict antibody stability to facilitate pharmaceutical development.

Enhanced O-glycosylation site prediction using explainable machine learning technique with spatial local environment

Tue, 04 Feb 2025 00:00:00 GMT

Enhanced O-glycosylation site prediction using explainable machine learning technique with spatial local environment Hong, Seokyoung; Chattaraj, Krishna Gopal; Guo, Jing; Trout, Bernhardt L; Braatz, Richard D Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning (ML) models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site. Additionally, we utilize sparse recurrent neural networks to effectively capture sequential nature of the proteins and to identify key factors influencing O-GlcNAcylation as an explainable ML model. Results: Our findings demonstrate the effectiveness of our proposed features with the model achieving an F1 score of 28.3%, as well as feature selection capability with the model using only the top 20% of features achieving the highest F1 score of 32.02%, a 1.4-fold improvement over existing PTM models. Statistical analysis of the top 20 features confirmed their consistency with literature. This method not only boosts prediction accuracy but also paves the way for further research in understanding and targeting O-GlcNAcylation. Availability and implementation: The entire code, data, features used in this study are available in the GitHub repository: https://github.com/ pseokyoung/o-glcnac-

Leveraging microtopography to pattern multi-oriented muscle actuators

Fri, 14 Mar 2025 00:00:00 GMT

Leveraging microtopography to pattern multi-oriented muscle actuators Rossy, Tamara; Schwendeman, Laura; Kohli, Sonika; Bawa, Maheera; Umashankar, Pavankumar; Habba, Roi; Tchaicheeyan, Oren; Lesmanbc, Ayelet; Raman, Ritu Engineering skeletal muscle tissue with precisely defined alignment is of significant importance for applications ranging from drug screening to biohybrid robotics. Aligning 2D contractile muscle monolayers, which are compatible with high-content imaging and can be deployed in planar soft robots, typically requires micropatterned cues. However, current protocols for integrating microscale topographical features in extracellular matrix hydrogels require expensive microfabrication equipment and multi-step procedures involving error-prone manual handling steps. To address this challenge, we present STAMP (simple templating of actuators via micro-topographical patterning), an easily accessible and cost-effective one-step method to pattern microtopography of various sizes and configurations on the surface of hydrogels using reusable 3D printed stamps. We demonstrate that STAMP enables precisely controlling the alignment of mouse and human skeletal muscle fibers without negatively impacting their maturation or function. To showcase the versatility of our technique, we designed a planar soft robot inspired by the iris, which leverages spatially segregated regions of concentric and radial muscle fibers to control pupil dilation. Optogenetic skeletal muscle fibers grown on a STAMPed iris substrates formed a multi-oriented actuator, and selective light stimulation of the radial and concentric fibers was used to control the function of the iris, including pupil constriction. Computational modeling of the biohybrid robot as an active bilayer matched experimental outcomes, showcasing the robustness of our STAMP method for designing, fabricating, and testing planar biohybrid robots capable of complex multi-DOF motion.

Enhancing Spray Retention Using Cloaked Droplets to Reduce Pesticide Pollution

Tue, 25 Mar 2025 00:00:00 GMT

Enhancing Spray Retention Using Cloaked Droplets to Reduce Pesticide Pollution Jayaprakash, Vishnu; Rufer, Simon; Panata, Sreedath; Varanasi, Kripa K. Enhancing agrochemical spray retention on plant surfaces would have tremendous benefits to global health and the environment. The bouncing of sprayed pesticide droplets from hydrophobic leaves is a major source of water and soil pollution, and the resultant overuse of pesticides is a human health hazard and a financial burden for farmers. Here we report on the development of sustainable agricultural sprays consisting of cloaked droplets that significantly enhance droplet retention on plant surfaces. By leveraging wetting dynamics, we create cloaked droplets that consist of an ultra-thin food and environmentally safe oil layer (<1% by volume) that encapsulates water droplets. We develop a fundamental understanding of the dynamics of cloaked droplet impact and retention on superhydrophobic surfaces. Using high-speed imaging, we capture how the oil cloak transforms into a wetting ridge that pins the droplets and suppresses their rebound. We span a wide range of impact conditions, oils, oil viscosities, and oil volume fractions to demonstrate the robustness of the approach. By considering a balance of kinetic energy, the work of adhesion, and viscous dissipation in this four-phase system, we develop a physical model that allows us to establish a regime map for rebound suppression. Finally, these findings are implemented into a prototype sprayer which leads to a ∼5-fold reduction in spray waste on crop leaves. We believe that our spray approach can greatly reduce agrochemical pollution as well as pesticide and surfactant usage.

Total Synthesis and 13C NMR Revision of Nagelamide C

Wed, 04 Jun 2025 00:00:00 GMT

Total Synthesis and 13C NMR Revision of Nagelamide C Tong, Guanghu; Nguyen, Long V.; Jamison, Timothy F. Nagelamide C (1), a dimeric pyrrole–imidazole alkaloid, exhibits antimicrobial and antibacterial activities. We demonstrate herein the first total synthesis of nagelamide C. This concise work was enabled by a series of significant transformations featuring: an imidazole benzylic Wittig olefination, a site selective bromination, and a regioselective trans-hydrostannylation/Stille coupling to construct a unique trisubstituted olefin. In addition, we show the original 13C NMR data of nagelamide C to be in error and revise the data.

Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search

Mon, 12 May 2025 00:00:00 GMT

Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search Subramanian, Akshay; Damewood, James; Nam, Juno; Greenman, Kevin P.; Singhal, Avni P.; Gómez-Bombarelli, Rafael Organic optoelectronic materials are a promising avenue for next-generation electronic devices due to their solution processability, mechanical flexibility, and tunable electronic properties. In particular, near-infrared (NIR) sensitive molecules have unique applications in night-vision equipment and biomedical imaging. Molecular engineering has played a crucial role in developing non-fullerene acceptors (NFAs) such as the Y-series molecules, which feature a rigid fused-ring electron donor core flanked by electron-deficient end groups, leading to strong intramolecular charge-transfer and extended absorption into the NIR region. However, systematically designing molecules with targeted optoelectronic properties while ensuring synthetic accessibility remains a challenge. To address this, we leverage structural priors from domain-focused, patent-mined datasets of organic electronic molecules using a symmetry-aware fragment decomposition algorithm and a fragment-constrained Monte Carlo Tree Search (MCTS) generator. Our approach generates candidates that retain symmetry constraints from the patent dataset, while also exhibiting red-shifted absorption, as validated by TD-DFT calculations.

Molecular analysis and design using generative artificial intelligence via multi-agent modeling

Fri, 24 Jan 2025 00:00:00 GMT

Molecular analysis and design using generative artificial intelligence via multi-agent modeling Stewart, Isabella; Buehler, Markus J. We report the use of a multiagent generative artificial intelligence framework, the X-LoRA-Gemma large language model (LLM), to analyze, design and test molecular design. The X-LoRA-Gemma model, inspired by biological principles and featuring 7 billion parameters, dynamically reconfigures its structure through a dual-pass inference strategy to enhance its problem-solving abilities across diverse scientific domains. The model is used to first identify molecular engineering targets through a systematic human–AI and AI–AI self-driving multi-agent approach to elucidate key targets for molecular optimization to improve interactions between molecules. Next, a multi-agent generative design process is used that includes rational steps, reasoning and autonomous knowledge extraction. Target properties of the molecule are identified either using a principal component analysis (PCA) of key molecular properties or sampling from the distribution of known molecular properties. The model is then used to generate a large set of candidate molecules, which are analyzed via their molecular structure, charge distribution, and other features. We validate that as predicted, increased dipole moment and polarizability is indeed achieved in the designed molecules. We anticipate an increasing integration of these techniques into the molecular engineering workflow, ultimately enabling the development of innovative solutions to address a wide range of societal challenges. We conclude with a critical discussion of challenges and opportunities of the use of multi-agent generative AI for molecular engineering, analysis and design.

Automated fast-flow synthesis of the immune checkpoint receptors PD-1 and PD-L1

Mon, 17 Mar 2025 00:00:00 GMT

Automated fast-flow synthesis of the immune checkpoint receptors PD-1 and PD-L1 Fittolani, Giulio; Callahan, Alex J.; Loas, Andrei; Pentelute, Bradley L. Programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) are key targets for cancer therapy. Here, we use automated fast-flow peptide synthesis (AFPS) to rapidly produce these challenging β-sheet-rich proteins in their active forms following oxidative refolding protocols. The methods presented here provide rapid access to synthetic, air-stable mutants of PD-1 and PD-L1 in which L-methionine residues are substituted with L-norleucine, potentially enabling investigation of post-translational modifications and mirror-image analogs for drug discovery.

GeoXCP: uncertainty quantification of spatial explanations in explainable AI

Mon, 27 Oct 2025 00:00:00 GMT

Open-source device for high sensitivity magnetic particle spectroscopy, relaxometry, and hysteresis loop tracing

Wed, 26 Jun 2024 00:00:00 GMT

Open-source device for high sensitivity magnetic particle spectroscopy, relaxometry, and hysteresis loop tracing Mattingly, E.; Barksdale, A. C.; Śliwiak, M.; Chacon-Caldera, J.; Mason, E. E.; Wald, L. L. Magnetic nanoparticles (MNPs) are used extensively across numerous disciples, with applications including Magnetic Particle Imaging (MPI), targeted hyperthermia, deep brain stimulation, immunoassays, and thermometry. The assessment of MNPs, especially those being designed for MPI, is performed with magnetic particle spectrometers, relaxometers, loop tracers, or similar devices. Despite the many applications and the need for particle assessment, there are few consolidated resources for designing or building such a MNP assessment system. Here, we describe the design and performance of an open-source device capable of spectroscopy, relaxometry, and loop tracing. We show example measurements from the device and quantify the detection sensitivity by measuring a dilution series of Synomag-D 70 nm (from 0.5 mg Fe/ml to 7 ng Fe/ml) with a 10 mT drive field at 23.8 kHz. The device measures 260 pg Fe with SNR = 1 and 1.3 ng at SNR = 5 in spectroscopy mode in under one second of measurement time. The system has a dynamic range of 60 μg to 260 pg Fe without changing the hardware configuration. As an example application, we characterize Synomag-D’s relaxation time constant for drive fields 2–18 mT and compare the magnetization responses of two commonly used MNPs.

Precise Fermi level engineering in a topological Weyl semimetal via fast ion implantation

Tue, 25 Jun 2024 00:00:00 GMT

Precise Fermi level engineering in a topological Weyl semimetal via fast ion implantation Mandal, Manasi; Chotrattanapituk, Abhijatmedhi; Woller, Kevin; Wu, Lijun; Xu, Haowei; Hung, Nguyen Tuan; Mao, Nannan; Okabe, Ryotaro; Boonkird, Artittaya; Nguyen, Thanh; Drucker, Nathan C; Chen, Xiaoqian M; Momiki, Takashi; Li, Ju; Kong, Jing; Zhu, Yimei; Li, Mingda The precise controllability of the Fermi level is a critical aspect of quantum materials. For topological Weyl semimetals, there is a pressing need to fine-tune the Fermi level to the Weyl nodes and unlock exotic electronic and optoelectronic effects associated with the divergent Berry curvature. However, in contrast to two-dimensional materials, where the Fermi level can be controlled through various techniques, the situation for bulk crystals beyond laborious chemical doping poses significant challenges. Here, we report the milli-electron-volt (meV) level ultra-fine-tuning of the Fermi level of bulk topological Weyl semimetal tantalum phosphide using accelerator-based high-energy hydrogen implantation and theory-driven planning. By calculating the desired carrier density and controlling the accelerator profiles, the Fermi level can be experimentally fine-tuned from 5 meV below, to 3.8 meV below, to 3.2 meV above the Weyl nodes. High-resolution transmission electron microscopy reveals the crystalline structure is largely maintained under irradiation, while electrical transport indicates that Weyl nodes are preserved and carrier mobility is also largely retained. Our work demonstrates the viability of this generic approach to tune the Fermi level in semimetal systems and could serve to achieve property fine-tuning for other bulk quantum materials with ultrahigh precision.

A facility for cryogenic ion irradiation and in situ characterization of rare-earth barium copper oxide superconducting tapes

Wed, 26 Jun 2024 00:00:00 GMT

A facility for cryogenic ion irradiation and in situ characterization of rare-earth barium copper oxide superconducting tapes Devitre, AR; Fischer, DX; Woller, KB; Clark, BC; Short, MP; Whyte, DG; Hartwig, ZS Superconducting magnets based on Rare Earth Barium Copper Oxides (REBCO) offer transformative capabilities in the fields of fusion energy, high energy physics, and space exploration. A challenge shared by these applications is the limited lifetime of REBCO due to radiation damage sustained during operation. Here we present a new ion-beam facility that enables simultaneous cryogenic irradiation and in situ characterization of commercial REBCO tapes. The ion source provides spatially uniform fluxes up to 1018 protons/m2s with kinetic energies up to 3.4 MeV, in addition to helium and higher-Z species. Using this facility, we can induce uniform damage profiles in the first 10–20 µm of REBCO tapes with less than 0.25 appm of hydrogen implanted in REBCO after a dose of 1020 protons/m2. The tape can be held between 20 and 300 K with an accuracy of ±0.1 K and is connected to a four-point probe measuring the critical current, Ic, and critical temperature, Tc, before, during, and after irradiation with transport current ranging from 100 nA to 100 A, and a typical voltage noise less than 0.1 μV. These capabilities are presently used to study the effect of irradiation temperature on REBCO performance change during and after proton bombardment, to assess the possibility of Ic and Tc recovery after irradiation through thermal annealing, and to explore the instantaneous and recoverable suppression of Ic and Tc observed during irradiation.

High temperature stability of regrown and alloyed Ohmic contacts to AlGaN/GaN heterostructure up to 500 °C

Wed, 15 May 2024 00:00:00 GMT

High temperature stability of regrown and alloyed Ohmic contacts to AlGaN/GaN heterostructure up to 500 °C Niroula, John; Xie, Qingyun; Rajput, Nitul S; Darmawi-Iskandar, Patrick K; Rahman, Sheikh Ifatur; Luo, Shisong; Palash, Rafid Hassan; Sikder, Bejoy; Yuan, Mengyang; Yadav, Pradyot; Micale, Gillian K; Chowdhury, Nadim; Zhao, Yuji; Rajan, Siddharth; Palacios, Tomás This Letter reports the stability of regrown and alloyed Ohmic contacts to AlGaN/GaN-on-Si high electron mobility transistors (HEMTs) for high temperature applications up to 500 °C. Transfer length method (TLM) measurements from 25 to 500 °C in air show that the regrown contacts appear to be stable up to 500 °C during short term (approximately 1 h) testing, while alloyed contacts appear to decrease in contact resistance from 300 to 500 °C though increases in the error bounds due to increase sheet resistance make it difficult to conclude definitely. Additionally, longer term testing shows both technologies remain stable at least up to 48 h at 500 °C, after which the large increase in sheet resistance makes the measurement uncertainty too large to conclude definitively. Advanced microscopy images indicate both the regrown and alloyed contact regions remain structurally intact after prolonged high temperature exposure with no visible degradation in crystallinity or metal composition.

Optical-pump–terahertz-probe spectroscopy in high magnetic fields with kHz single-shot detection

Tue, 12 Mar 2024 00:00:00 GMT

Optical-pump–terahertz-probe spectroscopy in high magnetic fields with kHz single-shot detection Dastrup, Blake S; Miedaner, Peter R; Zhang, Zhuquan; Nelson, Keith A We demonstrate optical pump–THz probe (OPTP) spectroscopy with a variable external magnetic field (0–9 T), in which the time-dependent THz signal is measured by echelon-based single-shot detection at a repetition rate of 1 kHz. The method reduces data acquisition times by more than an order of magnitude compared to conventional electro-optic sampling using a scanning delay stage. The approach illustrates the wide applicability of the single-shot measurement approach to non-equilibrium systems that are studied through OPTP spectroscopy, especially in cases where parameters such as magnetic field strength (B) or other experimental parameters are varied. We demonstrate the capabilities of our measurement by performing cyclotron resonance experiments in bulk silicon, where we observe B-field-dependent carrier relaxation and distinct relaxation rates for different carrier types. We use a pair of economical linear array detectors to measure 500 time points on each shot, offering an equivalent performance to camera-based detection with possibilities for higher repetition rates.

Validation of the OpenMC Code for Fusion Applications: The FNG-Streaming Benchmark Case

Fri, 04 Jul 2025 00:00:00 GMT

Validation of the OpenMC Code for Fusion Applications: The FNG-Streaming Benchmark Case Segantin, Stefano; Ebiwonjumi, Bamidele; Peterson, Ethan In this work, we benchmark OpenMC against the FNG-ITER streaming experiment. FNG-ITER streaming, a high-quality experiment carried out at the ENEA laboratories in Frascati, Italy, was initially included in SINBAD (Shielding Integral Benchmark Archive and Database). More recently, the benchmark was included in the Compilation of Nuclear Data Experiments for Radiation Characterization as well. It consists of a neutron shielding experiment with a rather complex geometry that constitutes an appropriate validation study for the use of weight windows within OpenMC. Measurements include flux detection via four different types of activation foils divided into three batches and a set of thermoluminescent detectors for nuclear heating. The OpenMC results are in very good agreement with those of MCNP and the experimental measurements, with the majority of the discrepancies within the combined statistical error and experimental uncertainty (less than 10% computed measured discrepancy).

Use of Bayesian decision analysis to maximize value in patient-centered randomized clinical trials in Parkinson’s disease

Wed, 03 Sep 2025 00:00:00 GMT

Use of Bayesian decision analysis to maximize value in patient-centered randomized clinical trials in Parkinson’s disease Chaudhuri, Shomesh E; Ben Chaouch, Zied; Hauber, Brett; Mange, Brennan; Zhou, Mo; Christopher, Stephanie; Bardot, Dawn; Sheehan, Margaret; Donnelly, Anne; McLaughlin, Lauren; Caldwell, Brittany; Benz, Heather L; Ho, Martin; Saha, Anindita; Gwinn, Katrina; Sheldon, Murray; Lo, Andrew W A fixed one-sided significance level of 5% is commonly used to interpret the statistical significance of randomized clinical trial (RCT) outcomes. While it is necessary to reduce the false positive rate, the threshold used could be chosen quantitatively and transparently to specifically reflect patient preferences regarding benefit–risk tradeoffs as well as other considerations. How can patient preferences be explicitly incorporated into RCTs in Parkinson’s disease (PD), and what is the impact on statistical thresholds for device approval? In this analysis, we apply Bayesian decision analysis (BDA) to PD patient preference scores elicited from survey data. BDA allows us to choose a sample size (𝑛) and significance level (𝛼) that maximizes the overall expected value to patients of a balanced two-arm fixed-sample RCT, where the expected value is computed under both null and alternative hypotheses. For PD patients who had previously received deep brain stimulation (DBS) treatment, the BDA-optimal significance levels fell between 4.0% and 10.0%, similar to or greater than the traditional value of 5%. Conversely, for patients who had never received DBS, the optimal significance level ranged from 0.2% to 4.4%. In both of these populations, the optimal significance level increased with the severity of the patients’ cognitive and motor function symptoms. By explicitly incorporating patient preferences into clinical trial designs and the regulatory decision-making process, BDA provides a quantitative and transparent approach to combine clinical and statistical significance. For PD patients who have never received DBS treatment, a 5% significance threshold may not be conservative enough to reflect their risk-aversion level. However, this study shows that patients who previously received DBS treatment present a higher tolerance to accept therapeutic risks in exchange for improved efficacy which is reflected in a higher statistical threshold.

Choice denied: impact of income and credit-based tenant screening on the Housing Choice Voucher program

Wed, 30 Apr 2025 00:00:00 GMT

Choice denied: impact of income and credit-based tenant screening on the Housing Choice Voucher program So, Wonyoung; Gade, Anisha; Hangen, Forrest The Housing Choice Voucher program supports over 2.5 million households by subsidizing rent payments within the private housing market. However, challenges arise due to exclusionary practices, undermining the program’s goal of ‘choice.’ Tenant screening practices have been critical in exacerbating these challenges, yet their impact remains understudied. Drawing on tenant screening criteria documents from property management websites and the Survey of Consumer Finances, this study finds that while voucher holders generally meet rent-to-income thresholds due to the subsidies—keeping their rent burden relative to their income, they still face barriers related to credit scores, bankruptcy history, and debt. These criteria, which apply to both voucher and non-voucher renters, may exclude approximately one in ten voucher holders, despite the guaranteed portion of rent covered by public assistance. These findings show an urgent need for policy interventions to the potential exclusionary impacts of tenant screening services.

Three-Dimensional Full-Core BEAVRS Using OpenMOC with Transport Equivalence

Fri, 04 Apr 2025 00:00:00 GMT

Three-Dimensional Full-Core BEAVRS Using OpenMOC with Transport Equivalence Giudicelli, G; Forget, B; Smith, K Using an optimized implementation of the three-dimensional (3D) method of characteristics for neutron transport, along with a novel equivalence method for transport calculations that was designed to correct self-shielding errors from neglecting the angular dependence of resonant group absorption, a 3D full-core light water reactor hybrid stochastic-deterministic eigenvalue calculation was achieved. This paper presents the optimizations developed and compares the transport solutions obtained. For the statepoint, run times near 10 000 CPU hours are achieved—improving on previous works by an order of magnitude—with near 1% error on pin fission to 238U capture ratios and a few dozen pcms on the eigenvalue.

Considering a US-Supported Self-Defense Option for Taiwan

Thu, 02 Jan 2025 00:00:00 GMT

Considering a US-Supported Self-Defense Option for Taiwan Glaser, Charles L. There is wide agreement that Taiwan is the most dangerous issue dividing the United States and China. China believes Taiwan is part of its homeland, views unification with Taiwan as a core interest, and is determined to gain full control of the island. China continues to prefer peaceful unification, but explicitly retains the option of using military forces to achieve unification and seeks to use the threat of military force to strengthen its negotiating hand. Current US policy includes an ambiguous commitment to defend Taiwan if attacked or severely coerced by China—it leaves open whether and how the United States would respond. In addition, the United States provides Taiwan with weapons to improve its ability to defend itself. The United States is pressing Taiwan to deploy smaller mobile weapons that would increase the survivability and lethality of its forces; these forces would support a “porcupine strategy” that makes Taiwan harder to invade and conquer and would, at a minimum, provide time for US forces to arrive to aid Taiwan’s defense.

Needs, Wants . . . and Excuses: What Executives Can Learn from Zig Ziglar About Working with Universities

Wed, 09 Apr 2025 00:00:00 GMT

Needs, Wants . . . and Excuses: What Executives Can Learn from Zig Ziglar About Working with Universities Wright, Randall S. Zig Ziglar was a famous sales trainer, motivational speaker, and author on salesmanship. When he died on November 28, 2012, Kevin Kruse (Citation2024)—best-selling author of Emotional Intelligence: 52 Strategies, coach to Fortune 500 CEOs, Marine Corps generals, and Silicon Valley entrepreneurs—wrote this in Forbes: “Zig Ziglar died today at age 86. A World War II veteran, Zig Ziglar became the top salesperson in several organizations before striking out on his own as a motivational speaker and trainer. With a Southern charm and lessons grounded in Christianity, Ziglar wrote over two dozen books and amassed a following of millions who were encouraged by his lessons for success.”

Computational studies of electric field effects in CO2 methanation on Ni metal surfaces

Thu, 14 Mar 2024 00:00:00 GMT

Computational studies of electric field effects in CO2 methanation on Ni metal surfaces Wakamatsu, Katsuhiro; Yasuda, Takaaki; Aratani, Masato; Ogura, Teppei Non-Faradaic electrochemical modification of catalytic activity (NEMCA) with an electric field (EF) has attracted attention as one of the methods to improve catalyst performance. However, this activation mechanism is not still clear. In this study, we focused on the NEMCA mechanism in CO2 methanation on Ni metal catalyst with solid oxide electrolysis cell (SOEC) and calculated two possible effects of the NEMCA mechanism; direct EF applications and oxygen atom co-adsorptions, using the density functional theory calculations and detailed kinetic simulations. Compared with these effects in terms of kinetic energy changes in the rate-determining steps, it has been revealed that the spillover effect of lattice oxygen toward the catalyst surface is dominant in the NEMCA mechanism. Also, we have found that overall CO2 methanation is promoted in SOEC mode with oxygen atom co-adsorptions in both cases of Ni flat and step sites.

Equilibrium configurations of line arrays with respect to the deviatoric mean drift forces

Thu, 02 May 2024 00:00:00 GMT

Equilibrium configurations of line arrays with respect to the deviatoric mean drift forces Tokić, Grgur; Yue, Dick KP Monochromatic waves incident on an array of structures give rise to nonlinear, time-constant mean drift forces (MDFs). These forces depend on the array's spatial configuration; their magnitude and the direction is, in general, different for every structure in the array. If the spatial configuration of an array is not fixed, as is the case in arrays of individually anchor-moored structures, the time-constant differences in MDF on individual bodies can lead to a change in spatial configuration, which could, in turn, significantly affect both the first-order, time-harmonic response of the array, as well as the downwave component of the MDF. Here, we explore the dependency of these deviatoric forces on array configurations and on the frequency of the incident monochromatic waves. We consider configurations of line arrays (consisting of 2–5 vertical circular cylinders) that are described by 1 or 2 parameters, and we focus on the along-array component of deviatoric forces. Using multiple scattering computational simulations, we identify the array configurations in which the deviatoric drift forces are zero, and we discuss the stability of these equilibrium configurations with respect to class-preserving configuration perturbations. Both stable and unstable equilibria exist, but the relative number of unstable equilibria grows as the number of degrees of freedom of the configuration perturbations increases. Interestingly, the stable configurations experience a generally lower downwave mean drift force on the entire array than the unstable ones. Overall, the variations in the deviatoric and the downwave MDFs between equilibria are significant (on the order of the isolated body MDF).

1000-MW CSP with 100-gigawatt-hour crushed-rock heat storage to replace dispatchable fossil-fuel electricity

Fri, 06 Oct 2023 00:00:00 GMT

1000-MW CSP with 100-gigawatt-hour crushed-rock heat storage to replace dispatchable fossil-fuel electricity Forsberg, Charles We are developing 100-GWh heat-storage systems for use with 1000-MW Concentrated Solar Power (CSP) and nuclear reactor systems with capital cost goals of several dollars per kWh of heat storage—a factor of 50 under lithium ion batteries per unit of electricity. The capabilities of a 100-GWh heat storage system are similar to the Tennessee Valley Authority Raccoon Mountain pumped hydro facility that can provide 1652 MW(e) for 22 hours to address daily to weekly storage. The low capital cost of the Crushed Rock Ultra-large Stored Heat (CRUSH) system is only possible in large-capacity systems; thus, the CSP system average 24/7 heat inputs may exceed 1000 MW to match the heat storage capacity. Hot oil or nitrate salt is pumped from multiple solar farms or towers to the central CRUSH system and associated power block. The peak power block output may be 2 to 4 times average output with large economics of scale relative to the smaller power blocks associated with existing CSP systems. The cost savings from the large storage and the power block exceed the cost of hot oil or hot nitrate salt insulated pipelines over 10+ kilometers. The heat is stored in crushed rock in piles 20 m high and up to 250 m by 250 m on a side within an insulated floor and building structure. The sides of the rock pile are sloped rock that allow rock expansion and contraction with temperature without generating mechanical forces against walls. Heat is transferred from CSP to the crushed rock and then to the power cycle using (1) heat transfer oils for lower-temperature power systems to 400°C or (2) nitrate salts for higher-temperature power systems to 600°C. In charging mode, hot heat transfer fluid is sprayed over crushed rock and drains through the rock to the collection pans at the bottom to be reheated. Sections of rock are heated sequentially. In discharge mode cold heat transfer fluid is sprayed over crushed rock and drains through the rock to the collection pans below to deliver hot fluid to the power cycle. Heat storage costs are minimized by three features. Crushed rock is the lowest-cost storage material. The large building size minimizes the surface-to-volume ratio and thus building, insulation and foundation costs. The inventory and thus cost of oil and nitrate salt is minimized by using these fluids to transfer heat from CSP collectors to storage and then to the power block—but not for heat storage.

The way forward: The path to monolithic additive manufacture of lower hybrid current drive launchers

Fri, 18 Aug 2023 00:00:00 GMT

The way forward: The path to monolithic additive manufacture of lower hybrid current drive launchers Seltzman, AH; Wukitch, SJ Additive Manufacturing (AM) is a key enabling technology for the rapid production of complex radio-frequency (RF) structures used in lower hybrid current drive (LHCD) launchers. Glenn Research Copper 84 (GRCop-84), a Niobium Chromide (Cr2Nb) 8 at. % Cr, 4 at. % Nb precipitation hardened alloy, is suitable for AM with Laser Powder Bed Fusion (L-PBF), achieving 99.5% density, Ra=3-4 µm surface roughness, yield strength of 470 MPa and an ultimate tensile strength (UTS) of 710 MPa in as-printed condition. AM of a high field side (HFS) lower LHCD launcher from GRCop-84 alloy demonstrated several critical advancements in AM of RF launchers. Waveguides with a pentagonal cross-section were designed to support the top internal waveguide surface with 45-degree chamfers from the sidewall, eliminating collapse of the ceiling, while maintaining RF properties near identical to a rectangular cross section. Hot Isostatic Pressing (HIPing) consolidated residual voids within the material, increasing density from 99.5% to 100%. Chemical-Mechanical Polishing (CMP) reduced residual surface roughness from the L-PBF process to Ra=0.1 µm / Rq=0.4 µm to lower RF losses. Advancements in L-PBF for the AM of copper alloys have increased the maximum build volume from 250x250x300mm on the Concept Laser M2 printer to 400x400x400mm on the EOS M400 printer. This increased build volume now enables monolithic AM of complete LHCD launchers with integrated cooling channels that eliminate the time-consuming laser welding assembly of launcher segments previously required by the smaller build volume.

Particle-in-cell simulations of parasitic electrostatic wave excitation in the ion cyclotron range of frequencies and high harmonic fast wave regimes

Fri, 18 Aug 2023 00:00:00 GMT

Particle-in-cell simulations of parasitic electrostatic wave excitation in the ion cyclotron range of frequencies and high harmonic fast wave regimes Diab, Raymond; Baek, Seung-Gyou; Bonoli, Paul; Jenkins, Thomas G; Ono, Masayuki; Smithe, David Using the open-source code SMILEI [J. Derouillat et al., Comput. Phys. Commun. 222, 351-373 (2018)], we perform one-dimensional full-f particle-in-cell (PIC) simulations of parasitic electrostatic wave excitation in the Ion Cyclotron Range of Frequencies (ICRF) and High Harmonic Fast Wave (HHFW) regimes in an inhomogeneous plasma. We first study direct coupling from the fast wave to electrostatic waves at the lower hybrid (LH) resonance (S=0). In the ICRF regime, we show that the fast wave can couple to the Ion Bernstein Wave (IBW), which propagates beyond the LH resonance layer. On the other hand, in the HHFW regime, no direct coupling to the IBW is observed, but electrostatic waves, likely to be Hot Ion Plasma Waves (HIPW or HPW), are seen on the low-density side of the LH resonance layer. The coupling efficiency to electrostatic waves is seen to increase with ion temperature. Parametric decay instabilities (PDIs) are then investigated in both regimes. In the ICRF regime, both resonant and non-resonant decay channels are observed and compared with theory. In the HHFW regime, we observe multiple sidebands separated by the ion cyclotron frequency, as measured experimentally on NSTX [J. R. Wilson et al., AIP Conf. Proc. 787, 66 (2005)]. The nature of these waves is discussed. Perpendicular ion heating is also found in the region where PDIs occur, consistent with experimental observations.

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Fri, 18 Aug 2023 00:00:00 GMT

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models Wallace, GM; Bai, Z; Bertelli, N; Bethel, EW; Perciano, T; Shiraiwa, S; Wright, JC Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (ne0, Te0, Ip, Bt, R0, n∥︀, Ze f f, Vloop, PLHCD) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. The πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

Decrypting the mechanisms of wicking and evaporation heat transfer on micro-pillars during the pool boiling of water using high-resolution infrared thermometry

Wed, 08 Mar 2023 00:00:00 GMT

Decrypting the mechanisms of wicking and evaporation heat transfer on micro-pillars during the pool boiling of water using high-resolution infrared thermometry Wang, Chi; Rahman, Md Mahamudur; Bucci, Matteo Surfaces with micrometer-scale pillars have shown great potential in delaying the boiling crisis and enhancing the critical heat flux (CHF). However, physical mechanisms enabling this enhancement remain unclear. This knowledge gap is due to a lack of diagnostics that allow elucidating how micro-pillars affect thermal transport phenomena on the engineered surface. In this study, for the first time, we are able to measure time-dependent temperature and heat flux distributions on a boiling surface with engineered micro-pillars using infrared thermometry. Using these data, we reveal the presence of an intra-pillar liquid layer, created by the nucleation of bubbles and partially refilled by capillary effects. However, contrarily to conventional wisdom, the energy removed by the evaporation of this liquid cannot explain the observed CHF enhancement. Yet, predicting its dry out is the key to delaying the boiling crisis. We achieve this goal using simple analytic models and demonstrate that this process is driven by conduction effects in the boiling substrates and, importantly, in the intra-pillar liquid layer itself. Importantly, these effects also control the wicking flow rate and its penetration length. The boiling crisis occurs when, by coalescing, the size of the intra-pillar liquid layer becomes too large for the wicking flow to reach its innermost region. Our study reveals and quantifies unidentified physical aspects, key to the performance optimization of boiling surfaces for cooling applications.

Regulating Wait-Driven Requests in Queues

Wed, 02 Jul 2025 00:00:00 GMT

Regulating Wait-Driven Requests in Queues Freund, Daniel; Hausman, David; Weng, Wentao The study of rational queueing has a long and distinguished history focused on individuals' preference to avoid waiting. Surprisingly, there are settings in which some potential arrivals (which we also refer to as requests) derive utility from waiting and disutility from service. Our primary example is the U.S. affirmative asylum process. In this context, applicants obtain a work permit while waiting for an asylum interview; hence, if the (expected) wait is long enough, then even an applicant who knows that their application will be denied and lead to deportation proceedings, may find it in their interest to apply and thus benefit from legally working during the wait. Similar dynamics could occur in other settings like content moderation in social networks. The common thread of these examples is the potentially self-exciting queue: when wait times are long, many arrivals are incentivized to join, and wait times become even longer. However, the system designer usually wants to avoid a large backlog. Indeed, the US Citizenship and Immigration Services (USCIS) mostly schedules asylum interviews in a Last-In-First-Out (LIFO) manner with the explicit goal of dissuading applicants with non-meritorious cases trying to exploit the long backlog. Despite this interesting scheduling choice in practice, and the potential prevalence of similar settings in other applications, the existing literature on rational queueing lacks frameworks to study the impact of wait-driven requests. Motivated by this gap in the literature, we formalize a dynamical system where in each round, a given scheduling policy and a realized request rate determine the wait time distribution in a fluid queueing system. Observing the expected benefit from waiting in one round, requests update their decisions, setting the request rate for the next round. Assuming a concave benefit function from waiting, alongside general conditions, we prove that, for minimizing the backlog, LIFO is most effective while First-In-First-Out (FIFO) is least effective among all work-conserving policies. Moreover, we show that the dynamical system exhibits metastability: for either FIFO or LIFO, the system converges to either a zero-wait or a congested equilibrium. Although some asylum practitioners support the use of LIFO, critics often admonish the real-world use of LIFO for its failure to maintain FIFO's order fairness: earlier requests should get earlier service. Our results demonstrate this trade-off between LIFO and FIFO. But we also show limitations of hybrid policies, which probabilistically follow either LIFO or FIFO, in navigating the trade-off between LIFO's efficiency and FIFO's fairness. Our work formalizes the concept of order fairness in queueing systems with abandonment and demonstrates that hybrid policies can be Pareto-dominated by LIFO: they may have both longer backlog and worse order fairness. Finally, we use real-world data on the scheduling of affirmative asylum applications to evaluate the change in fairness over the past 20 years under different policies. EC ’25, July 7–10, 2025, Stanford, CA, USA

DeepSeek Inside: Origins, Technology, and Impact

Wed, 18 Jun 2025 00:00:00 GMT

DeepSeek Inside: Origins, Technology, and Impact Cusumano, Michael The release of DeepSeek V3 and R1 in January 2025 caused steep declines in the stock prices of companies that provide generative artificial intelligence (GenAI) infrastructure technology and datacenter services. These two large language models (LLMs) came from a little-known Chinese startup with approximately 200 employees compared to at least 3,500 employees for industry-leader OpenAI. DeepSeek seemed to have developed this powerful technology much more cheaply than previously thought possible. If true, DeepSeek had the potential to disrupt the economics of the entire GenAI ecosystem and the dominance of U.S. companies ranging from OpenAI to Nvidia.

Density-Dependent Graph Orientation and Coloring in Scalable MPC

Fri, 13 Jun 2025 00:00:00 GMT

Density-Dependent Graph Orientation and Coloring in Scalable MPC Ghaffari, Mohsen; Grunau, Christoph This paper presents massively parallel computation (MPC) algorithms in the strongly sublinear memory regime (aka, scalable MPC) for orienting and coloring graphs as a function of its subgraph density. Our algorithms run in poly(log log n) rounds and compute an orientation of the edges with maximum outdegree O (α log log n) as well as a coloring of the vertices with O (α log log n) colors. Here, α denotes the density of the densest subgraph. Our algorithm's round complexity is notable because it breaks the [EQUATION] barrier, which applied to the previously best known density-dependent orientation algorithm [Ghaffari, Lattanzi, and Mitrovic ICML'19] and is common to many other scalable MPC algorithms. PODC ’25, Huatulco, Mexico

Privacy-Preserving Mechanisms for Coordinating Airspace Usage in Advanced Air Mobility

Mon, 30 Jun 2025 00:00:00 GMT

Privacy-Preserving Mechanisms for Coordinating Airspace Usage in Advanced Air Mobility Maheshwari, Chinmay; Mendoza, Maria; Tuck, Victoria; Su, Pan-Yang; Qin, Victor; Seshia, Sanjit; Balakrishnan, Hamsa; Sastry, Shankar Advanced Air Mobility (AAM) operations are expected to transform air transportation while challenging current air traffic management practices. By introducing a novel market-based mechanism, we address the problem of on-demand allocation of capacity-constrained airspace to AAM vehicles with heterogeneous and private valuations. We model airspace and air infrastructure as a collection of contiguous regions (or sectors) with constraints on the number of vehicles that simultaneously enter, stay, or exit each region. Vehicles request access to airspace with trajectories spanning multiple regions at different times. We use the graph structure of our airspace model to formulate the allocation problem as a path allocation problem on a time-extended graph. To ensure that the cost information of AAM vehicles remains private, we introduce a novel mechanism that allocates each vehicle a budget of "air-credits" (an artificial currency) and anonymously charges prices for traversing the edges of the time-extended graph. We seek to compute a competitive equilibrium that ensures that: (i) capacity constraints are satisfied, (ii) a strictly positive resource price implies that the sector capacity is fully utilized, and (iii) the allocation is integral and optimal for each AAM vehicle given current prices, without requiring access to individual vehicle utilities. However, a competitive equilibrium with integral allocations may not always exist. We provide sufficient conditions for the existence and computation of a fractional-competitive equilibrium, where allocations can be fractional. Building on these theoretical insights, we propose a distributed, iterative, two-step algorithm that: 1) computes a fractional competitive equilibrium, and 2) derives an integral allocation from this equilibrium. We validate the effectiveness of our approach in allocating trajectories for the emerging urban air mobility service of drone delivery.

Meschers: Geometry Processing of Impossible Objects

Sun, 27 Jul 2025 00:00:00 GMT

Meschers: Geometry Processing of Impossible Objects Dodik, Ana; Yu, Isabella; Chandra, Kartik; Ragan-Kelley, Jonathan; Tenenbaum, Joshua; Sitzmann, Vincent; Solomon, Justin Impossible objects, geometric constructions that humans can perceive but that cannot exist in real life, have been a topic of intrigue in visual arts, perception, and graphics, yet no satisfying computer representation of such objects exists. Previous work embeds impossible objects in 3D, cutting them or twisting/bending them in the depth axis. Cutting an impossible object changes its local geometry at the cut, which can hamper downstream graphics applications, such as smoothing, while bending makes it difficult to relight the object. Both of these can invalidate geometry operations, such as distance computation. As an alternative, we introduce Meschers, meshes capable of representing impossible constructions akin to those found in M.C. Escher's woodcuts. Our representation has a theoretical foundation in discrete exterior calculus and supports the use-cases above, as we demonstrate in a number of example applications. Moreover, because we can do discrete geometry processing on our representation, we can inverse-render impossible objects. We also compare our representation to cut and bend representations of impossible objects.

Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints

Mon, 09 Jun 2025 00:00:00 GMT

Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints Lechowicz, Adam; Christianson, Nicolas; Sun, Bo; Bashir, Noman; Hajiesmaili, Mohammad; Wierman, Adam; Shenoy, Prashant We introduce and study spatiotemporal online allocation with deadline constraints (SOAD), a new online problem motivated by emerging challenges in sustainability and energy. In SOAD, an online player completes a workload by allocating and scheduling it on the points of a metric space (X, d) while subject to a deadline T. At each time step, a service cost function is revealed that represents the cost of servicing the workload at each point, and the player must irrevocably decide the current allocation of work to points. Whenever the player moves this allocation, they incur a movement cost defined by the distance metric d(•, •) that captures, e.g., an overhead cost. SOAD formalizes the open problem of combining general metrics and deadline constraints in the online algorithms literature, unifying problems such as metrical task systems and online search. We propose a competitive algorithm for SOAD along with a matching lower bound establishing its optimality. Our main algorithm, ST-CLIP, is a learning-augmented algorithm that takes advantage of predictions (e.g., forecasts of relevant costs) and achieves an optimal consistency-robustness trade-off. We evaluate our proposed algorithms in a simulated case study of carbon-aware spatiotemporal workload management, an application in sustainable computing that schedules a delay-tolerant batch compute job on a distributed network of data centers. In these experiments, we show that ST-CLIP substantially improves on heuristic baseline methods. SIGMETRICS Abstracts ’25, Stony Brook, NY, USA

Faraday Cage Estimation of Normals for Point Clouds and Ribbon Sketches

Fri, 25 Jul 2025 00:00:00 GMT

Faraday Cage Estimation of Normals for Point Clouds and Ribbon Sketches Scrivener, Daniel; Cui, Daniel; Coldren, Ellis; Abulnaga, Mazdak; Bessmeltsev, Mikhail; Chien, Edward We propose a novel method (FaCE) for normal estimation of unoriented point clouds and VR ribbon sketches that leverages a modeling of the Faraday cage effect. Input points, or a sampling of the ribbons, form a conductive cage and shield the interior from external fields. The gradient of the maximum field strength over external field scenarios is used to estimate a normal at each input point or ribbon. The electrostatic effect is modeled with a simple Poisson system, accommodating intuitive user-driven sculpting via the specification of point charges and Faraday cage points. On inputs sampled from clean, watertight meshes, our method achieves comparable normal quality to existing methods tailored for this scenario. On inputs containing interior structures and artifacts, our method produces superior surfacing output when combined with Poisson Surface Reconstruction. In the case of ribbon sketches, our method accommodates sparser ribbon input while maintaining an accurate geometry, allowing for greater flexibility in the artistic process. We demonstrate superior performance to an existing approach for surfacing ribbon sketches in this sparse setting.

Networking Systems for Video Anomaly Detection: A Tutorial and Survey

Wed, 07 May 2025 00:00:00 GMT

Networking Systems for Video Anomaly Detection: A Tutorial and Survey Liu, Jing; Liu, Yang; Lin, Jieyu; Li, Jielin; Cao, Liang; Sun, Peng; Hu, Bo; Song, Liang; Boukerche, Azzedine; Leung, Victor The increasing utilization of surveillance cameras in smart cities, coupled with the surge of online video applications, has heightened concerns regarding public security and privacy protection, which propelled automated Video Anomaly Detection (VAD) into a fundamental research task within the Artificial Intelligence (AI) community. With the advancements in deep learning and edge computing, VAD has made significant progress and advances synergized with emerging applications in smart cities and video internet, which has moved beyond the conventional research scope of algorithm engineering to deployable Networking Systems for VAD (NSVAD), a practical hotspot for intersection exploration in the AI, IoVT, and computing fields. In this article, we delineate the foundational assumptions, learning frameworks, and applicable scenarios of various deep learning-driven VAD routes, offering an exhaustive tutorial for novices in NSVAD. In addition, this article elucidates core concepts by reviewing recent advances and typical solutions and aggregating available research resources accessible at https://github.com/fdjingliu/NSVAD. Lastly, this article projects future development trends and discusses how the integration of AI and computing technologies can address existing research challenges and promote open opportunities, serving as an insightful guide for prospective researchers and engineers.

Analysis and Performance Evaluation of Blockchain Consensus Mechanisms for Network Sharing

Tue, 27 Jan 2026 00:00:00 GMT

Analysis and Performance Evaluation of Blockchain Consensus Mechanisms for Network Sharing Zeydan, Engin; MANGUES-BAFALLUY, JOSEP; Arslan, Suayb; Turk, Yekta; Antevski, Kiril The growing demand for mobile data services has made it necessary to find efficient and cost-effective ways to share networks. Blockchain technology is a promising solution to the challenges of network sharing, such as interoperability, trust, and accountability. This paper presents a comprehensive classification and categorization of blockchain-based network sharing scenarios, highlighting their advantages and limitations. Seven network sharing scenarios are identified, ranging from centralized network sharing to fully decentralized spectrum sharing. The suitability of some selected blockchain consensus algorithms (namely Proof-of-Work (PoW) with Ethereum, Proof-of-Authority (PoA) with Ethereum, Practical Byzantine Fault Tolerance (PBFT) with Tendermint and Proof-of-Stake (PoS) with Cosmo) is assessed for selected scenarios through extensive evaluations. This paper also identifies gaps and opportunities in blockchain-based network sharing solutions, and presents future research directions.

MapTune: Versatile ASIC Technology Mapping via Reinforcement Learning Guided Library Tuning

Fri, 11 Jul 2025 00:00:00 GMT

MapTune: Versatile ASIC Technology Mapping via Reinforcement Learning Guided Library Tuning Liu, Mingju; Robinson, Daniel; Li, Yingjie; Maximilian Kuehn, Johannes; Liang, Rongjian; Ren, Haoxing; Yu, Cunxi Technology mapping involves mapping logical circuits to a library of cells. Traditionally, the full technology library is used, leading to a large search space and potential overhead. Motivated by randomly sampled technology mapping case studies, we propose a MapTune framework that addresses this challenge by utilizing reinforcement learning to make design-specific choices during cell selection. By learning from the environment, MapTune refines the cell selection process, resulting in a reduced search space and potentially improved mapping quality. The effectiveness of MapTune is evaluated on a wide range of benchmarks, different technology libraries, and various technology mappers. The experimental results demonstrate that MapTune achieves higher mapping accuracy and reduces delay/area across diverse circuit designs, technology libraries, and mappers. The paper also discusses the Pareto-Optimal exploration and confirms the perpetual delay-area trade-off. Conducted on benchmark suites ISCAS 85/89, ITC/ISCAS 99, VTR8.0, and EPFL benchmarks, the post-technology mapping and post-sizing quality-of-results (QoR) have been significantly improved, with average Area-Delay Product (ADP) improvement of 16.56\% among all different exploration settings in MapTune. The improvements consistently remained for four different technologies (7nm, 45nm, 130nm, and 180 nm) with various mappers from both state-of-the-art open-source and commercial synthesis tools.

A Two-Stage Approach to Improve Poverty Mapping Spatial Resolution

Wed, 28 Jan 2026 00:00:00 GMT

A Two-Stage Approach to Improve Poverty Mapping Spatial Resolution Salas, Joaquín; Zea-Ortiz, Marivel; Vera, Pablo; Wood, Danielle Global extreme poverty has fallen dramatically over the past two centuries, yet hundreds of millions remain impoverished, underscoring the need for scalable monitoring tools. In Mexico, poverty metrics are available only sporadically in terms of time and space (e.g., every 5 years at the municipal level), making it difficult for decision-makers to access reliable, up-to-date, and sufficiently detailed information, highlighting the need for higher-resolution, timely methods. To address this problem, we propose a two-stage approach that combines socioeconomic and Earth Observations-based data. Initially, a machine learning model maps census variables to official poverty indicators belonging to a multidimensional model, yielding fine-scale poverty estimates. A census-based model trained with eXtreme Gradient Boosting (XGBoost) achieved a determination coefficient (𝑅2) of approximately 0.842, indicating strong agreement with official poverty figures and providing high-resolution proxies. Afterward, we use features based on remote observations to predict these poverty estimates at a 469 m grid scale. In this case, advanced foundation models outperformed other machine learning (ML) approaches, achieving an 𝑅2 of 0.683. While foundation models enable more accurate, fine-scale poverty mapping and could accelerate poverty assessments, their use comes at a heavy price in terms of carbon emissions.

Effectiveness of a Participatory Voice Intervention on Psychological Well-Being Among Warehouse Workers: Results From the Fulfillment Center Intervention Study, United States, 2021‒2023

Thu, 15 Jan 2026 00:00:00 GMT

Effectiveness of a Participatory Voice Intervention on Psychological Well-Being Among Warehouse Workers: Results From the Fulfillment Center Intervention Study, United States, 2021‒2023 Siebach, Kirsten F.; Diaz-Linhart, Yaminette; Kubzansky, Laura D.; Berkman, Lisa F.; Wang, Molin; Ge, Lin; Kowalski, Alexander M.; Rahmandad, Hazhir; Kelly, Erin L. Objectives. To examine whether a novel workplace intervention designed to increase worker voice can reduce psychological distress and improve emotional vitality at 6- and 12-months follow-up. Methods. We conducted a cluster-randomized trial in 16 fulfillment centers throughout the United States between 2021-2023. Data were collected at three time points; 2813 workers participated in at least one survey. Treated fulfillment centers established a new, participatory committee called the Health and Well-Being Committee (HaWC). We compared differences in psychological distress and emotional vitality and explored differential treatment effects by gender. Results. At baseline, moderate or severe psychological distress was 51%. Intervention sites had lower average psychological distress at the 6-month follow-up compared to control sites, with no significant differences at 12-month follow-up. Gender moderation analyses suggest the HaWC was particularly effective in reducing psychological distress among men at 6-month follow-up. Conclusions. Our findings suggest that opportunities for workers to share concerns to a committee of their peers tasked with identifying solutions can support mental health. Our study contributes important experimental evidence on workplace interventions that improve the well-being of low-wage U.S. populations.

Quantum information science and underground facilities

Tue, 05 Sep 2023 00:00:00 GMT

Quantum information science and underground facilities Formaggio, Joseph A As both nuclear physics and particle physics involve the quantum interactions of many sub-atomic particles, there has always existed a strong interplay between these fields and the study of quantum physics and quantum information systems (QIS). This interplay has accelerated in recent years, particularly with the emergence of new, highly sensitive technologies, nascent access to quantum computing environments at the O(10)-O(100)-bit scale, and the use of coherence and entanglement to enhance sensitivity to novel and exotic phenomena. One unusual area of interplay between the two disciplines that has recently emerged is the role of background radiation and background mitigation on highly sensitive systems such as qubits.

Reduced-order model to predict thermal conductivity of dimensionally confined materials

Tue, 27 Jun 2023 00:00:00 GMT

Reduced-order model to predict thermal conductivity of dimensionally confined materials Hosseini, S Aria; Greaney, Alex; Romano, Giuseppe Predicting nanoscale thermal transport in dielectrics requires models, such as the Boltzmann transport equation (BTE), that account for phonon boundary scattering in structures with complex geometries. Although the BTE has been validated against several key experiments, its computational expense limits its applicability. Here, we demonstrate the use of an analytic reduced-order model for predicting the thermal conductivity in dimensionally confined materials, i.e., monolithic and porous thin films, and rectangular and cylindrical nanowires. The approach uses the recently developed “Ballistic Correction Model,” which accounts for materials' full distribution of phonon mean-free-paths. The model is validated against BTE simulations for a selection of base materials, obtaining excellent agreement. By furnishing a precise yet easy-to-use prediction of thermal transport in nanostructures, our work strives to accelerate the identification of materials for energy-conversion and thermal-management applications.

Parametric decay instabilities driven by high power helicon waves in DIII-D

Fri, 18 Aug 2023 00:00:00 GMT

Parametric decay instabilities driven by high power helicon waves in DIII-D Porkolab, M; Pinsker, RI; DeGrandchamp, GH; Baek, SG; Compernolle, B Van; Denk, S; Petty, CC; Tang, SX; Thome, KE High power helicon waves (whistler or very high harmonic fast lower hybrid waves) at a frequency of 476 MHz are being tested for efficient off-axis current drive on DIII-D with the goal of demonstrating profile control in AT plasmas [1-4]. In agreement with earlier theoretical predictions, strong Parametric Decay Instability (PDI) has been observed at injected RF power levels in the range of 0.05-0.5 MW with corresponding electric fields of 10-30 kV/m [5,6]. The dominant driver of the PDI is the E×B and the polarization drift velocity which can drive ion cyclotron quasi-modes and lower hybrid (or IBW) sideband waves unstable [5,6]. Initial experimental results have been obtained with powers up to 0.3 MW showing evidence of strong PDI measured with high-frequency one-turn magnetic probes located at both the outboard and the inboard wall at frequencies set by the usual selection rules [7,8]. Here we review the appropriate analytic formulation to predict such instabilities and present numerical evaluation of frequencies and growth rates relevant to DIII-D plasma parameters. We also assess the convective thresholds for the PDIs, and compared them with experimental observations.

Experimental footprints of a water-rich depletion layer in the Herschel–Bulkley pipe flow of solidifying polyelectrolytes

Fri, 27 Jan 2023 00:00:00 GMT

Experimental footprints of a water-rich depletion layer in the Herschel–Bulkley pipe flow of solidifying polyelectrolytes Nazari, B.; Moghimi, E.; Bousfield, D. W. A fundamental understanding of the transition from fluid-like to gel-like behavior is critical for a range of applications including personal care, pharmaceuticals, food products, batteries, painting, biomaterials, and concrete. The pipe flow behavior of a Herschel–Bulkley fluid is examined by a combination of rheology, ultrasound imaging velocimetry, and pressure measurements together with modeling. The system is a solution of 0.50 wt. % polyelectrolytes of sulfated polysaccharides in water that solidifies on cooling. Fluids with different ionic strengths were pumped at various rates from a reservoir at 80 °C into a pipe submerged in a bath maintained at 20 °C. The fluid velocity, pressure drop ΔP, and temperature were monitored. The same quantities were extracted by solving continuity, energy, and momentum equations. Moreover, the modeling results demonstrate that the local pressure gradient along the pipe dPdx|x is related to the local yield stress near the pipe wall τywall|x, which explains the variations of dPdx|x along the pipe. Experimental results show much lower values for ΔP compared to those from modeling. This discrepancy is exacerbated at higher ionic strengths and smaller flow rates, where fluid shows a higher degree of solidification. The tabulated experimental ΔP data against the solidification onset length Lonset (where the fluid is cool enough to solidify) along with the ultrasound imaging velocimetry associate these discrepancies between experiments and models to a depletion layer of ∼1 μm, reflecting the lubrication effects caused by the water layer at the wall.

Radiation pressure of radio frequency waves on turbulence in edge plasmas

Fri, 18 Aug 2023 00:00:00 GMT

Radiation pressure of radio frequency waves on turbulence in edge plasmas Ram, Abhay K; Hizanidis, Kyriakos The scattering of radio frequency (RF) waves – lower hybrid and helicon waves – by a single cylindrical filament, embedded in a background plasma, is studied using a full-wave analytical theory. While a filament can affect the propagation of RF waves, the radiation force exerted by the waves can influence the filament. The force on a filament is determined using the Maxwell stress tensor. The radiation force can either pull the filament towards the RF source or push it away. The radiation force, in the two frequency ranges, is large enough to impact the motion of a filament and could be measured experimentally. Consequently, it may be possible to modify the edge turbulence using RF waves.

Replies to Moran, Gallois, and Bar-On and Johnson

Sun, 04 Jan 2026 00:00:00 GMT

Replies to Moran, Gallois, and Bar-On and Johnson Byrne, Alex I am very grateful to Dorit Bar-On, Drew Johnson, André Gallois, and Dick Moran for their thoughtful commentaries. Bar-On, Gallois, and Moran are discussed extensively in Transparency and Self-Knowledge (hereafter T&SK), and their work has been an important source of inspiration for my own. In order to make my contribution to this symposium reasonably compact, I have not attempted to reply to every single point. (One especially notable omission is the alternative account of self-knowledge sketched by Bar-On and Johnson.) Instead, I have concentrated on the main objections.

The end of MAD? Technological innovation and the future of nuclear retaliatory capabilities

Thu, 30 Jan 2025 00:00:00 GMT

The end of MAD? Technological innovation and the future of nuclear retaliatory capabilities Glaser, Charles L. This article motivates the special issue, explaining the new debate over whether emerging technologies – including small satellites, machine learning, cyber weapons, and quantum technologies – will enable major powers to undermine each others’ nuclear retaliatory capabilities. The first article analyzes key relevant emerging technologies. Following articles explore how emerging technologies will influence the vulnerability of mobile missiles, ballistic missile submarines, and nuclear command-and-control; and the ability of missile defenses against intercontinental range missiles. The final article explores China’s views on the requirements of nuclear deterrence. Overall, the articles suggest that U.S. prospects for achieving a damage-limitation capability are poor and declining.

Prototyping longevity services: Tech-driven or human-assisted service?

Sun, 04 May 2025 00:00:00 GMT

Prototyping longevity services: Tech-driven or human-assisted service? Lee, Sheng-Hung; Coughlin, Joseph F; Yang, Maria The study investigates the design of longevity services through an experimental comparison of tech-driven and human-assisted service encounters, focusing on six key features: learnability, efficiency, safety, trustworthiness, confidence, and satisfaction. The controlled experiment, which involved 12 gender-balanced participants from Boston, USA, employed four qualitative methods, including surveys, the Think-aloud technique, semi-structured interviews, and transcript analysis supported by computer-assisted qualitative data analysis software (CAQDAS) and its AI-empowered coding function. The study concluded with two insights: 1. Tech-driven services can improve safety, trust, confidence, and satisfaction; and 2. both service encounters are context-sensitive, shaped by participants’ demographics, personality, culture, and environmental factors. Although the small sample size limits the study’s generalizability, the participants’ stories and perceptions offered valuable insights into their implicit needs and subtle behaviors in learning, experiencing, and addressing sensitive, private, and vulnerable topics related to longevity planning.

The Iraq Petroleum Company’s Infrastructure of “Desert Control” during the British Mandate in the Middle East

Sun, 01 Sep 2024 00:00:00 GMT

The Iraq Petroleum Company’s Infrastructure of “Desert Control” during the British Mandate in the Middle East Freeman, Margaret This article discusses the infrastructure of the Iraq Petroleum Company (IPC) in the interwar British Mandatory Middle East as belonging to a larger British imperial project for “desert control” through architecture. Britain’s so-called “desert control” was, more accurately, a programme for control over the pastoralist Bedouin tribespeople who were the primary inhabitants of the Mandatory territories’ desert zones. This article identifies the two pillars of Britain’s “desert control” strategy: the use of Bedouin police forces, and the architectural annexation and restriction of water resources from Bedouin tribes. It argues that Mandate Britain’s “desert control” programme was replicated and adapted by the IPC for its own needs to protect its commercial infrastructural investment, the Iraq–Mediterranean Pipeline, in the British Mandatory territories. It compares two building typologies, the Mandate’s “desert outposts” and the IPC pipeline’s pumping stations, as sites where the Bedouin were alternately welcomed into and excluded from imperial and commercial projects in the interest of controlling them.

Surrogate modelling of surface roughness for asphalt pavements using artificial neural networks: a mechanistic-empirical approach

Mon, 09 Dec 2024 00:00:00 GMT

Surrogate modelling of surface roughness for asphalt pavements using artificial neural networks: a mechanistic-empirical approach Li, Haoran; AzariJafari, Hessam; Kirchain, Randolph; Santos, João; Khazanovich, Lev Pavement surface smoothness (or roughness) is crucial for traffic safety, driving comfort, and fuel efficiency. As a widely applied roughness indicator, an accurate forecasting of the International Roughness Index (IRI) and its deterioration is essential for the design, maintenance, and management of asphalt pavements. Previous studies have used field measurement data or AASHTOWare Pavement ME Design simulations for the development of machine learning (ML) models to streamline the IRI modelling. However, these models frequently lack the accuracy and robustness of the measurement data or high-fidelity computational simulations they are intended to surrogate. To address this issue, we employed a new adaptive sampling technique to generate an informative yet efficient pavement damage database from Pavement ME simulations. Utilising Artificial Neural Networks (ANNs), we engineered two types of surrogate ML models: (a) Model I, an ANN-based IRI predictive model, and (b) Model II, a hybrid model combining ANN-based predictions of rutting, fatigue damage, and thermal cracking with closed-form relationships between these indicators and IRI. Our findings show that Model II outperforms Model I in IRI modelling accuracy both globally and locally. Moreover, Model II matches IRI simulations of Pavement ME while providing enhanced efficiency and adaptability to a broader spectrum of design considerations.

Honoring practices of community-based educators: lessons learned from the collaborative design of a creative mobile app

Fri, 29 Nov 2024 00:00:00 GMT

Honoring practices of community-based educators: lessons learned from the collaborative design of a creative mobile app Rusk, Natalie; Jain, Rupal; Martin, Caitlin K.; Roque, Ricarose; Freitas, João Adriano; Molaodi, Linford This paper shares reflections and stories from a collaborative design process between the Lifelong Kindergarten group at the MIT Media Lab and a global network of community-based educators to develop a creative coding app called OctoStudio, which supports children and families to create and share interactive projects on mobile devices. The app design is grounded in practices that community-based educators who are primarily from the Global South have developed around strengths, needs, and interests of children and their communities, as well as constraints and affordances of local infrastructure. We use the lens of minimal computing – which focuses on community context and constraints in decisions about technology – to describe our collaborative work on OctoStudio. We describe trade-offs involved in the design decisions, and highlight insights from the process of collaboration to develop tools and practices that are more responsive and meaningful to communities who are often excluded from design decisions that impact them.

Expected Constant Round Byzantine Broadcast under Dishonest Majority

Expected Constant Round Byzantine Broadcast under Dishonest Majority Wan, Jun; Xiao, Hanshen; Shi, Elaine; Devadas, Srinivas Byzantine Broadcast (BB) is a central question in distributed systems, and an important challenge is to understand its round complexity. Under the honest majority setting, it is long known that there exist randomized protocols that can achieve BB in expected constant rounds, regardless of the number of nodes n. However, whether we can match the expected constant round complexity in the corrupt majority setting --- or more precisely, when f > n/2 --- remains unknown, where f denotes the number of corrupt nodes. In this paper, we are the first to resolve this long-standing question. We show how to achieve BB in expected O((n/(n-f))2) rounds. Our results hold under a weakly adaptive adversary who cannot perform ``after-the-fact removal' of messages already sent by a node before it becomes corrupt. We also assume trusted setup and the Decision Linear (DLIN) assumption in bilinear groups.

Minimum Plane Bichromatic Spanning Trees

Minimum Plane Bichromatic Spanning Trees Akitaya, Hugo; Biniaz, Ahmad; Demaine, Erik; Kleist, Linda; Stock, Frederick; T?th, Csaba D. For a set of red and blue points in the plane, a minimum bichromatic spanning tree (MinBST) is a shortest spanning tree of the points such that every edge has a red and a blue endpoint. A MinBST can be computed in O(n log n) time where n is the number of points. In contrast to the standard Euclidean MST, which is always plane (noncrossing), a MinBST may have edges that cross each other. However, we prove that a MinBST is quasi-plane, that is, it does not contain three pairwise crossing edges, and we determine the maximum number of crossings. Moreover, we study the problem of finding a minimum plane bichromatic spanning tree (MinPBST) which is a shortest bichromatic spanning tree with pairwise noncrossing edges. This problem is known to be NP-hard. The previous best approximation algorithm, due to Borgelt et al. (2009), has a ratio of O(sqrt(n)). It is also known that the optimum solution can be computed in polynomial time in some special cases, for instance, when the points are in convex position, collinear, semi-collinear, or when one color class has constant size. We present an O(log n)-factor approximation algorithm for the general case.

Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time

Sat, 26 Jul 2025 00:00:00 GMT

Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time Dong, Sally; Gao, Yu; Goranci, Gramoz; Lee, Yin Tat; Sachdeva, Sushant; Peng, Richard; Ye, Guanghao We present a nearly-linear time algorithm for finding a minimum-cost flow in planar graphs with polynomially bounded integer costs and capacities. The previous fastest algorithm for this problem is based on interior point methods (IPMs) and works for general sparse graphs in O(n1.5 polylog n)) time [Daitch-Spielman, STOC'. Intuitively, ?(n1.5) is a natural runtime barrier for IPM-based methods, since they require ?n iterations, each routing a possibly-dense electrical flow. To break this barrier, we develop a new implicit representation for flows based on generalized nested dissection [Lipton-Rose-Tarjan, SINUM'79] and approximate Schur complements [Kyng-Sachdeva, FOCS'. This implicit representation permits us to design a data structure to route an electrical flow with sparse demands in roughly ?n update time, resulting in a total runtime of O(n polylog n). Our results immediately extend to all families of separable graphs.

Enhancing Electric Vehicle Security and Privacy through Decentralized Identity Management

Fri, 12 Sep 2025 00:00:00 GMT

Enhancing Electric Vehicle Security and Privacy through Decentralized Identity Management Aydeger, Abdullah; Zeydan, Engin; Mangues-Bafalluy, Josep; Arslan, Suayb; Turk, Yekta In the next decade, electric vehicles (EVs) are expected to contribute to reducing climate change and transforming road mobility significantly. However, the security and privacy of EV charging systems present considerable challenges that need to be addressed. This paper introduces a novel approach by integrating blockchain-based self-sovereign identity (SSI) to enhance the security and privacy of EV charging systems. By leveraging decentralized and immutable nature of blockchain, the proposed SSI framework can ensure secure and private data exchanges between EVs, charging stations, and backend systems. This three-way integration addresses the vulnerabilities identified in existing EV charging methods, such as conductive, inductive, and battery swapping, and complies with cybersecurity regulations like UNECE R155. This paper provides a comprehensive analysis, practical case study, and evaluation of the security and privacy enhancements achieved through the proposed SSI framework, offering valuable insights for industry professionals and researchers. We have conducted extensive end-to-end testing to evaluate the performance of our blockchain-based SSI framework in the EV charging ecosystem, focusing on identity verification, credential management and service orchestration. The results show that the system enables fast wallet creation, efficient metadata retrieval and low-latency service deployment, ensuring seamless identity management and service orchestration.

Local Distributed Rounding: Generalized to MIS, Matching, Set Cover, and Beyond

Local Distributed Rounding: Generalized to MIS, Matching, Set Cover, and Beyond Faour, Salwa; Ghaffari, Mohsen; Grunau, Christoph; Kuhn, Fabian; Rozho?, V?clav We develop a general deterministic distributed method for locally rounding fractional solutions of graph problems for which the analysis can be broken down into analyzing pairs of vertices. Roughly speaking, the method can transform fractional/probabilistic label assignments of the vertices into integral/deterministic label assignments for the vertices, while approximately preserving a potential function that is a linear combination of functions, each of which depends on at most two vertices (subject to some conditions usually satisfied in pairwise analyses). The method unifies and significantly generalizes prior work on deterministic local rounding techniques [Ghaffari, Kuhn FOCS'21; Harris FOCS'19; Fischer, Ghaffari, Kuhn FOCS'17; Fischer DISC' to obtain polylogarithmic-time deterministic distributed solutions for combinatorial graph problems. Our general rounding result enables us to locally and efficiently derandomize a range of distributed algorithms for local graph problems, including maximal independent set (MIS), maximum-weight independent set approximation, and minimum-cost set cover approximation.

Feasibility Study on Heat Pipes for Radio Frequency Antennas

Tue, 17 Feb 2026 00:00:00 GMT

Feasibility Study on Heat Pipes for Radio Frequency Antennas Jung, Minuk; Watterson, Amy; Wallace, Gregory M The applicability of a heat pipe is investigated for the cooling of radio frequency antennas in fusion reactors operating at high temperatures. A heat pipe is a passive cooling device that transfers a large amount of heat through the liquid-vapor phase change and pumps the working fluid by the surface tension of the wick structure without moving parts. As the heat pipe is expected to operate near 1000 K, refractory metals or ceramics should be used for wall materials, and liquid metals are primarily considered as the working fluid. However, liquid metals are electrically conductive, and the strong magnetic field perpendicular to the flow direction imposes significant magnetohydrodynamic (MHD) flow resistance in addition to viscous friction, which impairs heat transfer performance. Since a strong magnetic field is inevitable in magnetic confinement fusion reactors, materials with low electrical conductivity should be applied to wall coatings to reduce the MHD effect. Heat flux limitations at a magnetic field of 10 T and a condenser coolant temperature of 773 K are estimated using COMSOL multiphysics, which can capture the fully developed MHD wick flow, laminar/turbulent vapor flow, and heat transfer simultaneously. For simplicity, the generic heat pipe geometry of a straight horizontal cylinder with a length of 2 ft (0.6096 m) is employed. Optimal geometrical parameters are evaluated to meet radial evaporator/condenser heat fluxes greater than 0.1 MW/m2, even under a strong MHD effect.

Regional incidence and persistence of high-growth firms: testing ideas from the entrepreneurial ecosystems literature

Wed, 08 Jan 2025 00:00:00 GMT

Regional incidence and persistence of high-growth firms: testing ideas from the entrepreneurial ecosystems literature Coad, Alex; Domnick, Clemens; Santoleri, Pietro; Srhoj, Stjepan Policymakers and scholars often assume that a higher incidence of high-growth firms (HGFs) is synonymous with vibrant regional economic dynamics, and that HGF shares are persistent over time as entrepreneurial ecosystems (EEs) have slowly changing features. In this paper we test these hypotheses, which are deeply rooted in the EE literature. Results do not provide strong support for the hypothesis that more developed regions feature higher HGF shares. We do find evidence consistent with HGF shares displaying persistency over time. However, we show that more developed regions do not have higher persistence in their HGF shares, and that the strength in persistence does not increase across the HGFs distribution, which does not support path-dependency as the main mechanism behind the observed persistence. Overall, we call for a more nuanced interpretation of both regional HGF shares and the EEs literature.

Knives out: response to critics

Sat, 09 Aug 2025 00:00:00 GMT

Knives out: response to critics Khoo, Justin Writing a book can feel like a solitary endeavor. You labor for (in my case) years, sometimes talking about parts of the project with others, but mostly toiling alone to work out the consequences of commitments you made months and years prior. I'm grateful for the opportunity to engage with three brilliant interlocutors about these ideas, which for so long seemed to matter to no one besides myself (and maybe my publisher).

Toward Ontological Alignment: Coordinating Student Ideas with the Representational System of a Computational Modeling Unit for Science Learning

Mon, 18 Nov 2024 00:00:00 GMT

Toward Ontological Alignment: Coordinating Student Ideas with the Representational System of a Computational Modeling Unit for Science Learning Wagh, Aditi; Rosenbaum, Leah F.; Fuhrmann, Tamar; Eloy, Adelmo; Blikstein, Paulo; Wilkerson, Michelle Computational modeling tools present unique opportunities and challenges for student learning. Each tool has a representational system that impacts the kinds of explorations students engage in. Inquiry aligned with a tool’s representational system can support more productive engagement toward target learning goals. However, little research has examined how teachers can make visible the ways students’ ideas about a phenomenon can be expressed and explored within a tool’s representational system. In this paper, we elaborate on the construct of ontological alignment—that is, identifying and leveraging points of resonance between students’ existing ideas and the representational system of a tool. Using interaction analysis, we identify alignment practices adopted by a science teacher and her students in a computational agent-based modeling unit. Specifically, we describe three practices: (1) Elevating student ideas relevant to the tool’s representational system; (2) Exploring and testing links between students’ conceptual and computational models; and (3) Drawing on evidence resonant with the tool’s representational system to differentiate between theories. Finally, we discuss the pedagogical value of ontological alignment as a way to leverage students’ ideas in alignment with a tool’s representational system and suggest the presented practices as exemplary ways to support students’ computational modeling for science learning.

Stand Up and Split. Desiring Desertion in Jean Giono and Emmanuelle Lambert

Sat, 19 Oct 2024 00:00:00 GMT

Stand Up and Split. Desiring Desertion in Jean Giono and Emmanuelle Lambert Perreau, Bruno To face the powers that be, contemporary French writer Virginie Despentes proposes a straightforward solution: “stand up and split!” But where to go and with whom? How do we stop the proliferation of contested norms if we clear the decks? In a context of ecological crisis, desiring desertion is not rare even if we have only one world to inhabit. This article analyzes the desire to desert from two texts: Le Déserteur et autres récits (Citation1966 [1973]) by Jean Giono and La Désertion (Citation2018a) by Emmanuelle Lambert. It demonstrates that desertion does not make a clean sweep of the past but rather accepts the desert at the heart of existence. That is, both presence and disappearance.

Fuel Behavior Implications of Reactor Design Choices in Pressurized Water SMRs

Sun, 03 Aug 2025 00:00:00 GMT

Fuel Behavior Implications of Reactor Design Choices in Pressurized Water SMRs Halimi, Assil; Shirvan, Koroush Small pressurized water reactors can feature boron-free operation, natural circulation mode, reduced-height assemblies, and/or long refueling cycles. This paper attempts to explore core design optimization for each of these design evolutions. In consequence, five core design layouts are developed incorporating boron-free operation with continuous control rod insertion, natural circulation with low burnup/low power density design, natural circulation with high burnup/low power density design, forced circulation with standard core power density design, and forced circulation with high power density design. These cores’ performance is compared to a standard four-loop pressurized water reactor. The design process aims to improve the fuel cycle cost under safety constraints through core design optimization using the CASMO4E/SIMULATE3 reactor physics codes and the FRAPCON4.1 fuel performance assessment tool. Core modeling assumes standard 17×17 PWR fuel assemblies loaded with low enriched uranium up to 5 wt% or low enriched uranium plus (i.e. below 10 wt% enrichment) pellets with gadolinium oxide as the burnable poison. Satisfactory core and fuel performances are obtained for all the designed cores under steady state and considered overpower transients. For low power density operation, long cycle lengths are achieved reaching 2.5-year and 5-year cycles, and peak rod-average burnup is pushed to 83 MWd/kgU. Other cycle lengths are maintained at 18 months. Boron-free operation exhibits the ability to achieve longer cycle lengths at the cost of higher peaking factors leading to high local power and fuel temperatures, which prevents sizable power uprates and is deemed uneconomical. Fuel assembly height reduction allows coolant velocity retrofit, which enables higher core power density without violating the structural integrity of the fuel assembly. As a result, a core power density of 123 kW/L is reached where total cladding hoop strain becomes the limiting parameter.

Shades of authoritarian digital sovereignty: divergences in Russian and Chinese data localisation regimes

Tue, 02 Jan 2024 00:00:00 GMT

Shades of authoritarian digital sovereignty: divergences in Russian and Chinese data localisation regimes Khasanova, Liliya; Tai, Katharin The concept of sovereignty is now referred to in cyberspace-related policy by a range of governments, both authoritarian and democratic. At the same time, the most prominent proponents of state – or sovereignty-centric models of internet governance are Russia and China, whose positions are often characterised as a shared ‘Sino-Russian’ model. This paper subjects this idea of a shared Sino-Russian approach to empirical scrutiny by conducting a comparative analysis of rules, regulations and policies on data localisation in both countries. By delimiting the research question to regulations on data localisation and cross-border data transfers in both countries, we identify an important set of similarities and differences between the Russian and Chinese approaches. They share some features associated with authoritarian regimes, such as uncertainty around the selective enforcement of broadly formulated rules and a centralised assessment of outbound data transfers. However, we also find significant differences in the level of institutional centralisation, degrees of responsiveness within the policymaking process, and economic logics driving data localisation and cross-border transfer regulations. Based on these findings, we argue that despite a perception that Russia and China adhere to a similar model of authoritarian digital sovereignty, there are significant disparities in their data localisation regimes.

Race, profit, and algorithms: Neighborhood-level analysis of iBuyers’ profit margin

Tue, 29 Oct 2024 00:00:00 GMT

Race, profit, and algorithms: Neighborhood-level analysis of iBuyers’ profit margin So, Wonyoung iBuyers are firms that use automated valuation models (AVMs), streamline home buying processes, and provide all-cash offers to purchase homes. Although the previous literature has explored the roles and limitations of iBuyers in the housing market, empirical research on the racial implications of these algorithmic home buying processes remains understudied. Using a spatial lag model, this study shows the spatial clustering of iBuyer profit margins, that iBuyers gain more profits when they resell to individuals than institutions, and that some iBuyers have a statistically significant correlation between their profit margins and the proportion of marginalized racial groups within a census tract, while controlling for individual housing characteristics, neighborhood housing quality and demand, and neighborhood amenities and socioeconomic factors. These findings suggest that the more adeptly iBuyers can forecast housing values, the greater the potential to maximize profits from homeowners in communities of color. Consequently, this research contributes to the understanding of how technological mechanisms operate within a purportedly race-neutral framework and advocates for the development and deployment of algorithmic systems guided by the principles of antisubordination, rather than relying solely on notions of “fairness” and anticlassification.

Powering Through the Turn: Finding Time for Concept Exploration Before Industry Stagnation

Sat, 15 Mar 2025 00:00:00 GMT

Powering Through the Turn: Finding Time for Concept Exploration Before Industry Stagnation Noble, Connery; Cameron, Bruce G This study examines how the tension between exploration and exploitation affects early-stage development within the engineering teams of large corporations. Using survey data collected from over 900 system engineers and managers, it was observed that exploration decreased as an organization’s market growth declined, but dire market projections prompted a refocus on exploration. In addition, engineers routinely desire more concept exploration time than they perceive that they have available. The authors argue that engineering teams should more intentionally consider their innovation strategy, and that companies with stagnant market growth should invest in concept exploration before they get to a period of market decline.

Molecular dynamics simulations and structural bioinformatics of bacterial integral alpha-helical membrane enzymes and their AlphaFold2-predicted water-soluble QTY analogues

Mon, 29 Sep 2025 00:00:00 GMT

Molecular dynamics simulations and structural bioinformatics of bacterial integral alpha-helical membrane enzymes and their AlphaFold2-predicted water-soluble QTY analogues Sajeev-Sheeja, Akash; Karagöl, Alper; Karagöl, Taner; Zhang, Shuguang The study of integral membrane proteins has long been challenging because of their poor solubility in aqueous environments. We previously used QTY code to enhance the hydrophilicity in alpha-helices, beta-barrels, and monoclonal antibodies by systematically pairwise replacing the hydrophobic amino acids L (leucine) to Q (glutamine), V(valine)/I(isoleucine) to T (threonine), and F (phenylalanine) to Y (tyrosine). The superposed AlphaFold2-predicted structures of alpha-helical transmembrane enzyme variants with >41% amino acid substitutions displayed remarkable similarity to native structures (RMSD 0.3Å-0.7 Å). We conducted molecular dynamics (MD) simulations, which revealed that, even in the absence of a lipid bilayer, the QTY-modified enzymes retained stable dynamics comparable to their membrane-bound forms. Root mean square fluctuation (RMSF) values remained below 2 Å across the transmembrane and core regions, and residue-wise root mean square deviation (RMSD) values were minimal (<3 Å), indicating that the structural integrity of the protein core was largely preserved. These results suggest that the QTY variants, designed for soluble environments, effectively mimic the stability and conformational rigidity of natural membrane-bound enzymes. Our findings show that the QTY code is a simple method for designing water-soluble membrane protein enzymes in different biological scenarios, and it may encourage further experiments to validate our structural bioinformatics research.

City of ‘social saints’: the role of place in driving impact entrepreneurship in Turin, Italy

Mon, 15 Sep 2025 00:00:00 GMT

City of ‘social saints’: the role of place in driving impact entrepreneurship in Turin, Italy Burke, Mary Kathleen; Sydow, Alisa; Torchia, Daniel; Corazza, Laura This paper theorizes impact entrepreneurship (IE) in relation to place by examining dynamics at the individual, community, and organizational levels. While existing IE literature emphasizes entrepreneurship aimed at addressing grand challenges, it often adopts an aggregate view that overlooks how locally embedded entrepreneurs access and mobilize social and economic resources. We introduce a novel, multidimensional framework to show how sense of place, community embeddedness and IE interrelate to shape approaches to current social/environmental challenges. Adopting a qualitative approach, this paper investigates how different actors in Turin, Italy, contribute to IE through building on a legacy of social sector institutions. We find that individuals identifying with a place-based vocation of social impact find communities with a shared volition to work together and across organizations. We contribute to understanding how individuals’ senses of place can be leveraged into wider community efforts to support IE in the region. The paper advances the IE concept to account for the individual perspectives influencing local organizing practices and visions for IE rooted in place.

Plane Delivery: Towards a Physical Grammar for Large-Scale Digital Fabrication

Thu, 03 Jul 2025 00:00:00 GMT

Plane Delivery: Towards a Physical Grammar for Large-Scale Digital Fabrication Sass, Lawrence There will come a day when computers and robots will participate regularly in designing, fabricating, and delivering homes as customized kits of parts (Sass Citation2008). They will not replace builders. Instead, one possible future is where computers and robots operate as intelligent assistants, discovering, reasoning, and inferring the best solutions using large language models (LLMs). This language will be vector-based on points, lines, and planes of the type Stiny described (Stiny Citation2006). A standard design and builder language is a first step towards automation. The proposed system is of a Lego-style approach to physical house production, used to manage costs, enhance design variety, improve design quality, and, most importantly, facilitate building.

Techno-statecraft and industrial strategy: semiconductor development in Arizona

Tue, 27 May 2025 00:00:00 GMT

Techno-statecraft and industrial strategy: semiconductor development in Arizona Kollar, Justin The resurgence of U.S. industrial strategy discourse is not a centralised return of the state but a territorially fragmented form of techno-statecraft. This article analyzes Arizona's semiconductor expansion as a case in which subnational actors – agencies, utilities, universities, and developers – mobilise infrastructure, land-use policy, and regulatory coordination to attract global capital. Rather than a coherent national plan, Arizona's strategy reflects speculative governance oriented toward risk absorption and territorial readiness. The article situates this conjuncture within longer histories of militarised growth and infrastructural overbuild, contributing to debates on state capitalism, industrial strategy, and the spatial politics of techno-industrial transformation.

Ideology, Equity, and Structure: Comments on Tzu-wei Hung’s ‘Equity and Marxist Buddhism’

Tue, 01 Oct 2024 00:00:00 GMT

Ideology, Equity, and Structure: Comments on Tzu-wei Hung’s ‘Equity and Marxist Buddhism’ Haslanger, Sally In his essay, ‘Equity and Marxist Buddhism’, Tzu-wei Hung argues that Marxist Buddhism brings a commitment to social justice together with a distinctive form of virtue theory. In my commentary, I raise several questions from a Marxian perspective: (1) Might it be argued that Marxist Buddhism is (in the critical sense) ideological (similar to religion) because the spiritual goal of ‘transcendence’ distracts us from the need to fight for emancipation? (2) Can justice as equity be achieved by promoting individual altruism? (3) Aren’t both mainstream accounts of justice and Marxist Buddhism aspirational and so need to rely on non-ideal theory to achieve justice?

A data-driven and context-aware approach for demand forecasting in the beverage industry

Fri, 10 Oct 2025 00:00:00 GMT

A data-driven and context-aware approach for demand forecasting in the beverage industry Ma, Benedict Jun; Jackson, Ilya; Huang, Maggie; Villegas, Sebastian; Macias-Aguayo, Jaime Accurate demand forecasting is essential for logistics and supply chain management as it enables efficient inventory planning, reduces operational costs, and ensures high service levels across the network. However, in practice, diverse demand patterns of items make this task challenging, and a one-size-fits-all forecasting approach is inadequate. This paper proposes a data-driven and context-aware forecasting framework and tests it by using both endogenous data from a large private-label beverage manufacturer and exogenous features (such as holidays and temperature). Our method begins by classifying SKUs based on demand volume, volatility, and intermittency, and then refining the derived clusters by taking volume distribution into account. Totally, we obtain four distinct clusters, which are (i) stable and high volume, (ii) stable with low volume, (iii) erratic and intermittent, and (iv) lumpy. To explore the appropriate forecasting models for different demand patterns, we employ statistical models (exponential smoothing, ARIMA, and Croston), machine learning models (XGBoost), deep learning models (TiDE and N-BEATS), and even qualitative approaches such as collaborative planning, forecasting, and replenishment (CPFR). Our experimental results suggest which forecasting models are recommended for each demand pattern, and insightful implications are provided for the managers.

Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks

Mon, 09 Jun 2025 00:00:00 GMT

Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks Dai, Yan; Huang, Longbo Stochastic Network Optimization (SNO) concerns scheduling in stochastic queueing systems and has been widely studied in network theory. Classical SNO algorithms require network conditions to be stationary w.r.t. time, which fails to capture the non-stationary components in increasingly many real-world scenarios. Moreover, most existing algorithms in network optimization assume perfect knowledge of network conditions before decision, which again rules out applications where unpredictability in network conditions presents. Motivated by these issues, this paper considers Adversarial Network Optimization (ANO) under bandit feedback. Specifically, we consider the task of i) maximizing some unknown and time-varying utility function associated with scheduler's actions, where ii) the underlying network topology is a non-stationary multi-hop network whose conditions change arbitrarily with time, and iii) only bandit feedback (the effect of actually deployed actions) is revealed after decision-making. We propose the UMO2 algorithm, which does not require any pre-decision knowledge or counterfactual feedback, ensures network stability, and also matches the utility maximization performance of any ''mildly varying'' reference policy up to a polynomially decaying gap. To our knowledge, no previous algorithm can handle multi-hop networks or achieve utility maximization guarantees in ANO problems with bandit feedback, whereas ours is able to do both. Technically, our method builds upon a novel integration of online learning techniques into the Lyapunov drift-plus-penalty method. Specifically, we propose meticulous analytical techniques to jointly balance online learning and Lyapunov arguments, which is used to handle the complex inter-dependency among queues in multi-hop networks. To tackle the learning obstacles due to potentially unbounded queue sizes and negative queue differences, we design a new online linear optimization algorithm that automatically adapts to the unknown (potentially negative) loss magnitudes. Finally, we also propose a bandit convex optimization algorithm with novel queue-dependent learning rate scheduling that suites drastically varying queue lengths in utility maximization. Our new insights and techniques in online learning can also be of independent interest. SIGMETRICS Abstracts ’25, Stony Brook, NY, USA

IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents

Sun, 13 Jul 2025 00:00:00 GMT

IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents Mohanty, Shrestha; Arabzadeh, Negar; Tupini, Andrea; Sun, Yuxuan; Skrynnik, Alexey; Zholus, Artem; C?t?, Marc-Alexandre; Kiseleva, Julia Seamless interaction between AI agents and humans using natural language remains a key goal in AI research. This paper addresses the challenges of developing interactive agents capable of understanding and executing grounded natural language instructions through the IGLU competition. Despite advancements, challenges such as a scarcity of appropriate datasets and the need for effective evaluation platforms persist. We introduce a scalable data collection tool for gathering interactive grounded language instructions within a Minecraft-like environment, resulting in a Multi-Modal dataset with around 9,000 utterances and over 1,000 clarification questions. Additionally, we present a Human-in-the-Loop interactive evaluation platform for qualitative analysis and comparison of agent performance through multi-turn communication with human annotators. We offer to the community these assets referred to as IDAT (IGLU Dataset And Toolkit) which aim to advance the development of intelligent, interactive AI agents and provide essential resources for further research. SIGIR ’25, Padua, Italy

A Theory to Estimate, Bound, and Manage Systemic Cyber-Risk

Sun, 22 Jun 2025 00:00:00 GMT

A Theory to Estimate, Bound, and Manage Systemic Cyber-Risk Pal, Ranjan; Duan, Konnie; Sequeira, Rohan The market to manage critical infrastructure cyber-risks using cyber insurance (CI) has been growing steadily (but not fast enough) as it is still skeptical of the extent of economic and societal impact of systemic risk across networked supply chains in interdependent IT-driven enterprises. To demystify this skepticism, we first study in this paper the role of (a) the statistical nature of multiple enterprise cyber-risks contributing to aggregate supply chain risk and (b) the graph structure of the underlying enterprise supply chain network, in the statistical spread of aggregate cyber-risk. We provide statistical tail bounds on the aggregate cyber-risk that a risk managing firm such as a cyber insurer is exposed to in a supply chain. Subsequently, we study the problem of aggregate cyber-risk management by cyber re-insurance firms via portfolio design to optimally diversify aggregate/systemic cyber-risk sourced from multiple CIs insuring enterprises on a supply chain. We propose the first mathematical framework for re-insurers to test the operational sustainability of systemic cyber-risk diversification portfolios with respect to the standard Value-at-Risk (VaR) metric for general aggregate cyber risk distributions. We also propose a statistical copula methodology to make systemic cyber-risk portfolio diversification sustainable for re-insurers in scenarios where the sustainability test fails. We validate our theory via Monte Carlo simulations. SIGSIM-PADS ’25, Santa Fe, NM, USA

Dynamic Incentive Allocation for City-Scale Deep Decarbonization

Wed, 16 Jul 2025 00:00:00 GMT

Dynamic Incentive Allocation for City-Scale Deep Decarbonization Sitaraman, Anupama; Lechowicz, Adam; Bashir, Noman; Liu, Xutong; Hajiesmaili, Mohammad; Shenoy, Prashant Greenhouse gas emissions from the residential sector represent a large fraction of global emissions and must be significantly curtailed to achieve ambitious climate goals. To stimulate the adoption of relevant technologies such as rooftop PV and heat pumps, governments and utilities have designed incentives that encourage adoption of decarbonization technologies. However, studies have shown that many of these incentives are inefficient since a substantial fraction of spending does not actually promote adoption. Further, these incentives are not equitably distributed across socioeconomic groups. In this paper, we present a novel data-driven approach that adopts a holistic, emissions-based, and city-scale perspective on decarbonization. We propose an optimization model that dynamically allocates a total incentive budget to households to directly maximize the resultant carbon emissions reduction -- this is in contrast to prior work, which focuses on metrics such as the number of new installations. We leverage techniques from the multi-armed bandits problem to estimate human factors, such as a household's willingness to adopt new technologies given a certain incentive. We apply our proposed dynamic incentive framework to a city in the Northeast U.S., using real household energy data, grid carbon intensity data, and future price scenarios. We compare our learning-based technique to two baselines, one "status-quo' baseline using incentives offered by a state and utility, and one simple heuristic baseline. With these baselines, we show that our learning-based technique significantly outperforms both the status-quo baseline and the heuristic baseline, achieving up to 37.88% higher carbon reductions than the status-quo baseline and up to 28.76% higher carbon reductions compared to the heuristic baseline. Additionally, our incentive allocation approach is able to achieve significant carbon reduction even in a broad set of environments, with varying values for electricity and gas prices, and for carbon intensity of the grid. Finally, we show that our framework can accommodate equity-aware constraints to preserve an equitable allocation of incentives across socioeconomic groups while achieving 83.34% of the carbon reductions of the optimal solution on average.

The Economics of Large Language Models: Token Allocation, Fine-Tuning, and Optimal Pricing

Wed, 02 Jul 2025 00:00:00 GMT

The Economics of Large Language Models: Token Allocation, Fine-Tuning, and Optimal Pricing Bergemann, Dirk; Bonatti, Alessandro; Smolin, Alex We develop an economic framework to analyze the optimal pricing and product design of Large Language Models (LLM). Our framework captures several key features of LLMs: variable operational costs of processing input and output tokens; the ability to customize models through fine-tuning; and high-dimensional user heterogeneity in terms of task requirements and error sensitivity. In our model, a monopolistic seller offers multiple versions of LLMs through a menu of products. The optimal pricing structure depends on whether token allocation across tasks is contractible and whether users face scale constraints. When it is possible to contract on the entire assignment of tokens to tasks, the seller's problem ("Token Allocations") is an infinite-dimensional screening problem, which is well-known to be difficult. We are nonetheless able to make progress in two important classes of environments: binary environment and two dimensional value-scale heterogeneity, in which case users with similar aggregate value-scale characteristics choose similar levels of fine-tuning and token consumption. When only the total number of tokens is contractible ("Token Packages"), we leverage the tractability of a constant elasticity of substitution framework to drastically simplify the problem: the buyer's type-a function mapping each task to a value of precision- is an index. This index for the value of precision allows the seller to solve a one-dimensional screening problem. The optimal mechanism can be implemented through menus of two-part tariffs, with higher markups for more intensive users. Our results rationalize observed industry practices such as tiered pricing based on model customization and usage levels. EC ’25, July 7–10, 2025, Stanford, CA, USA

Alternates, Assemble! Selecting Optimal Alternates for Citizens’ Assemblies

Wed, 02 Jul 2025 00:00:00 GMT

Alternates, Assemble! Selecting Optimal Alternates for Citizens’ Assemblies Assos, Angelos; Baharav, Carmel; Flanigan, Bailey; Procaccia, Ariel Citizens' assemblies are an increasingly influential form of deliberative democracy, where randomly selected people discuss policy questions. The legitimacy of these assemblies hinges on their representation of the broader population, but participant dropout often leads to an unbalanced composition. In practice, dropouts are replaced by preselected alternates, but existing methods do not address how to choose these alternates. To address this gap, we introduce an optimization framework for alternate selection. Our algorithmic approach, which leverages learning-theoretic machinery, estimates dropout probabilities using historical data and selects alternates to minimize expected misrepresentation. Our theoretical bounds provide guarantees on sample complexity (with implications for computational efficiency) and on loss due to dropout probability mis-estimation. Empirical evaluation using real-world data demonstrates that, compared to the status quo, our method significantly improves representation while requiring fewer alternates. EC ’25, July 7–10, 2025, Stanford, CA, USA

Does Firm Size Influence the Collection of Sensitive Data?: A Study of Child-Orientated Apps

Wed, 02 Jul 2025 00:00:00 GMT

Does Firm Size Influence the Collection of Sensitive Data?: A Study of Child-Orientated Apps Cecere, Grazia; Tucker, Catherine; Lefrere, Vincent How does firm size affect the privacy protections offered to customers? On the one hand, it could be that larger firms use their size to amass more data. On the other hand, smaller firms may be less careful in their data protection practices, because they have a different perception of risk. Using data from the Google Play Store over a three-year period, we explore this empirical question in the U.S. children's app market. Our findings indicate that larger app developers consistently implement stronger privacy protections, requesting less sensitive data compared to smaller developers. These results hold across empirical approaches, including instrumental variables and the propensity-score matching approach. Additionally, our analysis shows that mergers between developers and sudden increases in size of the user-bases of the product are associated with reduced data collection. We show that newly created and updated apps produced by large developers collect less data compared to existing apps. Our findings indicate a trend toward standardized privacy practices across different national regulatory regimes. This research highlights the potential for growth-driven improvements in data privacy practices among app developers, regardless of their regulatory context. EC ’25, July 7–10, 2025, Stanford, CA, USA

Inertial Coordination Games

Wed, 02 Jul 2025 00:00:00 GMT

Inertial Coordination Games Koh, Andrew; Li, Ricky; Uzui, Kei Coordination lies at the heart of many economic phenomena. A well-known example is currency crises, in which traders decide whether to launch a speculative attack. On one hand, shocks to the currency's fundamentals can propagate: as more traders attack, the central bank's foreign reserves are depleted, which in turn encourages further attacks as traders seek to exploit a weakening currency. On the other hand, shocks can also fizzle out: traders may quickly learn that the central bank's balance sheet is strong, causing pessimism to dissipate and attacks to subside. When do shocks propagate, and when do they fizzle out? In particular, how do these outcomes depend on the speed at which traders learn about the fundamental? Motivated by these questions, we propose a model of inertial coordination games—dynamic coordination games where players repeatedly decide whether to take a risky action. The payoff from this risky action depends on (i) a persistent fundamental; and (ii) an endogenous component that depends on others' past play. Players receive private signals about the persistent fundamental over time and form beliefs about the current state. Notably, the current state depends on past play, which in turn depends on past beliefs about play yet farther back into the past. Thus, expectations about histories shape behavior in the present which, in turn, drives the evolution of future states and future play. Our main result develops a tight connection between the speed of learning and limit aggregate play: the risk-dominant action is played in the limit if and only if posterior precisions grow sub-quadratically. This has sharp implications for the long-run propagation of shocks. With slow (sub-quadratic) learning, limit play exhibits history independence: initial shocks have no lasting effect, and limit play is determined solely by fundamentals. By contrast, with fast (super-quadratic) learning, limit play is history dependent: initial shocks can be self-fulfilling, and whether they propagate depends jointly on fundamentals, the size of the shock, and the speed of learning. Our results offer a novel perspective on whether 'history' or 'expectations' shape long-run coordination outcomes: in our model, expectations about histories is what matters for whether self-fulfilling spirals occur. Finally, we show that the speed of learning also shapes the path of play, focusing on the case of sub-quadratic learning. When signals are precise, aggregate play exhibits a sudden transition from nearly all players choosing the non-risk-dominant action to nearly all players choosing the risk-dominant action. In contrast, when signals are noisy, the transition is gradual, with the share of players choosing the risk-dominant action increasing gradually over time. This suggests that "spikes" in aggregate behavior (such as a sudden and massive sell-off of a currency) can be consistent with transition to limit equilibrium play, and need not indicate an "equilibrium shift." EC ’25, July 7–10, 2025, Stanford, CA, USA

Galley: Modern Query Optimization for Sparse Tensor Programs

Wed, 18 Jun 2025 00:00:00 GMT

Galley: Modern Query Optimization for Sparse Tensor Programs Deeds, Kyle; Ahrens, Willow; Balazinska, Magdalena; Suciu, Dan The tensor programming abstraction is a foundational paradigm which allows users to write high performance programs via a high-level imperative interface. Recent work on sparse tensor compilers has extended this paradigm to sparse tensors (i.e., tensors where most entries are not explicitly represented). With these systems, users define the semantics of the program and the algorithmic decisions in a concise language that can be compiled to efficient low-level code. However, these systems still require users to make complex decisions about program structure and memory layouts to write efficient programs. This work presents .Galley, a system for declarative tensor programming that allows users to write efficient tensor programs without making complex algorithmic decisions. Galley is the first system to perform cost based lowering of sparse tensor algebra to the imperative language of sparse tensor compilers, and the first to optimize arbitrary operators beyond Σ and *. First, it decomposes the input program into a sequence of aggregation steps through a novel extension of the FAQ framework. Second, Galley optimizes and converts each aggregation step to a concrete program, which is compiled and executed with a sparse tensor compiler. We show that Galley produces programs that are 1-300x faster than competing methods for machine learning over joins and 5-20x faster than a state-of-the-art relational database for subgraph counting workloads with a minimal optimization overhead.

Virtualizing Cloud Data Infrastructures with BRAD

Sun, 22 Jun 2025 00:00:00 GMT

Virtualizing Cloud Data Infrastructures with BRAD Yu, Geoffrey; Wu, Ziniu; Kossmann, Ferdi; Li, Tianyu; Markakis, Markos; Ngom, Amadou; Zhang, Sophie; Kraska, Tim; Madden, Samuel Organizations usually manage their data using multiple specialized cloud database engines (e.g., Aurora, BigQuery, etc.). However, designing and managing multi-engine infrastructures is hard; there can be many designs, each with different performance and costs. Changing the design afterwards (e.g., due to growth) is even more challenging since application code usually ends up tightly coupled to the engines. We propose data infrastructure virtualization. The key idea is to declare a set of virtual database engines (VDBEs), which specify an engine's application-facing properties (e.g., query interface, performance) and its tables, but do not prescribe a concrete engine. An automated planner then decides how to best realize the VDBEs onto physical engines based on the workload. Clients connect to VDBE endpoints and are oblivious to the underlying physical engines-allowing for seamless infrastructure changes. We implemented VDBEs and an automated planner in BRAD: the first data infrastructure virtualization runtime. Our demo will showcase VDBEs and BRAD's automated planner under different workloads. SIGMOD-Companion ’25, Berlin, Germany

An Efficient Subcritical Multiplication Mode for Monte Carlo Solvers

Mon, 20 Oct 2025 00:00:00 GMT

An Efficient Subcritical Multiplication Mode for Monte Carlo Solvers Forget, Benoit This paper presents an efficient Monte Carlo mode for simulating subcritical systems with external sources. While solving these systems as a fixed source is possible, the length of the histories grows significantly as the system nears criticality, making run time significant. Instead, a hybrid method is proposed that leverages the traditional eigensolver while including elements of the external source. The method builds on prior work,but proposes an approach that maintains the size of the source bank and also provides a natural way of scaling tallies with the true multiplication factor. The method is demonstrated on a subcritical sphere with varying point source position and energy spectrum, as well as an approach to criticality problem. The results demonstrate good agreement with the fixed-source mode, with much improved particle tracking rates for near-critical problems.

Afterword: Reflections from Afar, with Hope for our Collective Future

Thu, 02 Oct 2025 00:00:00 GMT

Afterword: Reflections from Afar, with Hope for our Collective Future Henderson, Diana E Appearing in the wake of a decade of rapid growth in Indian screen Shakespeare as an academic subspeciality, ‘Adapting Shakespearean Romance in Indian Cinema’ reveals how cross-cultural comparison and attention to popular reception can profitably modify inherited critical assumptions for all Shakespeare’s readership. Taking ‘romance’ as a key term, this afterword considers the possibilities and potential problems of recasting its dominant meaning as thematic, focusing on modern love, rather than as a dramatic subgenre. In a time of increasing political censorship and existential threats to gender studies, greater engagement and exchange between those in other areas of Shakespeare studies with this rich cinematic corpus and its aligned subfield of cross-disciplinary criticism provides reasons for hope and renewed community.

Resolving the Contested Future of the GSEs: The Stakes Are High

Mon, 17 Nov 2025 00:00:00 GMT

Resolving the Contested Future of the GSEs: The Stakes Are High Golding, Edward; Wachter, Susan Seventeen years after entering conservatorship, Fannie Mae and Freddie Mac remain central to the future of U.S. housing finance. This paper evaluates the feasibility of their exit from conservatorship without Congressional action, assessing repayment of the federal bailout, capital adequacy under current regulatory frameworks, and the durability of structural reforms. It puts forth a utility model that preserves liquidity, affordability, and mission alignment while mitigating risks of increased mortgage costs. Treasury mechanisms—including commitment fees and stock warrant monetization—are examined as tools to support affordable housing and fulfill charter mandates. A carefully structured exit, supported by robust oversight and capital standards, can balance adequate financial returns with public purpose. A regulatory framework that maintains stable lending standards and pricing over the business cycle is essential to reducing investor-required returns and enhancing affordability, thereby resolving the contested future of the GSEs.

Stabilizing far-from-equilibrium (Mo,Ti)S2 thin films by metal sulfurization at reduced temperature

Thu, 16 Feb 2023 00:00:00 GMT

Stabilizing far-from-equilibrium (Mo,Ti)S2 thin films by metal sulfurization at reduced temperature Li, Yifei; Reidy, Kate; Penn, Aubrey; Lee, Seng Huat; Wang, Baoming; Ye, Kevin; Mao, Zhiqiang; Ross, Frances M; Jaramillo, R We report the synthesis of large-area, high-Ti-content, Mo1−xTixS2 alloy thin films in the 2H phase at temperature as low as 500 °C using a scalable two-step method of metal film deposition, followed by sulfurization in H2S. Film processing at higher temperature accelerates Ti segregation, film coarsening, and the formation of TiS2 in the 1T phase. Crystal growth at higher temperature results in the formation of multiple binary sulfide phases, in agreement with the equilibrium phase diagram. Making highly metastable, smooth, and uniform single-phase alloy films, therefore, hinges on developing low-temperature processing. Our results are relevant to the development of technologies based on designer transition metal dichalcogenide alloys, including in photonic integrated circuits and gas sensing.

Experimental study of lower hybrid wave power absorption on EAST

Fri, 18 Aug 2023 00:00:00 GMT

Experimental study of lower hybrid wave power absorption on EAST Baek, S-G; Li, MH; Bonoli, PT; Ding, BJ; Wallace, GM; Chen, JL; Duan, YM; Gong, XZ; Qian, JP; Wang, L; Yang, H; Zang, Q; Zhang, JY; Zhang, XJ Lower hybrid power absorption analysis is presented on the EAST high-density plasmas using the power modulation technique. The change in the plasma and magnetic energy is monitored to evaluate the power absorption coefficient by linearizing the change for the first 10 msec for the given input power. The power absorption coefficient evaluated is approximately 0.44 (0.35) for 4.6 GHz (2.45 GHz) at n̄e = 3.5x1019 m-3 GENRAY/CQL3D current drive modeling suggests a combination of antenna spectrum, accessibility, and edge losses could primarily be responsible for the observed level of power absorption. Evidence of first-pass parasite LH power flow causing impurity sputtering is also reported, suggesting a need for optimum power coupling. Implications of the experimental findings are discussed.

Limiting role of dislocations in high-current AlGaN/GaN hot electron transistors

Tue, 06 Feb 2024 00:00:00 GMT

Limiting role of dislocations in high-current AlGaN/GaN hot electron transistors Daulton, J. W.; Molnar, R. J.; Brinkerhoff, J. A.; Weir, T. J.; Hollis, M. A.; Zaslavsky, A. III-nitride-based hot electron transistors (HETs) hold significant promise as high-speed, high-power devices. In our previous work, we demonstrated high current density and common-emitter gain at room temperature. Here, we measure multiple devices at cryogenic temperatures, extending the Gummel characteristics past the onset of intervalley scattering at 77 K. We demonstrate a Gummel current gain of 4.7 at a collector current density of 2.6 MA/cm2 at 77 K as well as a peak current density exceeding 3 MA/cm2. From these data, we determine that dislocation-associated inhomogeneities play a limiting role in AlGaN/GaN HETs, controlling the current gain, density, knee voltage, and base-collector leakage. A comparison of two nominally identical devices suggests that even a modest reduction in dislocation density would result in a substantial improvement in HET performance.

SeerCuts: Explainable Attribute Discretization

Sun, 22 Jun 2025 00:00:00 GMT

SeerCuts: Explainable Attribute Discretization Lai, Eugenie; Croitoru, Inbal; Bitton, Noam; Shalem, Ariel; Youngmann, Brit; Galhotra, Sainyam; Rezig, El Kindi; Cafarella, Michael This demonstration showcases SeerCuts - a tool that suggests useful and semantically meaningful discretization strategies (partitions) for numerical attributes. SeerCuts is a generic, interactive framework where users specify attributes to discretize and their utility measure for a downstream task of choice. It uses GPT-4o to assess the semantic meaningfulness of candidate partitions and employs an efficient search strategy to explore the vast space of discretization options. With hierarchical clustering to group related partitions and a multi-armed bandit policy to identify useful partitions with only a few samples, SeerCuts quickly finds meaningful and useful partitions. In the demo, we will provide an overview of SeerCuts and allow the audience to explore various datasets and tasks, including data visualization and comprehensive modeling. The users will be able to evaluate how SeerCuts identifies meaningful discretization strategies and compare the tradeoff between different discretization options. SIGMOD-Companion ’25, Berlin, Germany

PalimpChat: Declarative and Interactive AI analytics

Sun, 22 Jun 2025 00:00:00 GMT

PalimpChat: Declarative and Interactive AI analytics Liu, Chunwei; Vitagliano, Gerardo; Rose, Brandon; Printz, Matthew; Samson, David Andrew; Cafarella, Michael Thanks to the advances in generative architectures and large language models, data scientists can now code pipelines of AI operations to process large collections of unstructured data. Recent progress has seen the rise of declarative AI frameworks (e.g., Palimpzest, Lotus, and DocETL) to build optimized and increasingly complex pipelines, but these systems often remain accessible only to expert programmers. In this demonstration, we present PalimpChat, a chat-based interface to Palimpzest that bridges this gap by letting users create and run sophisticated AI pipelines through natural language alone. By integrating Archytas, a ReAct-based reasoning agent, and Palimpzest's suite of relational and LLM-based operators, PalimpChat provides a practical illustration of how a chat interface can make declarative AI frameworks truly accessible to non-experts. Our demo system is publicly available online. At SIGMOD'25, participants can explore three real-world scenarios-scientific discovery, legal discovery, and real estate search-or apply PalimpChat to their own datasets. In this paper, we focus on how PalimpChat, supported by the Palimpzest optimizer, simplifies complex AI workflows such as extracting and analyzing biomedical data. SIGMOD-Companion ’25, Berlin, Germany

CauSumX: Summarized Causal Explanations For Group-By-Average Queries

Sun, 22 Jun 2025 00:00:00 GMT

CauSumX: Summarized Causal Explanations For Group-By-Average Queries Levy, Nativ; Cafarella, Michael; Gilad, Amir; Roy, Sudeepa; Youngmann, Brit Group-by-average SQL queries are a cornerstone of data analysis, often employed to uncover patterns and trends within datasets. However, interpreting the results of these queries can be challenging and time-intensive, particularly when working with large, high-dimensional datasets. Automating the generation of explanations for such queries can greatly enhance analysts' ability to derive meaningful insights while reducing human effort. Effective explanations must balance succinctness and depth, offering insights into different patterns across aggregate results, while crucially reflecting cause-effect relationships rather than mere correlations. This ensures that users can make informed, data-driven decisions grounded in reality. In this demonstration, we present CauSumX, a system that produces concise and causal explanations for group-by-average queries. Leveraging background causal knowledge, CauSumX identifies the key causal factors driving variations in the outcome variable across different groups. The system employs an efficient algorithm based on a recently published paper. We will demonstrate the utility of CauSumX for generating useful summarized causal explanations by interacting with the SIGMOD'25 participants, who will act as data analysts aiming to explain their query results. SIGMOD-Companion ’25, Berlin, Germany

CausaLens: A System for Summarizing Causal DAGs

Sun, 22 Jun 2025 00:00:00 GMT

CausaLens: A System for Summarizing Causal DAGs Chen, Noam; Zeng, Anna; Cafarella, Michael; Kenig, Batya; Markakis, Markos; Mishali, Oren; Youngmann, Brit; Salimi, Babak Causal inference aids researchers in discovering causal relationships, leading to scientific insights. Pearl's causal model uses causal DAGs to estimate causal effects, so DAG correctness is essential for reliable causal conclusions. However, for high-dimensional data, the causal DAGs are often complex beyond human verifiability. Graph summarization is a logical next step, but current methods for general-purpose graph summarization are inadequate for causal DAG summarization, as they are not designed to preserve causal information. In this demonstration, we present a system called CausaLens that summarizes a given causal DAG and balances graph simplification for better understanding and retention of essential causal information for reliable inference directly on the summary DAG. We illustrate that causal inference on the summary DAG is more robust to misspecification in the initial causal DAG compared to performing inference directly on the initial causal DAG, thereby enhancing the robustness of causal inference. We will demonstrate the utility of CausaLens for generating useful summary causal DAGs by interacting with the SIGMOD'25 participants, who will act as data analysts aiming to perform causal analysis on high dimensional datasets. SIGMOD-Companion ’25, Berlin, Germany

First Workshop on Novel Optimizations for Visionary AI Systems (NOVAS)

Sun, 22 Jun 2025 00:00:00 GMT

First Workshop on Novel Optimizations for Visionary AI Systems (NOVAS) Vitagliano, Gerardo; Liu, Chunwei; Cao, Lei; Sun, Huan; Papotti, Paolo The first NOVAS workshop (Novel Optimizations for Visionary AI Systems) is aimed at hosting novel work at the intersection between artificial intelligence and data management. This area has emerged with the rise of transformer-based architectures, which have revolutionized data processing across modalities. While these models benefit from massive pre-training and large-context inference, there are significant challenges related to scalability, determinism, and resource constraints. These issues-long studied in the data management community-have sparked a convergence between generative AI and traditional database research. The workshop will be held on June 22nd, in conjunction with SIGMOD/PODS 2025. The workshop solicits regular and short papers on topics including hardware and execution optimizations, high-level programming abstractions, integration of LLMs with relational databases, and new transformer architectures for structured data. By bridging together the different communities of machine learning, data systems, and information retrieval, NOVAS aims at becoming the venue to discuss, share ideas and early results, and spark new research collaborations for the next-generation of data-driven AI systems. SIGMOD-Companion ’25, Berlin, Germany

Data-Efficient Discovery of Hyperelastic TPMS Metamaterials with Extreme Energy Dissipation

Sun, 27 Jul 2025 00:00:00 GMT

Data-Efficient Discovery of Hyperelastic TPMS Metamaterials with Extreme Energy Dissipation Perroni-Scharf, Maxine; Ferguson, Zachary; Butruille, Thomas; Portela, Carlos; Konakovi? Lukovi?, Mina Triply periodic minimal surfaces (TPMS) are a class of metamaterials with a variety of applications and well-known primitive morphologies. We present a new method for discovering novel microscale TPMS structures with exceptional energy-dissipation capabilities, achieving double the energy absorption of the best existing TPMS primitive structure. Our approach employs a parametric representation, allowing seamless interpolation between structures and representing a rich TPMS design space. As simulations are intractable for efficiently optimizing microscale hyperelastic structures, we propose a sample-efficient computational strategy for rapid discovery with limited empirical data from 3D-printed and tested samples that ensures high-fidelity results. We achieve this by leveraging a predictive uncertainty-aware Deep Ensembles model to identify which structures to fabricate and test next. We iteratively refine our model through batch Bayesian optimization, selecting structures for fabrication that maximize exploration of the performance space and exploitation of our energy-dissipation objective. Using our method, we produce the first open-source dataset of hyperelastic microscale TPMS structures, including a set of novel structures that demonstrate extreme energy dissipation capabilities, and show several potential applications of these structures. SIGGRAPH Conference Papers ’25, Vancouver, BC, Canada

Splat and Replace: 3D Reconstruction with Repetitive Elements

Sun, 27 Jul 2025 00:00:00 GMT

Splat and Replace: 3D Reconstruction with Repetitive Elements Violante, Nicolas; Meuleman, Andr?as; Gauthier, Alban; Durand, Fredo; Groueix, Thibault; Drettakis, George We leverage repetitive elements in 3D scenes to improve novel view synthesis. Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have greatly improved novel view synthesis but renderings of unseen and occluded parts remain low-quality if the training views are not exhaustive enough. Our key observation is that our environment is often full of repetitive elements. We propose to leverage those repetitions to improve the reconstruction of low-quality parts of the scene due to poor coverage and occlusions. We propose a method that segments each repeated instance in a 3DGS reconstruction, registers them together, and allows information to be shared among instances. Our method improves the geometry while also accounting for appearance variations across instances. We demonstrate our method on a variety of synthetic and real scenes with typical repetitive elements, leading to a substantial improvement in the quality of novel view synthesis. SIGGRAPH Conference Papers ’25, Vancouver, BC, Canada

Variational Elastodynamic Simulation

Sun, 27 Jul 2025 00:00:00 GMT

Variational Elastodynamic Simulation Mattos Da Silva, Leticia; Sell?n, Silvia; Pacheco-Tallaj, Natalia; Solomon, Justin Numerical schemes for time integration are the cornerstone of dynamical simulations for deformable solids. The most popular time integrators for isotropic distortion energies rely on nonlinear root-finding solvers, most prominently, Newton’s method. These solvers are computationally expensive and sensitive to ill-conditioned Hessians and poor initial guesses; these difficulties can particularly hamper the effectiveness of variational integrators, whose momentum conservation properties require reliable root-finding. To tackle these difficulties, this paper shows how to express variational time integration for a large class of elastic energies as an optimization problem with a “hidden” convex substructure. This hidden convexity suggests uses of optimization techniques with rigorous convergence analysis, guaranteed inversion-free elements, and conservation of physical invariants up to tolerance/numerical precision. In particular, we propose an Alternating Direction Method of Multipliers (ADMM) algorithm combined with a proximal operator step to solve our formulation. Empirically, our integrator improves the performance of elastic simulation tasks, as we demonstrate in a number of examples. SIGGRAPH Conference Papers ’25, Vancouver, BC, Canada

Strain-Tunable Thermal Conductivity in Largely Amorphous Polyolefin Fibers via Alignment-Induced Vibrational Delocalization

Mon, 09 Feb 2026 00:00:00 GMT

Strain-Tunable Thermal Conductivity in Largely Amorphous Polyolefin Fibers via Alignment-Induced Vibrational Delocalization Developing fast, reversible, and recyclable thermal switches is essential to advance adaptive thermal management. Here, we present a strain-tunable thermal switch based on largely amorphous olefin block copolymer (OBC) fibers, achieving a continuous switching ratio above 2 over 1000 cycles, as well as very short response times below 0.22 s. Using Raman spectroscopy, we quantify vibrational delocalization with increasing strain and demonstrate its direct connection to the observed thermal conductivity changes. We show that unlike prior assumptions linking propagating heat carriers primarily to crystalline domains, alignment in amorphous systems can enable phonon-like modes that dominate transport. To our best knowledge, this work is the first to experimentally probe vibrational delocalization using Raman spectroscopy and to demonstrate that alignment alone can govern the dominant carrier in disordered polymers. These findings establish design strategies for fatigue-resistant, high-performance, and recyclable polymer thermal switches for advanced thermal energy transport applications.

Introducing synchromodality: One missing link between transportation and supply chain management

Mon, 24 May 2021 00:00:00 GMT

Introducing synchromodality: One missing link between transportation and supply chain management Acero, Beatriz; Saenz, Maria Jesus; Luzzini, Davide This study develops and tests the synchromodality construct, a novel supply chain concept that integrates the flexible use of different transport modes based on real-time information. At a time when global supply chains are complex and subject to uncertainty, synchromodality has emerged at the forefront of research and practice as a tool to ensure efficient delivery performance and thus supply chain competitiveness. Despite synchromodality is attracting the attention of leading companies and policy makers, only scholars within the transport research community have engaged with the topic so far. We believe a supply chain management perspective is missing, but essential, to develop the full potential of synchromodality. Our study shows that synchromodality capabilities encapsulate four key elements: visibility, integration, multi-modal transport, and flexibility. Thanks to a three-stage research approach exploiting multiple methods, this study conceptualizes, develops, and validates the first synchromodality measurement model, which reflects the multidimensional nature of the concept. We hope to set the stage for a number of potential future research opportunities that can explore synchromodality implementation and outcomes.

Shape Space Spectra

Sun, 27 Jul 2025 00:00:00 GMT

Shape Space Spectra Chang, Yue; Benchekroun, Otman; Chiaramonte, Maurizio M.; Chen, Peter Yichen; Grinspun, Eitan Eigenanalysis of differential operators, such as the Laplace operator or elastic energy Hessian, is typically restricted to a single shape and its discretization, limiting reduced order modeling (ROM). We introduce the first eigenanalysis method for continuously parameterized shape families. Given a parametric shape, our method constructs spatial neural fields that represent eigen-functions across the entire shape space. It is agnostic to the specific shape representation, requiring only an inside/outside indicator function that depends on shape parameters. Eigenfunctions are computed by minimizing a variational principle over nested spaces with orthogonality constraints. Since eigenvalues may swap dominance at points of multiplicity, we jointly train multiple eigenfunctions while dynamically reordering them based on their eigenvalues at each step. Through causal gradient filtering, this reordering is reflected in backpropagation. Our method enables applications to operate over shape space, providing a single ROM that encapsulates vibration modes for all shapes, including previously unseen ones. Since our eigenanalysis is differentiable with respect to shape parameters, it facilitates eigenfunction-aware shape optimization. We evaluate our approach on shape optimization for sound synthesis and locomotion, as well as reduced-order modeling for elastodynamic simulation.

Dynamic Mesh Processing on the GPU

Sun, 27 Jul 2025 00:00:00 GMT

Dynamic Mesh Processing on the GPU Mahmoud, Ahmed H.; Porumbescu, Serban D.; Owens, John D. We present a system for dynamic triangle mesh processing entirely on the GPU. Our system features an efficient data structure that enables rapid updates to mesh connectivity and attributes. By partitioning the mesh into small patches, we process all dynamic updates for each patch within the GPU's fast shared memory. This approach leverages speculative processing for conflict handling, minimizing rollback costs, maximizing parallelism, and reducing locking overhead. Additionally, we introduce a new programming model for dynamic mesh processing. This model provides concise semantics for dynamic updates, abstracting away concerns about conflicting updates during parallel execution. At the core of our model is the cavity operator, a general mesh update operator that facilitates any dynamic operation by removing a set of mesh elements and inserting new ones into the resulting void. We applied our system to various GPU applications, including isotropic remeshing, surface tracking, mesh decimation, and Delaunay edge flips. On large inputs, our system achieves an order-of-magnitude speedup compared to multi-threaded CPU solutions and is more than two orders of magnitude faster than state-of-the-art single-threaded CPU solutions. Furthermore, our data structure outperforms state-of-the-art GPU static data structures in terms of both speed and memory efficiency.

Exciton Fine Structure in 2D Perovskites: The Out‐of‐Plane Excitonic State

Tue, 23 Jul 2024 00:00:00 GMT

Exciton Fine Structure in 2D Perovskites: The Out‐of‐Plane Excitonic State Posmyk, Katarzyna; Dyksik, Mateusz; Surrente, Alessandro; Maude, Duncan K; Zawadzka, Natalia; Babiński, Adam; Molas, Maciej R; Paritmongkol, Watcharaphol; Mączka, Mirosław; Tisdale, William A; Plochocka, Paulina; Baranowski, Michał 2D Ruddlesden-Popper metal-halide perovskites feature particularly strong excitonic effects, making them a fascinating playground for studying exciton physics. A complete understanding of the properties of this quasi-particle is crucial to fully exploit the tremendous potential of 2D perovskites (2DP) in light emission applications. Despite intense investigations, some of the exciton properties remain elusive to date, for example, the energy-ordering of the exciton states within the so-called fine structure manifold. Using optical spectroscopy, it demonstrates that in the archetypical 2DP (PEA)2PbI4, in contradiction to theoretical predictions, the energy of the bright out-of-plane exciton state is higher than that of two in-plane states. Having elucidated the order of exciton fine structure, it determines the g-factor of the dark exciton transition, together with the values of the electron and hole g-factors in the direction parallel to the c-axis of the crystal. In this way, it provides for the first time, a complete picture of the exciton fine structure in (PEA)2PbI4 2DP.

Discovery of enhanced lattice dynamics in a single-layered hybrid perovskite

Wed, 16 Aug 2023 00:00:00 GMT

Discovery of enhanced lattice dynamics in a single-layered hybrid perovskite Zhang, Zhuquan; Zhang, Jiahao; Liu, Zi-Jie; Dahod, Nabeel S; Paritmongkol, Watcharaphol; Brown, Niamh; Stollmann, Alexia; Lee, Woo Seok; Chien, Yu-Che; Dai, Zhenbang; Nelson, Keith A; Tisdale, William A; Rappe, Andrew M; Baldini, Edoardo Layered hybrid perovskites exhibit emergent physical properties and exceptional functional performances, but the coexistence of lattice order and structural disorder severely hinders our understanding of these materials. One unsolved problem regards how the lattice dynamics are affected by the dimensional engineering of the inorganic frameworks and their interaction with the molecular moieties. Here, we address this question by using a combination of spontaneous Raman scattering, terahertz spectroscopy, and molecular dynamics simulations. This approach reveals the structural dynamics in and out of equilibrium and provides unexpected observables that differentiate single- and double-layered perovskites. While no distinct vibrational coherence is observed in double-layered perovskites, an off-resonant terahertz pulse can drive a long-lived coherent phonon mode in the single-layered system. This difference highlights the dramatic change in the lattice environment as the dimension is reduced, and the findings pave the way for ultrafast structural engineering and high-speed optical modulators based on layered perovskites.

Bright Excitonic Fine Structure in Metal-Halide Perovskites: From Two-Dimensional to Bulk

Wed, 07 Feb 2024 00:00:00 GMT

Bright Excitonic Fine Structure in Metal-Halide Perovskites: From Two-Dimensional to Bulk Posmyk, Katarzyna; Zawadzka, Natalia; Łucja Kipczak; Dyksik, Mateusz; Surrente, Alessandro; Maude, Duncan K; Kazimierczuk, Tomasz; Babiński, Adam; Molas, Maciej R; Bumrungsan, Wakul; Chooseng, Chanisara; Paritmongkol, Watcharaphol; Tisdale, William A; Baranowski, Michał; Plochocka, Paulina The optical response of two-dimensional (2D) perovskites, often referred to as natural quantum wells, is primarily governed by excitons, whose properties can be readily tuned by adjusting the perovskite layer thickness. We have investigated the exciton fine structure splitting in the archetypal 2D perovskite (PEA)2(MA)n−1PbnI3n+1 with varying numbers of inorganic octahedral layers n = 1, 2, 3, and 4. We demonstrate that the in-plane excitonic states exhibit splitting and orthogonally oriented dipoles for all confinement regimes. The evolution of the exciton states in an external magnetic field provides further insights into the g-factors and diamagnetic coefficients. With increasing n, we observe a gradual evolution of the excitonic parameters characteristic of a 2D to three-dimensional transition. Our results provide valuable information concerning the evolution of the optoelectronic properties of 2D perovskites with the changing confinement strength.

Persistent enhancement of exciton diffusivity in CsPbBr3 nanocrystal solids

Wed, 21 Feb 2024 00:00:00 GMT

Persistent enhancement of exciton diffusivity in CsPbBr3 nanocrystal solids Shcherbakov-Wu, Wenbi; Saris, Seryio; Sheehan, Thomas John; Wong, Narumi Nagaya; Powers, Eric R; Krieg, Franziska; Kovalenko, Maksym V; Willard, Adam P; Tisdale, William A In semiconductors, exciton or charge carrier diffusivity is typically described as an inherent material property. Here, we show that the transport of excitons among CsPbBr3 perovskite nanocrystals (NCs) depends markedly on how recently those NCs were occupied by a previous exciton. Using transient photoluminescence microscopy, we observe a striking dependence of the apparent exciton diffusivity on excitation laser power that does not arise from nonlinear exciton-exciton interactions or thermal heating. We interpret our observations with a model in which excitons cause NCs to transition to a long-lived metastable configuration that markedly increases exciton transport. The exciton diffusivity observed here (>0.15 square centimeters per second) is considerably higher than that observed in other NC systems, revealing unusually strong excitonic coupling between NCs. The finding of a persistent enhancement in excitonic coupling may help explain other photophysical behaviors observed in CsPbBr3 NCs, such as superfluorescence, and inform the design of optoelectronic devices.

All-Perovskite Multicomponent Nanocrystal Superlattices

Wed, 06 Mar 2024 00:00:00 GMT

All-Perovskite Multicomponent Nanocrystal Superlattices Sekh, Taras V; Cherniukh, Ihor; Kobiyama, Etsuki; Sheehan, Thomas J; Manoli, Andreas; Zhu, Chenglian; Athanasiou, Modestos; Sergides, Marios; Ortikova, Oleksandra; Rossell, Marta D; Bertolotti, Federica; Guagliardi, Antonietta; Masciocchi, Norberto; Erni, Rolf; Othonos, Andreas; Itskos, Grigorios; Tisdale, William A; Stöferle, Thilo; Rainò, Gabriele; Bodnarchuk, Maryna I; Kovalenko, Maksym V Nanocrystal superlattices (NC SLs) have long been sought as promising metamaterials, with nanoscale-engineered properties arising from collective and synergistic effects among the constituent building blocks. Lead halide perovskite (LHP) NCs come across as outstanding candidates for SL design, as they demonstrate collective light emission, known as superfluorescence, in single- and multicomponent SLs. Thus far, LHP NCs have only been assembled in single-component SLs or coassembled with dielectric NC building blocks acting solely as spacers between luminescent NCs. Here, we report the formation of multicomponent LHP NC-only SLs, i.e., using only CsPbBr3 NCs of different sizes as building blocks. The structural diversity of the obtained SLs encompasses the ABO6, ABO3, and NaCl structure types, all of which contain orientationally and positionally locked NCs. For the selected model system, the ABO6-type SL, we observed efficient NC coupling and Förster-like energy transfer from strongly confined 5.3 nm CsPbBr3 NCs to weakly confined 17.6 nm CsPbBr3 NCs, along with characteristic superfluorescence features at cryogenic temperatures. Spatiotemporal exciton dynamics measurements reveal that binary SLs exhibit enhanced exciton diffusivity compared to single-component NC assemblies across the entire temperature range (from 5 to 298 K). The observed coherent and incoherent NC coupling and controllable excitonic transport within the solid NC SLs hold promise for applications in quantum optoelectronic devices.

Electrical manipulation of dissipation in microwave photon–magnon hybrid system through the spin Hall effect

Mon, 12 Feb 2024 00:00:00 GMT

Electrical manipulation of dissipation in microwave photon–magnon hybrid system through the spin Hall effect Hou, Justin T; Chou, Chung-Tao; Han, Jiahao; Fan, Yabin; Liu, Luqiao Hybrid dynamic systems combine advantages from different subsystems for realizing information processing tasks in both classical and quantum domains. However, the lack of controlling knobs in tuning system parameters becomes a severe challenge in developing scalable, versatile hybrid systems for useful applications. Here, we report an on-chip microwave photon–magnon hybrid system where the dissipation rates and the coupling cooperativity can be electrically influenced by the spin Hall effect. Through magnon–photon coupling, the linewidths of the resonator photon mode and the hybridized magnon polariton modes are effectively changed by the spin injection into the magnetic wires from an applied direct current, which exhibit different trends in samples with low and high coupling strengths. Moreover, the linewidth modification by the spin Hall effect shows strong dependence on the detuning of the two subsystems, in contrast to the classical behavior of a standalone magnonic device. Our results point to a direction of realizing tunable, on-chip, scalable magnon-based hybrid dynamic systems, where spintronic effects provide useful control mechanisms.

When Will (Game) Wars End?

Fri, 02 Jan 2026 00:00:00 GMT

When Will (Game) Wars End? Bhatia, Manan; Chin, Byron; Mani, Nitya; Mossel, Elchanan We study several variants of the classical card game war. As anyone who has played this game knows, the game can take some time to terminate, but it usually does. Here, we analyze a number of asymptotic variants of the game, where the number of cards is n, and show that all have an expected termination time of order 𝑛2. This is the same expected termination time as the game where at each turn a fair coin toss decides which player wins a card, known as Gambler’s Ruin and was studied by Blaise Pascal, Pierre de Fermat and others in the seventeenth century.

Semiconductor-free, monolithically 3D-printed logic gates and resettable fuses

Sat, 21 Sep 2024 00:00:00 GMT

Semiconductor-free, monolithically 3D-printed logic gates and resettable fuses Cañada, Jorge; Velásquez-García, Luis Fernando Additive manufacturing has the potential to enable the inexpensive, single-step fabrication of fully functional electromechanical devices. However, while the 3D printing of mechanical parts and passive electrical components is well developed, the fabrication of fully 3D-printed active electronics, which are the cornerstone of intelligent devices, remains a challenge. Existing examples of 3D-printed active electronics show potential but lack integrability and accessibility. This work reports the first active electronics fully 3D-printed via material extrusion, i.e. one of the most accessible and versatile additive manufacturing processes. The technology is proof-of-concept demonstrated through the implementation of the first fully 3D-printed, semiconductor-free, solid-state logic gates, and the first fully 3D-printed resettable fuses. The devices take advantage of a positive temperature coefficient phenomenon found to affect narrow traces of 3D-printed copper-reinforced, polylactic acid. Although the reported devices don’t perform competitively against semiconductor-enabled integrated circuits, the customisability and accessibility intrinsic to material extrusion additive manufacturing make this technology promisingly disruptive. This work serves as a steppingstone for the semiconductor-free democratisation of electronic device fabrication and is of immediate relevance for the manufacture of custom, intelligent devices far from traditional manufacturing centres.

Rapid large-scale building damage level classification after earthquakes using deep learning with Lidar and satellite optical data

Tue, 31 Dec 2024 00:00:00 GMT

Rapid large-scale building damage level classification after earthquakes using deep learning with Lidar and satellite optical data Liu, Chang; Ge, Linlin; Bai, Ting In post-earthquake scenarios, the swift assessment of building damage levels is pivotal for efficient emergency response and recovery planning. Nevertheless, conventional in-situ damage evaluations consume time. Current satellite-based deep learning methods save time but often lack detail, usually classifying damage as either collapsed or intact. This two-level information is not enough for rescue or recovery planning. Light Detection and Ranging (Lidar)-based deep learning methods, which provide three-dimensional (3D) information, could address this issue of damage details. Therefore, this paper proposes a deep learning-based building damage level classification method using both Lidar and satellite data. The proposed method classifies damage into four levels, including no/minor damage, partially collapsed, totally collapsed, and story failure. The developed network builds upon RandLA-Net, incorporating surface normal vectors to enhance accuracy. A colourised Lidar dataset was created for the network. The network underscores the advantage of incorporating surface normal information. A framework is also proposed based on the damage level outcomes of the developed network, which aids in emergency response efforts. Consequently, this paper demonstrates the practical utility of deep learning networks in rapidly assessing detailed building damage levels after earthquakes. Its practical contribution is guiding decision-making during the critical phases of post-earthquake response and recovery.

Cortical somatostatin innervation follows a unique experience-independent developmental trajectory

Tue, 13 Jan 2026 00:00:00 GMT

Cortical somatostatin innervation follows a unique experience-independent developmental trajectory Boivin, Josiah R; Schmerl, Bettina; Martin, Kendyll B; Lee, Chia-Fang; Nedivi, Elly Despite the critical role of inhibition in regulating developmental plasticity, there are significant gaps in our understanding of inhibitory synapse development, particularly for the vast majority of inhibitory synapses that reside on dendrites. Dendritic inhibitory synapses, canonically arising from somatostatin (SST)-expressing neurons, are challenging to detect electrophysiologically and difficult to visualize without a molecular tag. Here, we integrate a genetic synapse labeling strategy with epitope-preserving magnified analysis of proteome (eMAP), a combination of tissue expansion and clearing, to reveal the development of SST innervation in the primary visual cortex of male and female mice. Unlike excitatory innervation, which follows a deep to shallow progression and undergoes pruning, we find that SST bouton formation occurs simultaneously across all cortical layers and is not subject to a period of net pruning. SST bouton and synapse formation occur most dramatically in the days following eye opening and during the opening of the critical period for ocular dominance plasticity. Yet, despite a coincidence with these visual milestones, neither SST bouton nor synapse formation depend on visual experience. This is in contrast to excitatory and non-SST inhibitory synapses, whose development has been shown to depend heavily on visual experience. Thus, SST cortical innervation follows a unique developmental trajectory that is independent of sensory experience and is optimally timed to regulate processes that are fundamental to cortical circuit maturation. Significance statement During development, neurons form extensive synaptic connections while maintaining a delicate balance of excitation and inhibition. It is critical to understand how different subpopulations of synapses form during development, because perturbations in this precisely coordinated process can cause neurodevelopmental disorders. Here, we reveal at unprecedented resolution the development of cortical inhibitory innervation from somatostatin-expressing neurons, which canonically target dendrites. We show that somatostatin neurons follow different rules than other cell types during development, and somatostatin innervation is well-timed to contribute to developmental processes that are central to healthy cortical function. Our results provide new insights on how somatostatin neurons, a critically influential cell type, integrate into cortical circuitry during development.

Neruda through copper-coloured glasses: the role of place attachment in the embeddedness of Chilean entrepreneurship

Sat, 11 Jan 2025 00:00:00 GMT

Neruda through copper-coloured glasses: the role of place attachment in the embeddedness of Chilean entrepreneurship Burke, M. Kathleen; Conley, Mark A.; Jack, Sarah L. Despite scholarly interest in how emotional and instrumental place attachments motivate entrepreneurship, the influences on embeddedness remain underexplored. Building on the notion that entrepreneurship becomes embedded in a locality, we argue that this process is packed with place-based interpretations of the material and imagined reality. Engaging with the empirical setting of Chile, the world’s largest copper producer, we embark on a study examining the interactions between the place attachment, embeddedness and natural resource-based entrepreneurship. We uncover these interactions through analysing several works of poetry by Nobel laureate Pablo Neruda, which focus on the diverging place attachment styles between local and multinational agents. Through reflecting on the poems, we show how historical changes within the Chilean mining industry and broader societal changes are visible in Neruda’s imagery of place attachments, emotions and concerns for local conditions. We problematize embeddedness and entrepreneurship through illuminating the place attachments shaping local actors’ entrepreneurial imagination, thus contributing to knowledge about being embedded in natural resource-based entrepreneurship contexts. We provide new insights into how place attachment can evolve alongside different forms of embedded entrepreneurship.

Human-centric manufacturing culture: a research study of MedTech manufacturers in Ireland

Wed, 31 Dec 2025 00:00:00 GMT

Human-centric manufacturing culture: a research study of MedTech manufacturers in Ireland Rhodes, Donna H; Cuddy, Sara; Jeffers, Malcolm; O’Rourke, Fiona Digital manufacturing is rapidly evolving; however, this transformation is predominantly technology centric. Human-centric manufacturing shifts the paradigm for the digital manufacturing enterprise towards a human focus to realising its envisioned digital future. In that context, Digital Manufacturing Ireland (DMI), Ireland’s expert body for driving digital adoption across manufacturing, initiated a research study in collaboration with two research partners, MIT and IAAE, in support of this important focus for future manufacturing. This paper discusses results of the DMI 2023 human-Centric Manufacturing Culture Study, which engaged manufacturing leaders from 11 MedTech companies with major manufacturing sites in Ireland. Overall findings are discussed, with a focus on 12 emergent themes grouped in four categories: imperatives, values, strategies, and practices. Planned collaboration initiatives and anticipated future research are described. This paper also highlights considerations regarding new thinking needed by manufacturing leaders, along with recommendations as to what leaders can begin to do differently.

Decomposition of Frobenius pushforwards of line bundles on wonderful compactifications

Tue, 28 Jan 2025 00:00:00 GMT

Decomposition of Frobenius pushforwards of line bundles on wonderful compactifications Cai, Merrick; Krylov, Vasily De Concini and Procesi introduced varieties known as wonderful compactifications, which are smooth projective compactifications of semisimple adjoint groups G. We study the Frobenius pushforwards of line bundles on the wonderful compactifications, and in particular we decompose them into a direct sum of vector subbundles and explicitly describe the ranks. We are especially interested in when these subbundles are line bundles, and in the case of 𝐺=𝖯𝖲𝖫𝑛, we offer lower bounds on the multiplicities (as direct summands) for these line bundles.

BrepDiff: Single-Stage B-rep Diffusion Model

Sun, 27 Jul 2025 00:00:00 GMT

BrepDiff: Single-Stage B-rep Diffusion Model Lee, Mingi; Zhang, Dongsu; Jambon, Cl?ment; Kim, Young Min The Boundary Representation (B-rep) is a widely used 3D model representation of most consumer products designed with CAD software. However, its highly irregular and sparse set of relationships poses significant challenges for designing a generative model tailored to B-reps. Existing approaches use multi-stage approaches to satisfy the complex constraints sequentially. As a result, the final geometry cannot incorporate user edits due to the non-deterministic dependencies between cascaded stages. In contrast, we propose BrepDiff, a single-stage diffusion model for B-rep generation. We present a masked UV grid representation consisting of structured point samples from faces, serving as input for a diffusion transformer. By introducing an asynchronous and shifted noise schedule, we improve the training signal, enabling the diffusion model to better capture the distribution of UV grids. The explicitness of our masked UV grid representation enables users to intuitively understand and freely design surface geometry without being constrained by topological validity. The interconnectivity can be derived from the face layout, which is later processed into a valid solid volume during post-processing. Our approach achieves performance on par with state-of-the-art cascaded models while offering complex and diverse manipulations of geometry and topology, such as shape completion, merging, and interpolation. SIGGRAPH Conference Papers ’25, Vancouver, BC, Canada

SwiftSketch: A Diffusion Model for Image-to-Vector Sketch Generation

Sun, 27 Jul 2025 00:00:00 GMT

SwiftSketch: A Diffusion Model for Image-to-Vector Sketch Generation Arar, Ellie; Frenkel, Yarden; Cohen-Or, Daniel; Shamir, Ariel; Vinker, Yael Recent advancements in large vision-language models have enabled highly expressive and diverse vector sketch generation. However, state-of-the-art methods rely on a time-consuming optimization process involving repeated feedback from a pretrained model to determine stroke placement. Consequently, despite producing impressive sketches, these methods are limited in practical applications. In this work, we introduce SwiftSketch, a diffusion model for image-conditioned vector sketch generation that can produce high-quality sketches in less than a second. SwiftSketch operates by progressively denoising stroke control points sampled from a Gaussian distribution. Its transformer-decoder architecture is designed to effectively handle the discrete nature of vector representation and capture the inherent global dependencies between strokes. To train SwiftSketch, we construct a synthetic dataset of image-sketch pairs, addressing the limitations of existing sketch datasets, which are often created by non-artists and lack professional quality. For generating these synthetic sketches, we introduce ControlSketch, a method that enhances SDS-based techniques by incorporating precise spatial control through a depth-aware ControlNet. We demonstrate that SwiftSketch generalizes across diverse concepts, efficiently producing sketches that combine high fidelity with a natural and visually appealing style. SIGGRAPH Conference Papers ’25, Vancouver, BC, Canada

Lifting the Winding Number: Precise Discontinuities in Neural Fields for Physics Simulation

Sun, 27 Jul 2025 00:00:00 GMT

Lifting the Winding Number: Precise Discontinuities in Neural Fields for Physics Simulation Chang, Yue; Liu, Mengfei; Wang, Zhecheng; Chen, Peter Yichen; Grinspun, Eitan Cutting thin-walled deformable structures is common in daily life, but poses significant challenges for simulation due to the introduced spatial discontinuities. Traditional methods rely on mesh-based domain representations, which require frequent remeshing and refinement to accurately capture evolving discontinuities. These challenges are further compounded in reduced-space simulations, where the basis functions are inherently geometry- and mesh-dependent, making it difficult or even impossible for the basis to represent the diverse family of discontinuities introduced by cuts. Recent advances in representing basis functions with neural fields offer a promising alternative, leveraging their discretization-agnostic nature to represent deformations across varying geometries. However, the inherent continuity of neural fields is an obstruction to generalization, particularly if discontinuities are encoded in neural network weights. We present Wind Lifter, a novel neural representation designed to accurately model complex cuts in thin-walled deformable structures. Our approach constructs neural fields that reproduce discontinuities precisely at specified locations, without “baking in” the position of the cut line. To achieve this, we augment the input coordinates of the neural field with the generalized winding number of any given cut line, effectively lifting the input from two to three dimensions. Lifting allows the network to focus on the easier problem of learning a 3D everywhere-continuous volumetric field, while a corresponding restriction operator enables the final output field to precisely resolve strict discontinuities. Crucially, our approach does not embed the discontinuity in the neural network’s weights, opening avenues to generalization of cut placement. Our method achieves real-time simulation speeds and supports dynamic updates to cut line geometry during the simulation. Moreover, the explicit representation of discontinuities makes our neural field intuitive to control and edit, offering a significant advantage over traditional neural fields, where discontinuities are embedded within the network’s weights, and enabling new applications that rely on general cut placement. SIGGRAPH Conference Papers ’25, Vancouver, BC, Canada

Making Concurrent Hardware Verification Sequential

Fri, 13 Jun 2025 00:00:00 GMT

Making Concurrent Hardware Verification Sequential Bourgeat, Thomas; Liu, Jiazheng; Chlipala, Adam; Arvind Compared to familiar hardware-description languages like Verilog, rule-based languages like Bluespec offer opportunities to import modularity features from software programming. While Verilog modules are about connecting wires between submodules, Bluespec modules resemble objects in object-oriented programming, where interactions with a module occur only through calls to its methods. However, while software objects can typically be characterized one method at a time, the concurrent nature of hardware makes it essential to consider the repercussions of invoking multiple methods simultaneously. Prior formalizations of rule-based languages conceptualized modules by describing their semantics considering arbitrary sets of simultaneous method calls. This internalized concurrency significantly complicates correctness proofs. Rather than analyzing methods one-at-a-time, as is done when verifying software object methods, validating the correctness of rule-based modules necessitated simultaneous consideration of arbitrary subsets of method calls. The result was a number of proof cases that grew exponentially in the size of the module’s API. In this work, we side-step the exponential blowup through a set of judicious language restrictions. We introduce a new Bluespec-inspired formal language, Fjfj, that supports sequential characterization of modules, while preserving the concurrent hardware nature of the language. We evaluated Fjfj by implementing it in Coq, proving the key framework principle: the refinement theorem. We demonstrated Fjfj’s expressivity via implementation and verification of three examples: a pipelined processor, a parameterized crossbar, and a network switch.

Lilo: A Higher-Order, Relational Concurrent Separation Logic for Liveness

Wed, 09 Apr 2025 00:00:00 GMT

Lilo: A Higher-Order, Relational Concurrent Separation Logic for Liveness Lee, Dongjae; Lee, Janggun; Yoon, Taeyoung; Cho, Minki; Kang, Jeehoon; Hur, Chung-Kil Concurrent separation logic (CSL) has excelled in verifying safety properties across various applications, yet its application to liveness properties remains limited. While existing approaches like TaDA Live and Fair Operational Semantics (FOS) have made significant strides, they still face limitations. TaDA Live struggles to verify certain classes of programs, particularly concurrent objects with non-local linearization points, and lacks support for general liveness properties such as "good things happen infinitely often". On the other hand, FOS’s scalability is hindered by the absence of thread modular reasoning principles and modular specifications. This paper introduces Lilo, a higher-order, relational CSL designed to overcome these limitations. Our core observation is that FOS helps us to maintain simple primitives for our logic, which enable us to explore design space with fewer restrictions. As a result, Lilo adapts various successful techniques from literature. It supports reasoning about non-terminating programs by supporting refinement proofs, and also provides Iris-style invariants and modular specifications to facilitate modular verification. To support higher-order reasoning without relying on step-indexing, we develop a technique called stratified propositions inspired by Nola. In particular, we develop novel abstractions for liveness reasoning that bring these techniques together in a uniform way. We show Lilo’s scalability through case studies, including the first termination-guaranteeing modular verification of the elimination stack. Lilo and examples in this paper are mechanized in Coq.

Stochastic Lazy Knowledge Compilation for Inference in Discrete Probabilistic Programs

Fri, 13 Jun 2025 00:00:00 GMT

Stochastic Lazy Knowledge Compilation for Inference in Discrete Probabilistic Programs Bowers, Maddy; Lew, Alexander K.; Tenenbaum, Joshua B.; Solar-Lezama, Armando; Mansinghka, Vikash K. We present new techniques for exact and approximate inference in discrete probabilistic programs, based on two new ways of exploiting lazy evaluation. First, we show how knowledge compilation, a state-of-the art technique for exact inference in discrete probabilistic programs, can be made lazy, enabling asymptotic speed-ups. Second, we show how a probabilistic program’s lazy semantics naturally give rise to a division of its random choices into subproblems, which can be solved in sequence by sequential Monte Carlo with locally-optimal proposals automatically computed via lazy knowledge compilation. We implement our approach in a new tool, Pluck, and evaluate its performance against state-of-the-art approaches to inference in discrete probabilistic languages. We find that on a suite of inference benchmarks, lazy knowledge compilation can be faster than state-of-the-art approaches, sometimes by orders of magnitude.

Probabilistic Programming with Vectorized Programmable Inference

Thu, 08 Jan 2026 00:00:00 GMT

Probabilistic Programming with Vectorized Programmable Inference Becker, McCoy R.; Huot, Mathieu; Matheos, George; Wang, Xiaoyan; Chung, Karen; Smith, Colin; Ritchie, Sam; Saurous, Rif A.; Lew, Alexander K.; Rinard, Martin C.; Mansinghka, Vikash K. We present GenJAX, a new language and compiler for vectorized programmable probabilistic inference. GenJAX integrates the vectorizing map (vmap) operation from array programming frameworks such as JAX into the programmable inference paradigm, enabling compositional vectorization of features such as probabilistic program traces, stochastic branching (for expressing mixture models), and programmable inference interfaces for writing custom probabilistic inference algorithms. We formalize vectorization as a source-to-source program transformation on a core calculus for probabilistic programming ($\gen$), and prove that it correctly vectorizes both modeling and inference operations. We have implemented our approach in \href{https://github.com/probcomp/genjax}{the GenJAX language and compiler}, and have empirically evaluated this implementation on several benchmarks and case studies. Our results show that our implementation supports a wide and expressive set of programmable inference patterns and delivers performance comparable to hand-optimized JAX code.

Waste-Efficient Work Stealing

Wed, 28 Jan 2026 00:00:00 GMT

Waste-Efficient Work Stealing Singer, Kyle; Agrawal, Kunal; Schardl, Tao B. Although randomized work stealing is effective at automatically load-balancing task-parallel programs, it can waste computational resources when scheduling programs that lack sufficient parallelism to use all available threads. For such programs, threads will waste cycles attempting to steal parallel tasks when none are available. This waste can reduce the machine’s efficiency by wasting computational resources and energy and needlessly burdening the operating system. This paper introduces WEWS, a simple, practical, and provably efficient extension to randomized work stealing that mitigates waste. WEWS dynamically adjusts the number of active threads to reduce the waste of randomized work stealing. WEWS executes a parallel computation with the same asymptotic running time as traditional randomized work stealing while bounding the waste to O(min{PT∞, T1 + P2}) instructions. WEWS also follows the work-first principle to perform well in practice. WEWS requires no special support from the operating system or hardware, which simplifies its implementation. We implemented WEWS within the OpenCilk runtime system and compared it to other common waste-mitigation strategies. Across 10 parallel benchmarks, we find that WEWS has minimal impact on parallel running times while, on programs with limited parallelism, substantially reducing waste. PPoPP ’26, Sydney, NSW, Australia

UniTe: A Universal Tensor Abstraction for Capturing Spatial Relationships

UniTe: A Universal Tensor Abstraction for Capturing Spatial Relationships Ray, Jessica; Collin, Teodoro; Sze, Vivienne; Reuther, Albert; Amarasinghe, Saman Tensors are an integral part of numerous domains, and while significant effort has been put into the design of tensor data structures in isolation, little attention has been paid to the relationships that exist across tensors and how this affects their representation and use. In this paper, we focus on spatial relationships across tensors in a program, where such tensors are defined relative to a common reference coordinate system. These relationships are complicated by the fact that the tensors may differ in their representations, such as having variations in their axes, spacings, origins, and overall shape. Due to the lack of existing abstractions and language support for these types of tensor semantics, users are currently forced to manually perform the bookkeeping necessary to account for these varying relationships and representations. Unfortunately, we cannot rely on a simple library to capture these relationships, as computations on these types of tensors often happen at the innermost levels of programs; we find that the overheads associated with an unoptimized implementation quickly accumulate, leading to performance up to nearly 65x slower than a reference C implementation on a series of image and video compression benchmarks. In this paper, we introduce the novel UniTe abstraction, which captures spatial relationships across all such tensors in a program. We also introduce two domain-specific languages and optimizing compilers, CoLa for Python and SHiM for C/C++, built off of UniTe. Both CoLa and SHiM provide users an intuitive set of tensor primitives based on spatial relationships, hiding the complexity that goes into maintaining the tensors and computing accesses across them. In addition, we discuss the optimizations necessary to remove the associated abstraction overhead, and describe their implementations. On the benchmarks, we show that both CoLa and SHiM successfully remove the overheads, achieving performance parity with existing C implementations.

Triplet Exciton Sensitization of Silicon Mediated by Defect States in Hafnium Oxynitride

Mon, 23 Dec 2024 00:00:00 GMT

Triplet Exciton Sensitization of Silicon Mediated by Defect States in Hafnium Oxynitride Nagaya, Narumi; Alexiu, Alexandra; Perkinson, Collin F; Nix, Oliver M; Koh, Dooyong; Bawendi, Moungi G; Tisdale, William A; Van Voorhis, Troy; Baldo, Marc A Singlet exciton fission has the potential to increase the efficiency of crystalline silicon solar cells beyond the conventional single junction limit. Perhaps the largest obstacle to achieving this enhancement is uncertainty about energy coupling mechanisms at the interfaces between silicon and exciton fission materials such as tetracene. Here, the previously reported silicon‐hafnium oxynitride‐tetracene structure is studied and a combination of magnetic‐field‐dependent silicon photoluminescence measurements and density functional theory calculations is used to probe the influence of the interlayer composition on the triplet transfer process across the hafnium oxynitride interlayer. It is found that hafnium oxide interlayers do not show triplet exciton sensitization of silicon, and that nitrogen content in hafnium oxynitride layers is correlated with enhanced sensitization. Calculation results reveal that defects in hafnium oxynitride interlayers with higher nitrogen content introduce states close to the band‐edge of silicon, which can mediate the triplet exciton transfer process. Some defects introduce additional deleterious mid‐gap states, which may explain observed silicon photoluminescence quenching. These results show that band‐edge states can mediate the triplet exciton transfer process, potentially through a sequential charge transfer mechanism.

Layered Metal–Organic Chalcogenides: 2D Optoelectronics in 3D Self-Assembled Semiconductors

Wed, 26 Mar 2025 00:00:00 GMT

Layered Metal–Organic Chalcogenides: 2D Optoelectronics in 3D Self-Assembled Semiconductors Paritmongkol, Watcharaphol; Feng, Zhifu; Refaely-Abramson, Sivan; Tisdale, William A; Kastl, Christoph; Maserati, Lorenzo Molecular self-assembly offers an effective and scalable way to design nanostructured materials with tunable optoelectronic properties. In the past 30 years, organic chemistry has delivered a plethora of metal-organic structures based on the combination of organic groups, chalcogens, and a broad range of metals. Among these, several layered metal-organic chalcogenides (MOCs)─including "mithrene" (AgSePh)─recently emerged as interesting platforms to host 2D physics embedded in 3D crystals. Their combination of broad tunability, easy processability, and promising optoelectronic performance is driving a renewed interest in the more general material group of "low-dimensional" hybrids. In addition, the covalent MOC lattice provides higher stability compared with polar materials in operating devices. Here, we provide a perspective on the rise of 2D MOCs in terms of their synthesis approaches, 2D quantum confined exciton physics, and potential future applications in UV and X-ray photodetection, chemical sensors, and electrocatalysis.

Exciton fission enhanced silicon solar cell

Wed, 16 Jul 2025 00:00:00 GMT

Exciton fission enhanced silicon solar cell Nagaya, Narumi; Lee, Kangmin; Perkinson, Collin F; Li, Aaron; Lee, Youri; Zhong, Xinjue; Lee, Sujin; Weisburn, Leah P; Wang, Janet Z; Baikie, Tomi K; Bawendi, Moungi G; Van Voorhis, Troy; Tisdale, William A; Kahn, Antoine; Seo, Kwanyong; Baldo, Marc A While silicon solar cells dominate global photovoltaic energy production, their continued improvement is hindered by the single-junction limit. One potential solution is to use molecular singlet exciton fission to generate two electrons from each absorbed high-energy photon. We demonstrate that the long-standing challenge of coupling molecular excited states to silicon solar cells can be overcome using sequential charge transfer. Combining zinc phthalocyanine, aluminum oxide, and a shallow junction crystalline silicon microwire solar cell, the peak charge generation efficiency per photon absorbed in tetracene is (138% ± 6%), comfortably surpassing the quantum efficiency limit for conventional silicon solar cells and establishing a new, scalable approach to low-cost, high-efficiency photovoltaics.

1D Silver Organochalcogenide Semiconductors: Color Tunable Luminescence, Polarized Emission, and Long-Range Exciton Diffusion

Tue, 14 Oct 2025 00:00:00 GMT

1D Silver Organochalcogenide Semiconductors: Color Tunable Luminescence, Polarized Emission, and Long-Range Exciton Diffusion Sakurada, Tomoaki; Pathoor, Nithin; Matsumoto, Takuma; Khamlue, Rattapon; Chatsiri, Petcharaphorn; Valenta, Jan; Kawamoto, Tadashi; Omagari, Shun; Tisdale, William A; Paritmongkol, Watcharaphol; Cho, Yeongsu; Vacha, Martin Metal organochalcogenides (MOCs) represent a promising class of organic-inorganic hybrid semiconductors with unique light-matter interactions. Their hybrid nature enables extensive structural and optoelectronic tunability via ligand engineering. In this study, we systematically modulated the electronic properties of ligands using Cl and Me functional groups, achieving precise control over the optoelectronic properties of Ag-based MOCs. Structural analysis revealed that these MOCs adopt a one-dimensional (1D) chain structure with organic ligands surrounding a Ag-chalcogen core. Density functional theory (DFT) calculations demonstrated that MOCs exhibit characteristics of 1D semiconductors with strongly dispersive conduction and valence bands aligned along the crystal rod directions. Experimentally, the MOCs displayed bright luminescence, with peaks centered between 560 and 690 nm. The substitution of Cl with Me groups in the benzene ligands induced a red shift in both absorption and photoluminescence, corroborated by experimental and theoretical analyses. Further optical measurements indicated that the emission from the MOCs is strongly polarized along the chain directions. Notably, Se-based MOCs exhibited enhanced exciton diffusivity along the chain axis with a diffusion length of 130 nm, which is among the highest reported for covalent systems. The observed trend in carrier diffusivity among individual compounds is attributed to differences in the effective masses of the carriers, as determined by DFT calculations. Our findings offer valuable insights into the systematic structural and property tuning of hybrid semiconductors and highlight the unique characteristics of the 1D MOC family.

Excitonic Anisotropy in Single‐Crystalline 2D Silver Phenylchalcogenides

Thu, 30 Oct 2025 00:00:00 GMT

Excitonic Anisotropy in Single‐Crystalline 2D Silver Phenylchalcogenides Lee, Woo Seok; Cho, Yeongsu; Posmyk, Katarzyna; Peksa, Paulina; Dyksik, Mateusz; Samulewicz, Nicholas; Plochocka, Paulina; Baranowski, Michał; Kulik, Heather J; Tisdale, William A 2D materials exhibiting in‐plane anisotropy enable new applications in directional energy transport and polarized optical response. Silver phenylchalcogenides (AgEPh) – including mithrene (AgSePh), tethrene (AgTePh), and thiorene (AgSPh) – represent an exciting new addition to this family, with optical response spanning the visible to near‐UV. Here, excitonic anisotropy is predicted and characterized in this family of materials using a combination of ab initio theory and optical micro‐spectroscopy of single‐crystalline flakes. Using density functional theory and GW with the Bethe–Salpeter equation calculations, it is revealed that all AgEPh compounds exhibit anisotropic electronic band structure and host multiple delocalized excitons with in‐plane anisotropy. Room‐temperature polarization‐resolved optical micro‐spectroscopy shows that orthogonally polarized excitons with similar energy lead to nearly isotropic absorption in AgSPh, whereas energy separation between excitonic resonances in AgSePh and AgTePh leads to strong absorption and emission anisotropy. Cryogenic reflectance micro‐spectroscopy further reveals exciton fine structure in AgSePh, reconciling the discrepancies between room‐temperature experiments and theoretical predictions. Finally, it is demonstrated that the optical response of thicker AgEPh crystals is influenced by photonic effects arising from finite crystal size. Overall, this work advances the understanding of the relationship between anisotropic structure, composition, and excitonic properties in AgEPh, providing a foundation for technological integration.

Revolutionize cold chain: an AI/ML driven approach to overcome capacity shortages

Wed, 19 Mar 2025 00:00:00 GMT

Revolutionize cold chain: an AI/ML driven approach to overcome capacity shortages Jackson, Ilya; Namdar, Jafar; Saénz, Maria Jesús; Elmquist III, Richard Augustus; Dávila Novoa, Luis Rodrigo This research investigates how Artificial Intelligence (AI) and Machine Learning (ML) forecasting methodologies can be leveraged for cold chain capacity planning, specifically utilising Prophet and Seasonal Autoregressive Integrated Moving Average parametrised through grid search. In collaboration with Americold, the world's second-largest refrigerated logistic service provider, the study explores the challenges and opportunities in applying AI/ML techniques to complex operations covering 385 customers and a capacity of 73,296 pallet positions. We train and test several AI/ML and traditional statistical models using extensive data for every customer over 3.5 years. Based on the results, MAPE of 5.28% was achieved on the whole site level, and SARIMA outperformed ML models in most cases. Next, we show that developing and applying a Customer Segmentation Matrix has enabled more accurate forecasting and planning across various customer segments, addressing the issue of forecasting inaccuracies. This approach effectively improves forecasting inaccuracies, underscoring the significance of tailoring AI/ML models for demand forecasting within the cold-chain industry. Ultimately, this research presents an AI-driven approach that transcends mere forecasting, offering a practical pathway to manage capacity in light of the constraints.

Beyond binary group categorization: towards a dynamic view of human groups

Sun, 01 Sep 2024 00:00:00 GMT

Beyond binary group categorization: towards a dynamic view of human groups Kish Bar-On, Kati Society is a composite of interacting people and groups. These groups play a significant role in maintaining social status, establishing group identity and social identity, and enforcing norms. As such, groups are essential for understanding human behavior. Nevertheless, the study of groups in everyday group life yields many diverse and sometimes contradicting theories of group behavior, and researchers tend to agree that we have yet to understand the emergence of groups out of aggregates of individuals. The current paper aims to shed new light on the convoluted interrelation between groups and individuals by focusing on individuals’ social identities and group categorization. It does so by exploring the dynamic nature of the self and its implications on identity and group membership, and introducing a framework recognizing the fluidity of groups and group categorization. Incorporating historical insights with contemporary theories, this paper argues for a flexible understanding of group dynamics that surpasses rigid in-group and out-group classifications, proposing instead that group affiliations exist along a continuum that reflects the ever-changing social landscape.

Reparative Urban Science: Challenging the Myth of Neutrality and Crafting Data-Driven Narratives

Sun, 26 May 2024 00:00:00 GMT

Reparative Urban Science: Challenging the Myth of Neutrality and Crafting Data-Driven Narratives So, Wonyoung I offer how urban planning should approach technology within the context of systemic racism, advocating for a reparative approach to address the issues of urban technology perpetuating today’s racial inequality and hindering efforts to redress historical oppression. I identify three mechanisms – formalization, context removal and legitimization, and penalization and extraction – that illustrate how urban technology perpetuates historical inequalities, often penalizing marginalized groups under the pretext of neutrality and fairness. Then, I discuss methodologies of reparative urban science, aiming to use urban technology to challenge race-neutral ideologies and create data-driven narratives for reparations.

What determines EV architecture? An analysis of the most influential battery electric vehicle design decisions from market data

Tue, 12 Aug 2025 00:00:00 GMT

What determines EV architecture? An analysis of the most influential battery electric vehicle design decisions from market data Khan, Mumin; Cameron, Bruce The penetration and variety of Battery Electric Vehicles (BEVs) in the automotive sector have been growing rapidly. While there is substantial research on hybrid ICE-battery vs. battery-only choices, little work has examined whether a dominant design for BEVs is emerging, as predicted by the innovation literature. This study provides a comprehensive exploration of BEV architectures, examining the influence of individual architectural decisions on vehicle performance and market prevalence. This study utilizes multivariate linear regression to analyze a curated dataset of global BEV models from 2022 and 2023, focusing on candidate architectural decisions such as battery cathode composition, battery voltage choice, number of motors, and drive layout. Our research aims to identify potential dominant designs by assessing their impact on performance metrics. The analysis then leverages statistical tools to evaluate the correlation between these architectural decisions and vehicle performance, using range as a primary indicator of consumer appeal. Findings from this research indicate significant variance in the adoption of specific BEV architectures, suggesting that the market has not yet consolidated down to a dominant design. We observe, however, that range is most strongly influenced by the architectural decisions for battery capacity, drive type, and motor type.

Chemical and Chemical-Mechanical Polishing of Surface Roughness on L-PBF/GRCop-42 Cu-Cr-Nb Additive Manufactured 10-GHz RF Structures

Tue, 30 Sep 2025 00:00:00 GMT

Chemical and Chemical-Mechanical Polishing of Surface Roughness on L-PBF/GRCop-42 Cu-Cr-Nb Additive Manufactured 10-GHz RF Structures Seltzman, AH; Wukitch, SJ Laser-based powder bed fusion (L-PBF) allows additive manufacture (AM) of lower hybrid current drive (LHCD) radio-frequency (RF) launchers from Glenn Research Copper, a Cr2Nb precipitation-hardened alloy (GRCop-42) in configurations unachievable with conventional machining. Rough surfaces in AM components increase RF losses and lead to arcing in high-power vacuum RF applications. Chemical polishing, chemical-mechanical polishing, or a combination of both were utilized to planarize the internal surfaces of RF structures, resulting in surface roughness as low as Ra = 0.2 µm. Refinement in polishing techniques now enables GRCop-42 alloys (4 at. % Cr, 2 at. % Nb) to achieve similar surface roughness to GRCop-84 (8 at. % Cr, 4 at. % Nb) and equivalent cavity losses to extruded oxygen-free copper waveguides at 10 GHz.

The Name of Moses in an Egyptian Context—A Hypothetical Etymology

Thu, 02 Jan 2025 00:00:00 GMT

The Name of Moses in an Egyptian Context—A Hypothetical Etymology Adair, Aaron The etymological origins of the name “Moses” have been unclear, but an Egyptian candidate is the most likely hypothesis. In this article, a new proposal is given that finds the best candidate as the Demotic word, mšꜥ, but only in the late Persian period or later would it fit the Hebrew Mōše. Evidence from Greek orthography and testimony from Manetho provide a stronger basis for this proposal over prior candidates. However, this results in a Hellenistic-era inclusion of “Moses” into the Exodus narrative.

Making Sense of Models: Connecting Science and Math Through Decoding and Modifying Computational Models

Mon, 24 Feb 2025 00:00:00 GMT

Making Sense of Models: Connecting Science and Math Through Decoding and Modifying Computational Models Lee, Irene A.; Sagartz, Mary; Meyer, Patricia; Anderson, Emma The Making Sense of Models (MSM) curriculum was designed to bridge math and science learning through agent-based modeling and rich computational thinking investigations that do not require teaching computer programming in middle school classrooms. The MSM curriculum supports students in the NGSS skill of reasoning about how and why a phenomenon happens. After developing decoding skills, students are able to assess the validity of a model based on comparing mechanisms in the model to what they learned about the phenomenon being modeled. In this article, the authors describe the decoding approach and how the MSM curriculum supports students’ ability to reason about scientific models and the real world.

Thermal analog computing: Application to matrix-vector multiplication with inverse-designed metastructures

Thu, 29 Jan 2026 00:00:00 GMT

Thermal analog computing: Application to matrix-vector multiplication with inverse-designed metastructures Silva, Caio; Romano, Giuseppe The rising computational demand of modern workloads has renewed interest in energy-efficient paradigms, such as neuromorphic and analog computing. A fundamental operation in these systems is matrix-vector multiplication (MVM), ubiquitous in signal processing and machine learning. Here, we demonstrate MVM using inverse-designed metastructures that exploit heat conduction as the signal carrier. The proposed approach is based on a generalization of effective thermal conductivity to systems with multiple input and output ports: The input signal is encoded as a set of applied temperatures, while the output is represented by the power collected at designated terminals. The metastructures are obtained via density-based topology optimization, enabled by a differentiable thermal transport solver and automatic differentiation, achieving an accuracy greater than 99% in most cases across a pool of matrices with dimensions 2 ×2 and 3 ×3. We apply this methodology—termed thermal analog computing—to realize matrices relevant to practical tasks, including the discrete Fourier transform and convolutional filters. These findings open avenues for analog information processing in thermally active environments, including temperature-gradient sensing in microelectronics and thermal control systems.

When competition becomes contagious: Strategic arms racing spillovers, alliance politics, and the Sino-American nuclear competition

Sun, 10 Aug 2025 00:00:00 GMT

When competition becomes contagious: Strategic arms racing spillovers, alliance politics, and the Sino-American nuclear competition Seitz, Samuel M.; Ji, Elliot S. The development of new conventional counterforce systems and improved missile defence systems enables non-nuclear states to directly influence the strategic nuclear balance. These dynamics increase the possibility of strategic arms racing spillovers, where arms racing in one dyad yields capabilities that threaten third parties’ arsenals and thus creates a type of security dilemma. It also increases the risk of non-nuclear allies entrapping their nuclear patrons in strategic arms racing. We illustrate this argument via the case of North and South Korea’s arms racing.

Building communities of critical inquiry in the language classroom

Thu, 02 Oct 2025 00:00:00 GMT

Building communities of critical inquiry in the language classroom Dessein, Eva; Ledford, Julian A Addressing issues of power, difference, and social stratification is essential in language education, where systemic inequities shape classroom experiences. This study examines the design and impact of three targeted modules implemented in beginner and intermediate French courses at two U.S. institutions. Grounded in critical pedagogical principles, the modules focused on language and power, inclusive language practices, and cultural and intercultural awareness. They aimed to foster critical inquiry through individual reflection and engagement with socially relevant topics. Analysis of student reflections and survey responses indicates that the modules supported learners in critically examining how language reinforces or challenges inequities, particularly in relation to gender biases and colonial legacies. Students reported increased awareness of linguistic hierarchies, a stronger sense of agency, and deeper reflection on language’s sociopolitical dimensions. The modules also encouraged engagement with inclusive language and cultural diversity. While the interventions promoted critical awareness and personal growth, findings point to limited peer interaction and community-building. This suggests a need for more structured opportunities for dialogic learning. Overall, the study highlights the transformative potential of critical pedagogy in language education and the importance of designing inclusive curricula that prepare students to reflect on and challenge systemic inequities.

Managing technology-related disruptions and vulnerabilities in highly automated warehouse systems: an integrative review and research agenda

Fri, 05 Sep 2025 00:00:00 GMT

Managing technology-related disruptions and vulnerabilities in highly automated warehouse systems: an integrative review and research agenda Rodríguez-García, Miguel; Kembro, Joakim Hans; Betts, Kellen; Ponce-Cueto, Eva Recent technological developments in warehousing have introduced new risks. This paper presents an integrative review that combines insights from highly automated warehouse systems (HAWS) and risk management, providing a comprehensive understanding of technology-related warehouse disruptions and vulnerabilities. We identify five major disruptions that can affect HAWS: cyberattacks, technology sabotage, technology failures, power and network outages, and human-machine interaction issues. Moreover, we identify 48 technology-related vulnerabilities across all disruptions. In particular, HAWS have become vulnerable to cyberattacks due to the increasing number of warehouse technology suppliers, greater complexity of multi-robot networks such as AMRs, reliance on cloud-based systems, and cascading effect of cyberattacks due to higher levels of interconnectivity in HAWS networks. Our review also shows that risk management strategies in HAWS are unevenly covered in the literature. In response, we propose a research agenda with 17 pathways aimed at enhancing prevention, detection, mitigation, and recovery strategies for HAWS. Managers also benefit from the identified disruptions and vulnerabilities, as they serve as a reference point for understanding their specific technology-related risks in HAWS. In addition, managers can use our review of current risk management practices as a benchmark and our research agenda to think about areas that they could develop further.

Preliminary Investigation of Gamma Radiation on the Chemical and Physical Characteristics of an Organic Coolant

Fri, 05 Dec 2025 00:00:00 GMT

Preliminary Investigation of Gamma Radiation on the Chemical and Physical Characteristics of an Organic Coolant Vasquez, Angel; Seshadri, Arunkumar; Shirvan, Koroush; Buongiorno, Jacopo Organic-cooled reactor concepts offer potential advantages over traditional light water reactors, including operation at elevated temperatures and reduced pressures. However, radiation-induced degradation of organic coolants remains a critical concern requiring thorough investigation. This study examines the effects of gamma irradiation (1-MGy dose) on Dowtherm A (27% biphenyl, 73% diphenyl ether) under varying atmospheric conditions (ambient air versus argon) and temperatures (room temperature versus 250°C). Chemical characterization using Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy (UV-Vis), and gas chromatography-mass spectrometry revealed the formation of higher molecular weight byproducts, including terphenyls and quaterphenyls, along with notable biphenyl degradation. Physical property measurements using differential scanning calorimetry, rheometry, and thermal conductivity analysis demonstrated significant changes in the thermophysical properties, including decreased heat capacity and viscosity, with increased thermal conductivity observed under argon irradiation conditions. Pronounced photodarkening occurred in all the irradiated samples, with atmospheric conditions significantly influencing degradation pathways. UV-Vis analysis indicated that oxygen presence during irradiation suppresses certain chromophoric species formation. These findings provide crucial insights into radiation-induced degradation mechanisms and their impact on coolant performance, informing future organic coolant system design and optimization strategies for advanced reactor applications.

Housing data politics in the United States: Inequitable open data, informal networks, and strategic neutrality

Thu, 11 Sep 2025 00:00:00 GMT

Housing data politics in the United States: Inequitable open data, informal networks, and strategic neutrality Aizman, Asya; So, Wonyoung; Navalkha, Chenab; D’Ignazio, Catherine Open housing data—property transactions, eviction filings, 311 complaints, and rental registries—have been a crucial resource for policymaking and real estate professionals. Meanwhile, housing data actors increasingly collect, analyze, and use data to address housing inequality, including efforts related to eviction prevention and land use reform, among others. This paper examines the motivations and practices of grassroots and institutional housing data actors. From a field scan of 67 entities engaged in housing data work across 12 U.S. states and 18 municipalities, we conducted 18 in-depth interviews to explore how housing data actors operate, their political goals, and data processes. We put forward a two‑axis framework that positions housing data actors according to their organizational structure (institutional/grassroots) and their stated data ideology (neutral/political). This framework contributes to understanding how different actors navigate complex issues such as embedded power dynamics and ethics in housing data. This two-axis view supplies a vocabulary for tracing how normative commitments and material constraints shape housing data pipelines and, ultimately, housing outcomes across the broader housing information ecosystem.

Unconstrained Sovereignty: Delegation of Authority and Reversibility

Fri, 17 Oct 2025 00:00:00 GMT

Unconstrained Sovereignty: Delegation of Authority and Reversibility Grinberg, Mariya The concept of sovereignty shapes our understanding of the world. Yet our current understanding of sovereignty conflates delegation of authority with loss of sovereignty. Delegation is relatively cheap, quick, and leads to an assured outcome; it’s an affirmation of sovereignty. Use of force, however, is required to regain lost sovereignty. I propose a definition of sovereignty that draws a clear distinction between sovereignty and delegated authority. Adopting this definition shows that sovereignty applies across time and space, it is indivisible, institutions do not place permanent constraints on supreme authority, and popular sovereignty is not a well-grounded concept.

Concurrent Balanced Augmented Trees

Wed, 28 Jan 2026 00:00:00 GMT

Concurrent Balanced Augmented Trees Wrench, Evan; Singh, Ajay; Roh, Younghun; Fatourou, Panagiota; Jayanti, Siddhartha; Ruppert, Eric; Wei, Yuanhao Augmentation makes search trees tremendously more versatile, allowing them to support efficient aggregation queries, order-statistic queries, and range queries in addition to insertion, deletion, and lookup. In this paper, we present the first lock-free augmented balanced search tree supporting generic augmentation functions. Our algorithmic ideas build upon a recent augmented unbalanced search tree presented by Fatourou and Ruppert [DISC, 2024]. We implement both data structures, solving some memory reclamation challenges in the process, and provide an experimental performance analysis of them. We also present optimized versions of our balanced tree that use delegation to achieve better scalability and performance (by more than 2x in most workloads). Our experiments show that our augmented balanced tree completes updates 2.2 to 30 times faster than the unbalanced augmented tree, and outperforms unaugmented trees by up to several orders of magnitude on 120 threads. PPoPP ’26, Sydney, NSW, Australia

Building Intelligent Agents with Neuro-Symbolic Concepts

Wed, 28 Jan 2026 00:00:00 GMT

Building Intelligent Agents with Neuro-Symbolic Concepts Mao, Jiayuan; Tenenbaum, Joshua; Wu, Jiajun This article presents a concept-centric paradigm for building agents that can learn continually and reason flexibly. The concept-centric agent utilizes a vocabulary of neuro-symbolic concepts. These concepts, such as object, relation, and action concepts, are grounded on sensory inputs and actuation outputs. They are also compositional, allowing for the creation of novel concepts through their structural combination. To facilitate learning and reasoning, the concepts are typed and represented using a combination of symbolic programs and neural network representations. Leveraging such neuro-symbolic concepts, the agent can efficiently learn and recombine them to solve various tasks across different domains, ranging from 2D images, videos, 3D scenes, and robotic manipulation tasks. This concept-centric framework offers several advantages, including data efficiency, compositional generalization, continual learning, and zero-shot transfer.

Foundational Verification of Running-Time Bounds for Interactive Programs

Thu, 08 Jan 2026 00:00:00 GMT

Foundational Verification of Running-Time Bounds for Interactive Programs Tockman, Andy; Singh, Pratap; Erbsen, Andres; Gruetter, Samuel; Chlipala, Adam Some important domains of software demand concrete bounds on how long functions may run, for instance for real-time cyberphysical systems where missed deadlines may damage industrial machinery. Such programs may interact with external devices throughout execution, where time deadlines ought to depend on, for instance, sensor readings (e.g. we only scramble to close a valve immediately when a sensor reports that a tank is about to overflow). We present the first software-development toolchain that delivers first-principles proofs of meaningful time bounds for interactive machine code, while allowing all per-application programming and verification to happen at the source-code level. We allow C-like programs to be proved against separation-logic specifications that also constrain their running time, and such proofs are composed with verification of a compiler to RISC-V machine code. All components are implemented and proved inside the Rocq proof assistant, producing final theorems whose statements depend only on machine-language formal semantics and some elementary specification constructions for describing running time. As a capstone case study, we extended a past verification (of a real microcontroller-based cyberphysical system) to bound time between arrival of network packets and actuation of an attached device. CPP ’26, Rennes, France

Network-RBV for Critical Minerals: How Standards, Permits, and Licensing Shape Midstream Bottlenecks

Tue, 20 Jan 2026 00:00:00 GMT

Network-RBV for Critical Minerals: How Standards, Permits, and Licensing Shape Midstream Bottlenecks Kegenbekov, Zhandos; Alipova, Alima; Jackson, Ilya Critical mineral supply chains underpin electric mobility, power electronics, clean hydrogen, and advanced manufacturing. Drawing on the resource-based view (RBV), the relational view, and dynamic capabilities, we conceptualize advantage not as ownership of ore bodies but as orchestration of multi-tier resource systems: upstream access, midstream processing know-how, standards and permits, and durable inter-organizational ties. In a world of high concentration at key stages (refining, separation, engineered materials), full “decoupling” is economically costly and technologically constraining. We argue for structured cooperation among the United States, European Union, China, and other producers and consumers, combined with selective domestic capability building for bona fide security needs. Methodologically, we conduct a structured conceptual synthesis integrating RBV, relational view, dynamic capabilities, and network-of-network research, combined with a structured comparative policy analysis of U.S./EU/Chinese instruments anchored in official documents. We operationalize the argument via technology–material dependency maps that identify midstream bottlenecks and the policy/standard levers most likely to expand qualified, compliant capacity.

REEV SENSE IMUs for Spatiotemporal Gait Analysis in Post-Stroke Patients: Validation Against Optical Motion Capture

Sun, 18 Jan 2026 00:00:00 GMT

REEV SENSE IMUs for Spatiotemporal Gait Analysis in Post-Stroke Patients: Validation Against Optical Motion Capture Marsan, Thibault; Clauzade, Sacha; Zhang, Xiang; Grandin, Nicolas; Urman, Tatiana; Linton, Evan; Sibachir, Samy; Ricciardi, Catherine E.; Temporelli, Robin Objective gait assessment is essential for post-stroke rehabilitation monitoring, yet optical motion capture systems remain inaccessible to most clinical settings due to cost and infrastructure constraints. This study assessed the validity of the REEV SENSE IMU for measuring spatiotemporal gait parameters in post-stroke individuals and evaluated assistive device effects on measurement accuracy. Twenty chronic post-stroke participants were enrolled, and fourteen completed the study (ten without an assistive device, four using a cane) after applying pre-defined exclusion criteria (walking speed <0.28 m/s, n = 6). Participants walked at self-selected speed while simultaneously being recorded by REEV SENSE IMUs and optical motion capture. Spatiotemporal parameters from matched heel strikes were compared using intraclass correlation coefficients (ICC), mean relative error (MRE), and Bland–Altman analysis. Temporal parameters demonstrated excellent reliability: contact time (ICC 0.96–0.99, MRE 2.77–5.45%), stride duration (ICC 0.95–0.99, MRE 2.57–2.62%), and cadence (ICC 0.98–0.99, MRE 1.80–1.93%). Spatial parameters showed greater variability, with stride length degrading substantially in slow-walking conditions (Cane group: ICC 0.76, MRE 8.60%). REEV SENSE provides reliable temporal parameter measurement comparable to commercial systems, positioning it as a practical tool for clinical gait monitoring in post-stroke rehabilitation. However, spatial parameter accuracy requires cautious interpretation in slow-walking regimes, necessitating independent validation when clinical decisions depend on precise stride length estimates.

Who Am I? Eyebrow Follicles Minimize Donor-Derived DNA for Germline Testing After Hematopoietic Stem Cell Transplantation

Sun, 11 Jan 2026 00:00:00 GMT

Who Am I? Eyebrow Follicles Minimize Donor-Derived DNA for Germline Testing After Hematopoietic Stem Cell Transplantation Mertens, Matthias; Sadlo, Mona; Kühl, Jörn-Sven; Metzeler, Klaus; Zschenderlein, Louisa; Edelmann, Jeanett; Lehmann, Claudia; Thull, Sarah; Karakaya, Mert; Velmans, Clara; Tumewu, Theresa; Böhme, Matthias; Klötzer, Christina; Weigert, Anne; Vucinic, Vladan; Hentschel, Julia; Mertens, Mareike Germline genetic testing plays a critical role in diagnosing inherited predispositions and increasingly guides therapeutic and surveillance choices—but becomes technically challenging after allogeneic hematopoietic stem cell transplantation (HSCT), when donor-derived DNA contaminates host tissues. To address this, we compared donor-derived DNA across three accessible tissues—buccal swab, nail, and eyebrow follicles—in recipients after hematopoietic stem cell transplantation using two orthogonal assays (34-SNP next-generation sequencing and a 27-marker short tandem repeat panel) and modeled clinical covariates that influence chimerism. Eyebrow follicles showed consistently low donor DNA (median 1% by NGS; 3% by STR) whereas buccal swabs and nails carried substantially higher donor fractions (+25 and +22 percentage points versus eyebrow, respectively; both p < 0.01). Across methods, STR yielded on average ≈6 percentage points higher donor fractions than NGS at low-level chimerism. Several transplant covariates correlated with chimerism: matched-related donors and a perfect HLA match (10/10) were each associated with lower donor DNA (≈12–14 and 15–20 percentage points, respectively); longer times since hematopoietic stem cell transplantation correlated with lower levels for nail samples, and donor–recipient sex match correlated with higher donor DNA (~7–8 percentage points). Even low-level chimerism can distort germline variant interpretation. We propose a pragmatic protocol for post-hematopoietic stem cell transplantation germline testing that prioritizes eyebrow follicles as the default tissue. An SNP-based quality control assay is used to flag unsafe donor fractions (≥ 5–10%) before comprehensive germline analysis, reducing the risk that chimeric donor DNA distorts germline variant interpretation.

Quantum Circuits Are Just a Phase

Thu, 08 Jan 2026 00:00:00 GMT

Quantum Circuits Are Just a Phase Heunen, Chris; Lemonnier, Louis; McNally, Christopher; Rice, Alex Quantum programs today are written at a low level of abstraction---quantum circuits akin to assembly languages - and the unitary parts of even advanced quantum programming languages essentially function as circuit description languages. This state of affairs impedes scalability, clarity, and support for higher-level reasoning. More abstract and expressive quantum programming constructs are needed. To this end, we introduce a simple syntax for generating unitaries from "just a phase"; we combine a (global) phase operation that captures phase shifts with a quantum analogue of the "if let" construct that captures subspace selection via pattern matching. This minimal language lifts the focus from gates to eigendecomposition, conjugation, and controlled unitaries; common building blocks in quantum algorithm design. We demonstrate several aspects of the expressive power of our language in several ways. Firstly, we establish that our representation is universal by deriving a universal quantum gate set. Secondly, we show that important quantum algorithms can be expressed naturally and concisely, including Grover's search algorithm, Hamiltonian simulation, Quantum Fourier Transform, Quantum Signal Processing, and the Quantum Eigenvalue Transformation. Furthermore, we give clean denotational semantics grounded in categorical quantum mechanics. Finally, we implement a prototype compiler that efficiently translates terms of our language to quantum circuits, and prove that it is sound with respect to these semantics. Collectively, these contributions show that this construct offers a principled and practical step toward more abstract and structured quantum programming.

A Digital Engineering Framework for Piston Pin Bearings via Multi-Physics Thermo-Elasto-Hydrodynamic Modeling

Sat, 10 Jan 2026 00:00:00 GMT

A Digital Engineering Framework for Piston Pin Bearings via Multi-Physics Thermo-Elasto-Hydrodynamic Modeling Shu, Zhiyuan; Tian, Tian The piston pin operates under severe mechanical and thermal conditions, making accurate lubrication prediction essential for engine durability. This study presents a comprehensive digital engineering framework for piston pin bearings, built upon a fully coupled thermo-elasto-hydrodynamic (TEHD) formulation. The framework integrates: (1) a Reynolds-equation hydrodynamic solver with temperature-/pressure-dependent viscosity and cavitation; (2) elastic deformation obtained from FEA (finite element analysis)-based compliance matrices; (3) a break-in module that iteratively adjusts surface profiles before steady-state simulation; (4) a three-body heat transfer model resolving heat conduction, convection, and solid–liquid interfacial heat exchange. Applied to a heavy-duty diesel engine, the framework reproduces experimentally observed behaviors, including bottom-edge rounding at the small end and the slow unidirectional drift of the floating pin. By integrating multi-physics modeling with design-level flexibility, this work aims to provide a robust digital twin for the piston-pin system, enabling virtual diagnostics, early-stage failure prediction, and data-driven design optimization for engine development.

The Wafold: Curvature-Driven Termination and Dimensional Compression in Black Holes

Tue, 23 Dec 2025 00:00:00 GMT

The Wafold: Curvature-Driven Termination and Dimensional Compression in Black Holes Viaña, Javier This work explores a geometric description of black holes in which spacetime terminates on a curvature-triggered hypersurface rather than extending to an interior singularity. We study the implications of a scenario in which, upon reaching a critical curvature threshold, the three-dimensional spatial geometry compresses into a thin, closed boundary identified here as the wafold. Beyond this, the manifold would no longer continue, and all mass–energy and information would be confined to the hypersurface itself. This framework combines two well-explored paths: (1) curvature-driven geometric compression, in which extreme curvature forces the bulk degrees of freedom to become supported on a thin hypersurface (without altering the underlying dimensionality of spacetime), and (2) the motivation underlying the holographic principle, namely that black-hole entropy scales with surface area rather than volume, suggesting that information is governed by a boundary geometry rather than a bulk volume. We elaborate a dimensional conversion law that would be required to describe the collapse of spatial volume into surface area as a conserved flux of geometric capacity across the wafold, and we analyze the resulting consequences of treating this hypersurface as the terminal boundary of the manifold.

Design and Implementation of an Automated Thermal Imaging Device for Lower Limb Prosthetic Applications

Thu, 18 Dec 2025 00:00:00 GMT

Design and Implementation of an Automated Thermal Imaging Device for Lower Limb Prosthetic Applications Pizarro, Daniel; Huegel, Joel C.; Diaz, Elias; Alemon, Beatriz; Herr, Hugh; Felix-Herran, Luis C. Since elevated temperature and humidity may occur at the prosthetic socket–skin interface, it is essential to collect thermal data from the residual limb, as this information serves as an indicator of adverse effects such as irritation, postural problems, and significant damage to health. These data are obtained non-invasively through the execution of a thermal imaging (TI) procedure. However, the precision and repeatability of a TI procedure rely significantly on its execution technique. This work presents the design and implementation of a mechatronic device that automates a thermal imaging technique. The application of the device is in lower-limb prosthetics evaluation. The proposed system improves data acquisition consistency by reducing execution time and minimizing human error, thereby enhancing the reproducibility and reliability of thermal measurements. The introduced device, Thermal Imaging Booth, proposes an automated solution for TI standardization in clinical and research settings. By minimizing inconsistencies, this system improves the diagnostic potential of thermography, facilitating its adoption in biomedical applications.

Peepco: Batch-Based Consistency Optimization

Wed, 09 Apr 2025 00:00:00 GMT

Peepco: Batch-Based Consistency Optimization Kuraj, Ivan; Feser, John; Polikarpova, Nadia; Solar-Lezama, Armando We present batch-based consistency, a new approach for consistency optimization that allows programmers to specialize consistency with application-level integrity properties. We implement the approach with a two-step process: we statically infer optimal consistency requirements for executions of bounded sets of operations, and then, use the inferred requirements to parameterize a new distributed protocol to relax operation reordering at run time when it is safe to do so. Our approach supports standard notions of consistency. We implement batch-based consistency in Peepco, demonstrate its expressiveness for partial data replication, and examine Peepco’s run-time performance impact in different settings.

Finch: Sparse and Structured Tensor Programming with Control Flow

Wed, 09 Apr 2025 00:00:00 GMT

Finch: Sparse and Structured Tensor Programming with Control Flow Ahrens, Willow; Collin, Teodoro; Patel, Radha; Deeds, Kyle; Hong, Changwan; Amarasinghe, Saman From FORTRAN to NumPy, tensors have revolutionized how we express computation. However, tensors in these, and almost all prominent systems, can only handle dense rectilinear integer grids. Real world tensors often contain underlying structure, such as sparsity, runs of repeated values, or symmetry. Support for structured data is fragmented and incomplete. Existing frameworks limit the tensor structures and program control flow they support to better simplify the problem. In this work, we propose a new programming language, Finch, which supports both flexible control flow and diverse data structures. Finch facilitates a programming model which resolves the challenges of computing over structured tensors by combining control flow and data structures into a common representation where they can be co-optimized. Finch automatically specializes control flow to data so that performance engineers can focus on experimenting with many algorithms. Finch supports a familiar programming language of loops, statements, ifs, breaks, etc., over a wide variety of tensor structures, such as sparsity, run-length-encoding, symmetry, triangles, padding, or blocks. Finch reliably utilizes the key properties of structure, such as structural zeros, repeated values, or clustered non-zeros. We show that this leads to dramatic speedups in operations such as SpMV and SpGEMM, image processing, and graph analytics.

Smooth, Integrated Proofs of Cryptographic Constant Time for Nondeterministic Programs and Compilers

Fri, 13 Jun 2025 00:00:00 GMT

Smooth, Integrated Proofs of Cryptographic Constant Time for Nondeterministic Programs and Compilers Conoly, Owen; Erbsen, Andres; Chlipala, Adam Formal verification of software and compilers has been used to rule out large classes of security-critical issues, but risk of unintentional information leakage has received much less consideration. It is a key requirement for formal specifications to leave some details of a system's behavior unspecified so that future implementation changes can be accommodated, and yet it is nonetheless expected that these choices would not be made based on confidential information the system handles. This paper formalizes that notion using omnisemantics and plain single-copy assertions, giving for the first time a specification of what it means for a nondeterministic program to be constant-time or more generally to avoid leaking (a part of) its inputs. We use this theory to prove data-leak-free execution of core cryptographic routines compiled from Bedrock2 C to RISC-V machine code, showing that the smooth specification and proof experience omnisemantics provides for nondeterminism extends to constant-time properties in the same setting. We also study variants of the key program-compiler contract, highlighting pitfalls of tempting simplifications and subtle consequences of how inputs to nondeterministic choices are constrained. Our results are backed by modular program-logic and compiler-correctness theorems, and they integrate into a neat end-to-end theorem in the Coq proof assistant.

NeuroChat: A Neuroadaptive AI Chatbot for Customizing Learning Experiences

Tue, 08 Jul 2025 00:00:00 GMT

NeuroChat: A Neuroadaptive AI Chatbot for Customizing Learning Experiences Baradari, D?nya; Kosmyna, Nataliya; Petrov, Oscar; Kaplun, Rebecah; Maes, Pattie Generative AI is reshaping education by enabling personalized, on-demand learning experiences. However, current AI systems lack awareness of the learner’s cognitive state, limiting their adaptability. In parallel, electroencephalography (EEG)-based neuroadaptive systems have shown promise in enhancing engagement through real-time physiological feedback. This paper introduces NeuroChat, a neuroadaptive AI tutor that integrates real-time EEG-based engagement tracking with a large language model to adapt its conversational responses. By continuously monitoring learners’ cognitive engagement, NeuroChat dynamically adjusts content complexity, tone, and response style in a closed-loop interaction. In a within-subjects study (n = 24), NeuroChat significantly increased both EEG-measured and self-reported engagement compared to a non-adaptive chatbot. However, no significant differences in short-term learning outcomes were observed. These findings demonstrate the feasibility of real-time brain–AI interaction for education and highlight opportunities for deeper personalization, longer-term adaptation, and richer learning assessment in future neuroadaptive systems. CUI ’25, Waterloo, ON, Canada

From Synthetic to Human: The Gap Between AI-Predicted and Actual Pro-Environmental Behavior Change After Chatbot Persuasion

Mon, 07 Jul 2025 00:00:00 GMT

From Synthetic to Human: The Gap Between AI-Predicted and Actual Pro-Environmental Behavior Change After Chatbot Persuasion Doudkin, Alexander; Pataranutaporn, Pat; Maes, Pattie Pro-environmental behavior (PEB) is vital to combat climate change, yet turning awareness into intention and action remains elusive. We explore large language models (LLMs) as tools to promote PEB, comparing their impact across 3,600 participants: real humans (n=1,200), simulated humans based on actual participant data (n=1,200), and fully synthetic personas (n=1,200). All three participant groups faced either personalized chatbots, standard chatbots, or static statements, employing four persuasion strategies (moral foundations, future self-continuity, action orientation, or ”freestyle” chosen by the LLM). Results reveal a ”synthetic persuasion paradox”: synthetic and simulated participants significantly change their post-intervention PEB stance, while human attitudes barely shift. Simulated participants better approximate human behavior but still overestimate effects. This disconnect underscores LLM’s potential for pre-evaluating PEB interventions but warns of its limits in predicting human responses. We call for refined synthetic modeling and sustained and extended human trials to align conversational AI’s promise with tangible sustainability outcomes. CUI ’25, Waterloo, ON, Canada

Adaptive Approximation Schemes for Matching Queues

Sun, 15 Jun 2025 00:00:00 GMT

Adaptive Approximation Schemes for Matching Queues AmaniHamedani, Alireza; Aouad, Ali; Saberi, Amin We study a continuous-time, infinite-horizon dynamic bipartite matching problem. Suppliers arrive according to a Poisson process; while waiting, they may abandon the queue at a uniform rate. Customers on the other hand must be matched upon arrival. The objective is to minimize the expected long-term average cost subject to a throughput constraint on the total match rate. Previous literature on dynamic matching focuses on ”static” policies, where the matching decisions do not depend explicitly on the state of the supplier queues, achieving constant-factor approximations. By contrast, we design ”adaptive” policies, which leverage queue length information, and obtain near-optimal polynomial-time algorithms for several classes of instances. First, we develop a bi-criteria fully polynomial-time approximation scheme for dynamic matching on networks with a constant number of queues—that computes a (1−є)-approximation of the optimal policy in time polynomial in both the input size and 1/є. A key new technique is a hybrid LP relaxation, which combines static and state-dependent LP approximations of the queue dynamics, after a decomposition of the network. Networks with a constant number of queues are motivated by deceased organ donation schemes, where the supply types can be divided according to blood and tissue types. The above algorithm, combined with a careful cell decomposition gives a polynomial-time approximation scheme for dynamic matching on Euclidean networks of fixed dimension. The Euclidean case is of interest in ride-hailing and spatial service platforms, where the goal is to fulfill as many trips as possible while minimizing driving distances. STOC ’25, Prague, Czechia

Output-Sensitive Approximate Counting via a Measure-Bounded Hyperedge Oracle, or: How Asymmetry Helps Estimate ��-Clique Counts Faster

Sun, 15 Jun 2025 00:00:00 GMT

Output-Sensitive Approximate Counting via a Measure-Bounded Hyperedge Oracle, or: How Asymmetry Helps Estimate ��-Clique Counts Faster Censor-Hillel, Keren; Even, Tomer; Vassilevska Williams, Virginia Dell, Lapinskas and Meeks [DLM SICOMP 2022] presented a general reduction from approximate counting to decision for a class of fine-grained problems that can be viewed as hyperedge counting or detection problems in an implicit hypergraph, thus obtaining tight equivalences between approximate counting and decision for many key problems such as k-clique, k-sum and more. Their result is a reduction from approximately counting the number of hyperedges in an implicit k-partite hypergraph to a polylogarithmic number of calls to a hyperedge oracle that returns whether a given subhypergraph contains an edge. The main result of this paper is a generalization of the DLM result for output-sensitive approximate counting, where the running time of the desired counting algorithm is inversely proportional to the number of witnesses. Our theorem is a reduction from approximately counting the (unknown) number of hyperedges in an implicit k-partite hypergraph to a polylogarithmic number of calls to a hyperedge oracle called only on subhypergraphs with a small “measure”. If a subhypergraph has ui nodes in the ith node partition of the k-partite hypergraph, then its measure is ∏i ui. Using the new general reduction and by efficiently implementing measure-bounded colorful independence oracles, we obtain new improved output-sensitive approximate counting algorithms for k-clique, k-dominating set and k-sum. In graphs with nt k-cliques, for instance, our algorithm (1± є)-approximates the k-clique count in time Õє(nω(k−t−1/3,k−t/3,k−t+2/3) +n2), where ω(a,b,c) is the exponent of na× nb by nb× nc matrix multiplication. For large k and t>2, this is a substantial improvement over prior work, even if ω=2. STOC ’25, Prague, Czechia

Lightweight and Locality-Aware Composition of Black-Box Subroutines

Fri, 13 Jun 2025 00:00:00 GMT

Lightweight and Locality-Aware Composition of Black-Box Subroutines Bansal, Manya; Sharlet, Dillon; Ragan-Kelley, Jonathan; Amarasinghe, Saman Subroutines are essential building blocks in software design: users encapsulate common functionality in libraries and write applications by composing calls to subroutines. Unfortunately, performance may be lost at subroutine boundaries due to reduced locality and increased memory consumption. Operator fusion helps recover performance lost at composition boundaries. Previous solutions fuse operators by manually rewriting code into monolithic fused subroutines, or by relying on heavy-weight compilers to generate code that performs fusion. Both approaches require a semantic understanding of the entire computation, breaking the decoupling necessary for modularity and reusability of subroutines. In this work, we attempt to identify the minimal ingredients required to fuse computations, enabling composition of subroutines without sacrificing performance or modularity. We find that, unlike previous approaches that require a semantic understanding of the computation, most opportunities for fusion require understanding only data production and consumption patterns. Exploiting this insight, we add fusion on top of black-box subroutines by proposing a lightweight enrichment of subroutine declarations to expose data-dependence patterns. We implement our approach in a system called Fern, and demonstrate Fern's benefits by showing that it is competitive with state-of-the-art, high-performance libraries with manually fused operators, can fuse across library and domain boundaries for unforeseen workloads, and can deliver speedups of up to $5\times$ over unfused code.

Prolonged photostability in hexagonal boron nitride quantum emitters

Mon, 06 Mar 2023 00:00:00 GMT

Prolonged photostability in hexagonal boron nitride quantum emitters Li, Sylvia Xin; Ichihara, Takeo; Park, Hyoju; He, Guangwei; Kozawa, Daichi; Wen, Yi; Koman, Volodymyr B; Zeng, Yuwen; Kuehne, Matthias; Yuan, Zhe; Faucher, Samuel; Warner, Jamie H; Strano, Michael S Single-photon emitters are crucial building blocks for optical quantum technologies. Hexagonal boron nitride (hBN) is a promising two-dimensional material that hosts bright, room-temperature single-photon emitters. However, photo instability is a persistent challenge preventing practical applications of these properties. Here, we reveal the ubiquitous photobleaching of hBN vacancy emitters. Independent of the source or the number of hBN layers, we find that the photobleaching of a common emission at 1.98 ± 0.05 eV can be described by two consistent time constants, namely a first bleaching lifetime of 5 to 10 s, and a second bleaching lifetime in the range of 150 to 220 s. Only the former is environmentally sensitive and can be significantly mitigated by shielding O2, whereas the latter could be the result of carbon-assisted defect migration. Annular dark-field scanning transmission electron microscopy of photobleached hBN allows for visualizing vacancy defects and carbon substitution at single atom resolution, supporting the migration mechanism along with X-ray photoelectron spectroscopy. Thermal annealing at 850 °C of liquid exfoliated hBN eliminates both bleaching processes, leading to persistent photostability. These results represent a significant advance to potentially engineer hBN vacancy emitters with the photostability requisite for quantum applications.

Discretized hexagonal boron nitride quantum emitters and their chemical interconversion

Tue, 03 Jan 2023 00:00:00 GMT

Discretized hexagonal boron nitride quantum emitters and their chemical interconversion Kozawa, Daichi; Li, Sylvia Xin; Ichihara, Takeo; Rajan, Ananth Govind; Gong, Xun; He, Guangwei; Koman, Volodymyr B; Zeng, Yuwen; Kuehne, Matthias; Silmore, Kevin S; Parviz, Dorsa; Liu, Pingwei; Liu, Albert Tianxiang; Faucher, Samuel; Yuan, Zhe; Warner, Jamie; Blankschtein, Daniel; Strano, Michael S Quantum emitters in two-dimensional hexagonal boron nitride (hBN) are of significant interest because of their unique photophysical properties, such as single-photon emission at room temperature, and promising applications in quantum computing and communications. The photoemission from hBN defects covers a wide range of emission energies but identifying and modulating the properties of specific emitters remain challenging due to uncontrolled formation of hBN defects. In this study, more than 2000 spectra are collected consisting of single, isolated zero-phonon lines (ZPLs) between 1.59 and 2.25 eV from diverse sample types. Most of ZPLs are organized into seven discretized emission energies. All emitters exhibit a range of lifetimes from 1 to 6 ns, and phonon sidebands offset by the dominant lattice phonon in hBN near 1370 cm−1. Two chemical processing schemes are developed based on water and boric acid etching that generate or preferentially interconvert specific emitters, respectively. The identification and chemical interconversion of these discretized emitters should significantly advance the understanding of solid-state chemistry and photophysics of hBN quantum emission.

Rational Design and Efficacy of Glucose‐Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models

Thu, 15 Jun 2023 00:00:00 GMT

Rational Design and Efficacy of Glucose‐Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models Yang, Sungyun; Yang, Jing Fan; Gong, Xun; Weiss, Michael A; Strano, Michael S Glucose‐responsive insulins (GRIs) use plasma glucose levels in a diabetic patient to activate a specifically designed insulin analogue to a more potent state in real time. Alternatively, some GRI concepts use glucose‐mediated release or injection of insulin into the bloodstream. GRIs hold promise to exhibit much improved pharmacological control of the plasma glucose concentration, particularly for the problem of therapeutically induced hypoglycemia. Several innovative GRI schemes are introduced into the literature, but there remains a dearth of quantitative analysis to aid the development and optimization of these constructs into effective therapeutics. This work evaluates several classes of GRIs that are proposed using a pharmacokinetic model as previously described, PAMERAH, simulating the glucoregulatory system of humans and rodents. GRI concepts are grouped into three mechanistic classes: 1) intrinsic GRIs, 2) glucose‐responsive particles, and 3) glucose‐responsive devices. Each class is analyzed for optimal designs that maintain glucose levels within the euglycemic range. These derived GRI parameter spaces are then compared between rodents and humans, providing the differences in clinical translation success for each candidate. This work demonstrates a computational framework to evaluate the potential clinical translatability of existing glucose‐responsive systems, providing a useful approach for future GRI development.

Wearable sensors for monitoring marine environments and their inhabitants

Mon, 26 Jun 2023 00:00:00 GMT

Wearable sensors for monitoring marine environments and their inhabitants Kaidarova, Altynay; Geraldi, Nathan R; Wilson, Rory P; Kosel, Jürgen; Meekan, Mark G; Eguíluz, Víctor M; Hussain, Muhammad Mustafa; Shamim, Atif; Liao, Hanguang; Srivastava, Mani; Saha, Swapnil Sayan; Strano, Michael S; Zhang, Xiangliang; Ooi, Boon S; Holton, Mark; Hopkins, Lloyd W; Jin, Xiaojia; Gong, Xun; Quintana, Flavio; Tovasarov, Adylkhan; Tasmagambetova, Assel; Duarte, Carlos M Human societies depend on marine ecosystems, but their degradation continues. Toward mitigating this decline, new and more effective ways to precisely measure the status and condition of marine environments are needed alongside existing rebuilding strategies. Here, we provide an overview of how sensors and wearable technology developed for humans could be adapted to improve marine monitoring. We describe barriers that have slowed the transition of this technology from land to sea, update on the developments in sensors to advance ocean observation and advocate for more widespread use of wearables on marine organisms in the wild and in aquaculture. We propose that large-scale use of wearables could facilitate the concept of an ‘internet of marine life’ that might contribute to a more robust and effective observation system for the oceans and commercial aquaculture operations. These observations may aid in rationalizing strategies toward conservation and restoration of marine communities and habitats.

Low-Cost Deep Learning for Building Detection with Application to Informal Urban Planning

Fri, 09 Jan 2026 00:00:00 GMT

Low-Cost Deep Learning for Building Detection with Application to Informal Urban Planning González, Lucas; Toutouh, Jamal; Nesmachnow, Sergio This article studies the application of deep neural networks for automatic building detection in aerial RGB images. Special focus is put on accuracy robustness in both well-structured and poorly planned urban scenarios, which pose significant challenges due to occlusions, irregular building layouts, and limited contextual cues. The applied methodology considers several CNNs using only RBG images as input, and both validation and transfer capabilities are studied. U-Net-based models achieve the highest single-model accuracy, with an Intersection over Union (𝐼⁢𝑜⁢𝑈) of 0.9101. A soft-voting ensemble of the best U-Net models further increases performance, reaching a best ensemble 𝐼⁢𝑜⁢𝑈 of 0.9665, improving over state-of-the-art building detection methods on standard benchmarks. The approach demonstrates strong generalization using only RGB imagery, supporting scalable, low-cost applications in urban planning and geospatial analysis.

Efficient Learning and Computation of Linear Correlated Equilibrium in General Convex Games

Sun, 15 Jun 2025 00:00:00 GMT

Efficient Learning and Computation of Linear Correlated Equilibrium in General Convex Games Daskalakis, Constantinos; Farina, Gabriele; Fishelson, Maxwell; Pipis, Charilaos; Schneider, Jon We propose efficient no-regret learning dynamics and ellipsoid-based methods for computing linear correlated equilibria—a relaxation of correlated equilibria and a strengthening of coarse correlated equilibria—in general convex games. These are games where the number of pure strategies is potentially exponential in the natural representation of the game, such as extensive-form games. Our work identifies linear correlated equilibria as the tightest known notion of equilibrium that is computable in polynomial time and is efficiently learnable for general convex games. Our results are enabled by a generalization of the seminal framework of Gordon et al. for Φ-regret minimization, providing extensions to this framework that can be used even when the set of deviations Φ is intractable to separate/optimize over. Our polynomial-time algorithms are similarly enabled by extending the Ellipsoid-Against-Hope approach of Papadimitriou and Roughgarden and its generalization to games of non-polynomial type proposed by Farina and Pipis. We provide an extension to these approaches when we do not have access to the separation oracles required by these works for the dual player. Constantinos Daskalakis, Gabriele Farina, Maxwell Fishelson, Charilaos Pipis, and Jon Schneider. 2025. Efficient Learning and Computation of Linear Correlated Equilibrium in General Convex Games. In Proceedings of the 57th Annual ACM Symposium on Theory of Computing (STOC '25). Association for Computing Machinery, New York, NY, USA, 542–553.

When Connectivity Is Hard, Random Walks Are Easy with Non-determinism

Sun, 15 Jun 2025 00:00:00 GMT

When Connectivity Is Hard, Random Walks Are Easy with Non-determinism Doron, Dean; Pyne, Edward; Tell, Roei; Williams, R. Ryan Two fundamental problems on directed graphs are to decide s-t connectivity, and to estimate the behavior of random walks. Currently, there is no known algorithm for s-t connectivity running in polynomial time and no(1) space, and no known algorithm for estimating the n-step random walk matrix running in non-deterministic logspace. We show that for every directed graph, at least one of these problems is solvable in time and space that significantly improve on the respective state-of-the-art. In particular, there is a pair of algorithms A1 and A2 such that for every graph G, either: A1(G) outputs the transitive closure of G in polynomial time and polylogarithmic space. A2(G) outputs an approximation of the n-step random walk matrix of G in non-deterministic logspace. As one application, we show surprisingly tight win-win results for space-bounded complexity. For example, for certain parameter regimes, either Savitch’s theorem can be non-trivially sped up, or randomized space can be almost completely derandomized. We also apply our techniques to significantly weaken the assumptions required to derandomize space-bounded computation, and to make non-deterministic space-bounded computation unambiguous. Specifically, we deduce such conclusions from lower bounds against uniform circuits of polynomial size, which is an exponential improvement on the required hardness in previous works (Doron–Pyne–Tell STOC 2024, Li–Pyne–Tell FOCS 2024). We further show similar results for minimal-memory derandomization (Doron–Tell CCC 2024). To prove these results, we substantially improve the array of technical tools introduced in recent years for studying hardness-vs.-randomness for bounded-space computation. In particular, we develop derandomized distinguish-to-predict transformations for new types of distinguishers (corresponding to compositions of PRGs with weak distinguishers), we construct a derandomized logspace reconstruction procedure for the Shaltiel–Umans generator (JACM 2005) that can compress hard truth-tables to polylogarithmic size, and we design a version of the Chen–Tell generator (FOCS 2021) that is particularly suitable for the space-bounded setting. STOC ’25, Prague, Czechia

QMA vs QCMA and Pseudorandomness

Sun, 15 Jun 2025 00:00:00 GMT

QMA vs QCMA and Pseudorandomness Liu, Jiahui; Mutreja, Saachi; Yuen, Henry We study a longstanding question of Aaronson and Kuperberg on whether there exists a classical oracle separating QMA from QCMA. Settling this question in either direction would yield insight into the power of quantum proofs over classical proofs. We show that such an oracle exists if a certain quantum pseudorandomness conjecture holds. Roughly speaking, the conjecture posits that quantum algorithms cannot, by making few queries, distinguish between the uniform distribution over permutations versus permutations drawn from so-called “dense” distributions. Our result can be viewed as establishing a “win-win” scenario: either there is a classical oracle separation of QMA from QCMA, or there is quantum advantage in distinguishing pseudorandom distributions on permutations. STOC ’25, Prague, Czechia

Semantics of Integrating and Differentiating Singularities

Fri, 13 Jun 2025 00:00:00 GMT

Semantics of Integrating and Differentiating Singularities Michel, Jesse; Lee, Wonyeol; Yang, Hongseok A singular function is a partial function such that at one or more points, the left and/or right limit diverge (e.g., the function 1/x). Since programming languages typically support division, programs may denote singular functions. Although on its own, a singularity may be considered a bug, introducing a division-by-zero error, singular integrals—a version of the integral that is well-defined when the integrand is a singular function and the domain of integration contains a singularity—arise in science and engineering, including in physics, aerodynamics, mechanical engineering, and computer graphics. In this paper, we present the first semantics of a programming language for singular integration. Our differentiable programming language, SingularFlow, supports the evaluation and differentiation of singular integrals. We formally define the denotational semantics of SingularFlow, deriving all the necessary mathematical machinery so that this work is rigorous and self-contained. We then define an operational semantics for SingularFlow that estimates integrals and their derivatives using Monte Carlo samples, and show that the operational semantics is a well-behaved estimator for the denotational semantics. We implement SingularFlow in JAX and evaluate the implementation on a suite of benchmarks that perform the finite Hilbert transform, an integral transform related to the Fourier transform, which arises in domains such as physics and electrical engineering. We then use SingularFlow to approximate the solutions to four singular integral equations—equations where the unknown function is in the integrand of a singular integral—arising in aerodynamics and mechanical engineering.

SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More

Sun, 15 Jun 2025 00:00:00 GMT

SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More Diakonikolas, Ilias; Hopkins, Samuel B.; Pensia, Ankit; Tiegel, Stefan We study sparse singular value certificates for random rectangular matrices. If M is a d × n matrix with independent Gaussian entries, we give a new family of polynomial-time algorithms which can certify upper bounds on the maximum of ||M u||, where u is a unit vector with at most η n nonzero entries for a given η ∈ (0,1). This basic algorithmic primitive lies at the heart of a wide range of problems across algorithmic statistics and theoretical computer science, including robust mean and covariance estimation, certification of distortion of random subspaces of n, certification of the 2 → p norm of a random matrix, and sparse principal component analysis. Our algorithms certify a bound which is asymptotically smaller than the naive one, given by the maximum singular value of M, for nearly the widest-possible range of n,d, and η. Efficiently certifying such a bound for a range of n,d and η which is larger by any polynomial factor than what is achieved by our algorithm would violate lower bounds in the statistical query and low-degree polynomials models. Our certification algorithm makes essential use of the Sum-of-Squares hierarchy. To prove the correctness of our algorithm, we develop a new combinatorial connection between the graph matrix approach to analyze random matrices with dependent entries, and the Efron-Stein decomposition of functions of independent random variables. As applications of our certification algorithm, we obtain new efficient algorithms for a wide range of well-studied algorithmic tasks. In algorithmic robust statistics, we obtain new algorithms for robust mean and covariance estimation with tradeoffs between breakdown point and sample complexity, which are nearly matched by statistical query and low-degree polynomial lower bounds (that we establish). We also obtain new polynomial-time guarantees for certification of ℓ1/ℓ2 distortion of random subspaces of n (also with nearly matching lower bounds), sparse principal component analysis, and certification of the 2→ p norm of a random matrix. STOC ’25, Prague, Czechia

Weak Recovery, Hypothesis Testing, and Mutual Information in Stochastic Block Models and Planted Factor Graphs

Sun, 15 Jun 2025 00:00:00 GMT

Weak Recovery, Hypothesis Testing, and Mutual Information in Stochastic Block Models and Planted Factor Graphs Mossel, Elchanan; Sly, Allan; Sohn, Youngtak The stochastic block model is a canonical model of communities in random graphs. It was introduced in the social sciences and statistics as a model of communities, and in theoretical computer science as an average case model for graph partitioning problems under the name of the “planted partition model.” Given a sparse stochastic block model, the two standard inference tasks are: (i) Weak recovery: can we estimate the communities with non-trivial overlap with the true communities? (ii) Detection/Hypothesis testing: can we distinguish if the sample was drawn from the block model or from a random graph with no community structure with probability tending to 1 as the graph size tends to infinity? In this work, we show that for sparse stochastic block models, the two inference tasks are equivalent except at a critical point. That is, weak recovery is information theoretically possible if and only if detection is possible. We thus find a strong connection between these two notions of inference for the model. We further prove that when detection is impossible, an explicit hypothesis test based on low-degree polynomials in the adjacency matrix of the observed graph achieves the optimal statistical power. This low-degree test is efficient as opposed to the likelihood ratio test, which is not known to be efficient. Moreover, we prove that the asymptotic mutual information between the observed network and the community structure exhibits a phase transition at the weak recovery threshold. Our results are proven in much broader settings including the hypergraph stochastic block models and general planted factor graphs. In these settings, we prove that the impossibility of weak recovery implies contiguity and provide a condition that guarantees the equivalence of weak recovery and detection. STOC ’25, Prague, Czechia

Near-Optimal Time-Sparsity Trade-Offs for Solving Noisy Linear Equations

Sun, 15 Jun 2025 00:00:00 GMT

Near-Optimal Time-Sparsity Trade-Offs for Solving Noisy Linear Equations Bangachev, Kiril; Bresler, Guy; Tiegel, Stefan; Vaikuntanathan, Vinod We present a polynomial-time reduction from solving noisy linear equations over in dimension Θ(klogn/(logk,logq,loglogn)) with a uniformly random coefficient matrix to noisy linear equations over in dimension n where each row of the coefficient matrix has uniformly random support of size k. This allows us to deduce the hardness of sparse problems from their dense counterparts. In particular, we derive hardness results in the following canonical settings: • Assuming the ℓ-dimensional (dense) learning with errors () problem over a polynomial-size field takes time 2Ω(ℓ), k-sparse in dimension n takes time nΩ(k/(logk · (logk + loglogn))) . • Assuming the ℓ-dimensional (dense) learning parity with noise () problem over ℤ/2ℤ takes time 2Ω(ℓ/logℓ), k-sparse in dimension n takes time nΩ(k/(logk · (logk + loglogn)2)) . These running time lower bounds are nearly tight as both sparse problems can be solved in time nO(k), given sufficiently many samples. Our reduction allows us to derive several consequences in cryptography and the computational complexity of statistical problems. In addition, as a new application, we give a reduction from k-sparse LWE to noisy tensor completion. Concretely, composing the two reductions implies that order-k rank-2k−1 noisy tensor completion in ℝn⊗ k takes time nΩ(k/ logk · (logk + loglogn)), assuming the exponential hardness of standard worst-case lattice problems. STOC ’25, Prague, Czechia

Stochastic Matching via In-n-Out Local Computation Algorithms

Sun, 15 Jun 2025 00:00:00 GMT

Stochastic Matching via In-n-Out Local Computation Algorithms Azarmehr, Amir; Behnezhad, Soheil; Ghafari, Alma; Rubinfeld, Ronitt Consider the following stochastic matching problem. We are given a known graph G=(V, E). An unknown subgraph Gp = (V, Ep) is realized where Ep includes every edge of E independently with some probability p ∈ (0, 1]. The goal is to query a sparse subgraph H of G, such that the realized edges in H include an approximate maximum matching of Gp. This problem has been studied extensively over the last decade due to its applications in kidney exchange, online dating, and online labor markets. For any fixed є > 0, [BDH STOC’20] showed that any graph G has a subgraph H with (1/p) = (1/p)(log(1/p)) maximum degree, achieving a (1−є)-approximation. A major open question is the best approximation achievable with (1/p)-degree subgraphs. A long line of work has progressively improved the approximation in the (1/p)-degree regime from .5 [BDH+ EC’15] to .501 [AKL EC’17], .656 [BHFR SODA’19], .666 [AB SOSA’19], .731 [BBD SODA’22] (bipartite graphs), and most recently to .68 [DS ’24]. In this work, we show that a (1/p)-degree subgraph can obtain a (1−є)-approximation for any desirably small fixed є > 0, achieving the best of both worlds. Beyond its quantitative improvement, a key conceptual contribution of our work is to connect local computation algorithms (LCAs) to the stochastic matching problem for the first time. While prior work on LCAs mainly focuses on their out-queries (the number of vertices probed to produce the output of a given vertex), our analysis also bounds the in-queries (the number of vertices that probe a given vertex). We prove that the outputs of LCAs with bounded in- and out-queries (in-n-out LCAs for short) have limited correlation, a property that our analysis crucially relies on and might find applications beyond stochastic matching STOC ’25, Prague, Czechia

Colloidal State Machines as Smart Tracers for Chemical Reactor Analysis

Thu, 29 Jun 2023 00:00:00 GMT

Colloidal State Machines as Smart Tracers for Chemical Reactor Analysis Zhang, Ge; Yang, Jing Fan; Yang, Sungyun; Brooks, Allan M; Koman, Volodymyr B; Gong, Xun; Strano, Michael S A widely utilized tool in reactor analysis is passive tracers that report the residence time distribution, allowing estimation of the conversion and other properties of the system. Recently, advances in microrobotics have introduced powered and functional entities with sizes comparable to some traditional tracers. This has motivated the concept of Smart Tracers that could record the local chemical concentrations, temperature, or other conditions as they progress through reactors. Herein, the design constraints and advantages of Smart Tracers by simulating their operation in a laminar flow reactor model conducting chemical reactions of various orders are analyzed. It is noted that far fewer particles are necessary to completely map even the most complex concentration gradients compared with their conventional counterparts. Design criteria explored herein include sampling frequency, memory storage capacity, and ensemble number necessary to achieve the required accuracy to inform a reactor model. Cases of severe particle diffusion and sensor noise appear to bind the functional upper limit of such probes and require consideration for future design. The results of the study provide a starting framework for applying the new technology of microrobotics to the broad and impactful set of problems classified as chemical reactor analysis.

Mitigation of ventilation air methane (VAM) using novel methanotrophic coating materials: a technical analysis

Fri, 20 Oct 2023 00:00:00 GMT

Mitigation of ventilation air methane (VAM) using novel methanotrophic coating materials: a technical analysis Lundberg, Daniel James; Kim, Jimin; Parviz, Dorsa; Strano, Michael S Ventilation air methane (VAM) is a potent greenhouse gas source originating from geological wells, current and extinct mineshafts and other terrestrial conduits venting methane to the atmosphere, contributing to global methane emissions and disproportionate warming potential. Herein, we introduce the concept of the methanotrophic material as an engineering solution. Such materials should be capable of converting methane at ambient temperatures and pressures to a binder product, capturing and permanently sequestering the methane while simultaneously restricting its further emission. While such materials are currently under research development, this goal is supported and facilities by the mathematical framework, introduced and used herein, to evaluate the ability to convert methane, using currently published activity data. We include a case study of the conversion of a characteristic stream of VAM (0.6% methane in air, 1.7 × 108 l hr−1 equivalent to 100 000 standard cubic feet per minute). We show that when appropriately designed, such systems require a surface coverage of less than 1000 m of mine tunnel length (equivalent to 20 000 m2 areal coverage) in order to reduce the methane emission from this stream by over 99%. Finally, we highlight formaldehyde as a reactive intermediate of methane oxidation which may itself be incorporated into these coating materials. As a component of binders and polymers already used ubiquitously in commercial products, this intermediate ultimately allows these systems to sequester the carbon from methane in a stable and solid form. The results presented here are easily extended to the treatment of other methane streams—either more concentrated or dilute—and the results herein will guide the design and development of a new class of carbon-negative materials.

Synergistic multi-source ambient RF and thermal energy harvester for green IoT applications

Fri, 01 Dec 2023 00:00:00 GMT

Synergistic multi-source ambient RF and thermal energy harvester for green IoT applications Bakytbekov, Azamat; Nguyen, Thang Q; Zhang, Ge; Strano, Michael S; Salama, Khaled N; Shamim, Atif In a future green Internet of Things (IoT) reality, billions of devices of the IoT infrastructure should be self-powered. Harvesting ambient energy to power IoT devices is an attractive solution that can extend battery life or can completely replace batteries. Considering the global applications of IoT, ubiquitous and continuous availability is an important requirement for ambient energy sources. Radio frequency (RF) energy from mobile phone towers and thermal energy from diurnal cycle temperature fluctuations are good candidates. In this study, we present a synergistic multi-source energy harvester (MSEH) comprising an RF energy harvester (RFEH) and a thermal energy harvester (TEH) integrated through a dual-function component, heatsink antenna. Both harvesters collect ambient energy 24 h a day and are not location specific. The TEH, which is in the shape of a box, collects energy using heatsinks on its sidewalls. The same heatsinks are optimized to also serve as receiving antennas of the RFEH, which collects energy from the GSM900, GSM1800, and 3G bands. Due to the synergistic integration, radiation efficiency of the antenna doubled from 40% to 80% which resulted in ∼ 10% increase in power conversion efficiency of the RFEH. Similarly, the average power of the TEH without heatsinks 120 μ W is doubled to 240 μ W for TEH with heatsinks. Field tests have shown that the outputs of the TEH and RFEH have increased 4 and 3 times compared to the independent TEH and RFEH respectively. A temperature and humidity sensor based IoT node has been successfully powered through this energy harvesting system. Overall, the MSEH can collect 3680 μ W h of energy per day which is sufficient to obtain the sensors data with a time interval of 3.5 s.

Chromatic covalent organic frameworks enabling in-vivo chemical tomography

Mon, 28 Oct 2024 00:00:00 GMT

Chromatic covalent organic frameworks enabling in-vivo chemical tomography Wang, Song; Han, Yangyang; Reddy, Vaishnavi Amarr; Ang, Mervin Chun-Yi; Sánchez-Velázquez, Gabriel; Saju, Jolly Madathiparambil; Cao, Yunteng; Khong, Duc Thinh; Jayapal, Praveen Kumar; Cheerlavancha, Raju; Loh, Suh In; Singh, Gajendra Pratap; Urano, Daisuke; Rajani, Sarojam; Marelli, Benedetto; Strano, Michael S Covalent organic frameworks designed as chromatic sensors offer opportunities to probe biological interfaces, particularly when combined with biocompatible matrices. Particularly compelling is the prospect of chemical tomography – or the 3D spatial mapping of chemical detail within the complex environment of living systems. Herein, we demonstrate a chromic Covalent Organic Framework (COF) integrated within silk fibroin (SF) microneedles that probe plant vasculature, sense the alkalization of vascular fluid as a biomarker for drought stress, and provide a 3D in-vivo mapping of chemical gradients using smartphone technology. A series of Schiff base COFs with tunable pKa ranging from 5.6 to 7.6 enable conical, optically transparent SF microneedles with COF coatings of 120 to 950 nm to probe vascular fluid and the surrounding tissues of tobacco and tomato plants. The conical design allows for 3D mapping of the chemical environment (such as pH) at standoff distances from the plant, enabling in-vivo chemical tomography. Chromatic COF sensors of this type will enable multidimensional chemical mapping of previously inaccessible and complex environments.

Decoding early stress signaling waves in living plants using nanosensor multiplexing

Mon, 01 Jan 2024 00:00:00 GMT

Decoding early stress signaling waves in living plants using nanosensor multiplexing Ang, Mervin Chun-Yi; Saju, Jolly Madathiparambil; Porter, Thomas K; Mohaideen, Sayyid; Sarangapani, Sreelatha; Khong, Duc Thinh; Wang, Song; Cui, Jianqiao; Loh, Suh In; Singh, Gajendra Pratap; Chua, Nam-Hai; Strano, Michael S; Sarojam, Rajani Increased exposure to environmental stresses due to climate change have adversely affected plant growth and productivity. Upon stress, plants activate a signaling cascade, involving multiple molecules like H2O2, and plant hormones such as salicylic acid (SA) leading to resistance or stress adaptation. However, the temporal ordering and composition of the resulting cascade remains largely unknown. In this study we developed a nanosensor for SA and multiplexed it with H2O2 nanosensor for simultaneous monitoring of stress-induced H2O2 and SA signals when Brassica rapa subsp. Chinensis (Pak choi) plants were subjected to distinct stress treatments, namely light, heat, pathogen stress and mechanical wounding. Nanosensors reported distinct dynamics and temporal wave characteristics of H2O2 and SA generation for each stress. Based on these temporal insights, we have formulated a biochemical kinetic model that suggests the early H2O2 waveform encodes information specific to each stress type. These results demonstrate that sensor multiplexing can reveal stress signaling mechanisms in plants, aiding in developing climate-resilient crops and pre-symptomatic stress diagnoses.

Polymeric Nanocarriers Autonomously Cross the Plant Cell Wall and Enable Protein Delivery for Stress Sensing

Fri, 16 Aug 2024 00:00:00 GMT

Polymeric Nanocarriers Autonomously Cross the Plant Cell Wall and Enable Protein Delivery for Stress Sensing Zhang, Yilin; Cao, Yunteng; Jiang, Wenzhi; Ma, Qingquan; Shin, Jinwoo; Sun, Hui; Cui, Jianqiao; Chen, Yongsheng; Giraldo, Juan Pablo; Strano, Michael S; Lowry, Gregory V; Sheen, Jen; Marelli, Benedetto Delivery of proteins in plant cells can facilitate the design of desired functions by modulation of biological processes and plant traits but is currently limited by narrow host range, tissue damage, and poor scalability. Physical barriers in plants, including cell walls and membranes, limit protein delivery to desired plant tissues. Herein, a cationic high aspect ratio polymeric nanocarriers (PNCs) platform is developed to enable efficient protein delivery to plants. The cationic nature of PNCs binds proteins through electrostatic. The ability to precisely design PNCs’ size and aspect ratio allowed us to find a cutoff of ≈14 nm in the cell wall, below which cationic PNCs can autonomously overcome the barrier and carry their cargo into plant cells. To exploit these findings, a reduction‐oxidation sensitive green fluorescent protein (roGFP) is deployed as a stress sensor protein cargo in a model plant Nicotiana benthamiana and common crop plants, including tomato and maize. In vivo imaging of PNC‐roGFP enabled optical monitoring of plant response to wounding, biotic, and heat stressors. These results show that PNCs can be precisely designed below the size exclusion limit of cell walls to overcome current limitations in protein delivery to plants and facilitate species‐independent plant engineering.

Analysis of Glucose Responsive Glucagon Therapeutics using Computational Models of the Glucoregulatory System

Thu, 29 Aug 2024 00:00:00 GMT

Analysis of Glucose Responsive Glucagon Therapeutics using Computational Models of the Glucoregulatory System Alizadehmojarad, Ali A; Yang, Sungyun; Gong, Xun; Strano, Michael S Glucose‐responsive glucagon (GRG) therapeutics are a promising technology for reducing the risk of severe hypoglycemia as a complication of diabetes mellitus. Herein, the performance of candidate GRGs in the literature by modeling the kinetics of activation and connecting them as input into physiological glucoregulatory models is evaluated and projected the two distinct GRG designs, experimental results reported in Wu et al. (GRG‐I) and Webber et al. (GRG‐II) is considered. Both are evaluated using a multi‐compartmental glucoregulatory model (IMPACT) and used to compare in‐vivo experimental data of therapeutic performance in rats and mice. For GRG‐I and GRG‐II, the total integrated glucose material balances are overestimated by 41.5% ± 14% and underestimated by 24.8% ± 16% compared to in‐vivo time‐course data, respectively. These large differences to the relatively simple computational descriptions of glucagon dynamics in the model, which underscores the urgent need for improved glucagon models is attributed. Additionally, therapeutic insulin and glucagon infusion pumps are modeled for type 1 diabetes mellitus (T1DM) human subjects to extend the results to additional datasets. These observations suggest that both the representative physiological and non‐physiological models considered in this work require additional refinement to successfully describe clinical data that involve simultaneous, coupled insulin, glucose, and glucagon dynamics.

A Microrobotic Design for the Spontaneous Tracing of Isochemical Contours in the Environment

Mon, 09 Sep 2024 00:00:00 GMT

A Microrobotic Design for the Spontaneous Tracing of Isochemical Contours in the Environment Brooks, A Merritt; Yang, Sungyun; Kang, Byung Ha; Strano, Michael S Microrobotic platforms hold significant potential to advance a variety of fields, from medicine to environmental sensing. Herein, minimally functional robotic entities modeled on readily achievable state-of-the-art features in a modern lab or cleanroom are computationally simulated. Inspired by Dou and Bishop (Phys Rev Res. 2019;1(3):1–5), it is shown that the simple combination of unidirectional steering connected to a single environmental (chemical) sensor along with constant propulsion gives rise to highly complex functions of significant utility. Such systems can trace the contours orthogonal to arbitrary chemical gradients in the environment. Also, pairs of such robots that are additionally capable of emitting the same chemical signal are shown to exhibit coupled relative motion. When the pair has unidirectional steering in opposite directions within the 2D plane (i.e., counter-rotating), they move in parallel trajectories to each other. Alternatively, when steering is in the same direction (corotation), the two move in the same epicyclical trajectory. In this way, the chirality of the unidirectional steering produces two distinct emergent phenomena. The behavior is understood as a ratchet mechanism that exploits the differential in the radii of curvature corresponding to different spatial locations. Applications to environmental detection, remediation, and monitoring are discussed.

Electrokinetic Motion of Neurotransmitter Ions through a 1.01 nm Diameter Single-Walled Carbon Nanotube

Tue, 11 Mar 2025 00:00:00 GMT

Electrokinetic Motion of Neurotransmitter Ions through a 1.01 nm Diameter Single-Walled Carbon Nanotube Ellison, Mark D; Allen, Jacqueline; Bonfiglio, Michael; Seeburger, Matthew; Setenet, Jean; DiGinto, Biagio; Bonanny, Harrison; Russell, Aaliyah; Baird, David; Davis, Liana; McCarthy, Ella; Manley, Alyson; Blatt, Sarah; Lippe, David; Ragone, Daniel; Dyer, Brock; Osgood, Jillian; Strano, Michael S The transport of cations of the neurotransmitters acetylcholine, choline, and dopamine through a 1.01 nm-diameter, 1.1 mm-long single-walled carbon nanotube (SWNT) has been studied for the first time. As a comparison, sodium and aniline ion transport was also investigated. All of these ions exhibited significantly enhanced electrophoretic mobilities over bulk transport. The electrophoretic mobilities of acetylcholine, choline, and sodium were found to depend on pH, specifically increasing as pH decreases. This result is explained by hydrogen ions saturating the surface charges of the SWNT. Conversely, dopamine and aniline have mobilities that do not depend on pH. This difference is attributed to the benzene ring and the size of these ions. An analysis of the time required for an ion to traverse the nanotube shows that the ions adsorb to and desorb from the walls as they pass through the tube. Acetylcholine, choline, and sodium show desorption rate constants that decrease with increasing pH, whereas dopamine and aniline have rate constants that remain constant over different pH values. This is consistent with the relationship between adsorption and desorption rate constants and mobility from an adsorption/desorption kinetic model.

Advancements in Plant Diagnostic and Sensing Technologies

Mon, 23 Jun 2025 00:00:00 GMT

Advancements in Plant Diagnostic and Sensing Technologies Krishnamoorthi, Shalini; Koh, Sally Shuxian; Ang, Mervin Chun‐Yi; Teo, Mark Ju Teng; Jie, Randall Ang; Dinish, US; Strano, Michael S; Urano, Daisuke Recent advancements in plant sensing technologies have significantly improved agricultural productivity while reducing resource inputs, resulting in higher yields by enabling early disease detection, precise diagnostics, and optimized fertilizer and pesticide applications. Each adopted technology offers unique advantages suitable for various farm operations, breeding programs, and laboratory research. This review article first summarizes key target traits, endogenous structures, and metabolites that serve as focal points for plant diagnostic and sensing technologies. Next, conventional plant sensing technologies based on light reflectance and fluorescence, which rely on foliar phytopigments and fluorophores such as chlorophylls are discussed. These methods, along with advanced analytical strategies incorporating machine learning, enable accurate stress detection and classification beyond general assessments of plant health and stress status. Advanced optical techniques such as Fourier transform infrared spectroscopy (FT‐IR) and Raman spectroscopy, which allow specific measurements of various plant metabolites and structural components are then highlighted. Furthermore, the design and applications of nanotechnology chemical sensors capable of highly sensitive and selective detection of specific phytochemicals, including phytohormones and signaling second messengers, which regulate physiological and developmental processes at micro‐ to sub‐micromolar concentrations are introduced. By selecting appropriate sensing methodologies, agricultural production, and relevant research activities can be significantly improved.

The Jacobi Factoring Circuit: Quantum Factoring with Near-Linear Gates and Sublinear Space and Depth

Sun, 15 Jun 2025 00:00:00 GMT

The Jacobi Factoring Circuit: Quantum Factoring with Near-Linear Gates and Sublinear Space and Depth Kahanamoku-Meyer, Gregory D.; Ragavan, Seyoon; Vaikuntanathan, Vinod; Van Kirk, Katherine We present a compact quantum circuit for factoring a large class of integers, including some whose classical hardness is expected to be equivalent to RSA (but not including RSA integers themselves). Most notably, we factor n-bit integers of the form P2 Q with logQ = Θ(na) for a ∈ (2/3, 1) in space and depth sublinear in n (specifically, O(logQ)) using O(n) quantum gates; for these integers, no known classical algorithms exploit the relatively small size of Q to run asymptotically faster than general-purpose factoring algorithms. To our knowledge, this is the first polynomial-time circuit to achieve sublinear qubit count for a classically-hard factoring problem. We thus believe that factoring such numbers has potential to be the most concretely efficient classically-verifiable proof of quantumness currently known. Our circuit builds on the quantum algorithm for squarefree decomposition discovered by Li, Peng, Du, and Suter (Nature Scientific Reports 2012), which relies on computing the Jacobi symbol in quantum superposition. The technical core of our contribution is a new space-efficient quantum algorithm to compute the Jacobi symbol of A mod B, in the regime where B is classical and much larger than A. Our circuit for computing the Jacobi symbol generalizes to related problems such as computing the greatest common divisor and modular inverses, and thus could be of independent interest. STOC ’25, Prague, Czechia

Classical Commitments to Quantum States

Sun, 15 Jun 2025 00:00:00 GMT

Classical Commitments to Quantum States Gunn, Sam; Tauman Kalai, Yael; Natarajan, Anand; Vill?nyi, ?gi We define the notion of a classical commitment scheme to quantum states, which allows a quantum prover to compute a classical commitment to a quantum state, and later open each qubit of the state in either the standard or the Hadamard basis. Our notion is a strengthening of the measurement protocol from Mahadev (STOC 2018). We construct such a commitment scheme from the post-quantum Learning With Errors (LWE) assumption, and more generally from any noisy trapdoor claw-free function family that has the distributional strong adaptive hardcore bit property (a property that we define in this work). Our scheme is succinct in the sense that the running time of the verifier in the commitment phase depends only on the security parameter (independent of the size of the committed state), and its running time in the opening phase grows only with the number of qubits that are being opened (and the security parameter). As a corollary we obtain a classical succinct argument system for QMA under the post-quantum LWE assumption. Previously, this was only known assuming post-quantum secure indistinguishability obfuscation. As an additional corollary we obtain a generic way of converting any X/Z quantum PCP into a succinct argument system under the quantum hardness of LWE. STOC ’25, Prague, Czechia

Symmetric Perceptrons, Number Partitioning and Lattices

Sun, 15 Jun 2025 00:00:00 GMT

Symmetric Perceptrons, Number Partitioning and Lattices Vafa, Neekon; Vaikuntanathan, Vinod The symmetric binary perceptron (SBPκ) problem with parameter κ : ℝ≥1 → [0,1] is an average-case search problem defined as follows: given a random Gaussian matrix A ∼ N(0,1)n × m as input where m ≥ n, output a vector x ∈ {−1,1}m such that || A x ||∞ ≤ κ(m/n) · √m . The number partitioning problem (NPPκ) corresponds to the special case of setting n=1. There is considerable evidence that both problems exhibit large computational-statistical gaps. In this work, we show (nearly) tight average-case hardness for these problems, assuming the worst-case hardness of standard approximate shortest vector problems on lattices. • For SBPκ, statistically, solutions exist with κ(x) = 2−Θ(x) (Aubin, Perkins and Zdeborová, Journal of Physics 2019). For large n, the best that efficient algorithms have been able to achieve is a far cry from the statistical bound, namely κ(x) = Θ(1/√x) (Bansal and Spencer, Random Structures and Algorithms 2020). The problem has been extensively studied in the TCS and statistics communities, and Gamarnik, Kızıldağ, Perkins and Xu (FOCS 2022) conjecture that Bansal-Spencer is tight: namely, κ(x) = Θ(1/√x) is the optimal value achieved by computationally efficient algorithms. We prove their conjecture assuming the worst-case hardness of approximating the shortest vector problem on lattices. • For NPPκ, statistically, solutions exist with κ(m) = Θ(2−m) (Karmarkar, Karp, Lueker and Odlyzko, Journal of Applied Probability 1986). Karmarkar and Karp’s classical differencing algorithm achieves κ(m) = 2−O(log2 m) . We prove that Karmarkar-Karp is nearly tight: namely, no polynomial-time algorithm can achieve κ(m) = 2−Ω(log3 m), once again assuming the worst-case subexponential hardness of approximating the shortest vector problem on lattices to within a subexponential factor. Our hardness results are versatile, and hold with respect to different distributions of the matrix A (e.g., i.i.d. uniform entries from [0,1]) and weaker requirements on the solution vector x. STOC ’25, Prague, Czechia

DNF Learning via Locally Mixing Random Walks

Sun, 15 Jun 2025 00:00:00 GMT

DNF Learning via Locally Mixing Random Walks Alman, Josh; Nadimpalli, Shivam; Patel, Shyamal; Servedio, Rocco A. We give two results on PAC learning DNF formulas using membership queries in the challenging “distribution-free” learning framework, where learning algorithms must succeed for an arbitrary and unknown distribution over {0,1}n. (1) We first give a quasi-polynomial time “list-decoding” algorithm for learning a single term of an unknown DNF formula. More precisely, for any target s-term DNF formula f = T1 ∨ ⋯ ∨ Ts over {0,1}n and any unknown distribution D over {0,1}n, our algorithm, which uses membership queries and random examples from D, runs in quasipoly(n,s) time and outputs a list L of candidate terms such that with high probability some term Ti of f belongs to L. (2) We then use result (1) to give a quasipoly(n,s)-time algorithm, in the distribution-free PAC learning model with membership queries, for learning the class of size-s DNFs in which all terms have the same size. Our algorithm learns using a DNF hypothesis. The key tool used to establish result (1) is a new result on “locally mixing random walks,” which, roughly speaking, shows that a random walk on a graph that is covered by a small number of expanders has a non-negligible probability of mixing quickly in a subset of these expanders. STOC ’25, Prague, Czechia

Near Optimal Constant Inapproximability under ETH for Fundamental Problems in Parameterized Complexity

Sun, 15 Jun 2025 00:00:00 GMT

Near Optimal Constant Inapproximability under ETH for Fundamental Problems in Parameterized Complexity Bafna, Mitali; Karthik C. S.; Minzer, Dor We prove that under the Exponential Time Hypothesis (ETH), for every ε > 0, there exists a constant C > 0 such that no algorithm running in time nk / logC k can determine whether a given 2-CSP instance with k variables, O(k) constraints, and alphabet size n, is perfectly satisfiable or if every assignment satisfies at most an ε fraction of the constraints. By known reductions in the literature, the above result implies near-optimal conditional lower bounds for approximating a host of parameterized problems, such as the k-Clique problem, k-Max-Coverage problem, k-Unique Set Cover problem, k-Median and k-Means problems, parameterized variants of the Nearest Codeword problem, Minimum Distance of a Code problem, Closest Vector problem, and Shortest Vector problem. We also establish a densification theorem for the parameterized 2-CSP problem, showing that the aforementioned conditional lower bound for sparse 2-CSPs also holds when the constraint graph is a complete graph. From this densification, we conclude that assuming ETH, there is no algorithm running in time n√k / logC k that approximates the k-Directed Steiner Network problem and the k-Strongly Connected Steiner Subgraph problem to some constant factors. Mitali Bafna, Karthik C. S., and Dor Minzer. 2025. Near Optimal Constant Inapproximability under ETH for Fundamental Problems in Parameterized Complexity. In Proceedings of the 57th Annual ACM Symposium on Theory of Computing (STOC '25). Association for Computing Machinery, New York, NY, USA, 2118–2129.

Oblivious Defense in ML Models: Backdoor Removal without Detection

Sun, 15 Jun 2025 00:00:00 GMT

Oblivious Defense in ML Models: Backdoor Removal without Detection Goldwasser, Shafi; Shafer, Jonathan; Vafa, Neekon; Vaikuntanathan, Vinod As society grows more reliant on machine learning, ensuring the security of machine learning systems against sophisticated attacks becomes a pressing concern. A recent result of Goldwasser, Kim, Vaikuntanathan, and Zamir (FOCS ’22) shows that an adversary can plant undetectable backdoors in machine learning models, allowing the adversary to covertly control the model’s behavior. Backdoors can be planted in such a way that the backdoored machine learning model is computationally indistinguishable from an honest model without backdoors. In this paper, we present strategies for defending against backdoors in ML models, even if they are undetectable. The key observation is that it is sometimes possible to provably mitigate or even remove backdoors without needing to detect them, using techniques inspired by the notion of random self-reducibility. This depends on properties of the ground-truth labels (chosen by nature), and not of the proposed ML model (which may be chosen by an attacker). We give formal definitions for secure backdoor mitigation, and proceed to show two types of results. First, we show a “global mitigation” technique, which removes all backdoors from a machine learning model under the assumption that the ground-truth labels are close to a Fourier-heavy function. Second, we consider distributions where the ground-truth labels are close to a linear or polynomial function in ℝn. Here, we show “local mitigation” techniques, which remove backdoors with high probability for every input of interest, and are computationally cheaper than global mitigation. All of our constructions are black-box, so our techniques work without needing access to the model’s representation (i.e., its code or parameters). Along the way we prove a simple result for robust mean estimation. STOC ’25, Prague, Czechia

Faster Rates for No-Regret Learning in General Games via Cautious Optimism

Sun, 15 Jun 2025 00:00:00 GMT

Faster Rates for No-Regret Learning in General Games via Cautious Optimism Soleymani, Ashkan; Piliouras, Georgios; Farina, Gabriele We establish the first uncoupled learning algorithm that attains O(n log2 d logT) per-player regret in multi-player general-sum games, where n is the number of players, d is the number of actions available to each player, and T is the number of repetitions of the game. Our results exponentially improve the dependence on d compared to the O(n  d logT) regret attainable by Log-Regularized Lifted Optimistic FTRL introduced by Farina, Anagnostides, Luo, Lee, Kroer, and Sandholm [2022], and also reduce the dependence on the number of iterations T from log4 T to logT compared to Optimistic Hedge, the previously well-studied algorithm with O(n logd log4 T) regret shown by Daskalakis, Fishelson, and Golowich [2021]. Our algorithm is obtained by combining the classic Optimistic Multiplicative Weights Update (OMWU) with an adaptive, non-monotonic learning rate that paces the learning process of the players, making them more cautious when their regret becomes too negative. STOC ’25, Prague, Czechia

Explicit Two-Sided Vertex Expanders beyond the Spectral Barrier

Sun, 15 Jun 2025 00:00:00 GMT

Explicit Two-Sided Vertex Expanders beyond the Spectral Barrier Hsieh, Jun-Ting; Lin, Ting-Chun; Mohanty, Sidhanth; O'Donnell, Ryan; Zhang, Rachel Yun We construct the first explicit two-sided vertex expanders that bypass the spectral barrier. Previously, the strongest known explicit vertex expanders were given by d-regular Ramanujan graphs, whose spectral properties imply that every small subset of vertices S has at least 0.5d|S| distinct neighbors. However, it is possible to construct Ramanujan graphs containing a small set S with no more than 0.5d|S| neighbors. In fact, no explicit construction was known to break the 0.5 d-barrier. In this work, we give an explicit construction of an infinite family of d-regular graphs (for large enough d) where every small set expands by a factor of ≈ 0.6d. More generally, for large enough d1,d2, we give an infinite family of (d1,d2)-biregular graphs where small sets on the left expand by a factor of ≈ 0.6d1, and small sets on the right expand by a factor of ≈ 0.6d2. In fact, our construction satisfies an even stronger property: small sets on the left and right have unique-neighbor expansion 0.6d1 and 0.6d2 respectively. Our construction follows the tripartite line product framework of Hsieh et. al., and instantiates it using the face-vertex incidence of the 4-dimensional Ramanujan clique complex as its base component. As a key part of our analysis, we derive new bounds on the triangle density of small sets in the Ramanujan clique complex. STOC ’25, Prague, Czechia

All-Pairs Shortest Paths with Few Weights per Node

Sun, 15 Jun 2025 00:00:00 GMT

All-Pairs Shortest Paths with Few Weights per Node Abboud, Amir; Fischer, Nick; Jin, Ce; Williams, Virginia Vassilevska; Xi, Zoe We study the central All-Pairs Shortest Paths (APSP) problem under the restriction that there are at most d distinct weights on the outgoing edges from every node. For d=n this is the classical (unrestricted) APSP problem that is hypothesized to require cubic time n3−o(1), and at the other extreme, for d=1, it is equivalent to the Node-Weighted APSP problem. We present new algorithms that achieve the following results: * Node-Weighted APSP can be solved in time Õ(n(3+ω)/2) = Õ(n2.686), improving on the 15-year-old subcubic bounds Õ(n(9+ω)/4) = Õ(n2.843) [Chan; STOC ’07] and Õ(n2.830) [Yuster; SODA ’09]. This positively resolves the question of whether Node-Weighted APSP is an ”intermediate” problem in the sense of having complexity n2.5+o(1) if ω=2, in which case it also matches an n2.5−o(1) conditional lower bound. * For up to d ≤ n3−ω−є distinct weights per node (where є > 0), the problem can be solved in subcubic time O(n3−f(є)) (where f(є) > 0). In particular, assuming that ω = 2, we can tolerate any sublinear number of distinct weights per node d ≤ n1−є, whereas previous work [Yuster; SODA ’09] could only handle d ≤ n1/2−є in subcubic time. This promotes our understanding of the APSP hypothesis showing that the hardest instances must exhaust a linear number of weights per node. With the current bounds on ω, we achieve a subcubic algorithm for d ≤ n0.628 whereas previously a subcubic running time could only be achieved for d ≤ n0.384. Our result also applies to the All-Pairs Exact Triangle problem, thus generalizing a result of Chan and Lewenstein on “Clustered 3SUM” from arrays to matrices. Notably, our technique constitutes a rare application of additive combinatorics in graph algorithms. We complement our algorithmic results with simple hardness reductions extending the n2.5−o(1) conditional lower bound for Node-Weighted APSP to undirected graphs. Interestingly, under fine-grained assumptions, the complexity in the undirected case jumps from O(nω) for d=1 to n2.5−o(1) for d ≥ 2. STOC ’25, Prague, Czechia

Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses

Sun, 15 Jun 2025 00:00:00 GMT

Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses Huang, Brice; Mohanty, Sidhanth; Rajaraman, Amit; Wu, David X. There has been a recent surge of powerful tools to show rapid mixing of Markov chains, via functional inequalities such as Poincaré inequalities. In many situations, Markov chains fail to mix rapidly from a worst-case initialization, yet are expected to approximately sample from a random initialization. For example, this occurs if the target distribution has metastable states, small clusters accounting for a vanishing fraction of the mass that are essentially disconnected from the bulk of the measure. Under such conditions, a Poincaré inequality cannot hold, necessitating new tools to prove sampling guarantees. We develop a framework to analyze simulated annealing, based on establishing so-called weak Poincaré inequalities. These inequalities imply mixing from a suitably warm start, and simulated annealing provides a way to chain such warm starts together into a sampling algorithm. We further identify a local-to-global principle to prove weak Poincaré inequalities, mirroring the spectral independence and localization schemes frameworks for analyzing mixing times of Markov chains. As our main application, we prove that simulated annealing samples from the Gibbs measure of a spherical spin glass for inverse temperatures up to a natural threshold, matching recent algorithms based on algorithmic stochastic localization. This provides the first Markov chain sampling guarantee that holds beyond the uniqueness threshold for spherical spin glasses, where mixing from a worst-case initialization is provably slow due to the presence of metastable states. As an ingredient in our proof, we prove bounds on the operator norm of the covariance matrix of spherical spin glasses in the full replica-symmetric regime. Additionally, we resolve a question related to sampling using data-based initializations. The full version of this paper can be found on arXiv (arXiv ID: 2411.09075). STOC ’25, Prague, Czechia

Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics

Sun, 15 Jun 2025 00:00:00 GMT

Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics Gaitonde, Jason; Moitra, Ankur; Mossel, Elchanan We consider the problem of learning graphical models, also known as Markov random fields (MRFs) from temporally correlated samples. As in many traditional statistical settings, fundamental results in the area all assume independent samples from the distribution. However, these samples generally will not directly correspond to more realistic observations from nature, which instead evolve according to some stochastic process. From the computational lens, even generating a single sample from the true MRF distribution is intractable unless NP=RP, and moreover, any algorithm to learn from i.i.d. samples requires prohibitive runtime due to hardness reductions to the parity with noise problem. These computational barriers for sampling and learning from the i.i.d. setting severely lessen the utility of these breakthrough results for this important task; however, dropping this assumption typically only introduces further algorithmic and statistical complexities. In this work, we surprisingly demonstrate that the direct trajectory data from a natural evolution of the MRF overcomes the fundamental computational lower bounds to efficient learning. In particular, we show that given a trajectory with Ok(n) site updates of an order k MRF from the Glauber dynamics, a well-studied, natural stochastic process on graphical models, there is an algorithm that recovers the graph and the parameters in Ok(n2) time. By contrast, all prior algorithms for learning order k MRFs inherently suffer from nΘ(k) runtime even in sparse instances due to the reductions to sparse parity with noise. Our results thus surprisingly show that this more realistic, but intuitively less tractable, model for MRFs actually leads to efficiency far beyond what is known and believed to be true in the traditional i.i.d. case. STOC ’25, Prague, Czechia

Simulating Time with Square-Root Space

Sun, 15 Jun 2025 00:00:00 GMT

Simulating Time with Square-Root Space Williams, R. Ryan We show that for all functions t(n) ≥ n, every multitape Turing machine running in time t can be simulated in space only O(√t logt). This is a substantial improvement over Hopcroft, Paul, and Valiant’s simulation of time t in O(t/logt) space from 50 years ago [FOCS 1975, JACM 1977]. Among other results, our simulation implies that bounded fan-in circuits of size s can be evaluated on any input in only √s · poly(logs) space, and that there are explicit problems solvable in O(n) space which require at least n2−ε time on every multitape Turing machine for all ε > 0, thereby making a little progress on the P versus PSPACE problem. Our simulation reduces the problem of simulating time-bounded multitape Turing machines to a series of implicitly-defined Tree Evaluation instances with nice parameters, leveraging the remarkable space-efficient algorithm for Tree Evaluation recently found by Cook and Mertz [STOC 2024]. STOC ’25, Prague, Czechia

Model Stealing for Any Low-Rank Language Model

Sun, 15 Jun 2025 00:00:00 GMT

Model Stealing for Any Low-Rank Language Model Liu, Allen; Moitra, Ankur Model stealing, where a learner tries to recover an unknown model via carefully chosen queries, is a critical problem in machine learning, as it threatens the security of proprietary models and the privacy of data they are trained on. In recent years, there has been particular interest in stealing large language models (LLMs). In this paper, we aim to build a theoretical understanding of stealing language models by studying a simple and mathematically tractable setting. We study model stealing for Hidden Markov Models (HMMs), and more generally low-rank language models. We assume that the learner works in the conditional query model, introduced by Kakade, Krishnamurthy, Mahajan and Zhang. Our main result is an efficient algorithm in the conditional query model, for learning any low-rank distribution. In other words, our algorithm succeeds at stealing any language model whose output distribution is low-rank. This improves upon the previous result which also requires the unknown distribution to have high “fidelity” – a property that holds only in restricted cases. There are two key insights behind our algorithm: First, we represent the conditional distributions at each timestep by constructing barycentric spanners among a collection of vectors of exponentially large dimension. Second, for sampling from our representation, we iteratively solve a sequence of convex optimization problems that involve projection in relative entropy to prevent compounding of errors over the length of the sequence. This is an interesting example where, at least theoretically, allowing a machine learning model to solve more complex problems at inference time can lead to drastic improvements in its performance. STOC ’25, Prague, Czechia

Maximum Circuit Lower Bounds for Exponential-Time Arthur Merlin

Sun, 15 Jun 2025 00:00:00 GMT

Maximum Circuit Lower Bounds for Exponential-Time Arthur Merlin Chen, Lijie; Li, Jiatu; Liang, Jingxun We show that the complexity class of exponential-time Arthur Merlin with sub-exponential advice (AMEXP/2nε) requires circuit complexity at least 2n/n. Previously, the best known such near-maximum lower bounds were for symmetric exponential time by Chen, Hirahara, and Ren (STOC’24) and Li (STOC’24), or randomized exponential time with MCSP oracle and sub-exponential advice by Hirahara, Lu, and Ren (CCC’23). Our result is proved by combining the recent iterative win-win paradigm of Chen, Lu, Oliveira, Ren, and Santhanam (FOCS’23) together with the uniform hardness-vs-randomness connection for Arthur-Merlin protocols by Shaltiel-Umans (STOC’07) and van Melkebeek-Sdroievski (CCC’23). We also provide a conceptually different proof using a novel ”critical win-win” argument that extends a technique of Lu, Oliveira, and Santhanam (STOC’21). Indeed, our circuit lower bound is a corollary of a new explicit construction for properties in coAM. We show that for every dense property P ∈ coAM, there is a quasi-polynomial-time Arthur-Merlin protocol with short advice such that the following holds for infinitely many n: There exists a canonical string wn ∈ P ∩ {0,1}n so that (1) there is a strategy of Merlin such that Arthur outputs wn with probability 1 and (2) for any strategy of Merlin, with probability 2/3, Arthur outputs either wn or a failure symbol ⊥. As a direct consequence of this new explicit construction, our circuit lower bound also generalizes to circuits with an AM ∩ coAM oracle. To our knowledge, this is the first unconditional lower bound against a strong non-uniform class using a hard language that is only ”quantitatively harder”. STOC ’25, Prague, Czechia

List-Decoding Capacity Implies Capacity on the 𝑞-ary Symmetric Channel

Sun, 15 Jun 2025 00:00:00 GMT

List-Decoding Capacity Implies Capacity on the 𝑞-ary Symmetric Channel Pernice, Francisco; Sprumont, Oscar; Wootters, Mary It is known that the Shannon capacity of the q-ary symmetric channel (qSC) is the same as the list-decoding capacity of an adversarial channel, raising the question of whether there is a formal (and black-box) connection between the two. We show that there is: Any linear code C⊆ Fqn that has superconstant minimum distance and achieves list-decoding capacity also achieves capacity on the qSC. STOC ’25, Prague, Czechia

A molecularly impermeable polymer from two-dimensional polyaramids

Wed, 12 Nov 2025 00:00:00 GMT

A molecularly impermeable polymer from two-dimensional polyaramids Ritt, Cody L; Quien, Michelle; Wei, Zitang; Gress, Hagen; Dronadula, Mohan T; Altmisdort, Kaan; Nguyen, Huong Giang T; Zangmeister, Christopher D; Tu, Yu-Ming; Garimella, Sanjay S; Amirabadi, Shahab; Gadaloff, Michael; Hu, Weiguo; Aluru, Narayana R; Ekinci, Kamil L; Bunch, J Scott; Strano, Michael S All polymers exhibit gas permeability through the free volume of entangled polymer chains1, 2–3. By contrast, two-dimensional (2D) materials including graphene stack densely and can exhibit molecular impermeability4, 5–6. Solution-synthesized 2D polymers that exhibit the latter by poly-condensation have been a longstanding goal. Herein, we demonstrate self-supporting, spin-coated 2D polyaramid nanofilms that exhibit nitrogen permeability below 3.1 × 10−9 Barrer, nearly four orders of magnitude lower than every class of existing polymer, and similar for other gases tested (helium, argon, oxygen, methane and sulfur hexafluoride). Optical interference during the pressurization of nanofilm-coated microwells allows measurement of mechanosensitive rim opening and sealing, creating gas-filled bulges that are stable exceeding three years. This discovery enables 2D polymer resonators with high resonance frequencies (about 8 MHz) and quality factors up to 537, similar to graphene. A 60-nm coating of air-sensitive perovskites reduces the lattice degradation rate 14-fold with an oxygen permeability of 3.3 × 10−8 Barrer. Molecularly impermeable polymers promise the next generation of barriers that are synthetically processable, chemically amenable and maximize molecular rejection with minimal material, ultimately advancing sustainability goals.

Molecularly Thin Polyaramid Nanomechanical Resonators

Wed, 03 Dec 2025 00:00:00 GMT

Molecularly Thin Polyaramid Nanomechanical Resonators Gress, Hagen; Ritt, Cody L; Shomakhov, Inal; Altmisdort, Kaan; Quien, Michelle; Wei, Zitang; Lawall, John R; Boddeti, Narasimha; Strano, Michael S; Bunch, J Scott; Ekinci, Kamil L Two-dimensional polyaramids exhibit strong hydrogen bonding to create molecularly thin nanosheets analogous to graphene. Here, we report the first nanomechanical resonators made out of a two-dimensional polyaramid, 2DPA-1, with thicknesses as small as 8 nm. To fabricate these molecular-scale resonators, we transferred nanofilms of 2DPA-1 onto chips with previously etched arrays of circular microwells. We then characterized the thermal resonances of these resonators under different conditions. When there is no residual gas inside the 2DPA-1-covered microwells, the eigenfrequencies are well-described by a tensioned plate theory, providing the Young's modulus and tension of the 2DPA-1 nanofilms. With gas present, the nanofilms bulge up and mechanical resonances are modified due to the adhesion, bulging and slack present in the system. The fabrication and mechanical characterization of these first 2DPA-1 nanomechanical resonators represent a convincing path toward molecular-scale polymeric NEMS with high mechanical strength, low density, and synthetic processability.

Interferometric Deflection Analysis of Suspended 2D Polyaramid Thin Films

Fri, 05 Dec 2025 00:00:00 GMT

Interferometric Deflection Analysis of Suspended 2D Polyaramid Thin Films Quien, Michelle; Ritt, Cody L; Garimella, Sanjay S; Gress, Hagen; Ekinci, Kamil L; Bunch, Joseph Scott; Strano, Michael S The 2D nanofilm bulge test, which uses an Atomic Force Microscope (AFM) to measure the deflection of a suspended film under various conditions, has emerged as an important measurement platform for understanding mechanical, barrier, and permeability properties of 2D materials as thickness approaches the angstrom scale. The problem considered in this work is the limitation of such bulge analyses imposed by the AFM whereby dynamic measurements under high pressure, high temperature, and chemically corrosive conditions are limited. In this work, a technique is developed for measuring nanofilm deflection using only visible light interferometry. Both theoretical and semi‐empirical models are applied to translate multicolor interference patterns from broadband excitation into estimates of nano‐film deflection, allowing nanoscale precision in most cases. The technique and algorithm advanced in this work allows the use of widespread optical microscopy to widen the study of these important 2D nanofilm systems to more relevant conditions.

Quantum One-Time Programs, Revisited

Sun, 15 Jun 2025 00:00:00 GMT

Quantum One-Time Programs, Revisited Gupte, Aparna; Liu, Jiahui; Raizes, Justin; Roberts, Bhaskar; Vaikuntanathan, Vinod One-time programs (Goldwasser, Kalai and Rothblum, CRYPTO 2008) are programs that can be run on any single input of a user’s choice, but not on a second input. Classically, they are unachievable without trusted hardware, but the destructive nature of quantum measurements seems to provide an alternate path to constructing them. Unfortunately, Broadbent, Gutoski and Stebila (CRYPTO 2013) showed that even with quantum techniques, a strong notion of one-time programs, similar to ideal obfuscation, cannot be achieved for any non-trivial quantum function. On the positive side, Ben-David and Sattath (Quantum, 2023) showed how to construct a quantum one-time program for a certain (probabilistic) digital signature scheme, under a weaker notion of one-time program security. There is a vast gap between achievable and provably impossible notions of one-time program security, and it is unclear what functionalities are one-time programmable and which are not, under the achievable notions of security. In this work, we present new, meaningful, yet achievable definitions of one-time program security for probabilistic classical functions. We show how to construct one time programs satisfying these definitions for all functions in the classical oracle model and for constrained pseudorandom functions in the plain model. Finally, we examine the limits of these notions: we show a class of functions which cannot be one-time programmed in the plain model, as well as a class of functions which appears to be highly random given a single query, but whose quantum one-time program leaks the entire function even in the oracle model. STOC ’25, Prague, Czechia

Learning the Closest Product State

Sun, 15 Jun 2025 00:00:00 GMT

Learning the Closest Product State Bakshi, Ainesh; Bostanci, John; Kretschmer, William; Landau, Zeph; Li, Jerry; Liu, Allen; O'Donnell, Ryan; Tang, Ewin We study the problem of finding a product state with optimal fidelity to an unknown n-qubit quantum state ρ, given copies of ρ. This is a basic instance of a fundamental question in quantum learning: is it possible to efficiently learn a simple approximation to an arbitrary state? We give an algorithm which finds a product state with fidelity ε-close to optimal, using N = npoly(1/ε) copies of ρ and poly(N) classical overhead. We further show that estimating the optimal fidelity is NP-hard for error ε = 1/poly(n), showing that the error dependence cannot be significantly improved. For our algorithm, we build a carefully-defined cover over candidate product states, qubit by qubit, and then demonstrate that extending the cover can be reduced to approximate constrained polynomial optimization. For our proof of hardness, we give a formal reduction from polynomial optimization to finding the closest product state. Together, these results demonstrate a fundamental connection between these two seemingly unrelated questions. Building on our general approach, we also develop more efficient algorithms in three simpler settings: when the optimal fidelity exceeds 5/6; when we restrict ourselves to a discrete class of product states; and when we are allowed to output a matrix product state. STOC ’25, Prague, Czechia

Breaking the T^(2/3) Barrier for Sequential Calibration

Sun, 15 Jun 2025 00:00:00 GMT

Breaking the T^(2/3) Barrier for Sequential Calibration Dagan, Yuval; Daskalakis, Constantinos; Fishelson, Maxwell; Golowich, Noah; Kleinberg, Robert; Okoroafor, Princewill A set of probabilistic forecasts is calibrated if each prediction of the forecaster closely approximates the empirical distribution of outcomes on the subset of timesteps where that prediction was made. We study the fundamental problem of online calibrated forecasting of binary sequences, which was initially studied by Foster and Vohra. They derived an algorithm with O(T2/3) calibration error after T time steps, and showed a lower bound of Ω(T1/2). These bounds remained stagnant for two decades, until Qiao and Valiant improved the lower bound to Ω(T0.528) by introducing a combinatorial game called sign preservation and showing that lower bounds for this game imply lower bounds for calibration. In this paper, we give the first improvement to the O(T2/3) upper bound on calibration error of Foster and Vohra. We do this by introducing a variant of Qiao and Valiant’s game that we call sign preservation with reuse (SPR). We prove that the relationship between SPR and calibrated forecasting is bidirectional: not only do lower bounds for SPR translate into lower bounds for calibration, but algorithms for SPR also translate into new algorithms for calibrated forecasting. We then give an improved upper bound for the SPR game, which implies, via our equivalence, a forecasting algorithm with calibration error O(T2/3 − ) for some > 0, improving Foster and Vohra’s upper bound for the first time. Using similar ideas, we then prove a slightly stronger lower bound than that of Qiao and Valiant, namely Ω(T0.54389). Our lower bound is obtained by an oblivious adversary, marking the first ω(T1/2) calibration lower bound for oblivious adversaries. STOC ’25, Prague, Czechia

PrEP attitudes, willingness, and preferences among men incarcerated in jail in Massachusetts

Wed, 26 Nov 2025 00:00:00 GMT

PrEP attitudes, willingness, and preferences among men incarcerated in jail in Massachusetts Al Abosy, Jude; Kalavacherla, Sruthi; Koutoujian, Peter J.; Siddiqi, Kashif; Senst, Thomas; Caro, Jose; Grossman, Anna; Dong, Kimberly R. Background People who inject drugs (PWID) are both disproportionately incarcerated and affected by HIV infection. Systemic inequities perpetuate the cyclic nature of injection drug use (IDU) and incarceration, and both IDU and incarceration are linked to higher rates of HIV infection. Pre-exposure prophylaxis (PrEP) is highly effective in HIV prevention and is currently available as a daily oral pill. Longer-acting PrEP options, such as injectables and implants, are also in development to improve accessibility and adherence. Despite these advancements, PrEP uptake remains low among PWID and individuals recently released from jail, and there is limited literature exploring the preferences for PrEP uptake within this population. Methods We conducted qualitative interviews using a semi-structured interview guide with 20 male participants (19 incarcerated in a Massachusetts jail and 1 recently released) to assess perceived HIV risk, knowledge of PrEP, barriers to PrEP uptake, and preferences for PrEP modality and frequency. The data were analyzed using a directed content analysis approach. Results Most participants were aware of their HIV risk but were largely unaware of PrEP and had never been educated about PrEP by a healthcare provider. Participants cited a lack of access to healthcare, stigma around HIV infection, and feasibility as barriers to uptake. While participants expressed interest in longer-acting PrEP, most preferred the oral pill due to distrust of the safety and efficacy of injectables and implants, countering the assumption that modality changes alone can improve low PrEP uptake. Conclusions Our findings underscore the urgent need for targeted education and interventions to improve HIV prevention in vulnerable populations impacted by incarceration. While long-acting injectables have been touted to help address barriers to accessing healthcare among this population, skepticism about the efficacy of long-acting injectables among this population may prevent these efforts. It is important to further research the willingness to uptake PrEP and modality preferences among this population to meet their needs.

Search for a new scalar resonance decaying to a Higgs boson and another new scalar particle in the final state with two bottom quarks and two photons in proton-proton collisions at $$\sqrt{s}=13$$ TeV

Tue, 23 Dec 2025 00:00:00 GMT

Search for a new scalar resonance decaying to a Higgs boson and another new scalar particle in the final state with two bottom quarks and two photons in proton-proton collisions at $$\sqrt{s}=13$$ TeV Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Dragicevic, M.; Giordano, C.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Matthewman, M.; Mikulec, I. A search is presented for a new scalar resonance, X, decaying to a standard model Higgs boson and another new scalar particle, Y, in the final state where the Higgs boson decays to a $$\text{b}\overline{\text{b} }$$ pair, while the Y particle decays to a pair of photons. The search is performed in the mass range 240–1000 GeV for the resonance X, and in the mass range 70–800 GeV for the particle Y, using proton-proton collision data collected by the CMS experiment at $$\sqrt{s}=13$$ TeV, corresponding to an integrated luminosity of 132 fb−1. In general, the data are found to be compatible with the standard model expectation. Observed (expected) upper limits at 95% confidence level on the product of the production cross section and the relevant branching fraction are extracted for the X → YH process, and are found to be within the range of 0.05–2.69 (0.08–1.94) fb, depending on mX and mY. The most significant deviation from the background-only hypothesis is observed for X and Y masses of 300 and 77 GeV, respectively, with a local (global) significance of 3.33 (0.65) standard deviations.

Public Service Provision and the Virtuous Circle: Evidence from Malawi

Mon, 29 Dec 2025 00:00:00 GMT

Public Service Provision and the Virtuous Circle: Evidence from Malawi Chen, Nuole; Grady, Christopher; Dulani, Boniface; Masumbu, Mwayi; Chiona, Busta; Bowers, Jake; Winters, Matthew S. Many governments struggle to obtain the resources they need to govern effectively. In the virtuous circle model of state development, tax revenue allows governments to provide public goods and services to citizens, and citizens comply with taxation when governments provide sufficient levels of goods and services. The model, however, also suggests a vicious version of the circle, where citizens do not pay taxes, governments lack revenue to provide public goods and services, and citizens therefore continue to not pay taxes. Under this suboptimal equilibrium, governments cannot deliver on their governing and service provision mandates. We study whether a shock to public service provision in a major city in Malawi can induce citizens to pay taxes, thereby shifting the relationship between the city and its citizens from a vicious circle to a virtuous circle. With a difference-in-differences-style analysis, we show that households exposed to new government-provided waste collection expressed more trust in and better perceptions of the local government. Most importantly, these households were more likely to make tax payments. We find that this increase in tax payments largely came from people paying more of what they owed rather than from new taxpayers entering the rolls.

NonlinearSolve.jl: High-Performance and Robust Solvers for Systems of Nonlinear Equations in Julia

Mon, 01 Dec 2025 00:00:00 GMT

NonlinearSolve.jl: High-Performance and Robust Solvers for Systems of Nonlinear Equations in Julia Pal, Avik; Holtorf, Flemming; Larsson, Axel; Loman, Torkel; Rajput, Utkarsh; Sch?fer, Frank; Qu, Qingyu; Edelman, Alan; Rackauckas, Chris Efficiently solving nonlinear equations underpins numerous scientific and engineering disciplines, yet scaling these solutions for challenging system models remains a challenge. This paper presents NonlinearSolve.jl -- a suite of high-performance open-source nonlinear equation solvers implemented natively in the Julia programming language. NonlinearSolve.jl distinguishes itself by offering a unified API that accommodates a diverse range of solver specifications alongside features such as automatic algorithm selection based on runtime analysis, support for static array kernels for improved GPU computation on smaller problems, and the utilization of sparse automatic differentiation and Jacobian-free Krylov methods for large-scale problem-solving. Through rigorous comparison with established tools such as PETSc SNES, Sundials KINSOL, and MINPACK, NonlinearSolve.jl demonstrates robustness and efficiency, achieving significant advancements in solving nonlinear equations while being implemented in a high-level programming language. The capabilities of NonlinearSolve.jl unlock new potentials in modeling and simulation across various domains, making it a valuable addition to the computational toolkit of researchers and practitioners alike.

Property Testing with Online Adversaries

Tue, 02 Dec 2025 00:00:00 GMT

Property Testing with Online Adversaries Ben Eliezer, Omri; Kelman, Esty; Meir, Uri; Raskhodnikova, Sofya The online manipulation-resilient testing model, proposed by Kalemaj, Raskhodnikova and Varma (Theory of Computing 2023), studies property testing in situations where access to the input degrades continuously and adversarially. Our main contributions are as follows: - An extension of the model, introducing \emph{batch queries} where multiple queries are made and answered between each round of manipulation, and \emph{fractional manipulation rate}, where the adversary makes less than one manipulation per round. - New optimal testers for linearity testing of Boolean functions in the original online and offline models. - A new lower-bound for testing low-degree of Boolean functions in the original model which can be overcome by an algorithm using batch queries. - Efficient testers for local properties of sequences when the manipulation rate is fractional. Specifically, for sortedness, we show a sharp transition from optimal query complexity to the impossibility of testability, depending on the manipulation rate.

Engineered yeast tolerance enables efficient production from toxified lignocellulosic feedstocks

Fri, 25 Jun 2021 00:00:00 GMT

Engineered yeast tolerance enables efficient production from toxified lignocellulosic feedstocks Lam, Felix H; Turanlı-Yıldız, Burcu; Liu, Dany; Resch, Michael G; Fink, Gerald R; Stephanopoulos, Gregory Lignocellulosic biomass remains unharnessed for the production of renewable fuels and chemicals due to challenges in deconstruction and the toxicity its hydrolysates pose to fermentation microorganisms. Here, we show in Saccharomyces cerevisiae that engineered aldehyde reduction and elevated extracellular potassium and pH are sufficient to enable near-parity production between inhibitor-laden and inhibitor-free feedstocks. By specifically targeting the universal hydrolysate inhibitors, a single strain is enhanced to tolerate a broad diversity of highly toxified genuine feedstocks and consistently achieve industrial-scale titers (cellulosic ethanol of >100 grams per liter when toxified). Furthermore, a functionally orthogonal, lightweight design enables seamless transferability to existing metabolically engineered chassis strains: We endow full, multifeedstock tolerance on a xylose-consuming strain and one producing the biodegradable plastics precursor lactic acid. The demonstration of “drop-in” hydrolysate competence enables the potential of cost-effective, at-scale biomass utilization for cellulosic fuel and nonfuel products alike.

Removal of lycopene substrate inhibition enables high carotenoid productivity in Yarrowia lipolytica

Mon, 31 Jan 2022 00:00:00 GMT

Removal of lycopene substrate inhibition enables high carotenoid productivity in Yarrowia lipolytica Ma, Yongshuo; Liu, Nian; Greisen, Per; Li, Jingbo; Qiao, Kangjian; Huang, Sanwen; Stephanopoulos, Gregory Substrate inhibition of enzymes can be a major obstacle to the production of valuable chemicals in engineered microorganisms. Here, we show substrate inhibition of lycopene cyclase as the main limitation in carotenoid biosynthesis in Yarrowia lipolytica. To overcome this bottleneck, we exploit two independent approaches. Structure-guided protein engineering yields a variant, Y27R, characterized by complete loss of substrate inhibition without reduction of enzymatic activity. Alternatively, establishing a geranylgeranyl pyrophosphate synthase-mediated flux flow restrictor also prevents the onset of substrate inhibition by diverting metabolic flux away from the inhibitory metabolite while maintaining sufficient flux towards product formation. Both approaches result in high levels of near-exclusive β-carotene production. Ultimately, we construct strains capable of producing 39.5 g/L β-carotene at a productivity of 0.165 g/L/h in bioreactor fermentations (a 1441-fold improvement over the initial strain). Our findings provide effective approaches for removing substrate inhibition in engineering pathways for efficient synthesis of natural products.

Isotope tracing in health and disease

Mon, 01 Aug 2022 00:00:00 GMT

Isotope tracing in health and disease Dong, Wentao; Rawat, Eshaan S; Stephanopoulos, Gregory; Abu-Remaileh, Monther Biochemical characterization of metabolism provides molecular insights for understanding biology in health and disease. Over the past decades, metabolic perturbations have been implicated in cancer, neurodegeneration, and diabetes, among others. Isotope tracing is a technique that allows tracking of labeled atoms within metabolites through biochemical reactions. This technique has become an integral component of the contemporary metabolic research. Isotope tracing measures substrate contribution to downstream metabolites and indicates its utilization in cellular metabolic networks. In addition, isotopic labeling data are necessary for quantitative metabolic flux analysis. Here, we review recent work utilizing metabolic tracing to study health and disease, and highlight its application to interrogate subcellular, intercellular, and in vivo metabolism. We further discuss the current challenges and opportunities to expand the utility of isotope tracing to new research areas.

Engineering a universal and efficient platform for terpenoid synthesis in yeast

Wed, 28 Dec 2022 00:00:00 GMT

Engineering a universal and efficient platform for terpenoid synthesis in yeast Ma, Yongshuo; Zu, Yuexuan; Huang, Sanwen; Stephanopoulos, Gregory Engineering microbes for the production of valuable natural products is often hindered by the regulation of native competing metabolic networks in host. This is particularly evident in the case of terpenoid synthesis in yeast, where the canonical terpenoid precursors are tightly coupled to the biosynthesis of sterols essential for yeast viability. One way to circumvent this limitation is by engineering product pathways less connected to the host native metabolism. Here, we introduce a two-step isopentenol utilization pathway (IUP) in Saccharomyces cerevisiae to augment the native mevalonate pathway by providing a shortcut to the synthesis of the common terpenoid precursors, isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP). As such, the IUP was capable of elevating the IPP/DMAPP pool by 147-fold compared with the native pathway. We further demonstrate that cofeeding isoprenol and prenol enhances geranyl diphosphate (GPP) content for monoterpene biosynthesis. More importantly, we established a synthetic three-step route for efficient synthesis of di-and tetraterpene precursor geranylgeranyl diphosphate (GGPP), circumventing the competition with farnesyl diphosphate (FPP) for sterol biosynthesis and elevating the GGPP level by 374-fold. We combine these IUP-supported precursor-forming platforms with downstream terpene synthases to harness their potential and improve the production of industrially relevant terpenoids by several fold. Our exploration provides a universal and effective platform for supporting terpenoid synthesis in yeast.

Oscillatory control of cortical space as a computational dimension

Mon, 22 Dec 2025 00:00:00 GMT

Oscillatory control of cortical space as a computational dimension Chen, Zhen; Brincat, Scott L.; Lundqvist, Mikael; Loonis, Roman F.; Warden, Melissa R.; Miller, Earl K. Flexible cognition depends on the ability to represent and apply relevant information to the current task at hand. This allows the brain to interpret sensory input and guide behavior in a context-dependent manner. Recent work has proposed “spatial computing” as a mechanism for this flexibility, suggesting that task-related signals organize information processing through spatial patterns of oscillatory activity across the cortical surface. These patterns are proposed to act as “inhibitory stencils” that constrain where sensory-related information (the “content” of cognition) can be expressed in spiking activity. Here, we provide a comprehensive empirical test of spatial computing using multi-electrode recordings from the lateral prefrontal cortex in non-human primates performing a range of cognitive tasks (object working memory, sequence working memory, and categorization). We found that alpha/beta oscillations encoded task-related information, were organized into spatial patterns that changed with task conditions, and inversely correlated with the spatial expression of sensory-related spiking activity. Furthermore, we found that alpha/beta oscillations reflected misattributions of task conditions and correlated with subjects’ trial-by-trial decisions. These findings validate core predictions of spatial computing, suggesting that oscillatory dynamics not only gate information in time but also shape where in the cortex cognitive content is represented. This framework offers a unifying principle for understanding how the brain flexibly coordinates cognition through structured population dynamics.

Working memory readout varies with frontal theta rhythms

Wed, 07 Jan 2026 00:00:00 GMT

Working memory readout varies with frontal theta rhythms Han, Hio-Been; Brincat, Scott L.; Buschman, Timothy J.; Miller, Earl K. Increasing evidence suggests that attention varies rhythmically, phase locked to ongoing cortical oscillations. Here, we report that the phase of theta oscillations (3–6 Hz) in the frontal eye field (FEF) is associated with the spatiotemporal variation of information readout from working memory (WM). Non-human primates were briefly shown a sample array of colored squares. A short time later, they viewed a test array and were rewarded for identifying which square changed color (the target). Behavioral performance varied systematically with theta phase at the time of test array onset, as well as with the target’s location. This is consistent with theta “scanning” across the FEF and thus visual space from top to bottom. Theta was coupled, on opposing phases, to both spiking and beta (12–20 Hz). These results could be explained by a wave of activity that moves across the FEF, modulating the readout of information from WM.

Exploring the Emotional Effects of Enhanced Interoception via Heartbeat-Synchronized Haptic Feedback

Tue, 02 Dec 2025 00:00:00 GMT

Exploring the Emotional Effects of Enhanced Interoception via Heartbeat-Synchronized Haptic Feedback Kim, Minsol; Whitmore, Nathan; Chua, Phoebe; Pei, Serena; Abdalla, Malak; Maes, Pattie This study examines how amplifying real-time heartbeat feedback affects emotion regulation. Accurate heartbeat perception—a key facet of cardiac interoception—has been linked to emotional awareness and mental well-being, yet the causal role of interoceptive feedback in emotion regulation remains underexplored. We empirically tested whether making heart rate signals more perceptible through wearable haptic feedback could facilitate implicit emotion regulation during emotionally evocative experiences. Using a custom Fitbit-based system, thirty participants received real-time, sham, or no heartbeat-synchronized vibrations while viewing fear- and amusement-inducing film clips. Interoceptive accuracy, emotional disturbance, and the linguistic complexity of emotion descriptions were measured. Exploratory analyses showed that real-time feedback reduced emotional disturbance during fear stimuli, especially among individuals attentive to bodily sensations, though effects did not remain significant after multiple comparisons correction. Feedback primarily modulated arousal rather than valence and did not significantly affect heartbeat counting or linguistic complexity. As one of the first causal, empirical investigations of interoceptive feedback and emotion regulation, this work identifies boundary conditions for its effectiveness and offers insights for designing personalized, interoception-aware wearable technologies.

EcoLearn: Optimizing the Carbon Footprint of Federated Learning

Wed, 03 Dec 2025 00:00:00 GMT

EcoLearn: Optimizing the Carbon Footprint of Federated Learning Mehboob, Talha; Bashir, Noman; Iglesias, Jesus Oma?a; Zink, Michael; Irwin, David Federated Learning (FL) distributes machine learning (ML) training across edge devices to reduce data transfer overhead and protect data privacy. Since FL model training may span hundreds of devices and is thus resource- and energy-intensive, it has a significant carbon footprint. Importantly, since energy's carbon-intensity differs substantially (by up to 60×) across locations, training on the same device using the same amount of energy, but at different locations, can incur widely different carbon emissions. While prior work has focused on improving FL's resource- and energy-efficiency by optimizing time-to-accuracy, it implicitly assumes all energy has the same carbon intensity and thus does not optimize carbon efficiency, i.e., work done per unit of carbon emitted. To address the problem, we design EcoLearn, which minimizes FL's carbon footprint without significantly affecting model accuracy or training time. EcoLearn achieves a favorable tradeoff by integrating carbon awareness into multiple aspects of FL training, including i) selecting clients with high data utility and low carbon, ii) provisioning more clients during the initial training rounds, and iii) mitigating stragglers by dynamically adjusting client over-provisioning based on carbon. We implement EcoLearn and its carbon-aware FL training policies in the Flower framework and show that it reduces the carbon footprint of training (by up to 10.8×) while maintaining model accuracy and training time (within ~1%) compared to state-of-the-art approaches. SEC ’25, Arlington, VA, USA

Democratizing Multi-Granularity Spatio-Temporal Intelligence with Multi-Agent Systems

Sun, 02 Nov 2025 00:00:00 GMT

Democratizing Multi-Granularity Spatio-Temporal Intelligence with Multi-Agent Systems Wu, Che-Cheng; Huang, Syuan-Bo; Song, Yu-Lun; Lin, Po-Han; Lin, Michael; Lin, Yu-Ta We propose a system that democratizes multi-granularity spatio-temporal analysis by integrating a Discrete Global Grid System (DGGS) data pipeline with a Multi-Agent System (MAS). Unlike existing single-agent spatial AI solutions that primarily target experts and lack support for heterogeneous data, persistent memory, and validation, our platform converts diverse datasets into standardized H3-indexed cells, enabling consistent analysis across scales. To enhance usability for non-experts, the system interactively guides users to refine queries, which are decomposed into sub-tasks managed by specialized agents for data retrieval, transformation, analysis, and visualization. Agents communicate through a decentralized framework with shared memory, supporting persistent reasoning and multi-turn dialogue. Reflection modules and human-in-the-loop validation further strengthen robustness. Demonstrated through real-world scenarios, such as analyzing the relationship between aging rate patterns and average income to inform social welfare policy in Taiwan, the system illustrates how natural language queries, combined with intuitive map- and chart-based visualizations, can support evidence-based decision-making. GeoGenAgent ’25, Minneapolis, MN, USA

One String to Pull Them All: Fast Assembly of Curved Structures from Flat Auxetic Linkages

Thu, 04 Dec 2025 00:00:00 GMT

One String to Pull Them All: Fast Assembly of Curved Structures from Flat Auxetic Linkages Zaman, Akib; Aslarus, Jacqueline; Li, Jiaji; Mueller, Stefanie; Konakovic Lukovic, Mina We present a computational approach for designing freeform structures that can be rapidly assembled from initially flat configurations by a single string pull. The target structures are decomposed into rigid spatially varied quad tiles that are optimized to approximate the user-provided surface, forming a flat mechanical linkage. Our algorithm then uses a two-step method to find a physically realizable string path that controls only a subset of tiles to smoothly actuate the structure from flat to assembled configuration. We initially compute the minimal subset of tiles that are required to be controlled with the string considering the geometry of the structure and interaction among the tiles. We then find a valid string path through these tiles that minimizes friction, which will assemble the flat linkage into the target 3D structure upon tightening a single string. The resulting designs can be easily manufactured with computational fabrication techniques such as 3D printing, CNC milling, molding, etc. in flat configuration that, in addition to manufacturing, facilitates storage and transportation. We validate our approach by developing a series of physical prototypes and showcasing various application case studies, ranging from medical devices, space shelters, to architectural designs.

Discovering Folding Lines for Surface Compression

Sun, 14 Dec 2025 00:00:00 GMT

Discovering Folding Lines for Surface Compression Aoki, Toshiki; Tachi, Tomohiro; Konakovic Lukovic, Mina The miniaturization of shell structures presents a versatile and complex challenge, bridging geometry with diverse practical applications. In this paper, we introduce a novel approach for computing origami crease patterns to compress arbitrary 3D shell objects. First, we employ the adapted Material Point Method (MPM) to simulate the compression of a target surface and obtain an initial folded configuration. Since MPM produces overly smooth curved surfaces, their crease patterns are unsuitable for practical origami fabrication. We then propose a novel Folding Line Extraction (FLE) method that optimizes these smoothed surfaces to extract folding lines that achieve the target compression with minimal deformation and stretching outside the crease lines. This method produces smooth curved folding lines. Fabrication and experimental validation of the extracted patterns demonstrate their effectiveness and applicability in real-world scenarios. SA Conference Papers ’25, Hong Kong, Hong Kong

3DPR: Single Image 3D Portrait Relighting with Generative Priors

Sun, 14 Dec 2025 00:00:00 GMT

3DPR: Single Image 3D Portrait Relighting with Generative Priors Rao, Pramod; Meka, Abhimitra; Zhou, Xilong; Fox, Gereon; B R, Mallikarjun; Zhan, Fangneng; Weyrich, Tim; Bickel, Bernd; Pfister, Hanspeter; Matusik, Wojciech; Beeler, Thabo; Elgharib, Mohamed; Habermann, Marc; Theobalt, Christian Rendering novel, relit views of a human head, given a monocular portrait image as input, is an inherently underconstrained problem. The traditional graphics solution is to explicitly decompose the input image into geometry, material and lighting via differentiable rendering; but this is constrained by the multiple assumptions and approximations of the underlying models and parameterizations of these scene components. We propose 3DPR, an image-based relighting model that leverages generative priors learnt from multi-view One-Light-at-A-Time (OLAT) images captured in a light stage. We introduce a new diverse and large-scale multi-view 4K OLAT dataset of 139 subjects to learn a high-quality prior over the distribution of high-frequency face reflectance. We leverage the latent space of a pre-trained generative head model that provides a rich prior over face geometry learnt from in-the-wild image datasets. The input portrait is first embedded in the latent manifold of such a model through an encoder-based inversion process. Then a novel triplane-based reflectance network trained on our lightstage data is used to synthesize high-fidelity OLAT images to enable image-based relighting. Our reflectance network operates in the latent space of the generative head model, crucially enabling a relatively small number of lightstage images to train the reflectance model. Combining the generated OLATs according to a given HDRI environment maps yields physically accurate environmental relighting results. Through quantitative and qualitative evaluations, we demonstrate that 3DPR outperforms previous methods, particularly in preserving identity and in capturing lighting effects such as specularities, self-shadows, and subsurface scattering. SA Conference Papers ’25, December 15–18, 2025, Hong Kong, Hong Kong

Shoot-Bounce-3D: Single-Shot Occlusion-Aware 3D from Lidar by Decomposing Two-Bounce Light

Sun, 14 Dec 2025 00:00:00 GMT

Shoot-Bounce-3D: Single-Shot Occlusion-Aware 3D from Lidar by Decomposing Two-Bounce Light Klinghoffer, Tzofi; Somasundaram, Siddharth; Xiang, Xiaoyu; Fan, Yuchen; Richardt, Christian; Dave, Akshat; Raskar, Ramesh; Ranjan, Rakesh 3D scene reconstruction from a single measurement is challenging, especially in the presence of occluded regions and specular materials, such as mirrors. We address these challenges by leveraging single-photon lidars. These lidars estimate depth from light that is emitted into the scene and reflected directly back to the sensor. However, they can also measure light that bounces multiple times in the scene before reaching the sensor. This multi-bounce light contains additional information that can be used to recover dense depth, occluded geometry, and material properties. Prior work with single-photon lidar, however, has only demonstrated these use cases when a laser sequentially illuminates one scene point at a time. We instead focus on the more practical – and challenging – scenario of illuminating multiple scene points simultaneously. The complexity of light transport due to the combined effects of multiplexed illumination, two-bounce light, shadows, and specular reflections is challenging to invert analytically. Instead, we propose a data-driven method to invert light transport in single-photon lidar. To enable this approach, we create the first large-scale simulated dataset of ~100k lidar transients for indoor scenes. We use this dataset to learn a prior on complex light transport, enabling measured two-bounce light to be decomposed into the constituent contributions from each laser spot. Finally, we experimentally demonstrate how this decomposed light can be used to infer 3D geometry in scenes with occlusions and mirrors from a single measurement. Our code and dataset are released on our project webpage. SA Conference Papers ’25, Hong Kong, Hong Kong

PhysiOpt: Physics-Driven Shape Optimization for 3D Generative Models

Sun, 14 Dec 2025 00:00:00 GMT

PhysiOpt: Physics-Driven Shape Optimization for 3D Generative Models Zhan, Xiao; Jambon, Cl?ment; Thompson, Evan; Ng, Kenney; Konakovi? Lukovi?, Mina Generative models have recently demonstrated impressive capabilities in producing high-quality 3D shapes from a variety of user inputs (e.g., text or images). However, generated objects often lack physical integrity. We introduce PhysiOpt, a differentiable physics optimizer designed to improve the physical behavior of 3D generative outputs, enabling them to transition from virtual designs to physically plausible, real-world objects. While most generative models represent geometry as continuous implicit fields, physics-based approaches often rely on the finite element method (FEM), requiring ad hoc mesh extraction to perform shape optimization. In addition, these methods are typically slow, limiting their integration in fast, iterative generative design workflows. Instead, we bridge the representation gap and propose a fast and effective differentiable simulation pipeline that optimizes shapes directly in the latent space of generative models using an intuitive and easy-to-implement differentiable mapping. This approach enables fast optimization while preserving semantic structure, unlike traditional methods relying on local mesh-based adjustments. We demonstrate the versatility of our optimizer across a range of shape priors, from global and part-based latent models to a state-of-the-art large-scale 3D generator, and compare it to a traditional mesh-based shape optimizer. Our method preserves the native representation and capabilities of the underlying generative model while supporting user-specified materials, loads, and boundary conditions. The resulting designs exhibit improved physical behavior, remain faithful to the learned priors, and are suitable for fabrication. We demonstrate the effectiveness of our approach on both virtual and fabricated objects. SA Conference Papers ’25, Hong Kong, Hong Kong

Low-Rank Adaptation of Neural Fields

Sun, 14 Dec 2025 00:00:00 GMT

Low-Rank Adaptation of Neural Fields Truong, Anh; Mahmoud, Ahmed; Konakovi? Lukovi?, Mina; Solomon, Justin Processing visual data often involves small adjustments or sequences of changes, e.g., image filtering, surface smoothing, and animation. While established graphics techniques like normal mapping and video compression exploit redundancy to encode such small changes efficiently, the problem of encoding small changes to neural fields—neural network parameterizations of visual or physical functions—has received less attention. We propose a parameter-efficient strategy for updating neural fields using low-rank adaptations (LoRA). LoRA, a method from the parameter-efficient fine-tuning LLM community, encodes small updates to pre-trained models with minimal computational overhead. We adapt LoRA for instance-specific neural fields, avoiding the need for large pre-trained models and yielding lightweight updates. We validate our approach with experiments in image filtering, geometry editing, video compression, and energy-based editing, demonstrating its effectiveness and versatility for representing neural field updates. Anh Truong, Ahmed H. Mahmoud, Mina Konaković Luković, and Justin Solomon. 2025. Low-Rank Adaptation of Neural Fields. In Proceedings of the SIGGRAPH Asia 2025 Conference Papers (SA Conference Papers '25). Association for Computing Machinery, New York, NY, USA, Article 86, 1–12.

Participatory Evolution of Artificial Life Systems via Semantic Feedback

Sun, 14 Dec 2025 00:00:00 GMT

Participatory Evolution of Artificial Life Systems via Semantic Feedback Li, Shuowen; Wang, Kexin; Fang, Minglu; Huang, Danqi; Asadipour, Ali; Mi, Haipeng; Sun, Yitong We present a semantic-feedback framework that treats natural language as a regulatory signal for evolving artificial-life systems. Instead of using prompts to select finished images, text in our system shapes the dynamics of an interactive ecosystem, allowing audiences to cultivate behaviors over time. The framework couples a learned mapping from prompts to simulation parameters with evolutionary search and vision–language evaluation, so user intent modulates both visible outcomes and the underlying generative rules. It supports iterative prompt refinement, multi-agent interaction, and the synthesis of new collective rules from community input. In a user study, participants achieved higher semantic alignment and reported a greater sense of control than with manual tuning, while behaviors remained diverse across generations. As an art-led contribution, the work reframes authoring as participatory cultivation and advances open-ended evolution as a socially distributed, not solely algorithmic, process; as a tool contribution, it offers a practical platform for co-creative generative design. SA Art Papers ’25, Hong Kong, Hong Kong

Physical Manifestation of Generative AI Music Systems for Live Performance

Sun, 14 Dec 2025 00:00:00 GMT

Physical Manifestation of Generative AI Music Systems for Live Performance Naseck, Perry; Blanchard, Lancelot; Lavakare, Madhav; Lecamwasam, Kimaya; Paradiso, Joseph This paper explores the physical manifestation of generative AI music systems for live performance, focusing on bridging the expressive gap between AI-generated music and audience perception. Through a year-long collaboration with a human performer, we constructed a kinetic sculpture that visualizes the outputs of an AI jam_bot during concerts. The sculpture, powered by ML-based and pattern-driven mapping methodologies, interprets real-time AI musical decisions as expressive movements. Audience feedback indicates increased engagement and curiosity, although interpretability remains a challenge. Our work highlights the potential of embodied visualization to establish communicative presence for AI performers and suggests avenues for future research. SA Art Papers ’25, Hong Kong, Hong Kong

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision

Sat, 20 Dec 2025 00:00:00 GMT

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision Ringoot, Evelyne; Alomairy, Rabab; Churavy, Valentin; Edelman, Alan This paper presents a portable, GPU-accelerated implementation of a QR-based singular value computation algorithm in Julia. The singular value decomposition (SVD) is a fundamental numerical tool in scientific computing and machine learning, providing optimal low-rank matrix approximations. Its importance has increased even more in large-scale machine learning pipelines, including large language models (LLMs), where it enables low-rank adaptation (LoRA). The implemented algorithm is based on the classic two-stage QR reduction, consisting of successive matrix reduction to band form and bidiagonal form. Our implementation leverages Julia’s multiple dispatch and metaprogramming capabilities, integrating with the GPUArrays and KernelAbstractions frameworks to provide a unified type and hardware-agnostic function. It supports diverse GPU architectures and data types, and is, to our knowledge, the first GPU-accelerated singular value implementation to support Apple Metal GPUs and half precision. Performance results on multiple GPU backends and data types demonstrate that portability does not require sacrificing performance: the unified function outperforms most linear algebra libraries (MAGMA, SLATE, rocSOLVER, oneMKL) for matrix sizes larger than 1024 × 1024, and achieves 80%-90% of the performance of cuSOLVER for large matrices. ICPP ’25, San Diego, CA, USA

UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction

Fri, 12 Dec 2025 00:00:00 GMT

UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction Yu, Dahai; Zhuang, Dingyi; Jiang, Lin; Xu, Rongchao; Ye, Xinyue; Bu, Yuheng; Wang, Shenhao; Wang, Guang Spatiotemporal prediction plays a critical role in numerous real-world applications such as urban planning, transportation optimization, disaster response, and pandemic control. In recent years, researchers have made significant progress by developing advanced deep learning models for spatiotemporal prediction. However, most existing models are deterministic, i.e., predicting only the expected mean values without quantifying uncertainty, leading to potentially unreliable and inaccurate outcomes. While recent studies have introduced probabilistic models to quantify uncertainty, they typically focus on a single phenomenon (e.g., taxi, bike, crime, or traffic crashes), thereby neglecting the inherent correlations among heterogeneous urban phenomena. To address the research gap, we propose a novel Graph Neural Network with Uncertainty Quantification, termed UQGNN for multivariate spatiotemporal prediction. UQGNN introduces two key innovations: (i) an Interaction-aware Spatiotemporal Embedding Module that integrates a multivariate diffusion graph convolutional network and an interaction-aware temporal convolutional network to effectively capture complex spatial and temporal interaction patterns, and (ii) a multivariate probabilistic prediction module designed to estimate both expected mean values and associated uncertainties. Extensive experiments on four real-world multivariate spatiotemporal datasets from Shenzhen, New York City, and Chicago demonstrate that UQGNN consistently outperforms state-of-the-art baselines in both prediction accuracy and uncertainty quantification. For example, on the Shenzhen dataset, UQGNN achieves a 5% improvement in both prediction accuracy and uncertainty quantification. SIGSPATIAL ’25, Minneapolis, MN, USA

SONAR Web: A Platform-Agnostic Framework for Real-Time Decentralized Learning Across Heterogeneous Edge Clients

Tue, 02 Dec 2025 00:00:00 GMT

SONAR Web: A Platform-Agnostic Framework for Real-Time Decentralized Learning Across Heterogeneous Edge Clients Yuan, Joyce; Le, Brian; Le, Kathryn; Shi, Yichuan; Singh, Abhishek; Sharma, Rishi; Patricio, Angel; Raskar, Ramesh Most federated learning (FL) frameworks assume reliable networks and homogeneous devices, limiting their applicability in mobile and edge environments where connectivity is intermittent and devices are highly heterogeneous. We introduce SONAR Web, an open-source framework for fully decentralized, cross-platform collaborative learning between browsers, servers, tablets, and smartphones. SONAR Web decouples the learning protocol from the underlying client platform through a platform-agnostic configuration interface—enabling Python, JavaScript, and mobile clients to seamlessly interoperate in real time. By combining peer-to-peer RTC protocols with communication-efficient techniques from FL, SONAR Web supports privacy-preserving training without centralized orchestration. We demonstrate SONAR Web's robustness through deployments on real-world devices and networks, showing resilience under heterogeneous network conditions and resource variability. SONAR Web provides a unified, language-agnostic interface for decentralized learning, enabling seamless collaboration across heterogeneous devices and runtimes—advancing scalable, inclusive, and real-time model training at the mobile and edge frontier. FLEdge-AI ’25, November 4-8, 2025, Hong Kong, China

Ferrozuit: Ferromagnetic Electronic Textile System for Zero-Gravity Spatial Anchoring

Mon, 29 Dec 2025 00:00:00 GMT

Ferrozuit: Ferromagnetic Electronic Textile System for Zero-Gravity Spatial Anchoring Honnet, Cedric; Freire, Rachel; Cherston, Juliana; Guenther, Maximilian; Paradiso, Joseph; Wicaksono, Irmandy Long-duration human space missions introduce persistent physical, physiological, and psychological challenges stemming from the absence of gravity. Beyond major concerns like bone deterioration, cardiovascular deconditioning, and muscle atrophy, astronauts frequently experience spatial disorientation, discomfort during routine tasks, and difficulty maintaining stable body positioning. These subtle yet pervasive issues impact daily functioning, underscoring the need for lightweight, unobtrusive solutions that support orientation, comfort, and stability in microgravity environments. Ferrozuit introduces a solution to address these challenges in microgravity. It is a prototype crafted from custom ferromagnetic thread, woven and tailored to interact with programmable (electro)permanent magnets embedded within the microgravity environment. This system aims to provide an anchoring force intended to improve stability during tasks, enhance comfort during rest, and create a sense of orientation. This paper details the design rationale, the fabrication of the ferromagnetic textile, the magnetic docking system, initial technical evaluations, and potential applications. Ferrozuit reimagines spatial anchoring as an embedded, textile-driven experience, blending textile craft with advanced materials for adaptive wearable anchoring in microgravity environments. UbiComp Companion ’25, Espoo, Finland

Intelligent Soft Wearables

Mon, 29 Dec 2025 00:00:00 GMT

Intelligent Soft Wearables Yu, Tianhong; Honnet, Cedric; Cheng, Tingyu; Takahashi, Ryo; Zhou, Bo; Zhang, Cheng; Lukowicz, Paul; Kawahara, Yoshihiro; Hester, Josiah; Paradiso, Joseph; Luo, Yiyue; Wicaksono, Irmandy Human bodies are almost always in contact with soft materials like clothing, for warmth, protection, self-expression, etc. Recent advancements in intelligent soft wearables have augmented these on-body soft objects with computational functions and intelligence with little compromise on the softness and comforts of wearables, allowing prolonged wear. These innovations, which combine advanced soft sensor design, fabrication, and computational power, offer unprecedented opportunities to improve our health, productivity, and overall well-being with monitoring and assistive capabilities. However, the inherent physical properties of soft materials present unique challenges in achieving practical interactions. The complexity of intelligent soft wearables, multiplexing intricate designs, soft materials, flexible electronics, advanced signal processing algorithms, and machine learning models, necessitates collaborative efforts from experts across diverse domains. This workshop aims to bring together interested researchers and practitioners across relevant domains to discuss the challenges and opportunities of intelligent soft wearables.

Quantum dots: A journey from fundamental discovery to technological impacts

Thu, 13 Nov 2025 00:00:00 GMT

Quantum dots: A journey from fundamental discovery to technological impacts Hassan, Abeera; Kaur, Jaspreet; Chen, Ou; Bawendi, Moungi G. This article traces the evolution of quantum dots (QDs) from their initial discovery to growing technological impacts. We highlight the key breakthroughs in the development of colloidal QDs that have enabled precise control over their unique optical and optoelectronic properties. We also discuss a range of QD-based applications and address commercialization efforts. Finally, we examine ongoing challenges and emerging opportunities that are set to shape the future of QD research and technological advancement.

Proximity-labeling proteomics reveals remodeled interactomes and altered localization of pathogenic SHP2 variants

Mon, 22 Dec 2025 00:00:00 GMT

Proximity-labeling proteomics reveals remodeled interactomes and altered localization of pathogenic SHP2 variants van Vlimmeren, Anne E.; Tang, Lauren C.; Jiang, Ziyuan; Iyer, Abhishek; Voleti, Rashmi; Krismer, Konstantin; Gaublomme, Jellert T.; Jovanovic, Marko; Shah, Neel H. Missense mutations in PTPN11, which encodes the protein tyrosine phosphatase SHP2, are common in several developmental disorders and cancers. While many mutations disrupt auto-inhibition and hyperactivate SHP2, several do not enhance catalytic activity. Both activating and non-activating mutations could potentially drive pathogenic signaling by altering SHP2 interactions or localization. We employed proximity-labeling proteomics to map the interaction networks of wild-type SHP2, ten clinically relevant mutants, and SHP2 bound to an inhibitor that stabilizes its auto-inhibited state. Our analyses reveal mutation- and inhibitor-dependent alterations in the SHP2 interactome, with several mutations also changing localization. Some mutants show increased mitochondrial localization and impact mitochondrial function. This study provides a resource for exploring SHP2 signaling and offers new insights into the molecular basis of SHP2-driven diseases. Furthermore, this work highlights the capacity for proximity-labeling proteomics to detect missense-mutation-dependent changes in protein interactions and localization.

Perspective on patient and non-academic partner engagement for the responsible integration of large language models in health chatbots

Mon, 22 Dec 2025 00:00:00 GMT

Perspective on patient and non-academic partner engagement for the responsible integration of large language models in health chatbots Jaiswal, Nikhil; Ma, Yuanchao; Lebouché, Bertrand; Poenaru, Dan; Pomey, Marie-Pascale; Achiche, Sofiane; Lessard, David; Engler, Kim; Montiel, Zully; Acevedo, Hector; Gameiro, Rodrigo R.; Celi, Leo A.; Osmanlliu, Esli Uses of large language models (LLMs) in health chatbots are expanding into high-stakes clinical contexts, heightening the need for tools that are evidence-based, accountable, accurate, and patient-centred. This conceptual, practice-informed Perspective reflects on engaging patients and non-academic partners for the responsible integration of LLMs, grounded in the co-construction of MARVIN (for people living with HIV) and in an emerging collaboration with MIT Critical Data. Organised by the Software Development Life Cycle, we describe: conception/needs assessment with patient partners to identify use cases, acceptable trade-offs, and privacy expectations; development that prioritises grounding via vetted sources, structured human feedback, and data-validation committees including patient partners; testing and evaluation using patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) chosen in collaboration with patients to capture usability, acceptability, trust, and perceived safety, alongside task performance and harmful-output monitoring; and implementation via diverse governance boards, knowledge-mobilisation materials to set expectations, and risk-management pathways for potentially unsafe outputs. Based on our experience with MARVIN, we recommend early and continuous engagement of patients and non-academic partners, fair compensation, shared decision-making power, transparent decision logging, and inclusive, adaptable governance that can evolve with changing models and standards. These lessons highlight how patient partnership can directly shape chatbot design and oversight, helping teams align LLM-enabled tools with patient-centred goals while building accountable, safe, and equitable systems.

Study of charm mixing and CP violation with D0 → K±π∓π±π∓ decays

Fri, 19 Dec 2025 00:00:00 GMT

Study of charm mixing and CP violation with D0 → K±π∓π±π∓ decays Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. A study of charm mixing and CP violation in D0 → K±π∓π±π∓ decays is performed using data collected by the LHCb experiment in proton-proton collisions from 2015 to 2018, corresponding to an integrated luminosity of 6 fb−1. The ratio of promptly produced D0 → K+π−π+π− to D0 → K−π+π−π+ decay rates is measured as a function of D0 decay time, both inclusive over phase space and in bins of phase space. Taking external inputs for the D 0 − D ¯ 0 mixing parameters x and y allows constraints to be obtained on the hadronic parameters of the charm decay. When combined with previous measurements from charm-threshold experiments and at LHCb, improved knowledge is obtained for these parameters, which is valuable for studies of the angle γ of the Unitarity Triangle. An alternative analysis is also performed, in which external inputs are taken for the hadronic parameters, and the mixing parameters are determined, including ∆x and ∆y, which are nonzero in the presence of CP violation. It is found that x = 0 . 85 − 0.24 + 0.15 % , y = 0 . 21 − 0.27 + 0.29 % , ∆x = (−0.02 ± 0.04) % and Δ y = 0.0 2 − 0.03 + 0.04 % . These results are consistent with previous measurements and the hypothesis of CP conservation.

Energy-energy correlator at hadron colliders: celestial blocks and singularities

Mon, 22 Dec 2025 00:00:00 GMT

Energy-energy correlator at hadron colliders: celestial blocks and singularities Chen, Hao; Ruan, Hongyi; Zhu, Hua X. Energy-energy correlator (EEC) is an event shape observable that characterizes the distribution of energy flux in collision events. We initiate the study of full-range EEC at hadron colliders, generalizing the extensively studied EEC in e+e− collision as well as the transverse EEC in hadron collisions. We derive celestial blocks from Lorentz symmetry to perform partial wave decomposition of the EEC at hadron colliders. These celestial blocks are essentially conformal blocks on the 2d celestial sphere, which have additional dependence on the collinear spin of “light-ray transition matrix” along the collision axis. In this work, we perform the leading-order (LO) analytic calculation of this observable in pure Yang-Mills theory and use it as an example to illustrate the block decomposition. Numerically, the block expansion demonstrates superior accuracy in the collinear limit compared to conventional power series expansion. Analytically, we observe in this example that the block coefficients exhibit analyticity in both collinear and transverse spin. In addition, we analyze several kinematic limits at LO — collinear, back-to-back, opposite coplanar and Regge limit. While the first three limits naturally generalize their e+e− collision counterparts or transverse EEC and are governed by soft-collinear dynamics, the Regge limit requires complete angular dependence and reveals BFKL physics. Phenomenologically, we propose a realistic experimental setup and briefly discuss how the convolution of parton distribution function modifies the perturbative EEC result. Our work suggests that the full-range EEC at hadron colliders is an elegant observable which probes a broader kinematic space and connects various regimes of different QCD dynamics through a single measurement.

Measurement of the B0 → ρ(770)0γ branching fraction

Fri, 19 Dec 2025 00:00:00 GMT

Measurement of the B0 → ρ(770)0γ branching fraction Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. The ratio between the branching fractions of the B0 → ρ(770)0γ and B0 → K*(892)0γ decays is measured with proton-proton collision data collected by the LHCb experiment at centre-of-mass energies of 7, 8, and 13 TeV, corresponding to an integrated luminosity of 9 fb−1. The measured value is B B 0 → ρ 770 0 γ B B 0 → K ∗ 892 0 γ = 0.0189 ± 0.0007 ± 0.0005 , where the first uncertainty is statistical and the second systematic. The branching fraction for B0 → ρ(770)0γ decays is hence obtained as B B 0 → ρ 770 0 γ = 7.9 ± 0.3 ± 0.2 ± 0.2 × 10 − 7 , where the last uncertainty is due to the branching fraction of the normalisation mode. This result assumes that both the ρ(770)0 and K*(892)0 decays saturate the dihadron mass spectra considered in the analysis. It is consistent with the current world-average value and by far the most precise measurement to date.

A Beamdump facility at Jefferson Lab

Wed, 24 Dec 2025 00:00:00 GMT

A Beamdump facility at Jefferson Lab Achenbach, Patrick; Afanasev, Andrei; Ambrozewicz, Pawel; Ashkenazi, Adi; Banerjee, Dipanwita; Battaglieri, Marco; Benesch, Jay; Bondí, Mariangela; Brindza, Paul; Camsonne, Alexandre; Christy, Eric M.; Cline, Ethan W.; Cuevas, Chris; Dilling, Jens; Doria, Luca; Fegan, Stuart; Filippini, Marco; Fulci, Antonino; Giovannella, Simona; Grazzi, Stefano The potential of the intense secondary muon, neutrino, and (hypothetical) light dark matter beams at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) is explored. These are produced in the high-power dumps with high-current electron beams. Light dark matter searches with the approved Beam Dump eXperiment (BDX) are driving the realization of a new underground vault behind Hall A that could be extended to a Beamdump Facility with little additional installations. High-energy muons created via the Bethe–Heitler process uniquely do not proceed through the more common pion production and decay channels. Several possible muon physics applications are highlighted. Neutrino detector technologies and experiments suitable for a beamdump facility are outlined.

Linking Chemical Phase and Mechanical Properties to Evaluate the Use of Millimeter-Wave Induced Vitrified Basalt in Enhanced Geothermal Systems

Mon, 22 Dec 2025 00:00:00 GMT

Linking Chemical Phase and Mechanical Properties to Evaluate the Use of Millimeter-Wave Induced Vitrified Basalt in Enhanced Geothermal Systems Meltzer, Eve R.; Stefaniuk, Damian; Einstein, Herbert H. Extraction of geothermal energy from Earth’s heat could significantly contribute to long-term energy needs, yet the current geothermal drilling process faces significant technical limitations. A promising advancement in enhanced geothermal systems is the use of a millimeter-wave (MMW) gyrotron, which enables faster and more efficient drilling. The MMW drilling process offers two key advantages over traditional methods: (1) rock is melted rather than mechanically drilled, leading to faster well hole advancement, and (2) the molten rock solidifies into a vitrified wall, eliminating the need for additional casing materials. This integrated drilling and casing method has the potential to save costs, time, and materials. This paper examines the strength, structural integrity, and microscale mechanical and chemical properties of the vitrified material formed during the mm-wave process, focusing on basalt as the test material. By employing a suite of experimental and analytical characterization techniques, this study aims to provide a comprehensive comparison of the structural, mechanical, and chemical changes in the rock before and after melting, offering insights into the effectiveness and implications of mm-wave drilling for enhanced geothermal systems. Highlights There is a clear change of phase between the basalt, the transition zone, and the melt, due to mm-wave exposure. The region exposed to mm-waves is completely vitrified, while there is partial melting of minerals within the zone right outside of the mm-wave beam. The transition zone created from mm-waves poses high risk to wellbore stability due to its variable mechanical strength and chemical composition. A better understanding of this new material can be achieved by overlaying a series of chemical and mechanical characterization data.

Reimagining Commercial Health Insurance in India: A System-Dynamics Approach to Complex Stakeholder Incentives and Policy Outcomes

Mon, 08 Dec 2025 00:00:00 GMT

Reimagining Commercial Health Insurance in India: A System-Dynamics Approach to Complex Stakeholder Incentives and Policy Outcomes Mor, Nachiket; Gupta, Aakriti; Roy, Rahul Most low- and middle-income governments are unwilling and unable to adequately fund their health systems using tax resources. Despite this route’s popularity in public discourse, it is neither a feasible nor a desirable route for financing Universal Health Coverage (UHC), given competing public finance priorities and limited citizen demand, among other challenges. It thus becomes essential to study the underlying mechanisms behind commercial health insurance and offer citizens the best possible product, which ensures that they not only receive a high degree of protection from health and financial risk on a sustained basis but also find reasonable access and support to improve their health outcomes. In this paper, we build a system-dynamics model that simulates the aggregate behavior of the Indian health-insurance industry, with interacting feedbacks between decisions by stakeholders such as the insurer, healthy and chronically ill populations, and the regulator to outcomes like insurance penetration among segments, overall coverage, health status over the long run, a mechanism of market-discovered premium, and financial viability of the private insurer. We then investigate policy choices and scenarios to explore contrast between design choices and ideal or targeted states of this market, such as a market with 100% enrollment, risk selection by insurers, group insurance models, and managed care, and study the impact on our outcomes of interest, i.e., insurance penetration and pricing, the financial sustainability of the insurers, and the population’s health outcomes. The simulations show that even while insurers and the different population segments optimize for their respective near-term objectives, the best outcomes for all come from the managed-care policy option, which has greater insurance penetration, lower premiums, higher profitability for insurers, and better long-term health outcomes. All other choices and scenarios yield suboptimal, imbalanced systemic outcomes. We thus recommend managed care as a desirable policy alternative for low-income countries intending to improve UHC by leveraging commercial health insurance.

A Symbiotic Digital Environment Framework for Industry 4.0 and 5.0: Enhancing Lifecycle Circularity

Sat, 06 Dec 2025 00:00:00 GMT

A Symbiotic Digital Environment Framework for Industry 4.0 and 5.0: Enhancing Lifecycle Circularity Ponce, Pedro; Maldonado-Romo, Javier; Anthony, Brian W.; Bradley, Russel; Montesinos, Luis This paper introduces a Symbiotic Digital Environment Framework (SDEF) that integrates Human Digital Twins (HDTs) and Machine Digital Twins (MDTs) to advance lifecycle circularity across all stages of the CADMID model (i.e., Concept, Assessment, Design, Manufacture, In-Service, and Disposal). Unlike existing frameworks that address either digital twins or sustainability in isolation, SDEF establishes a bidirectional adaptive system where human, machine, and environmental digital entities continuously interact to co-optimize performance, resource efficiency, and well-being. The framework’s novelty lies in unifying human-centric adaptability (via HDTs) with circular economy principles to enable real-time symbiosis between industrial processes and their operators. Predictive analytics, immersive simulation, and continuous feedback loops dynamically adjust production parameters based on operator states and environmental conditions, extending asset lifespan while minimizing waste. Two simulation-based scenarios in VR using synthetic data demonstrate the framework’s capacity to integrate circularity metrics (material throughput, energy efficiency, remanufacturability index) with human-machine interaction variables in virtual manufacturing environments. SDEF bridges Industry 4.0’s automation capabilities and Industry 5.0’s human-centric vision, offering a scalable pathway toward sustainable and resilient industrial ecosystems by closing the loop between physical and digital realms.

Development of a Test Bed to Investigate Wetting Behaviours of High-Temperature Heavy Liquid Metals for Advanced Nuclear Applications

Wed, 26 Nov 2025 00:00:00 GMT

Development of a Test Bed to Investigate Wetting Behaviours of High-Temperature Heavy Liquid Metals for Advanced Nuclear Applications Saraswat, Abhishek; Bhattacharyay, Rajendraprasad; Chaudhuri, Paritosh; Gedupudi, Sateesh Specifically engineered heavy liquid metals are proposed as candidate coolants and tritium breeders for advanced nuclear applications. Understanding the wetting behaviours of these liquids on relevant substrate configurations is crucial to tackle the challenges associated with corrosion protection and flow diagnostics development. However, detailed investigations are scarce in the literature. In this experimental study, an apparatus is designed to measure contact angles of different liquid metals over a mirror-polished horizontal SS-304 substrate. This paper presents design aspects of the developed test facility, as well as initial results obtained using direct imaging and the Low-Bond Axisymmetric Drop Shape Analysis algorithm-based image processing technique. Methodological validation is achieved through surrogate liquids/liquid metals (H2O, Hg, Ga, GaInSn), prior to taking measurements from molten lead (Pb) droplets at 425 °C. Estimated contact angles obtained using the two techniques lie within ±10% deviation. Towards the end, the paper lays out plans for future upgrades for studies of wetting behaviours of molten Pb/Pb alloys on substrates with relevant surface properties, including bare P-91 and reduced-activation ferritic–martensitic steels, along with Al2O3/Er2O3-coated versions of these materials, to generate a database for Gen-IV fission reactors and fusion power plants.

Future Circular Collider Feasibility Study Report

Wed, 24 Dec 2025 00:00:00 GMT

Future Circular Collider Feasibility Study Report Benedikt, M.; Zimmermann, F.; Auchmann, B.; Bartmann, W.; Burnet, J. P.; Carli, C.; Chancé, A.; Craievich, P.; Giovannozzi, M.; Grojean, C.; Gutleber, J.; Hanke, K.; Henriques, André; Janot, P.; Lourenço, C.; Mangano, M.; Otto, T.; Poole, J.; Rajagopalan, S.; Raubenheimer, T. Volume 1 of the FCC Feasibility Report presents an overview of the physics case, experimental programme, and detector concepts for the Future Circular Collider (FCC). This volume outlines how FCC would address some of the most profound open questions in particle physics, from precision studies of the Higgs and EW bosons and of the top quark, to the exploration of physics beyond the Standard Model. The report reviews the experimental opportunities offered by the staged implementation of FCC, beginning with an electron-positron collider (FCC-ee), operating at several centre-of-mass energies, followed by a hadron collider (FCC-hh). Benchmark examples are given of the expected physics performance, in terms of precision and sensitivity to new phenomena, of each collider stage. Detector requirements and conceptual designs for FCC-ee experiments are discussed, as are the specific demands that the physics programme imposes on the accelerator in the domains of the calibration of the collision energy, and the interface region between the accelerator and the detector. The report also highlights advances in detector, software and computing technologies, as well as the theoretical tools/reconstruction techniques that will enable the precision measurements and discovery potential of the FCC experimental programme. The content and structure of this report are guided by the scope and priorities defined in the mandate of the FCC Feasibility Study. It is therefore not intended to serve as an exhaustive review of the full physics potential of FCC. Several topics, already covered in earlier reports such as the FCC CDR, are not reiterated here or are addressed only briefly, in alignment with the study’s focus. This volume reflects the outcome of a global collaborative effort involving hundreds of scientists and institutions, aided by a dedicated community-building coordination, and provides a targeted assessment of the scientific opportunities and experimental foundations of the FCC programme.

Unregulated Vertical Urban Growth Alters Microclimate: Coupling Building-Scale Digital Surface Models with High-Resolution Microclimate Simulations

Mon, 10 Nov 2025 00:00:00 GMT

Unregulated Vertical Urban Growth Alters Microclimate: Coupling Building-Scale Digital Surface Models with High-Resolution Microclimate Simulations Falcão, Jonatas Goulart Marinho; Furtado, Luiz Felipe de Almeida; Barbosa, Gisele Silva; Teixeira Coelho, Luiz Carlos Rio de Janeiro’s favelas house over 20% of the city’s population in just 5% of its territory, with Rio das Pedras emerging as a critical case study: ranking as Brazil’s fifth most populous favela and its most vertically intensified. This study quantifies how uncontrolled vertical growth in informal settlements disrupts microclimate dynamics, directly impacting thermal comfort. Using high-resolution geospatial analytics, we integrated digital surface models (DSMs) derived from LiDAR and photogrammetric data (2013, 2019, and 2024) with microclimatic simulations to assess urban morphology changes and their thermal effects. A spatiotemporal cadastral analysis tracked vertical expansion (new floors) and demolition patterns, while ENVI-met simulations mapped air temperature anomalies across decadal scenarios. Results reveal two key findings: (1) rapid, unregulated construction has significantly altered local airflow and surface energy balance, exacerbating the urban heat island (UHI) effect; (2) microclimatic simulations consistently recorded elevated temperatures, with the most pronounced impacts in densely built zones. These findings underscore the need for public policies to mitigate such negative effects observed in informal settlement areas.

Striking a Pose: DIY Computer Vision Sensor Kit to Measure Public Life Using Pose Estimation Enhanced Action Recognition Model

Sat, 01 Nov 2025 00:00:00 GMT

Striking a Pose: DIY Computer Vision Sensor Kit to Measure Public Life Using Pose Estimation Enhanced Action Recognition Model Williams, Sarah; Kang, Minwook Observing and measuring public life is essential for designing inclusive, vibrant, and climate-resilient public spaces. While urban planners have traditionally relied on manual observation, recent advances in open-source Computer Vision (CV) now enable automated analysis. However, most CV sensors in urban studies focus on transportation analysis, offering limited insight into nuanced human behaviors such as sitting or socializing. This limitation stems in part from the challenges CV algorithms face in detecting subtle activities within public spaces. This study introduces the Public Life Sensor Kit (PLSK), an open-source, do-it-yourself system that integrates a GoPro camera with an NVIDIA Jetson edge device, and evaluates whether pose estimation-enhanced CV models can improve the detection of fine-grained public life behaviors, such as sitting and social interaction. The PLSK was deployed during a public space intervention project in Sydney, Australia. The resulting data were measured against data collected from the Vivacity sensor, a commercial transportation-focused CV system, and traditional human observation. The results show that the PLSK outperforms the commercial sensor in detecting and classifying key public life activities, including pedestrian traffic, sitting, and socializing. These findings highlight the potential of the PLSK to support ethically collected and behavior-rich public space analysis and advocate for its adoption in next-generation urban sensing technologies.

Pretreatment of Mice with 830 nm Light Enhances Endurance During Acute Exercise

Thu, 23 Oct 2025 00:00:00 GMT

Pretreatment of Mice with 830 nm Light Enhances Endurance During Acute Exercise Cheema, Nashwa; Ghag, Namrata; Pham, Linh; Wise, Emma; Fuchs, Christiane; Anderson, Rox; Tam, Joshua Light therapy has been shown to produce several beneficial physiological effects in a wide range of tissues. The musculoskeletal system can be irradiated with deeply penetrating wavelengths in near infrared (NIR) regions. Photobiomodulation therapy (PBMT) reduces pain and inflammation and enhances physical performance. However, the mechanism(s) of cellular responses to PBMT in muscle is not clearly understood. Therefore, the goal of this study is to improve our understanding of the mechanism(s) of action of PBMT effects in exercised and sedentary muscle. In sedentary mice, PBMT using a wavelength of 830 nm increased the gene expression for muscle tissue development, including cFos, which is critical for activating interstitial and satellite cells that repair muscle. Immunostaining for cFOS expression confirmed an increase in the number of activated cells in PBMT-treated muscle. We observed that PBMT-treated mice showed increased performance on the treadmill, reduced muscle fiber damage, and altered mitochondrial structure. RNA sequencing from fatigued TA tissue suggested that PBMT treatment increased the gene expression of tissue regeneration and remodeling, suggesting tissue adaptation and muscle repair after exercise with PBMT. In conclusion, our study suggests that the 830 nm wavelength may have altered the muscle by activating regenerative genes that protect the tissue from exercise-induced cellular stress.

Integrating Physiologic Assessment into Virtual Reality-Based Pediatric Pain Intervention: A Feasibility Study

Wed, 22 Oct 2025 00:00:00 GMT

Integrating Physiologic Assessment into Virtual Reality-Based Pediatric Pain Intervention: A Feasibility Study Marwah, Harsheen; Moldovanu, Stefania R.; Reks, Talis; Anthony, Brian; Logan, Deirdre E. This feasibility study explored the integration of physiological monitoring into a virtual reality (VR) intervention for pediatric pain management. The goal of this study is to identify a feasible strategy for collecting physiologic data in the context of a VR intervention currently being developed for youth with chronic pain. We assess the potential of Cognitive Load (CL)—derived from heart rate and pupillometry/eye-tracking data—as a marker of arousal and user engagement in a VR simulation to promote school functioning in youth with chronic pain. The HP Reverb G2 Omnicept headset and Polar H10 heart-rate sensor were utilized. The Child Presence Questionnaire (CPQ) assessed participants’ self-reported immersion and engagement. Data collection focused on feasibility and utility of physiologic data in assessing arousal and correlations with self-reported experience. Nine participants engaged in the simulation, with eight yielding complete data. The simulation and headset were well tolerated. CPQ Transportation subscale showed trend-level correlation with mean CL. Due to small sample and feasibility focus, individual-level results were examined. Combining multiple physiologic markers into a construct like CL is intriguing, but data interpretability was limited. Pupillometry and related metrics show promise as feasible markers of engagement and arousal for VR-based intervention but require appropriate expertise to fully interpret. The study found that integration of physiologic monitoring is feasible, but further work is needed to standardize metrics and identify the most useful and user-friendly markers.

Two Decades of CARICOMP Mangrove Monitoring (1992–2013) Reveal Variability in Tree Structure and Productivity of Rhizophora mangle Across the Wider Caribbean

Mon, 01 Dec 2025 00:00:00 GMT

Two Decades of CARICOMP Mangrove Monitoring (1992–2013) Reveal Variability in Tree Structure and Productivity of Rhizophora mangle Across the Wider Caribbean Kjerfve, Björn; Oxenford, Hazel A.; Collin, Rachel; Pestana, Inácio Abreu; Samper-Villarreal, Jimena; Medina-Gómez, Israel; Cortés, Jorge; Smith, Struan R.; Koltes, Karen; Feller, Ilka C.; Bastidas, Carolina; Juman, Rahanna; Geraldes, Francisco X.; Filippo, Alessandro; Varela, Ramon; McCoy, Croy; Garzón-Ferreira, Jaime; Polanía, Jaime; Capelo, Juan C.; Ogden, John The Caribbean Coastal Marine Productivity (CARICOMP) program was conceptualized in 1985 to monitor coral reefs, seagrass beds, and mangrove forests at multiple sites across the wider Caribbean. Mangrove monitoring was focused on the dominant Caribbean species, red mangrove (Rhizophora mangle). Forest structure and productivity were monitored at 21 sites (18 countries) across different geomorphological settings, from tropical to subtropical mainland and island systems. Here, we provide the key findings from the CARICOMP mangrove data collected, mostly from 1992 to 2013, to assess spatial and temporal variability across the region. Red mangrove above-ground biomass averaged 190 t ha−1 (far higher than previously reported) but ranged widely across sites from 33 to 590 t ha−1, equating to an average above-ground ‘blue carbon’ of 84 t ha−1 (range 15–260 t ha−1). Tree density averaged 3237 trees ha−1, tree basal area averaged 19.7 m2 ha−1, tree height averaged 6.1 ± 2.8 m, and seedling density varied from 1.2 to 74 seedlings m−2 across the sites. Among the environmental factors that influence mangroves, local temperature and rainfall explained 48% of the variability in measured tree structure parameters. Annual litterfall, as a proxy for productivity, measured on average 1.24 ± 0.70 kg m−2 yr−1, with 60% of the total litterfall composed of leaves. Litterfall varied seasonally by 42%. No relationship was apparent between litterfall and seasonal ocean–atmosphere climate indices (ONI and AMM). With exception of the three most southwesterly CARICOMP sites, hurricanes and tropical storms impacted the mangrove sites repeatedly, resulting in considerable damage. A direct strike by a category-4 hurricane in 1998 in Dominican Republic killed 67% of the red mangrove trees, lowered above-ground biomass by 91%, basal area by 89%, litterfall by 63%, and resulted in the subsequent growth of many tall and thin saplings, totally changing the structure of the forest ecosystem in the first few years after the hurricane. In comparing mangrove systems, major differences may be explained by time elapsed since the last destructive event (hurricane) affecting each site. This highlights the fact that despite an increasing focus on preserving these valuable ecosystems, they are still highly vulnerable to natural hazards and likely to face a poor outcome under ongoing climate change.

Thallium(I) Uptake and Accumulation by Wheat and Rice Plants

Wed, 17 Dec 2025 00:00:00 GMT

Thallium(I) Uptake and Accumulation by Wheat and Rice Plants Yang, Puu-Tai; Chang, Hsin-Fang; Huang, Liang-Sin; Chuang, Tsung-Ju; Wang, Shan-Li Thallium (Tl) is a highly toxic trace metal of increasing concern in agricultural soils. This study investigated the uptake, accumulation, and tissue-level distribution of Tl(I) in rice (Oryza sativa L.) and wheat (Triticum aestivum L.) grown in three agricultural soils differing in soil pH and texture. In the seedling pot experiment (0–100 mg kg−1 soil Tl), plant Tl concentrations increased dose-dependently, and were at least an order of magnitude lower in the alkaline soil than in the acidic soils. Bioaccumulation factors of roots and shoots generally exceeded unity and declined with increasing Tl dose in acidic soils, consistent with uptake saturation and physiological stress at high exposure. To elucidate how soil Tl speciation and pH regulate Tl availability, X-ray absorption spectroscopy (XAS) was used; it showed that Tl(I)—sorbed on illite was the predominant species in all soils (89–95%), with a minor fraction (5–11%) associated with non-specific adsorption. In maturity pots (5 mg kg−1 soil Tl), both crops grown in the moderately acidic, coarse-textured soil translocated a small fraction of absorbed Tl to grains, with wheat and rice containing 0.24 and 0.10 mg kg−1 Tl, respectively. Comparatively, plants in the more acidic soil failed to reach maturity, and grain Tl was not detected in the alkaline soil. LA-ICP-MS mapping revealed Tl enrichment in the bran and embryo of rice and in the crease, bran, and embryo of wheat, indicating that unpolished grains may pose higher dietary exposure risks than polished products. Overall, these findings demonstrate the key roles of soil pH and mineral composition in governing soil Tl availability and plant Tl uptake, whereas plant transport processes regulate grain Tl loading. In the absence of food-safety standards for Tl, the results of this study underscore the need to better understand and mitigate Tl transfer from contaminated soils into human food chains via cereal crops.

Proximity Loses: Real-Time Resolution of Ambiguous Wh-Questions in Japanese

Tue, 25 Nov 2025 00:00:00 GMT

Proximity Loses: Real-Time Resolution of Ambiguous Wh-Questions in Japanese Nakamura, Chie; Flynn, Suzanne; Miyamoto, Yoichi; Yusa, Noriaki This study investigated how Japanese speakers interpret structurally ambiguous wh-questions, testing whether filler–gap resolution is guided by syntactic resolution based on hierarchical structure or linear locality based on surface word order. We combined behavioral key-press responses with fine-grained eye-tracking data and applied cluster-based permutation analysis to capture the moment-by-moment time course of syntactic interpretation as sentences were processed in real time. Key-press responses revealed a preference for resolving the dependency at the main clause (MC) gap position. Eye-tracking data showed early predictive fixations to the MC picture, followed by shifts to the embedded clause (EC) picture as the embedded event was described. These shifts occurred prior to the appearance of syntactic cues that signal the presence of an EC structure, such as the complementizer -to, and were therefore most likely guided by referential alignment with the linguistic input rather than by syntactic reanalysis. A subsequent return of the gaze to the MC picture occurred when the clause-final question particle -ka became available, confirming the interrogative use of the wh-phrase. Both key-press and eye-tracking data showed that participants did not commit to the first grammatically available EC interpretation but instead waited until clause-final particle information confirmed the interrogative use of the wh-phrase, ultimately favoring the MC interpretation. This pattern supports the view that filler–gap resolution is guided by structural locality rather than linear locality. By using high-resolution temporal data and statistically robust analytic techniques, this study demonstrates that Japanese comprehenders engage in predictive yet structurally cautious parsing. These findings challenge earlier claims that filler–gap resolution in Japanese is primarily driven by linear locality and instead showed a preference for resolving dependencies at the structurally higher MC position, consistent with parsing biases previously observed in English, despite typological differences in word order between the two languages. This preference also reflects sensitivity to language-specific morpho-syntactic cues in Japanese, such as clause-final particles.

Engineering peroxisomal biosynthetic pathways for maximization of triterpene production in Yarrowia lipolytica

Tue, 23 Jan 2024 00:00:00 GMT

Engineering peroxisomal biosynthetic pathways for maximization of triterpene production in Yarrowia lipolytica Ma, Yongshuo; Shang, Yi; Stephanopoulos, Gregory Constructing efficient cell factories for product synthesis is frequently hampered by competing pathways and/or insufficient precursor supply. This is particularly evident in the case of triterpenoid biosynthesis in Yarrowia lipolytica, where squalene biosynthesis is tightly coupled to cytosolic biosynthesis of sterols essential for cell viability. Here, we addressed this problem by reconstructing the complete squalene biosynthetic pathway, starting from acetyl-CoA, in the peroxisome, thus harnessing peroxisomal acetyl-CoA pool and sequestering squalene synthesis in this organelle from competing cytosolic reactions. This strategy led to increasing the squalene levels by 1,300-fold relatively to native cytosolic synthesis. Subsequent enhancement of the peroxisomal acetyl-CoA supply by two independent approaches, 1) converting cellular lipid pool to peroxisomal acetyl-CoA and 2) establishing an orthogonal acetyl-CoA shortcut from CO2-derived acetate in the peroxisome, further significantly improved local squalene accumulation. Using these approaches, we constructed squalene-producing strains capable of yielding 32.8 g/L from glucose, and 31.6 g/L from acetate by employing a cofeeding strategy, in bioreactor fermentations. Our findings provide a feasible strategy for protecting intermediate metabolites that can be claimed by multiple reactions by engineering peroxisomes in Y. lipolytica as microfactories for the production of such intermediates and in particular acetyl-CoA-derived metabolites.

Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy

Thu, 30 May 2024 00:00:00 GMT

Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy Rawat, Vipin; DeLear, Patrick; Prashanth, Prarthana; Ozgurses, Mete Emir; Tebeje, Anteneh; Burns, Philippa A; Conger, Kelly O; Solís, Christopher; Hasnain, Yasir; Novikova, Anna; Endress, Jennifer E; González-Sánchez, Paloma; Dong, Wentao; Stephanopoulos, Greg; DeNicola, Gina M; Harris, Isaac S; Sept, David; Mason, Frank M; Coloff, Jonathan L The nonphysiological nutrient levels found in traditional culture media have been shown to affect numerous aspects of cancer cell physiology, including how cells respond to certain therapeutic agents. Here, we comprehensively evaluated how physiological nutrient levels affect therapeutic response by performing drug screening in human plasma-like medium. We observed dramatic nutrient-dependent changes in sensitivity to a variety of FDA-approved and clinically trialed compounds, including rigosertib, an experimental cancer therapeutic that recently failed in phase III clinical trials. Mechanistically, we found that the ability of rigosertib to destabilize microtubules is strongly inhibited by the purine metabolism end product uric acid, which is uniquely abundant in humans relative to traditional in vitro and in vivo cancer models. These results demonstrate the broad and dramatic effects nutrient levels can have on drug response and how incorporation of human-specific physiological nutrient medium might help identify compounds whose efficacy could be influenced in humans.

Metabolic Engineering of E. coli for Enhanced Diols Production from Acetate

Fri, 18 Apr 2025 00:00:00 GMT

Metabolic Engineering of E. coli for Enhanced Diols Production from Acetate Ricci, Luca; Cen, Xuecong; Zu, Yuexuan; Antonicelli, Giacomo; Chen, Zhen; Fino, Debora; Pirri, Fabrizio C; Stephanopoulos, Gregory; Woolston, Benjamin M; Re, Angela Effective employment of renewable carbon sources is highly demanded to develop sustainable biobased manufacturing. Here, we developed Escherichia coli strains to produce 2,3-butanediol and acetoin (collectively referred to as diols) using acetate as the sole carbon source by stepwise metabolic engineering. When tested in fed-batch experiments, the strain overexpressing the entire acetate utilization pathway was found to consume acetate at a 15% faster rate (0.78 ± 0.05 g/g/h) and to produce a 35% higher diol titer (1.16 ± 0.01 g/L) than the baseline diols-producing strain. Moreover, singularly overexpressing the genes encoding alternative acetate uptake pathways as well as alternative isoforms of genes in the malate-to-pyruvate pathway unveiled that leveraging ackA-pta and maeA is more effective in enhancing acetate consumption and diols production, compared to acs and maeB. Finally, the increased substrate consumption rate and diol production obtained in flask-based experiments were confirmed in bench-scale bioreactors operated in fed-batch mode. Consequently, the highest titer of 1.56 g/L achieved in this configuration increased by over 30% compared to the only other similar effort carried out so far.

Constant Degree Networks for Almost-Everywhere Reliable Transmission

Sun, 15 Jun 2025 00:00:00 GMT

Constant Degree Networks for Almost-Everywhere Reliable Transmission Bafna, Mitali; Minzer, Dor In the almost-everywhere reliable message transmission problem, introduced by [Dwork, Pippenger, Peleg, Upfal’86], the goal is to design a sparse communication network G that supports efficient, fault-tolerant protocols for interactions between all node pairs. By fault-tolerant, we mean that that even if an adversary corrupts a small fraction of vertices in G, then all but a small fraction of vertices can still communicate perfectly via the constructed protocols. Being successful to do so allows one to simulate, on a sparse graph, any fault-tolerant distributed computing task and secure multi-party computation protocols built for a complete network, with only minimal overhead in efficiency. Previous works on this problem achieved either constant-degree networks tolerating o(1) faults, constant-degree networks tolerating a constant fraction of faults via inefficient protocols (exponential work complexity), or poly-logarithmic degree networks tolerating a constant fraction of faults. We show a construction of constant-degree networks with efficient protocols (i.e., with polylogarithmic work complexity) that can tolerate a constant fraction of adversarial faults, thus solving the main open problem of Dwork et al. Our main contribution is a composition technique for communication networks, based on graph products. Our technique combines two networks tolerant to adversarial edge-faults to construct a network with a smaller degree while maintaining efficiency and fault-tolerance. We apply this composition result multiple times, using the polylogarithmic-degree edge-fault tolerant networks constructed in a recent work of [Bafna, Minzer, Vyas’24] (that are based on high-dimensional expanders) with itself, and then with the constant-degree networks (albeit with inefficient protocols) of [Upfal’92]. STOC ’25, Prague, Czechia

Quasi-Linear Size PCPs with Small Soundness from HDX

Sun, 15 Jun 2025 00:00:00 GMT

Quasi-Linear Size PCPs with Small Soundness from HDX Bafna, Mitali; Minzer, Dor; Vyas, Nikhil; Yun, Zhiwei We construct 2-query, quasi-linear size probabilistically checkable proofs (PCPs) with arbitrarily small constant soundness, improving upon Dinur’s 2-query quasi-linear size PCPs with soundness 1 − Ω(1). As an immediate corollary, we get that under the exponential time hypothesis, for all𝜀 > 0 no approximation algorithm for 3-SAT can obtain an approximation ratio of 7/8+𝜀 in time 2 𝑛/log𝐶 𝑛 , where 𝐶 is a constant depending on 𝜀. Our result builds on a recent line of independent works by Bafna, Lifshitz and Minzer, and Dikstein, Dinur and Lubotzky, that showed the existence of linear size direct product testers with small soundness. The main new ingredient in our proof is a technique that embeds a given 2-CSP into a 2-CSP on a prescribed graph, provided that the latter is a graph underlying a sufficiently good high-dimensional expander (HDX). We achieve this by establishing a novel connection between PCPs and fault-tolerant distributed computing, more precisely, to the almost-everywhere reliable transmission problem introduced by Dwork, Peleg, Pippenger and Upfal (1986). We instantiate this connection by showing that graphs underlying HDXs admit routing protocols that are tolerant to adversarial edge corruptions, also improving upon the state of the art constructions of sparse edge-fault-tolerant networks in the process. Our PCP construction requires variants of the aforementioned direct product testers with poly-logarithmic degree. The existence and constructability of these variants is shown in the full version. STOC ’25, Prague, Czechia

Approximately Counting and Sampling Hamiltonian Motifs in Sublinear Time

Sun, 15 Jun 2025 00:00:00 GMT

Approximately Counting and Sampling Hamiltonian Motifs in Sublinear Time Eden, Talya; Levi, Reut; Ron, Dana; Rubinfeld, Ronitt Counting small subgraphs, referred to as motifs, in large graphs is a fundamental task in graph analysis, extensively studied across various contexts and computational models. In the sublinear-time regime, the relaxed problem of approximate counting has been explored within two prominent query frameworks: the standard model, which permits degree, neighbor, and pair queries, and the strictly more powerful augmented model, which additionally allows for uniform edge sampling. Currently, in the standard model, (optimal) results have been established only for approximately counting edges, stars, and cliques, all of which have a radius of one. This contrasts sharply with the state of affairs in the augmented model, where algorithmic results (some of which are optimal) are known for any input motif, leading to a disparity which we term the “scope gap" between the two models. In this work, we make significant progress in bridging this gap. Our approach draws inspiration from recent advancements in the augmented model and utilizes a framework centered on counting by uniform sampling, thus allowing us to establish new results in the standard model and simplify on previous results. In particular, our first, and main, contribution is a new algorithm in the standard model for approximately counting any Hamiltonian motif in sublinear time, where the complexity of the algorithm is the sum of two terms. One term equals the complexity of the known algorithms by Assadi, Kapralov, and Khanna (ITCS 2019) and Fichtenberger and Peng (ICALP 2020) in the (strictly stronger) augmented model and the other is an additional, necessary, additive overhead. Our second contribution is a variant of our algorithm that enables nearly uniform sampling of these motifs, a capability previously limited in the standard model to edges and cliques. Our third contribution is to introduce even simpler algorithms for stars and cliques by exploiting their radius-one property. As a result, we simplify all previously known algorithms in the standard model for stars (Gonen, Ron, Shavitt (SODA 2010)), triangles (Eden, Levi, Ron Seshadhri (FOCS 2015)) and cliques (Eden, Ron, Seshadri (STOC 2018)). STOC ’25, Prague, Czechia

Sandwiching Random Geometric Graphs and Erdos-Renyi with Applications: Sharp Thresholds, Robust Testing, and Enumeration

Sun, 15 Jun 2025 00:00:00 GMT

Sandwiching Random Geometric Graphs and Erdos-Renyi with Applications: Sharp Thresholds, Robust Testing, and Enumeration Bangachev, Kiril; Bresler, Guy The distribution RGG(n,Sd−1,p) is formed by sampling independent vectors {Vi}i = 1n uniformly on Sd−1 and placing an edge between pairs of vertices i and j for which ⟨ Vi,Vj⟩ ≥ τdp, where τdp is such that the expected density is p. Our main result is a poly-time implementable coupling between Erdős-Rényi and RGG such that G(n,p(1 − O(√np/d)))⊆ RGG(n,Sd−1,p)⊆ G(n,p(1 + O(√np/d))) edgewise with high probability when d≫ np. We apply the result to: 1) Sharp Thresholds: We show that for any monotone property having a sharp threshold with respect to the Erdős-Rényi distribution and critical probability pnc, random geometric graphs also exhibit a sharp threshold when d≫ npnc, thus partially answering a question of Perkins. 2) Robust Testing: The coupling shows that testing between G(n,p) and RGG(n,Sd−1,p) with є n2p adversarially corrupted edges for any constant є>0 is information-theoretically impossible when d≫ np. We match this lower bound with an efficient (constant degree SoS) spectral refutation algorithm when d≪ np. 3) Enumeration: We show that the number of geometric graphs in dimension d is at least exp(dnlog−7n), recovering (up to the log factors) the sharp result of Sauermann. STOC ’25, Prague, Czechia

Sample-Optimal Private Regression in Polynomial Time

Sun, 15 Jun 2025 00:00:00 GMT

Sample-Optimal Private Regression in Polynomial Time Anderson, Prashanti; Bakshi, Ainesh; Majid, Mahbod; Tiegel, Stefan We consider the task of privately obtaining prediction error guarantees in ordinary least-squares regression problems with Gaussian covariates (with unknown covariance structure). We provide the first sample-optimal polynomial time algorithm for this task under both pure and approximate differential privacy. We show that any improvement to the sample complexity of our algorithm would violate either statistical-query or information-theoretic lower bounds. Additionally, our algorithm is robust to a small fraction of arbitrary outliers and achieves optimal error rates as a function of the fraction of outliers. In contrast, all prior efficient algorithms either incurred sample complexities with sub-optimal dimension dependence, scaling with the condition number of the covariates, or obtained a polynomially worse dependence on the privacy parameters. Our technical contributions are two-fold: first, we leverage resilience guarantees of Gaussians within the sum-of-squares framework. As a consequence, we obtain efficient sum-of-squares algorithms for regression with optimal robustness rates and sample complexity. Second, we generalize the recent robustness-to-privacy framework of Hopkins, Kamath, Majid, and Narayanan to account for the geometry induced by the covariance of the input samples. This framework crucially relies on the robust estimators to be sum-of-squares algorithms, and combining the two steps yields a sample-optimal private regression algorithm. We believe our techniques are of independent interest, and we demonstrate this by obtaining an efficient algorithm for covariance-aware mean estimation, with an optimal dependence on the privacy parameters. STOC ’25, Prague, Czechia

Faster Weighted and Unweighted Tree Edit Distance and APSP Equivalence

Sun, 15 Jun 2025 00:00:00 GMT

Faster Weighted and Unweighted Tree Edit Distance and APSP Equivalence Nogler, Jakob; Polak, Adam; Saha, Barna; Vassilevska Williams, Virginia; Xu, Yinzhan; Ye, Christopher The tree edit distance (TED) between two rooted ordered trees with n nodes labeled from an alphabet Σ is the minimum cost of transforming one tree into the other by a sequence of valid operations consisting of insertions, deletions and relabeling of nodes. The tree edit distance is a well-known generalization of string edit distance and has been studied since the 1970s. Its running time has seen steady improvements starting with an O(n6) algorithm [Tai, J.ACM 1979], improved to O(n4) [Shasha, Zhang, SICOMP 1989] and to O(n3logn) [Klein, ESA 1998], and culminating in an O(n3) algorithm [Demaine, Mozes, Rossman, Weimann, ACM TALG 2010]. The latter is known to be optimal for any dynamic programming based algorithm that falls under a certain decomposition framework that captures all known sub-n4 time algorithms. Fine-grained complexity casts further light onto this hardness showing that a truly subcubic time algorithm for TED implies a truly subcubic time algorithm for All-Pairs Shortest Paths (APSP) [Bringmann, Gawrychowski, Mozes, Weimann, ACM TALG 2020]. Therefore, under the popular APSP hypothesis, a truly subcubic time algorithm for TED cannot exist. However, unlike many problems in fine-grained complexity for which conditional hardness based on APSP also comes with equivalence to APSP, whether TED can be reduced to APSP has remained unknown. In this paper, we resolve this. Not only we show that TED is fine-grained equivalent to APSP, our reduction is tight enough, so that combined with the fastest APSP algorithm to-date [Williams, SICOMP 2018] it gives the first ever subcubic time algorithm for TED running in n3/2Ω(√logn) time. We also consider the unweighted tree edit distance problem in which the cost of each edit (insertion, deletion, and relabeling) is one. For unweighted TED, a truly subcubic algorithm is known due to Mao [Mao, FOCS 2022], and later improved slightly by Dürr [Dürr, IPL 2023] to run in O(n2.9148) time. Since their algorithm uses bounded monotone min-plus product as a crucial subroutine, and the best running time for this product is Õ(n3+ω/2)≤ O(n2.6857) (where ω is the exponent of fast matrix multiplication), the much higher running time of unweighted TED remained unsatisfactory. In this work, we close this gap and give an algorithm for unweighted TED that runs in Õ(n3+ω/2) time. STOC ’25, Prague, Czechia

The Structure of Catalytic Space: Capturing Randomness and Time via Compression

Sun, 15 Jun 2025 00:00:00 GMT

The Structure of Catalytic Space: Capturing Randomness and Time via Compression Cook, James; Li, Jiatu; Mertz, Ian; Pyne, Edward In the catalytic logspace (CL) model of (Buhrman et. al. STOC 2013), we are given a small work tape, and a larger catalytic tape that has an arbitrary initial configuration. We may edit this tape, but it must be exactly restored to its initial configuration at the completion of the computation. This model is of interest from a complexity-theoretic perspective as it gains surprising power over traditional space. However, many fundamental structural questions remain open. We substantially advance the understanding of the structure of CL, addressing several questions raised in prior work. Our main results are as follows. 1: We unconditionally derandomize catalytic logspace: CBPL = CL. 2: We show time and catalytic space bounds can be achieved separately if and only if they can be achieved simultaneously: any problem in both CL and P can be solved in polynomial time-bounded CL. 3: We characterize deterministic catalytic space by the intersection of randomness and time: CL is equivalent to polytime-bounded, zero-error randomized CL. Our results center around the compress--or--random framework. For the second result, we introduce a simple yet novel compress--or--compute algorithm which, for any catalytic tape, either compresses the tape or quickly and successfully computes the function at hand. For our first result, we further introduce a compress--or--compress--or--random algorithm that combines runtime compression with a second compress--or--random algorithm, building on recent work on distinguish-to-predict transformations and pseudorandom generators with small-space deterministic reconstruction. STOC ’25, Prague, Czechia

Rounding Large Independent Sets on Expanders

Sun, 15 Jun 2025 00:00:00 GMT

Rounding Large Independent Sets on Expanders Bafna, Mitali; Hsieh, Jun-Ting; Kothari, Pravesh K. We develop a new approach for approximating large independent sets when the input graph is a one-sided spectral expander - that is, the uniform random walk matrix of the graph has its second eigenvalue bounded away from 1. Consequently, we obtain a polynomial time algorithm to find linear-sized independent sets in one-sided expanders that are almost 3-colorable or are promised to contain an independent set of size (1/2−є)n. Our second result above can be refined to require only a weaker vertex expansion property with an efficient certificate. In a surprising contrast to our algorithmic result, we observe that the analogous task of finding a linear-sized independent set in almost 4-colorable one-sided expanders (even when the second eigenvalue is on(1)) is NP-hard, assuming the Unique Games Conjecture. All prior algorithms that beat the worst-case guarantees for this problem rely on bottom eigenspace enumeration techniques (following the classical spectral methods of Alon and Kahale) and require two-sided expansion, meaning a bounded number of negative eigenvalues of magnitude Ω(1). Such techniques naturally extend to almost k-colorable graphs for any constant k, in contrast to analogous guarantees on one-sided expanders, which are Unique Games-hard to achieve for k ≥ 4. Our rounding scheme builds on the method of simulating multiple samples from a pseudo-distribution introduced in Bafna et. al. for rounding Unique Games instances. The key to our analysis is a new clustering property of large independent sets in expanding graphs - every large independent set has a larger-than-expected intersection with some member of a small list - and its formalization in the low-degree sum-of-squares proof system. STOC ’25, Prague, Czechia

Universal SNARGs for NP from Proofs of Correctness

Sun, 15 Jun 2025 00:00:00 GMT

Universal SNARGs for NP from Proofs of Correctness Jin, Zhengzhong; Kalai, Yael Tauman; Lombardi, Alex; Mathialagan, Surya We give new constructions of succinct non-interactive arguments (SNARGs) for NP in the settings of both non-adaptive and adaptive soundness. Our construction of non-adaptive SNARG is universal assuming the security of a (leveled or unleveled) fully homomorphic encryption (FHE) scheme as well as a batch argument (BARG) scheme. Specifically, for any choice of parameters ℓ and L, we construct a candidate SNARG scheme for any NP language L with the following properties: (i) the proof length is ℓ· poly(λ), (ii) the common reference string crs has length L· poly(λ), and (iii) the setup is transparent (no private randomness). We prove that this SNARG has non-adaptive soundness assuming the existence of any SNARG where the proof size is ℓ, the crs size is L, and there is a size L Extended Frege (EF) proof of completeness for the SNARG. Moreover, we can relax the underlying SNARG to be any 2-message privately verifiable argument where the first message is of length L and the second message is of length ℓ. This yields new SNARG constructions based on any “EF-friendly” designated-verifier SNARG or witness encryption scheme. We emphasize that our SNARG is universal in the sense that it does not depend on the argument system. We show several new implications of this construction that do not reference proof complexity: (1) a non-adaptive SNARG for NP with transparent crs from LWE under the evasive LWE heuristic. This gives a candidate lattice-based SNARG for NP. (2) a non-adaptive SNARG for NP with transparent crs assuming the (non-explicit) existence of any iO and LWE. (3) a non-adaptive SNARG for NP with a short and transparent (i.e., uniform) crs assuming LWE, FHE and the (non-explicit) existence of any hash function that makes Micali’s SNARG construction sound. (4) a non-adaptive SNARG for languages such as QR and DCR assuming only LWE. In the setting of adaptive soundness, we show how to convert any designated verifier SNARG into publicly verifiable SNARG, assuming the underlying designated verifier SNARG has an EF proof of completeness. As a corollary, we construct an adaptive SNARG for UP with a transparent crs assuming subexponential LWE under the evasive LWE heuristic. We prove our results by extending the encrypt-hash-and-BARG paradigm of [Jin-Kalai-Lombardi-Vaikuntanathan, STOC ’24]. STOC ’25, Prague, Czechia

The Medium is the Message: How Non-Clinical Information Shapes Clinical Decisions in LLMs

Mon, 23 Jun 2025 00:00:00 GMT

The Medium is the Message: How Non-Clinical Information Shapes Clinical Decisions in LLMs Gourabathina, Abinitha; Gerych, Walter; Pan, Eileen; Ghassemi, Marzyeh The integration of large language models (LLMs) into clinical diagnostics necessitates a careful understanding of how clinically irrelevant aspects of user inputs directly influence generated treatment recommendations and, consequently, clinical outcomes for end-users. Building on prior research that examines the impact of demographic attributes on clinical LLM reasoning, this study explores how non-clinically relevant attributes shape clinical decision-making by LLMs. Through the perturbation of patient messages, we evaluate whether LLM behavior remains consistent, accurate, and unbiased when non-clinical information is altered. These perturbations assess the brittleness of clinical LLM reasoning by replicating structural errors that may occur during electronic data processing patient questions and simulating interactions between patient-AI systems in diverse, vulnerable patient groups. Our findings reveal notable inconsistencies in LLM treatment recommendations and significant degradation of clinical accuracy in ways that reduce care allocation to patients. Additionally, there are significant disparities in treatment recommendations between gender subgroups as well as between model-inferred gender subgroups. We also apply our perturbation framework to a conversational clinical dataset to find that even in conversation, LLM clinical accuracy decreases post-perturbation, and disparities exist in how perturbations impact gender subgroups. By analyzing LLM outputs in response to realistic yet modified clinical contexts, our work deepens understanding of the sensitivity, inaccuracy, and biases inherent in medical LLMs, offering critical insights for the deployment of patient-AI systems. FAccT ’25, Athens, Greece

High-Performance Mixed-Precision Matrix Multiplication via Tile-Centric Design on Modern Architectures

Sat, 20 Dec 2025 00:00:00 GMT

High-Performance Mixed-Precision Matrix Multiplication via Tile-Centric Design on Modern Architectures Zhang, Qiao; Alomairy, Rabab; Wang, Dali; Gu, Zhuowei; Cao, Qinglei General Matrix Multiplication (GEMM) is a critical operation underpinning a wide range of applications in high-performance computing (HPC) and artificial intelligence (AI). The emergence of hardware optimized for low-precision arithmetic necessitates a reevaluation of numerical algorithms to leverage mixed-precision computations, achieving improved performance and energy efficiency. This research presents an adaptive mixed-precision GEMM framework that enables support for various precision formats at fine-grained tile and block levels, offering a reliable foundation for trustworthy mixed-precision computations. Furthermore, we leverage the PaRSEC runtime system to effectively balance workloads across diverse architectures. The performance exhibits strong scalability across both homogeneous platforms (Intel CPU-based systems and the ARM CPU-based Fugaku supercomputer) and heterogeneous systems (Nvidia V100, A100, and H100 GPU-based platforms, as well as the AMD GPU-based Frontier supercomputer). This work aims to improve computational efficiency and accuracy by bridging algorithmic innovations with hardware capabilities, fostering transformative advancements across a wide range of applications.

Search for t-channel scalar and vector leptoquark exchange in the high-mass dimuon and dielectron spectra in proton-proton collisions at √s = 13 TeV

Tue, 09 Dec 2025 00:00:00 GMT

Search for t-channel scalar and vector leptoquark exchange in the high-mass dimuon and dielectron spectra in proton-proton collisions at √s = 13 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R. A search for t-channel exchange of leptoquarks (LQs) is performed in dimuon and dielectron spectra using proton-proton collision data collected at √ s = 13 TeV with the CMS detector at the CERN LHC. The data correspond to an integrated luminosity of 138 fb−1 . Eight scenarios are considered, in which up or down quarks couple to muons or electrons via a scalar or vector LQ exchange, for dilepton invariant masses above 500 GeV. The LQ masses are probed up to 5 TeV, beyond a regime probed by previous pair-production and single-production searches. The differential distributions of dilepton events are fit to templates that model the nonresonant LQ exchange and various standard model background processes. Limits are set on LQ-fermion coupling strengths for scalar and vector LQ masses in the 1–5 TeV range at 95% confidence level, establishing stringent limits on first- and second-generation LQs.

Search for charged-lepton flavour violation in top quark interactions with an up-type quark, a muon, and a τ lepton in proton-proton collisions at √s = 13 TeV

Wed, 10 Dec 2025 00:00:00 GMT

Search for charged-lepton flavour violation in top quark interactions with an up-type quark, a muon, and a τ lepton in proton-proton collisions at √s = 13 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J. A search for charged-lepton flavour violation (CLFV) in top quark (t) production and decay is presented. The search uses proton-proton collision data corresponding to 138 fb−1 collected with the CMS experiment at √ s = 13 TeV. The signal consists of the production of a single top quark via a CLFV interaction or top quark pair production followed by a CLFV decay. The analysis selects events containing a hadronically decaying τ lepton and a muon of opposite electric charge, as well as at least three jets, one of which is identified as originating from the fragmentation of a bottom quark. Machine learning classification techniques are used to distinguish signal from standard model background events. The results of this search are consistent with the standard model expectations. The upper limits at 95% confidence level on the branching fraction B for CLFV top quark decays to a muon, a τ lepton, and an up or a charm quark are set at B(t → µτu) < (0.04, 0.08, and 0.12) × 10−6 , and B(t → µτ c) < (0.81, 1.71, and 2.05) × 10−6 for scalar, vector, and tensor-like operators, respectively.

Anyon delocalization transitions out of a disordered fractional quantum anomalous Hall insulator

Fri, 19 Dec 2025 00:00:00 GMT

Anyon delocalization transitions out of a disordered fractional quantum anomalous Hall insulator Shi, Zhengyan Darius; Todadri, Senthil Motivated by the experimental discovery of the fractional quantum anomalous Hall effect, we develop a theory of doping-induced transitions out of the = 2/3 lattice Jain state in the presence of quenched disorder. We show that disorder strongly affects the evolution into the conducting phases described in our previous work. The delocalization of charge 2/3 anyons leads to a chiral superconductor through a direct second-order transition for a smooth random potential with long-wavelength modulations. The longitudinal resistance has a universal peak at the associated quantum critical point. Close to the transition, we show that the superconducting ground state is an “Anomalous Vortex Glass” stabilized in the absence of an external magnetic field. For short-wavelength disorder, this transition generically splits into three distinct ones with intermediate insulating topological phases. If instead, the charge 1/3 anyon delocalizes, then at low doping the resulting phase is a Reentrant Integer Quantum Hall state with xy = h/e 2 . At higher doping this undergoes a second transition to a Fermi liquid metal. We show that this framework provides a plausible explanation for the complex phase diagram recently observed in twisted MoTe2 near = 2/3 and discuss future experiments that can test our theory in more detail.

From Data to Transformative Change: Designing Interactive Systems for Citizen Science Empowerment

Sat, 05 Jul 2025 00:00:00 GMT

From Data to Transformative Change: Designing Interactive Systems for Citizen Science Empowerment Prandi, Catia; Herodotou, Christothea; Dionisio, Mara; Reeves, Neal; Reitsma, Lizette; Mora, Simone Citizen Science (CS) is a research approach in which scientists and everyday people collaborate to address a research problem. Advancements in digital technologies have significantly expanded the reach of Citizen Science by enabling large-scale data collection and collaboration. In addition to its scientific benefits, citizen science enhances participants’ science literacy, fosters public engagement, and promotes collaborative problem-solving. Despite this being true, we believe that the true potential of CS has not yet been fully explored as a collaborative practice for transformative change. With this in mind, we planned a one-day workshop as a forum for critical discussions and reflections on the role of HCI researchers, designers, and practitioners in designing CS-empowered interactive systems for increasing awareness about social good and societal issues and promoting concrete actions and behavioural change, from data to sustainable futures. Participants will have the possibility to reflect on and discuss the main open challenges still affecting the design of CS-empowered interactive systems, and to prototype, exploiting data physicalization and co-design, solutions that focus on a specific real-world challenge as presented by experts of the Madeira Island that offers a unique ecosystem to spark reflections on the interplay between sustainability, technology and CS. DIS ’25 Companion, Funchal, Portugal

Lost in Transplantation: Characterizing Racial Gaps in Physician Organ Offer Acceptance

Mon, 23 Jun 2025 00:00:00 GMT

Lost in Transplantation: Characterizing Racial Gaps in Physician Organ Offer Acceptance Adam, Hammaad; Bermea, Rene; Yang, Ming Ying; Celi, Leo Anthony; Ghassemi, Marzyeh There are known racial disparities in the organ transplant allocation system in the United States. While recent research has focused on designing scores and matching algorithms for organ allocation, prior work has yet to study how transplant center physician decisions on offer acceptance—the final step in the allocation process—contribute to the observed disparities. In this paper, we use data from the Scientific Registry of Transplant Recipients to examine the role of candidate race in the acceptance of heart, liver, and lung transplant offers. We find that Black race was associated with significantly lower odds of offer acceptance for livers and lungs. Further, existing allocation scores such as MELD and LAS did not account for clinical factors that made Black patients harder to match. Our analysis also revealed that donor candidate race-match was associated with significantly higher odds of offer acceptance for hearts, livers, and lungs. Finally, we found that rejecting an offer was associated with lower survival times for all three organs. Our findings demonstrate the additional barriers that Black patients face in accessing organ transplants and the consequences of these barriers on patient survival. Overall, our work highlights the limitations of technical solutions to socio-technical problems; new allocation scores and other algorithmic updates will not improve equity if they do not explicitly account for gaps in the ensuing human decisions. FAccT ’25, Athens, Greece

Coboundary Expansion of Coset Complexes

Sun, 15 Jun 2025 00:00:00 GMT

Coboundary Expansion of Coset Complexes Kaufman, Tali; Oppenheim, Izhar; Weinberger, Shmuel Coboundary expansion is a high dimensional generalization of the Cheeger constant to simplicial complexes. Originally, this notion was motivated by the fact that it implies topological expansion, but nowadays a significant part of the motivation stems from its deep connection to problems in theoretical computer science such as list agreement expansion and agreement expansion in the low soundness regime. In this paper, we prove coboundary expansion with non-Abelian coefficients for the coset complex construction of Kaufman and Oppenheim. Our proof uses a novel global argument, as opposed to the local-to-global arguments that are used to prove cosystolic expansion. STOC ’25, Prague, Czechia

Disclosure without Engagement: An Empirical Review of Positionality Statements at FAccT

Mon, 23 Jun 2025 00:00:00 GMT

Disclosure without Engagement: An Empirical Review of Positionality Statements at FAccT Schroeder, Hope; Pareek, Akshansh; Barocas, Solon Positionality statements have become more common in engineering fields in recent years, despite ongoing debates across many fields about the merits of the practice. In 2024, the Program Chairs of FAccT recommended that authors include positionality statements with their paper submissions, dramatically increasing their use at the conference. In this paper, we analyze all positionality statements at FAccT from 2018 to 2024, highlighting the different aspects of identity commonly disclosed by authors and the degree to which authors explore the potential impact of these aspects of their positionality on their research. While we encountered and highlight a number of thoughtful positionality statements, we also identified and describe several concerning trends, including patterns of identity disclosure without discussion of corresponding impacts, a notable lack of reflection on the potential impacts of industry affiliation, and cases where identity is invoked to excuse what are really methodological choices, among others. We raise particular concerns about the possibility that disclosure without engagement may cause readers to rely on stereotypes to make guesses about the perspectives that individuals from certain groups bring to their work. We conclude by considering potential mechanisms for encouraging reflexivity in the FAccT community, with a focus on setting policies that protect researchers from risks, supporting researchers from backgrounds without existing traditions of reflexive practice, and empirically evaluating the efficacy of interventions designed to foster reflexivity. FAccT ’25, Athens, Greece

LEAD: Towards Learning-Based Equity-Aware Decarbonization in Ridesharing Platforms

Mon, 23 Jun 2025 00:00:00 GMT

LEAD: Towards Learning-Based Equity-Aware Decarbonization in Ridesharing Platforms Sahebdel, Mahsa; Zeynali, Ali; Bashir, Noman; Shenoy, Prashant; Hajiesmaili, Mohammad Ridesharing platforms such as Uber, Lyft, and DiDi have grown in popularity due to their on-demand availability, ease of use, and commute cost reductions, among other benefits. However, not all ridesharing promises have panned out. Recent studies demonstrate that the expected drop in traffic congestion and reduction in greenhouse gas (GHG) emissions have not materialized. This is primarily due to the substantial distances traveled by the ridesharing vehicles without passengers between rides, known as deadhead miles. Recent work has focused on reducing the impact of deadhead miles while considering additional metrics such as rider waiting time, GHG emissions from deadhead miles, or driver earnings. However, most prior studies consider these environmental and equity-based metrics individually despite them being interrelated. In this paper, we propose a Learning-based Equity-Aware Decarabonization approach, LEAD, for ridesharing platforms. LEAD targets minimizing emissions while ensuring that the driver’s utility, defined as the difference between the trip distance and the deadhead miles, is fairly distributed. LEAD uses reinforcement learning to match riders with drivers based on the expected future utility of drivers and the expected carbon emissions of the platform without increasing the rider waiting times. Extensive experiments based on a real-world ridesharing dataset show that LEAD improves the defined notion of fairness by 150% when compared to emission-aware ride-assignment and reduces emissions by 14.6% while ensuring fairness within 28–52% of the fairness-focused baseline. It also reduces the rider wait time, by at least 32.1%, compared to a fairness-focused baseline. FAccT ’25, Athens, Greece

LuciEntry: Towards Understanding the Design of Lucid Dream Induction

Fri, 04 Jul 2025 00:00:00 GMT

LuciEntry: Towards Understanding the Design of Lucid Dream Induction Wang, Po-Yao (Cosmos); Fang, Xiao Zoe; Ducos, Gabriel; Lee, Nathaniel Yung Xiang; Loose, Antony; Rajesh, Rohit; Botheju, Nethmini; Chen, Eric; Montoya, Maria; Kitson, Alexandra; Konkoly, Karen; Sagi, Rohan; Patibanda, Rakesh; Whitmore, Nathan; Jafarzadeh Esfahani, Mahdad; Deng, Jialin; Bu, Jiajun; Dresler, Martin; Elvitigala, Don Samitha; Semertzidis, Nathan; Mueller, Florian Lucid dreaming, a state in which people become aware that they are dreaming, is known for its many mental and physical health benefits. However, most lucid dream induction techniques, such as reality testing, require significant time and effort to master, creating a barrier for people seeking these experiences. We designed LuciEntry, a portable interactive prototype aimed at helping people induce lucid dreaming through well-timed visual and auditory cues. We conducted a lab and a field study to understand LuciEntry’s user experience. The interview data allowed us to identify three themes. Building on these findings and our design practice, we derived seven considerations to guide the design of future lucid dream systems. Ultimately, this work aims to inspire further research into interactive technologies for altered states of consciousness. DIS ’25, Funchal, Portugal

The Reality of AI and Biorisk

Mon, 23 Jun 2025 00:00:00 GMT

The Reality of AI and Biorisk Peppin, Aidan; Reuel, Anka; Casper, Stephen; Jones, Elliot; Strait, Andrew; Anwar, Usman; Agrawal, Anurag; Kapoor, Sayash; Koyejo, Sanmi; Pellat, Marie; Bommasani, Rishi; Frosst, Nick; Hooker, Sara To accurately and confidently answer the question “could an AI model or system increase biorisk”, it is necessary to have both a sound theoretical threat model for how AI models or systems could increase biorisk and a robust method for testing that threat model. This paper provides an analysis of existing available research surrounding two AI and biorisk threat models: 1) access to information and planning via large language models (LLMs), and 2) the use of AI-enabled biological tools (BTs) in synthesizing novel biological artifacts. We find that existing studies around AI-related biorisk are nascent, often speculative in nature, or limited in terms of their methodological maturity and transparency. The available literature suggests that current LLMs and BTs do not pose an immediate risk, and more work is needed to develop rigorous approaches to understanding how future models could increase biorisks. We end with recommendations about how empirical work can be expanded to more precisely target biorisk and ensure rigor and validity of findings. FAccT ’25, Athens, Greece

SoS Certifiability of Subgaussian Distributions and Its Algorithmic Applications

Sun, 15 Jun 2025 00:00:00 GMT

SoS Certifiability of Subgaussian Distributions and Its Algorithmic Applications Diakonikolas, Ilias; Hopkins, Samuel; Pensia, Ankit; Tiegel, Stefan We prove that there is a universal constant C>0 so that for every d ∈ ℕ, every centered subgaussian distribution D on ℝd, and every even p ∈ ℕ, the d-variate polynomial (Cp)p/2 · ||v||2p − EX ∼ D ⟨ v,X⟩p is a sum of square polynomials. This establishes that every subgaussian distribution is SoS-certifiably subgaussian—a condition that yields efficient learning algorithms for a wide variety of high-dimensional statistical tasks. As a direct corollary, we obtain computationally efficient algorithms with near-optimal guarantees for the following tasks, when given samples from an arbitrary subgaussian distribution: robust mean estimation, list-decodable mean estimation, clustering mean-separated mixture models, robust covariance-aware mean estimation, robust covariance estimation, and robust linear regression. Our proof makes essential use of Talagrand’s generic chaining/majorizing measures theorem. STOC ’25, Prague, Czechia

Using collective dialogues and AI to find common ground between Israeli and Palestinian peacebuilders

Mon, 23 Jun 2025 00:00:00 GMT

Using collective dialogues and AI to find common ground between Israeli and Palestinian peacebuilders Konya, Andrew; Thorburn, Luke; Almasri, Wasim; Leshem, Oded Adomi; Procaccia, Ariel; Schirch, Lisa; Bakker, Michiel A growing body of work has shown that AI-assisted methods — leveraging large language models, social choice methods, and collective dialogues — can help navigate polarization and surface common ground in controlled lab settings. But what can these approaches contribute in real-world contexts? We present a case study applying these techniques to find common ground between Israeli and Palestinian peacebuilders in the period following October 7th, 2023. From April to July 2024 an iterative deliberative process combining LLMs, bridging-based ranking, and collective dialogues was conducted in partnership with the Alliance for Middle East Peace. Around 138 civil society peacebuilders participated including Israeli Jews, Palestinian citizens of Israel, and Palestinians from the West Bank and Gaza. The process resulted in a set of collective statements, including demands to world leaders, with at least 84% agreement from participants on each side. In this paper, we document the process, results, challenges, and important open questions. FAccT ’25, Athens, Greece

Recourse, Repair, Reparation, & Prevention: A Stakeholder Analysis of AI Supply Chains

Mon, 23 Jun 2025 00:00:00 GMT

Recourse, Repair, Reparation, & Prevention: A Stakeholder Analysis of AI Supply Chains Hopkins, Aspen; Struckman, Isabella; Klyman, Kevin; Silbey, Susan S. The AI industry is exploding in popularity, with increasing attention to potential harms and unwanted consequences. In the current digital ecosystem, AI deployments are often the product of AI supply chains (AISC): networks of outsourced models, data, and tooling through which multiple entities contribute to AI development and distribution. AI supply chains lack the modularity, redundancies, or conventional supply chain practices that enable identification, isolation, and easy correction of failures, exacerbating the already difficult processes of responding to ML-generated harms. As the stakeholders participating in and impacted by AISCs have scaled and diversified, so too have the risks they face. In this stakeholder analysis of AI supply chains, we consider who participates in AISCs, what harms they face, where sources of harm lie, and how market dynamics and power differentials inform the type and probability of remedies. Because AI supply chains are purposely invented and implemented, they may be designed to account for, rather than ignore, the complexities, consequences, and risks of deploying AI systems. To enable responsible design and management of AISCs, we offer a typology of responses to AISC-induced harms: recourse, repair, reparation or prevention. We apply this typology to stakeholders participating in a health-care AISC across three stylized markets—vertical integration, horizontal integration, free market—to illustrate how stakeholder positioning and power within an AISC may shape responses to an experienced harm. FAccT ’25, Athens, Greece

When to Ask a Question: Understanding Communication Strategies in Generative AI Tools

Thu, 12 Jun 2025 00:00:00 GMT

When to Ask a Question: Understanding Communication Strategies in Generative AI Tools Park, Charlotte; Donahue, Kate; Raghavan, Manish Generative AI tools (GAITs) fundamentally differ from traditional machine learning tools in that they allow users to provide as much or as little information as they choose in their inputs. This flexibility often leads users to omit certain details, relying on the GAIT to infer and fill in less critical information based on distributional knowledge of user preferences. Inferences about preferences lead to natural questions about fairness, since a GAIT’s “best guess” may skew towards the preferences of larger groups at the expense of smaller ones. Unlike more traditional recommender systems, GAITs can acquire additional information about a user’s preferences through feedback or by explicitly soliciting it. This creates an interesting communication challenge: the user is aware of their specific preference, while the GAIT has knowledge of the overall distribution of preferences, and both parties can only exchange a limited amount of information. In this work, we present a mathematical model to describe human-AI co-creation of content under information asymmetry. Our results suggest that GAITs can use distributional information about overall preferences to determine the “right” questions to ask to maximize both welfare and fairness, opening up a rich design space in human-AI collaboration. UMAP Adjunct ’25, New York City, NY, USA

The Cloud Next Door: Investigating the Environmental and Socioeconomic Strain of Datacenters on Local Communities

Mon, 21 Jul 2025 00:00:00 GMT

The Cloud Next Door: Investigating the Environmental and Socioeconomic Strain of Datacenters on Local Communities Ngata, Wacuka M; Bashir, Noman; Westerlaken, Michelle; Liote, Laurent; Chandio, Yasra; Olivetti, Elsa Datacenters have become the backbone of modern digital infrastructure, powering the rapid rise of artificial intelligence and promising economic growth and technological progress. However, this expansion has brought growing tensions in the local communities where datacenters are already situated or being proposed. While the mainstream discourse often focuses on energy usage and carbon footprint of the computing sector at a global scale, the local socio-environmental consequences—such as health impacts, water usage, noise pollution, infrastructural strain, and economic burden—remain largely underexplored and poorly addressed. In this work1, we surface these community-level consequences through a mixed-methods study that combines quantitative data with qualitative insights. Focusing on Northern Virginia’s “Data Center Alley,” we highlight how datacenter growth reshapes local environments and everyday life, and examine the power dynamics that determine who benefits and who bears the costs. Our goal is to bring visibility to these impacts and prompt more equitable and informed decisions about the future of digital infrastructure. COMPASS ’25, Toronto, ON, Canada

SuperSONIC: Cloud-Native Infrastructure for ML Inferencing

Fri, 18 Jul 2025 00:00:00 GMT

SuperSONIC: Cloud-Native Infrastructure for ML Inferencing Kondratyev, Dmitry; Riedel, Benedikt; Chou, Yuan-Tang; Cochran-Branson, Miles; Paladino, Noah; Schultz, David; Liu, Mia; Duarte, Javier; Harris, Philip; Hsu, Shih-Chieh The increasing computational demand from growing data rates and complex machine learning (ML) algorithms in large-scale scientific experiments has driven the adoption of the Services for Optimized Network Inference on Coprocessors (SONIC) approach. SONIC accelerates ML inference by offloading it to local or remote coprocessors to optimize resource utilization. Leveraging its portability to different types of coprocessors, SONIC enhances data processing and model deployment efficiency for cutting-edge research in high energy physics (HEP) and multi-messenger astrophysics (MMA). We developed the SuperSONIC project, a scalable server infrastructure for SONIC, enabling the deployment of computationally intensive tasks to Kubernetes clusters equipped with graphics processing units (GPUs). Using NVIDIA Triton Inference Server, SuperSONIC decouples client workflows from server infrastructure, standardizing communication, optimizing throughput, load balancing, and monitoring. SuperSONIC has been successfully deployed for the CMS and ATLAS experiments at the CERN Large Hadron Collider (LHC), the IceCube Neutrino Observatory (IceCube), and the Laser Interferometer Gravitational-Wave Observatory (LIGO) and tested on Kubernetes clusters at Purdue University, the National Research Platform (NRP), and the University of Chicago. SuperSONIC addresses the challenges of the Cloud-native era by providing a reusable, configurable framework that enhances the efficiency of accelerator-based inference deployment across diverse scientific domains and industries. PEARC ’25, Columbus, OH, USA

What I Don’t Get About AI . . .

Tue, 05 Nov 2024 00:00:00 GMT

What I Don’t Get About AI . . . Wright, Randall S. In a recent MIT News article titled “Explained: Generative AI,” Adam Zewe (Citation2023) writes But what do people really mean when they say ‘generative AI?’ Before the generative AI boom of the past few years, when people talked about AI, typically they were talking about machine-learning models that can learn to make a prediction based on data. For instance, such models are trained, using millions of examples, to predict whether a certain X-ray shows signs of a tumor or if a particular borrower is likely to default on a loan. Generative AI can be thought of as a machine-learning model that is trained to create new data, rather than making a prediction about a specific dataset. A generative AI system is one that learns to generate more objects that look like the data it was trained on.

Bringing a Working-Class Archive Online: Multimodal Storytelling in a Post-Industrial City

Fri, 03 May 2024 00:00:00 GMT

Bringing a Working-Class Archive Online: Multimodal Storytelling in a Post-Industrial City Walley, Christine We find it familiar to consider objects as useful or aesthetic, as necessities or vain indulgences. We are on less familiar ground when we consider objects as companions to our emotional lives or as provocations to thought. The notion of evocative objects brings together these two less familiar ideas, underscoring the inseparability of thought and feeling in our relationship to things. We think with the objects we love; we love the objects we think with.

What is a Right?

Thu, 02 Jan 2025 00:00:00 GMT

What is a Right? Setiya, Kieran This paper argues for a theory of natural rights on which they are explained in terms of reasons supplied by rational consent. When B has a claim-right against A that A φ, A’s non-consent is not a reason for B not to simply make A φ. This theory solves a puzzle that defeats alternative views, including standard will and interest theories, the demand theory of rights, and the view that rights are irreducible or primitive.

The Afterlife of Energy: Post-carbon and Feminist Post-work Politics

Tue, 02 Jul 2024 00:00:00 GMT

The Afterlife of Energy: Post-carbon and Feminist Post-work Politics Ghosn, Rania; Vronskaya, Alla; Jia, Ruo; Pohl, Ethel Baraona; Dharia, Namita Vijay; Aidoo, Fallon Samuels; Wolff, Ilze In the conclusion to her book The Birth of Energy: Fossil Fuels, Thermodynamics, and the Politics of Work, political scientist Cara Daggett considers “A Post-Work Energy Politics” in which she examines the historical coupling of energy and work—meaning human, waged work—in an invitation to disassociate their values and futures. The exponential power of fossil fuels animated the pipedream that powerful, inorganic slaves could substitute unfree human labor, ideas that have driven European imperialism. Fossil fuel systems did not lead, however, to a world beyond work. Rather, today’s “patriarchal slave states” continue to manage the project of putting the world to work through the maximization of productivity, and the subordination of racialized, immigrant, and gendered bodies—who would work for lower, or for no, wages. “The project of work,” Daggett argues, “is in tension with the project of life.” 1 And the rise of “work–life balance” is a mere tactic of governance in which the enemy is fatigue, exhaustion, and burn-out. She suggests, in turn, an alliance between post-carbon and feminist post-work politics and asks: what might it mean for energy politics to refer to the politics of ensuring public vitality? In order to advance a feminist revaluation of work, Daggett draws on Kathi Weeks’s The Problem with Work to outline a project that makes two utopian demands. One demand articulates a paradoxical relationship between the pragmatism of (present) demands and the speculative seeds of possibility; a second demand outlines a utopian form for such politics: partial, fragmented kin to the genre of the manifesto. Daggett concludes with an invitation that “a radical planet politics, if it seeks to contest ecomodernist claims, needs its own politics of pleasure.” 2 In an echo to Daggett’s invitation, the authors of this Educators’ Roundtable were invited to contribute a short text that picks up on the possibilities of a post-carbon, post-work politics.

‘May Our Egos Die So That the World May Live’

Tue, 02 Jul 2024 00:00:00 GMT

‘May Our Egos Die So That the World May Live’ Gupta, Huma This image-based essay reflects upon the author’s experience of running an experimental filmmaking workshop titled Climate Futures, Cities Past in the spring of 2023 at MIT’s School of Architecture featuring stills from four student films set in Greece, Italy, Pakistan, and Syria. It explores how architectural pedagogy can intersect with filmmaking to offer a critical space outside the studio or seminar paper. Engaging eco-critical and narrative approaches of Stefanie K. Dunning, Jennifer Fay, Ursula K. Le Guin, Donna Harraway, Saidiya Hartman, Adrian J. Ivakhiv, and Ousmane Sembène, it explores how ‘cinema might teach us to die’ or rather, embrace a different eschatological paradigm that moves beyond individual authorship, accomplishment, and post-mortem legacy towards more mutualist, collectivist, and anarchic models of existence. It argues that filmmaking as inquiry can offer a way to collect different kinds of stories that help facilitate the messy, uncomfortable, and wildly creative processes of unworlding and reworlding.

From Oil to Information: Caudill, Rowlett, Scott and Architectures of the Energy Crisis

Tue, 02 Jul 2024 00:00:00 GMT

From Oil to Information: Caudill, Rowlett, Scott and Architectures of the Energy Crisis Hanly, B. Jack This paper traces the history of architecture-engineering firm Caudill Rowlett Scott (CRS), roughly 1948–1983, in the context of the postwar oil economy and the 1973 energy crisis. The paper examines CRS’s transformation from a design firm into an energy conglomerate over the course of three decades, as it both concretized the fossil economy between Houston and Saudi Arabia and modeled its own corporate structure after its oil clientele. Analyzing numerous CRS projects designed and built for the oil industry, from corporate office towers to industrial training colleges, the paper looks at a moment in which energy systems and the architectural profession were coproduced through the discourses, practices, and institutions of oil at its most vulnerable historical inflection points. CRS thereby epitomized an energy transition from oil as a substance to oil as information, where a growing postindustrial society would leverage the immaterial dimensions of energy as a foundation for building.

Demonstrating Xstrings: 3D Printing Cable-driven Mechanism for Actuation, Deformation, and Manipulation

Fri, 25 Apr 2025 00:00:00 GMT

Demonstrating Xstrings: 3D Printing Cable-driven Mechanism for Actuation, Deformation, and Manipulation Li, Jiaji; Feng, Shuyue; Perroni-Scharf, Maxine; Liu, Yujia; Guan, Emily; Mueller, Stefanie In this Demo, we present Xstrings, a method for designing and fabricating 3D printed objects with integrated cable-driven mechanisms that can be printed in one go without the need for manual assembly. Xstrings supports four types of cable-driven interactions—bend, coil, screw and compress—which are activated by applying an input force to the cables. To facilitate the design of Xstrings objects, we developed a design tool that allows users to embed cable-driven mechanisms into the object geometry based on the desired interaction by automatically placing joints and cables at the respective locations. The application potential of Xstrings is demonstrated through examples such as manipulable gripping, bionic robot manufacturing, and dynamic prototyping. CHI EA ’25, Yokohama, Japan

My CXL Pool Obviates Your PCIe Switch

Fri, 06 Jun 2025 00:00:00 GMT

My CXL Pool Obviates Your PCIe Switch Zhong, Yuhong; Berger, Daniel; Zardoshti, Pantea; Saurez, Enrique; Nelson, Jacob; Psistakis, Antonis; Fried, Joshua; Cidon, Asaf Pooling PCIe devices across multiple hosts offers a promising solution to mitigate stranded I/O resources, enhance device utilization, address device failures, and reduce total cost of ownership. The only viable option today are PCIe switches, which decouple PCIe devices from hosts by connecting them through a hardware switch. However, the high cost and limited flexibility of PCIe switches hinder their widespread adoption beyond specialized datacenter use cases. This paper argues that PCIe device pooling can be effectively implemented in software using CXL memory pools. CXL memory pools improve memory utilization and already have positive return on investment. We find that, once CXL pools are in place, they can serve as a building block for pooling any kind of PCIe device. We demonstrate that PCIe devices can directly use CXL memory as I/O buffers without device modifications, which enables routing PCIe traffic through CXL pool memory. This software-based approach is deployable on today's hardware and is more flexible than hardware PCIe switches. In particular, we explore how disaggregating devices such as NICs can transform datacenter infrastructure. HOTOS 25, May 14–16, 2025, Banff, AB, Canada

PolyMOF nanoparticles constructed from intrinsically microporous polymer ligand towards scalable composite membranes for CO2 separation

Thu, 14 Dec 2023 00:00:00 GMT

PolyMOF nanoparticles constructed from intrinsically microporous polymer ligand towards scalable composite membranes for CO2 separation Lee, Tae Hoon; Lee, Byung Kwan; Yoo, Seung Yeon; Lee, Hyunhee; Wu, Wan-Ni; Smith, Zachary P; Park, Ho Bum Integrating different modification strategies into a single step to achieve the desired properties of metal–organic frameworks (MOFs) has been very synthetically challenging, especially in developing advanced MOF/polymer mixed matrix membranes (MMMs). Herein, we report a polymer–MOF (polyMOF) system constructed from a carboxylated polymer with intrinsic microporosity (cPIM-1) ligand. This intrinsically microporous ligand could coordinate with metals, leading to ~100 nm-sized polyMOF nanoparticles. Compared to control MOFs, these polyMOFs exhibit enhanced ultramicroporosity for efficient molecular sieving, and they have better dispersion properties in casting solutions to prepare MMMs. Ultimately, integrating coordination chemistries through the cPIM-1 and polymer-based functionality into porous materials results in polyMOF/PIM-1 MMMs that display excellent CO2 separation performance (surpassing the CO2/N2 and CO2/CH4 upper bounds). In addition to exploring the physicochemical and transport properties of this polyMOF system, scalability has been demonstrated by converting the developed MMM material into large-area (400 cm2) thin-film nanocomposite (TFN) membranes.

Single Layer Silk and Cotton Woven Fabrics for Acoustic Emission and Active Sound Suppression

Mon, 01 Apr 2024 00:00:00 GMT

Single Layer Silk and Cotton Woven Fabrics for Acoustic Emission and Active Sound Suppression Yang, Grace H; Lin, Jinuan; Cheung, Henry; Rui, Guanchun; Zhao, Yongyi; Balachander, Latika; Joo, Taigyu; Lee, Hyunhee; Smith, Zachary P; Zhu, Lei; Ma, Chu; Fink, Yoel Whether intentionally generating acoustic waves or attempting to mitigate unwanted noise, sound control is an area of challenge and opportunity. This study investigates traditional fabrics as emitters and suppressors of sound. When attached to a single strand of a piezoelectric fiber actuator, a silk fabric emits up to 70 dB of sound. Despite the complex fabric structure, vibrometer measurements reveal behavior reminiscent of a classical thin plate. Fabric pore size relative to the viscous boundary layer thickness is found—through comparative fabric analysis—to influence acoustic‐emission efficiency. Sound suppression is demonstrated using two distinct mechanisms. In the first, direct acoustic interference is shown to reduce sound by up to 37 dB. The second relies on pacifying the fabric vibrations by the piezoelectric fiber, reducing the amplitude of vibration waves by 95% and attenuating the transmitted sound by up to 75%. Interestingly, this vibration‐mediated suppression in principle reduces sound in an unlimited volume. It also allows the acoustic reflectivity of the fabric to be dynamically controlled, increasing by up to 68%. The sound emission and suppression efficiency of a 130 µm silk fabric presents opportunities for sound control in a variety of applications ranging from apparel to transportation to architecture.

Implications of changing the base raw material – the case of license plate manufacturing

Tue, 31 Dec 2024 00:00:00 GMT

Implications of changing the base raw material – the case of license plate manufacturing Uygun, Yilmaz; Mohammadian, Noushin; Un Nisa, Mehr License plates to uniquely identify vehicles mainly use aluminum as the base material. Currently, there is no distinction of different use cases of license plates, such as short-time usage for test drive and transportation purposes that do not need such long-lasting materials not only from cost but also from sustainability perspectives. This paper presents a methodology to select the best material for different use cases under the holistic consideration of specifically defined criteria as to material properties, sustainability aspects, and supply chain implications. We show that there are several candidate materials for different use cases that stick out by changing the importance of these numerous criteria. In addition, the paper delves deeper into the sustainability aspect by means of a comprehensive System Dynamics model. We show that a scenario in which the company picks up used license plates by relying on a logistics service provider to get them delivered to an external recycling service provider yields the best results.

Metalite, a new class of composite laminates with unique properties

Sun, 21 Jul 2024 00:00:00 GMT

Metalite, a new class of composite laminates with unique properties Miravete, Antonio Metalite is a new class of antisymmetric composite laminates composed of angle-plies, 0-degree, and 90-degree plies, presenting unique properties. These include extremely thin laminates suitable for minimum gauge applications, remarkable weight savings compared to conventional quads, adjustable zero and negative coefficients of thermal expansion (CTE), ease of manufacturing, excellent ability to adjust mode frequency, change sound radiation characteristics, and high tunability. In this study, Metalite laminates ranging from 3 to 8 plies are described using their feasible spaces and compared with quads, detailing the weight savings achieved for hard, soft, and neutral laminates. Through an experimental study, the CTE value of a hybrid Metalite is correlated with theory, demonstrating how to tune zero and negative CTE values. The proposed work offers significant benefits through practical solutions for designing and manufacturing lightweight composite laminates with unique properties.

Tertiary-Amine-Functional Poly(arylene ether)s for Acid-Gas Separations

Wed, 02 Oct 2024 00:00:00 GMT

Tertiary-Amine-Functional Poly(arylene ether)s for Acid-Gas Separations Dean, Pablo A; Wu, Yifan; Guo, Sheng; Swager, Timothy M; Smith, Zachary P Competitive sorption enables the emergent phenomenon of enhanced CO₂-based selectivities for gas separation membranes when using microporous polymers with primary amines. However, strong secondary forces in these polymers through hydrogen bonding results in low solvent solubility, precluding standard solution processing approaches to form these polymers into membrane films. Herein, we circumvent these manufacturing constraints while maintaining competitive-sorption enhancements by synthesizing eight representative microporous poly(arylene ether)s (PAEs) with tertiary amines. High-pressure H₂S, CO₂, and CH₄ sorption isotherms were collected for these samples to demonstrate enhanced affinity for acid gases relative to the unfunctional control polymer. Although competitive sorption was observed for all samples, improvements were less pronounced than for primary-amine-functional analogs. For H₂S-based separations, the benefits of competitive sorption offset decreases in selectivity due to plasticization. This detailed study helps to elucidate the role of tertiary amines for acid gas separations in solution-processable microporous PAEs.

Weathering the storm: examining how organisations navigate the sea of cybersecurity regulations

Sun, 04 May 2025 00:00:00 GMT

Weathering the storm: examining how organisations navigate the sea of cybersecurity regulations Proudfoot, Jeffrey G; Cram, W Alec; Madnick, Stuart Governments around the world routinely regulate the activities of private enterprises to guide the behaviour of individuals and organisations towards acceptable norms. This holds true in a cybersecurity context. However, practitioners report that cybersecurity regulations are often out of date and compliance is confusing, expensive, and time consuming. As a result, organisational leaders are often uncertain about the practicalities of adopting and implementing the various rules, which can lead to trickle-down effects on the robustness of lower-level cybersecurity controls and compliance activities. In this research, we aim to clarify how cybersecurity regulations are operationalised in organisations, as well as reveal the compliance and performance consequences of cybersecurity regulations. To do so, we interviewed 22 senior leaders with expertise in cybersecurity regulations. Our analysis reveals 7 distinct themes (i.e., concept groupings) that are ordered within four phases (i.e., temporal stages), which we use to create the Institutional Cybersecurity Regulations Model (ICRM). The results provide a holistic view of the cybersecurity regulations process in organisations that can serve to clarify current theory relationships and inform future research. As well, the ICRM can provide a practical roadmap for managers to navigate regulatory cybersecurity challenges in their own companies.

Assessment of Technoeconomic Opportunities in Automation for Nuclear Microreactors

Wed, 24 Jul 2024 00:00:00 GMT

Assessment of Technoeconomic Opportunities in Automation for Nuclear Microreactors Naranjo de Candido, Isabel; Al Rashdan, Ahmad; Abou Jaoude, Abdalla; Buongiorno, Jacopo Achieving full decarbonization of all economic sectors remains a challenge, especially in niche markets. For example, remote communities and industrial or mining activities detached from the main electric grid heavily rely on fossil fuels, similar to urban and industrial microgrids with combined heat and power needs. A combination of renewables and energy storage is often not suitable due to cost, reliability, intermittency, and large storage requirements. Small nuclear reactors with a flexible purpose could serve these applications. Microreactors (MR) are a class of reactors that are compact, factory manufactured, transportable, and self-regulating. Typically, they generate much less power than their large reactor counterparts. The main advantages of microreactors include the versatile nature of the energy produced, the reliability of supply, and freedom from having to transport and store large quantities of fuels on-site, coupled with the absence of dependence on an electrical grid. A strong business case is needed to move from the microreactor prototype to the commercialization phase. In fact, fossil fuels are still relatively inexpensive, and in the near term, carbon credits will be available to virtually compensate for emissions. For microreactors, one of the main costs in operation and maintenance (O&M) is their staffing levels. In this study, we investigate how to optimize the number (and thus the cost) of workers, moving from a traditional, fully manned, on-site personnel approach to an unmanned, remote personnel approach. We examine four different staffing models that can be implemented as the technology matures and evolves. We estimate the staffing needs of each model and build a business case to justify the substitution of on-site personnel with adequate technologies. To do so, we propose a cost model to quantify potential cost reductions from automating O&M activities. The model accounts for both the reduction in cost derived from the reduced number of full-time-equivalent (FTE) employees and the increase in cost derived from the need to buy new control hardware as needed. Applying the cost model that we created to different scenarios, an on-site O&M cost reduction exceeding 80% can be expected. Additionally, we found that it is more impactful to focus on automating routine O&M tasks rather than attempting to automate transient management (shutdowns, restarts, monitoring condition deviations). In fact, transients typically account for less than 1% of the total FTE time spent on the reactors.

Enhancing acid–gas separations using free volume manipulation for microporous poly(arylene ether)s

Mon, 27 Jan 2025 00:00:00 GMT

Enhancing acid–gas separations using free volume manipulation for microporous poly(arylene ether)s Joo, Taigyu; Wu, Yifan; Lee, Tae Hoon; Dean, Pablo A; Wu, Wan-Ni; Swager, Timothy M; Smith, Zachary P To address global energy needs, traditional and renewable natural gas will likely be key energy sources for years to come. However, raw feeds require removal of impurities like hydrogen sulfide (H2S) and carbon dioxide (CO2) before use. In this study, we illustrate the key challenges of using traditional post-synthetic modification approaches to simultaneously enhance H2S/CH4 and CO2/CH4 selectivities in microporous polymer membranes, while also demonstrating how free volume manipulation (FVM) can overcome some of these challenges. By integrating tert-butoxycarbonyl-protected piperazinyl (PIP-tBOC) groups into a microporous poly(arylene ether) (PAE-1) and applying thermal treatment with oxygen to degrade the incorporated units in solid-state films, we successfully increased sorption capacity and diffusion selectivity. This modification enhanced the mixed-gas selectivity of H2S/CH4 and CO2/CH4 by 88% and 114%, respectively, compared to the original PAE-1 films. Consequently, the films achieved a combined acid gas (CAG) selectivity of 48, which approached the CAG upper bound for glassy polymers. The FVM process not only improved the selectivity of these membrane films but also markedly increased their resistance to plasticization, making them more suitable for industrial applications in acid–gas separation. This post-synthetic modification strategy, applicable to any glassy polymer containing a nucleophilic aromatic unit, provides a means to leverage the competitive sorption of H2S molecules and the molecular sieving properties of the polymer.

Knowledge and ignorance in forensic identification: the origins of a contested human rights fact

Tue, 31 Dec 2024 00:00:00 GMT

Knowledge and ignorance in forensic identification: the origins of a contested human rights fact Medina, Eden In 2006, DNA testing revealed that the Chilean Medical Legal Service had misidentified at least half of the 96 human rights victims whose remains had been exhumed in 1991 from a lot in the Santiago General Cemetery known as Patio 29. Years earlier the government had returned those remains to the victims' families. This examination of the history of that forensic misidentification uncovers the role played by the shifting relations of knowledge and ignorance in establishing the legal facts of those identities. Building on the growing literature in agnotology, the article demonstrates the ways in which the context of dictatorship created varied and overlapping forms of ignorance that continued to shape the outcome of the forensic work even after Chile returned to democracy. By detailing different examples of ignorance production by the state, a human rights organization, and a university department under military surveillance, the article illuminates the diverse ways that the civil–military dictatorship worked against knowledge production in the domains of science and human rights.

Tweeting during the Pandemic in New York City: Unveiling the Evolving Sentiment Landscape of NYC through a Spatiotemporal Analysis of Geolocated Tweets

Sun, 26 May 2024 00:00:00 GMT

Tweeting during the Pandemic in New York City: Unveiling the Evolving Sentiment Landscape of NYC through a Spatiotemporal Analysis of Geolocated Tweets Ignaccolo, Carmelo; Wibisono, Kevin; Sutto, Maria Paola; Plunz, Richard A. This article explores the relationship between spatial factors, socioeconomic conditions, and Twitter (now called X) sentiment in New York City (NYC) during the COVID-19 pandemic. Using Twitter data, the study investigates how sentiment varied across different geographies. It examines whether sentiment scores, unemployment rates, and COVID-19 hospitalization rates in NYC zip codes revealed spatial associations. The research employs sentiment analysis, a natural language processing technique used to algorithmically determine the emotional tone of a text, on a database of geo-located tweets spanning January to December 2020. The findings reveal a shift towards more negative sentiment during the initial year of the pandemic. Moreover, the study uncovers variations in sentiment trends across boroughs and zip codes. Additionally, a zip code-level fixed-effects model demonstrates a statistically significant relationship between sentiment scores and unemployment rates. In summary, this article makes a two-fold contribution: firstly, it adds a spatial lens to the scholarly debate regarding the use of Twitter data as an indicator of publicly expressed sentiment; secondly, it provides empirical evidence on the spatial interconnectedness of sentiment, health (hospitalization), and socioeconomic factors (unemployment). Overall, this research sheds light on the nuanced relationship between sentiment and space during the COVID-19 pandemic in NYC.

Solution‐Processable, Ladder‐Branched Polyimides of Intrinsic Microporosity by [4+4] Cycloaddition for Membrane Gas Separation

Wed, 15 Oct 2025 00:00:00 GMT

Solution‐Processable, Ladder‐Branched Polyimides of Intrinsic Microporosity by [4+4] Cycloaddition for Membrane Gas Separation Lee, Tae Hoon; Dean, Pablo A; Yeo, Jing Ying; Smith, Zachary P Advancements in membrane-based gas separation have the potential to address global challenges related to energy and the environment. However, new membrane materials must have excellent separation performance, stability, and processability, and simultaneously achieving all three metrics is extremely challenging. To circumvent these issues, a post-synthetic modification of polyimides of intrinsic microporosity (PIM-PIs) synthesized with a UV light (UV)-reactive anthracene co-monomer is reported. UV irradiation on the PIM-PI solution converts the anthracene units into dianthracene linkages by [4+4] cycloaddition, while the resultant PIM-PI is still solution-processable due to the branched structure. The ladder-like dianthracene moieties significantly increased both microporosity (<20 Å) and ultramicroporosity (<7 Å) of the precursor PIM-PI. Notably, the UV-treated PIM-PI membrane exhibits a large boost in pure-gas CO2 permeability by up to 260%, reaching 376 barrer, while maintaining CO2/CH4 ideal selectivity of 35 at 1 bar. Moreover, the developed membrane material has enhanced stability against physical aging and plasticization and showcases excellent CO2/CH4 mixed-gas selectivity (>30 up to 31 bar feed pressure), which surpasses the 2018 mixed-gas upper bound.

Interactive infill topology optimisation guided by user drawn patterns

Tue, 31 Dec 2024 00:00:00 GMT

Interactive infill topology optimisation guided by user drawn patterns Schiffer, Gillian; Schmidt, Martin-Pierre; Pedersen, Claus BW; Carstensen, Josephine V Widespread use of topology optimisation as a design tool for additive manufacturing faces major inhibiting obstacles, such as high computational costs and complexity, concern for other failure modes, and manufacturability. Interactive infill topology optimisation presents an alternative approach to circumvent some of these barriers. The novel contribution of the present work prompts the user to draw a tailored infill pattern, specify regions of interest to locate the infill, and control how strictly the pattern is replicated in the material layout of the design using appearance constraints. This approach improves engineering metrics not directly included in the optimisation formulation by incorporating the user’s engineering experience, thereby avoiding increased computational costs, parameter tuning, and numerical artifacts associated with complex objective functions and constraints. Two 2D benchmark examples increase the linear buckling resistance and energy absorption, respectively, and a 2.5D example minimises compliance while reducing the quantity of overhang supports for additive manufacturing.

Minimum Bucket and Car Battery Problems

Tue, 11 Jun 2024 00:00:00 GMT

Minimum Bucket and Car Battery Problems Feng, Raymond A solar car needs 5 fully charged batteries to run, and it depletes those batteries in 5 hours. The batteries are rechargeable, and solar panels on the car are able to charge 3 batteries simultaneously. It takes 3 hours for the solar panels to finish charging 3 batteries. Furthermore, batteries cannot be charging and in use at the same time. If the car always starts running as soon as 5 full batteries are available, and the solar panels can only operate if 3 empty batteries are available, how many batteries are needed so that the car can eventually run without stopping? We investigate this resource optimization problem and its different variations.

Developers Grappling with Flood Risks: Evaluating Boston’s Climate Resiliency Checklist

Tue, 02 Jan 2024 00:00:00 GMT

Developers Grappling with Flood Risks: Evaluating Boston’s Climate Resiliency Checklist Loescher-Montal, Angela; Mazereeuw, Miho; Shen, Kairos Ongoing waterfront development in risky areas across the globe raises the continued paradox between resilience initiatives and broader market mechanisms. Even as flood risk increases, existing development patterns do not often adequately account for future flood risk. This research examines using resiliency checklists as a growing regulatory tool to improve predevelopment flood resilience standards. The research employs mixed quantitative and qualitative methods to evaluate how four large-scale developments interacted with Boston’s Climate Resiliency Checklist in the last decade and how its current design criteria influenced design decisions. The checklist’s format, design, and time horizon considerations are evaluated. Increased format and smaller-scale tools are considered.

The “content” of intergroup contact: lessons from the Denton Women’s Interracial Fellowship

Sun, 14 Apr 2024 00:00:00 GMT

The “content” of intergroup contact: lessons from the Denton Women’s Interracial Fellowship English, Jasmine Does the content of intergroup contact matter? Despite extensive research on the benefits of contact for intergroup relations, we know little about what happens during contact-based programs and interventions. This article addresses this gap by inductively building theory about the desired content of contact. My analysis draws on oral history interviews and archival data from the Denton Women’s Interracial Fellowship: a real-world case of intergroup contact that emerged to ease the process of school desegregation in Denton, Texas. My analysis of these data moves beyond the scope conditions suggested by (Allport, Gordon W. 1954. The Nature of Prejudice. 25th ed. Cambridge, MA: Perseus Books) to highlight the role of conversations about outgroup experiences. I illuminate how these conversations produce positive impacts on intergroup relations and draw out the implications for research on intergroup contact: namely, that forms of intergroup contact that incorporate these conversations are more likely to improve intergroup relations, and that intergroup contact interventions should explicitly encourage or incorporate these kinds of conversations.

Roadmap of Graphite Moderator and Graphite-Matrix TRISO Fuel Management Options

Sun, 01 Sep 2024 00:00:00 GMT

Roadmap of Graphite Moderator and Graphite-Matrix TRISO Fuel Management Options Forsberg, CW Most high-temperature reactors use graphite as a moderator and structural material. This includes high-temperature gas-cooled reactors with helium cooling and TRi-structural ISOtropic (TRISO) fuel particles embedded in graphite, as well as fluoride salt–cooled high-temperature reactors with clean salt coolant and TRISO fuel particles embedded in graphite and thermal spectrum molten salt reactors with a graphite moderator and fuel dissolved in the salt. The largest volume radioactive waste stream from these reactors is the irradiated graphite. We describe herein a roadmap for management of these graphite wastes that contain radioactive 14C, tritium, and other radionuclides. There may be some graphite wastes with sufficiently low radioactivity levels that can be treated as nonradioactive waste and managed like other graphite waste. Management options for the graphite include (1) direct disposal, (2) recycled back to the reactor or other nuclear applications, and (3) oxidizing the graphite with release as an effluent or underground sequestration of the carbon dioxide. Cosequestration of this carbon dioxide with carbon dioxide from industrial, biological, and cement production processes can isotopically dilute the 14C before sequestration to eliminate the possibility of exceeding individual radiation exposure limits. We also describe options for processing graphite-matrix TRISO fuel, including separating the bulk graphite to reduce the volumes of used fuel for disposal or processing to recover fissile materials. The inventories of radioactive isotopes in different carbon wastes vary by many orders of magnitude; thus, there is no single economic option for the management of all graphite waste.

Adaptive Model Reduction of High-Order Solutions of Compressible Flows via Optimal Transport

Sun, 28 Apr 2024 00:00:00 GMT

Adaptive Model Reduction of High-Order Solutions of Compressible Flows via Optimal Transport Van Heyningen, Robert Loek; Nguyen, Ngoc Cuong; Blonigan, Patrick; Peraire, Jaime The solution of conservation laws with parametrised shock waves presents challenges for both high-order numerical methods and model reduction techniques. We introduce an r-adaptivity scheme based on optimal transport and apply it to develop reduced order models for compressible flows. The optimal transport theory allows us to compute high-order r-adaptive meshes from a starting reference mesh by solving the Monge–Ampère equation. A high-order discretization of the conservation laws enables high-order solutions to be computed on the resulting r-adaptive meshes. Furthermore, the Monge–Ampère solutions contain mappings that are used to reduce the spatial locality of the resulting solutions and make them more amenable to model reduction. We use a non-intrusive model reduction method to construct reduced order models of both the mesh and the solution. The procedure is demonstrated on three supersonic and hypersonic test cases, with the hybridisable discontinuous Galerkin method being used as the full order model.

Demonstrating Thermochromorph: Dynamic Relief Printing with Thermochromic Inks

Fri, 25 Apr 2025 00:00:00 GMT

Demonstrating Thermochromorph: Dynamic Relief Printing with Thermochromic Inks Sethapakdi, Ticha; Myers, Paris; Yu, Tianyu; Covarrubias, Juliana; Leake, Mackenzie; Mueller, Stefanie We demonstrate Thermochromorph, a novel relief printing technique that produces multicolored images that transition into each other through changes in temperature. Our process utilizes two sets of CMYK thermochromic inks that exhibit complementary color-changing behaviors: one shifting from color to transparency, the other from transparency to color at the same activation temperature. We describe our printmaking workflow, provide an open-source software toolkit, showcase prints made with our system, and explore how our system can be used in creative practice through an artist workshop. By incorporating new materials and technology with the rich history of printmaking, our work extends the expressive capabilities of relief printing as the medium continues to evolve. CHI EA ’25, Yokohama, Japan

Demonstrating OpenEarable 2.0: An AI-Powered Ear Sensing Platform

Fri, 25 Apr 2025 00:00:00 GMT

Demonstrating OpenEarable 2.0: An AI-Powered Ear Sensing Platform R?ddiger, Tobias; Zitz, Valeria; Hummel, Jonas; K?ttner, Michael; Lepold, Philipp; King, Tobias; Paradiso, Joseph; Clarke, Christopher; Beigl, Michael In this demo, we present OpenEarable 2.0, an open-source earphone platform designed to provide an interactive exploration of physiological ear sensing and the development of AI applications. Attendees will have the opportunity to explore real-time sensor data and understand the capabilities of OpenEarable 2.0’s sensing components. OpenEarable 2.0 integrates a rich set of sensors, including two ultrasound-capable microphones (inward/outward), a 3-axis ear canal accelerometer/bone conduction microphone, a 9-axis head inertial measurement unit, a pulse oximeter, an optical temperature sensor, an ear canal pressure sensor, a microSD slot, and a microcontroller. Participants will be able to try out the web-based dashboard and mobile app for real-time control and data visualization. Furthermore, the demo will show different applications and real-time data based on OpenEarable 2.0 across physiological sensing and health monitoring, movement and activity tracking, and human-computer interaction. CHI EA ’25, Yokohama, Japan

Conductive Ceramics: Embedding Electronics in Everyday Ceramic Objects

Fri, 25 Apr 2025 00:00:00 GMT

Conductive Ceramics: Embedding Electronics in Everyday Ceramic Objects Chin, Sam; Kim, Keunwook; An, Audrey; Kuang, Quincy; Zhang, Kai We present a method for integrating conductive traces into ceramic objects using a silver-based glaze compatible with traditional firing processes. Our glaze combines silver powder with a glass former and xanthan gum, enabling application through standard ceramic techniques while maintaining the durability of conventional ceramics. Through a material-driven experimentation approach, we characterized how glaze composition and post-processing methods affect conductivity and surface quality. We demonstrate this technique through functional prototypes including a temperature-responsive heating vessel, a touch-sensitive musical controller utilizing kintsugi repair, and an interactive marble machine. This work bridges traditional ceramic craft with interactive technology, offering ceramicists a way to incorporate electronic functionality while preserving traditional methods. CHI EA ’25, Yokohama, Japan

Towards Resource-Efficient Compound AI Systems

Fri, 06 Jun 2025 00:00:00 GMT

Towards Resource-Efficient Compound AI Systems Chaudhry, Gohar Irfan; Choukse, Esha; Goiri, ??igo; Fonseca, Rodrigo; Belay, Adam; Bianchini, Ricardo Compound AI Systems, integrating multiple interacting components like models, retrievers, and external tools, have emerged as essential for addressing complex AI tasks. However, current implementations suffer from inefficient resource utilization due to tight coupling between application logic and execution details, a disconnect between orchestration and resource management layers, and the perceived exclusiveness between efficiency and quality. We propose a vision for resource-efficient Compound AI Systems through a declarative workflow programming model and an adaptive runtime system for dynamic scheduling and resource-aware decision-making. Decoupling application logic from low-level details exposes levers for the runtime to flexibly configure the execution environment and resources, without compromising on quality. Enabling collaboration between the workflow orchestration and cluster manager enables higher efficiency through better scheduling and resource management. We are building a prototype system, called Murakkab, to realize this vision. Our preliminary evaluation demonstrates speedups up to ~ 3.4× in workflow completion times while delivering ~ 4.5× higher energy efficiency, showing promise in optimizing resources and advancing AI system design. HOTOS 25, May 14–16, 2025, Banff, AB, Canada

Fits like a Flex-Glove: Automatic Design of Personalized FPCB-Based Tactile Sensing Gloves

Fri, 25 Apr 2025 00:00:00 GMT

Fits like a Flex-Glove: Automatic Design of Personalized FPCB-Based Tactile Sensing Gloves Murphy, Devin; Li, Yichen; Owens, Crystal; Stanton, Layla; Liang, Paul Pu; Luo, Yiyue; Torralba, Antonio; Matusik, Wojciech Resistive tactile sensing gloves have captured the interest of researchers spanning diverse domains, such as robotics, healthcare, and human-computer interaction. However, existing fabrication methods often require labor-intensive assembly or costly equipment, limiting accessibility. Leveraging flexible printed circuit board (FPCB) technology, we present an automated pipeline for generating resistive tactile sensing glove design files solely from a simple hand photo on legal-size paper, which can be readily supplied to commercial board houses for manufacturing. Our method enables cost-effective, accessible production at under $130 per glove with sensor assembly times under 15 minutes. Sensor performance was characterized under varying pressure loads, and a preliminary user evaluation showcases four unique automatically manufactured designs, evaluated for their reliability and comfort. CHI EA ’25, Yokohama, Japan

Randomness, Not Representation: The Unreliability of Evaluating Cultural Alignment in LLMs

Mon, 23 Jun 2025 00:00:00 GMT

Randomness, Not Representation: The Unreliability of Evaluating Cultural Alignment in LLMs Khan, Ariba; Casper, Stephen; Hadfield-Menell, Dylan Research on the ‘cultural alignment’ of Large Language Models (LLMs) has emerged in response to growing interest in understanding representation across diverse stakeholders. Current approaches to evaluating cultural alignment through survey-based assessments that borrow from social science methodologies often overlook systematic robustness checks. We identify and test three assumptions behind current survey-based evaluation methods: (1) Stability: that cultural alignment is a property of LLMs rather than an artifact of evaluation design, (2) Extrapolability: that alignment with one culture on a narrow set of issues predicts alignment with that culture on others, and (3) Steerability: that LLMs can be reliably prompted to represent specific cultural perspectives. Through experiments examining both explicit and implicit preferences of leading LLMs, we find a high level of instability across presentation formats, incoherence between evaluated versus held-out cultural dimensions, and erratic behavior under prompt steering. We show that these inconsistencies can cause the results of an evaluation to be very sensitive to minor variations in methodology. Finally, we demonstrate in a case study on evaluation design that narrow experiments and a selective assessment of evidence can be used to paint an incomplete picture of LLMs’ cultural alignment properties. Overall, these results highlight significant limitations of current survey-based approaches to evaluating the cultural alignment of LLMs and highlight a need for systematic robustness checks and red-teaming for evaluation results. Data and code are available at https://doi.org/akhan02/cultural-dimension-cover-letters and https://doi.org/ariba-k/llm-cultural-alignment-evaluation, respectively. FAccT ’25, Athens, Greece

Aptly: Making Mobile Apps from Natural Language

Fri, 25 Apr 2025 00:00:00 GMT

Aptly: Making Mobile Apps from Natural Language Patton, Evan; Kim, David; Granquist, Ashley; Liu, Robin; Scott, Arianna; Zamanova, Jennet; Abelson, Harold This paper introduces Aptly, a platform designed to democratize mobile app development, particularly for young learners. Aptly integrates a Large Language Model (LLM) with App Inventor, enabling users to create apps using their natural language. User’s description is translated into a programming language that corresponds with App Inventor’s visual blocks. A preliminary study with high school students demonstrated the usability and potential of the platform. Prior programming experience influenced how users interact with Aptly. Participants identified areas for improvement and expressed a shift in perspective regarding programming accessibility and AI’s role in creative endeavors. CHI EA ’25, Yokohama, Japan

AcceloPrint: Fabricating Customizable Accelerometers with Multi-Material 3D Printing

Fri, 25 Apr 2025 00:00:00 GMT

AcceloPrint: Fabricating Customizable Accelerometers with Multi-Material 3D Printing Ozbek, Doga; AlAlawi, Marwa; Wessely, Michael We introduce AcceloPrint, 3D-printed acceleration sensors that can be fabricated in one pass alongside a 3D object and report on its angular orientation or acceleration. AcceloPrint utilizes capacitive sensing to track the deflection of a 3D printed cantilever beam to a sensor patch. Our AcceloPrint tool integrated into a 3D editor generates a sensor with a user-defined sensing range generated by our computational model. We also propose a novel sensor design with an adjustable sensing range post-fabrication. Our technical evaluation shows our sensor can detect acceleration up to 50 m/s2, with a root mean squared error of 0.35 m/s2 (%3.57) in the range up to 10 m/s2. We demonstrate AcceloPrint with three application examples on sports performance tracking and tangible tools. CHI EA ’25, Yokohama, Japan

"How can we learn and use AI at the same time?": Participatory Design of GenAI with High School Students

Mon, 23 Jun 2025 00:00:00 GMT

"How can we learn and use AI at the same time?": Participatory Design of GenAI with High School Students Pu, Isabella; Ravi, Prerna; Dinh, Linh; Joe, Chelsea; Ogoe, Caitlin; Li, Zixuan; Breazeal, Cynthia; Ostrowski, Anastasia As generative AI (GenAI) emerges as a transformative force, clear understanding of high school students’ perspectives is essential for GenAI’s meaningful integration in high school environments. In this work, we draw insights from a participatory design workshop where we engaged 17 high school students—a group rarely involved in prior research in this area—through the design of novel GenAI tools and school policies addressing their key concerns. Students identified challenges and developed solutions outlining their ideal features in GenAI tools, appropriate school use, and regulations. These centered around the problem spaces of combating bias & misinformation, tackling crime & plagiarism, preventing over-reliance on AI, and handling false accusations of academic dishonesty. Building on our participants’ underrepresented perspectives, we propose new guidelines targeted at educational technology designers for development of GenAI technologies in high schools. We also argue for further incorporation of student voices in development of AI policies in their schools. IDC ’25, Reykjavik, Iceland

Bird: A Point Cursor for Virtual Immersive Environments

Fri, 25 Apr 2025 00:00:00 GMT

Bird: A Point Cursor for Virtual Immersive Environments Simonson, Aubrey; Gretton, Dana; Harteveld, Casper This paper introduces the Bird, a novel point cursor for immersive virtual environments (IVEs) that enables precise, one-handed control over a point in 3D space beyond arm’s reach. Interaction techniques commonly used in VR today lack this functionality. While direct manipulation allows for control of the position of an object in 3D space, it is limited to arm’s reach. Ray-casting enables interaction at a distance but specifies a line rather than a point, making it impossible to move objects closer or farther without additional mechanics. The Bird overcomes these limitations by allowing users to select any visible object and place it anywhere within view, with one hand and without requiring a controller. We explore a range of use cases that highlight the Bird’s potential to expand the design space for spatial computing. CHI EA ’25, Yokohama, Japan

On Approximability of Satisfiable 𝑘-CSPs: V

Sun, 15 Jun 2025 00:00:00 GMT

On Approximability of Satisfiable 𝑘-CSPs: V Bhangale, Amey; Khot, Subhash; Minzer, Dor We propose a framework of algorithm vs. hardness for all Max-CSPs and demonstrate it for a large class of predicates. This framework extends the work of Raghavendra [STOC, 2008], who showed a similar result for almost satisfiable Max-CSPs. Our framework is based on a new hybrid approximation algorithm, which uses a combination of the Gaussian elimination technique (i.e., solving a system of linear equations over an Abelian group) and the semidefinite programming relaxation. We complement our algorithm with a matching dictator vs. quasirandom test that has perfect completeness. The analysis of our dictator vs. quasirandom test is based on a novel invariance principle, which we call the mixed invariance principle. Our mixed invariance principle is an extension of the invariance principle of Mossel, O’Donnell and Oleszkiewicz [Annals of Mathematics, 2010] which plays a crucial role in Raghavendra’s work. The mixed invariance principle allows one to relate 3-wise correlations over discrete probability spaces with expectations over spaces that are a mixture of Guassian spaces and Abelian groups, and may be of independent interest. STOC ’25, Prague, Czechia

Fewer Than 1% of Explainable AI Papers Validate Explainability with Humans

Fri, 25 Apr 2025 00:00:00 GMT

Fewer Than 1% of Explainable AI Papers Validate Explainability with Humans Suh, Ashley; Hurley, Isabelle; Smith, Nora; Siu, Ho Chit This late-breaking work presents a large-scale analysis of explainable AI (XAI) literature to evaluate claims of human explainability. We collaborated with a professional librarian to identify 18,254 papers containing keywords related to explainability and interpretability. Of these, we find that only 253 papers included terms suggesting human involvement in evaluating an XAI technique, and just 128 of those conducted some form of a human study. In other words, fewer than 1% of XAI papers (0.7%) provide empirical evidence of human explainability when compared to the broader body of XAI literature. Our findings underscore a critical gap between claims of human explainability and evidence-based validation, raising concerns about the rigor of XAI research. We call for increased emphasis on human evaluations in XAI studies and provide our literature search methodology to enable both reproducibility and further investigation into this widespread issue. CHI EA ’25, Yokohama, Japan

Characteristics of Driver Peripheral Vision: How Drivers Respond to Ubiquitous Information on Wide-Area In-Vehicle Displays

Fri, 25 Apr 2025 00:00:00 GMT

Characteristics of Driver Peripheral Vision: How Drivers Respond to Ubiquitous Information on Wide-Area In-Vehicle Displays Huang, Hongwei; Li, Jiateng; Feng, Xuejing; Ma, Jun; Mehler, Bruce Despite advancements in In-Vehicle Information Systems (IVIS) and extensive research on screen layouts, the influence of drivers’ peripheral vision on interactions with evolving multi-screen and large display technologies remains poorly understood. This study examines drivers’ responses to in-vehicle interactive information through peripheral vision, aiming to optimize visual interaction efficiency and enhance driving safety. Analyzing data from 216 participants in a driving simulator, we explored how horizontal eccentricity, screen type, cognitive load, visual crowding, and stimulus type affect perception rates and reaction times. Our findings highlight the significance of these factors and the need for driver-centered design. The results suggest designing IVIS that align with natural visual tendencies to improve interaction efficiency and driving safety. CHI EA ’25, Yokohama, Japan

Guiding Evolutionary AutoEncoder Training with Activation-Based Pruning Operators

Sun, 13 Jul 2025 00:00:00 GMT

Guiding Evolutionary AutoEncoder Training with Activation-Based Pruning Operators Jorgensen, Steven; Hemberg, Erik; Toutouh, Jamal; O'Reilly, Una-May This study explores a novel approach to neural network pruning using evolutionary computation, focusing on simultaneously pruning the encoder and decoder of an autoencoder. We introduce two new mutation operators that use layer activations to guide weight pruning. Our findings reveal that one of these activation-informed operators outperforms random pruning, resulting in more efficient autoencoders with comparable performance to canonically trained models. Prior work has established that autoencoder training is effective and scalable with a spatial coevolutionary algorithm that cooperatively coevolves a population of encoders with a population of decoders, rather than one autoencoder. We evaluate how the same activity-guided mutation operators transfer to this context. We find that random pruning is better than guided pruning, in the coevolutionary setting. This suggests activation-based guidance proves more effective in low-dimensional pruning environments, where constrained sample spaces can lead to deviations from true uniformity in randomization. Conversely, population-driven strategies enhance robustness by expanding the total pruning dimensionality, achieving statistically uniform randomness that better preserves system dynamics. We experiment with pruning according to different schedules and present best combinations of operator and schedule for the canonical and coevolving populations cases. GECCO ’25, July 14–18, 2025, Malaga, Spain

Mirai: A Wearable Proactive AI "Inner-Voice" for Contextual Nudging

Fri, 25 Apr 2025 00:00:00 GMT

Mirai: A Wearable Proactive AI "Inner-Voice" for Contextual Nudging Fang, Cathy Mengying; Samaradivakara, Yasith; Maes, Pattie; Nanayakkara, Suranga People often find it difficult to turn their intentions into real actions—a challenge that affects both personal growth and mental well-being. While established methods like cognitive-behavioral therapy and mindfulness training help people become more aware of their behaviors and set clear goals, these approaches cannot provide immediate guidance when people fall into automatic reactions or habits. We introduce Mirai, a novel wearable AI system with an integrated camera, real-time speech processing, and personalized voice-cloning to provide proactive and contextual nudges for positive behavior change. Mirai continuously monitors and analyzes the user’s environment to anticipate their intentions, generating contextually-appropriate responses delivered in the user’s own cloned voice. We demonstrate the application of Mirai through three scenarios focusing on dietary choices, work productivity, and communication skills. We also discuss future work on improving the proactive agent via human feedback and the need for a longitudinal study in naturalistic settings. CHI EA ’25, Yokohama, Japan

Structural Tuning of Self‐Conductive Polymer as Gas Diffusion Layer for Electrocatalytic Reactions at High Current

Tue, 21 Oct 2025 00:00:00 GMT

Structural Tuning of Self‐Conductive Polymer as Gas Diffusion Layer for Electrocatalytic Reactions at High Current Noh, Hwiyoon; Lee, Tae Hoon; Ahn, Sang Hyun; Davis, Jonathan T; Jeong, Daecheol; Gounder, Rajamani; Smith, Zachary P; Boudouris, Bryan W; Tackett, Brian M Electrocatalytic conversions offer a promising route for sustainable chemical production using renewable energy. Gas diffusion layers (GDLs) enable selective product formation at high current densities but suffer from electrolyte flooding, and polytetrafluoroethylene (PTFE)-based GDLs typically require metal conductive layers, which constrain catalyst development. A recently developed GDL configuration, electropolymerized poly(3,4-ethylenedioxythiophene) (PEDOT)-coated PTFE, demonstrates notable flooding resistance, but suffers from gas diffusion limitations at elevated currents due to limited gas diffusion through the PEDOT layer. Here, different dopants in PEDOT are exploited to modify the physical properties and enhance gas transport. ClO4−-doped PEDOT exhibits superior performance due to optimized physical structure, leading to increased gas permeance and faradaic efficiency (FE) for CO production during electrocatalytic CO2 reduction. Further optimization of coverage and thickness achieved by adjusting charge density led to an optimal configuration at 33 mC cm−2. This GDL supports various metal electrocatalysts and demonstrates FECO of > 90% for over 150 h at −200 mA cm−2 using a commercial silver electrocatalyst. This work highlights the importance of GDL engineering in enhancing performance and durability for long-term electrocatalytic processes.

Navigating Emotions Through Art

Fri, 25 Apr 2025 00:00:00 GMT

Navigating Emotions Through Art Wu, Christine; Kumar, Ila; Picard, Rosalind In this study, we design and deploy a novel system to examine the safety and efficacy of using a chatbot to conduct aspects of art therapy with youth who have experienced developmental trauma, focusing on supporting emotion identification, processing, and expression. This publication describes phase one, gathering feedback on the system from practicing art therapists (n = 17) and making recommendations for how to evolve such work in beneficial ways to meet the needs of trauma-impacted youth. Our findings highlight the potential value of chatbots for trauma-impacted youth as well as important reflection questions these chatbots should ask. Additionally, the study discusses the risk of harm associated with chatbot interventions, particularly if the conversation brings up negative emotions that the chatbot fails to help process. Finally, we end by presenting a set of practitioner-driven recommendations for chatbot designers who are interested in helping trauma-impacted youth understand and cope with their emotions, leveraging art therapy techniques. CHI EA ’25, Yokohama, Japan

Bridging Tradition and Technology: Human-AI Interface for Exploration and Co-Creation of Classical Dance Heritage

Fri, 25 Apr 2025 00:00:00 GMT

Bridging Tradition and Technology: Human-AI Interface for Exploration and Co-Creation of Classical Dance Heritage Pataranutaporn, Pat; Archiwaranguprok, Chayapatr; Bhongse-tong, Piyaporn; Maes, Pattie; Klunchun, Pichet This paper introduces Text2Tradition, a system designed to bridge the epistemological gap between modern language processing and traditional dance knowledge by translating user-generated prompts into Thai classical dance repertoire. Our system interprets user prompts through the lens of Mae Bot Yai—the 59 foundational movements constituting the vocabulary of traditional Thai dance—and incorporates six choreographic elements that encode centuries of cultural knowledge. This research explores the fertile tension between two knowledge systems: the embodied, culturally-specific wisdom of traditional dance and the data-driven, statistically-derived, and often Western-centric intelligence of LLMs. By mediating between these epistemologies, we highlight the potential of AI-mediated systems not only to preserve traditional forms but also to foster new cultural co-creations, suggesting that these tensions can be harnessed to stimulate cultural dialogue and innovation. CHI EA ’25, Yokohama, Japan

A Write-Optimized Distributed B+Tree Index on Disaggregated Memory

Tue, 15 Apr 2025 00:00:00 GMT

A Write-Optimized Distributed B+Tree Index on Disaggregated Memory Kraska, Tim If it were possible to scale memory independently from compute, it would be feasible to dynamically adjust the amount of memory based on the workload. It would further enable better resource utilization. Consider a dynamic workload regarding the number of queries but with very strict response time requirements, which can only be met, if data is kept in-memory. In this case, the separation of compute and memory would enable to scale the compute with the number of queries while keeping all the data constantly in-memory. This design principle is already used by services such as Google, which keeps the entire web-index in-memory.

Data-Driven AI Avatars for Valuation in Dating Scenarios

Fri, 25 Apr 2025 00:00:00 GMT

Data-Driven AI Avatars for Valuation in Dating Scenarios Baradari, D?nya; Polimetla, Tejaswi; Maes, Pattie Dating applications facilitate partner selection by presenting curated information about potential matches. However, traditional dating profiles often fail to convey the depth of a person’s personality, communication style, and lived experience, leading to inefficiencies in the match-finding process. This work-in-progress study introduces and evaluates two novel, data-driven dating interfaces: (1) a Data Dashboard, which aggregates and visualizes insights from a user’s digital footprint, and (2) an AI Avatar, an interactive, voice-enabled model using personal data to simulate real-world interactions. A user study with nine participants comparing these interfaces against traditional dating profiles reveals that the Data Dashboard enables more accurate personality assessments but imposes a high cognitive load. Meanwhile, the AI Avatar enhances engagement and enjoyability but raises concerns about trust and emotional investment. Our findings highlight the challenge of maintaining authenticity in AI-mediated interactions and bridging the gap between digital and real-life personas. CHI EA ’25, Yokohama, Japan

Cultivating a Supportive Sphere: Designing Technology to Increase Social Support for Foster-Involved Youth

Fri, 02 May 2025 00:00:00 GMT

Cultivating a Supportive Sphere: Designing Technology to Increase Social Support for Foster-Involved Youth Kumar, Ila; Ferguson, Craig; Wu, Jiayi; Picard, Rosalind Approximately 400,000 youth in the US are living in foster care due to experiences with abuse or neglect at home [17]. For multiple reasons, these youth often don’t receive adequate social support from those around them. Despite technology’s potential, very little work has explored how these tools can provide more support to foster-involved youth. To begin to fill this gap, we worked with current and former foster-involved youth to develop the first digital tool that aims to increase social support for this population, creating a novel system in which users complete reflective check-ins in an online community setting. We then conducted a pilot study with 15 current and former foster-involved youth, comparing the effect of using the app for two weeks to two weeks of no intervention. We collected qualitative and quantitative data, which demonstrated that this type of interface can provide youth with types of social support that are often not provided by foster care services and other digital interventions. The paper details the motivation behind the app, the trauma-informed design process, and insights gained from this initial evaluation study. Finally, the paper concludes with recommendations for designing digital tools that effectively provide social support to foster-involved youth.

Allocation Multiplicity: Evaluating the Promises of the Rashomon Set

Mon, 23 Jun 2025 00:00:00 GMT

Allocation Multiplicity: Evaluating the Promises of the Rashomon Set Jain, Shomik; Wang, Margaret; Creel, Kathleen; Wilson, Ashia The Rashomon set of equally-good models promises less discriminatory algorithms, reduced outcome homogenization, and fairer decisions through model ensembles or reconciliation. However, we argue from the perspective of allocation multiplicity that these promises may remain unfulfilled. When there are more qualified candidates than resources available, many different allocations of scarce resources can achieve the same utility. This space of equal-utility allocations may not be faithfully reflected by the Rashomon set, as we show in a case study of healthcare allocations. We attribute these unfulfilled promises to several factors: limitations in empirical methods for sampling from the Rashomon set, the standard practice of deterministically selecting individuals with the lowest risk, and structural biases that cause all equally-good models to view some qualified individuals as inherently risky. FAccT ’25, Athens, Greece

Interactive Sketchpad: A Multimodal Tutoring System for Collaborative, Visual Problem-Solving

Fri, 25 Apr 2025 00:00:00 GMT

Interactive Sketchpad: A Multimodal Tutoring System for Collaborative, Visual Problem-Solving Lee, Jimin; Chen, Steven-Shine; Liang, Paul Pu Humans have long relied on visual aids like sketches and diagrams to support reasoning and problem-solving. Visual tools, like auxiliary lines in geometry or graphs in calculus, are essential for understanding complex ideas. However, many tutoring systems remain text-based, providing feedback only through natural language. Leveraging recent advances in Large Multimodal Models (LMMs), this paper introduces Interactive Sketchpad, a tutoring system that combines language-based explanations with interactive visualizations to enhance learning. Built on a pre-trained LMM, Interactive Sketchpad is fine-tuned to provide step-by-step guidance in both text and visuals, enabling natural multimodal interaction with the student. Accurate and robust diagrams are generated by incorporating code execution into the reasoning process. User studies conducted on math problems such as geometry, calculus, and trigonometry demonstrate that Interactive Sketchpad leads to improved task comprehension, problem-solving accuracy, and engagement levels, highlighting its potential for transforming educational technologies. All code is available at: https://stevenshinechen.github.io/interactivesketchpad/. CHI EA ’25, Yokohama, Japan

Meeting at Crossroads: An exploration of playful listening through a co-creative AI game

Fri, 25 Apr 2025 00:00:00 GMT

Meeting at Crossroads: An exploration of playful listening through a co-creative AI game Lee, Cassandra; Dimitrakopoulou, Dimitra; Roy, Deb Active listening is a well-established cornerstone of empathetic communication and a hallmark of “civic competence”, but is a challenging and energy consuming skill. Games offer a provocative lens to consider how active listening could be explored playfully. In this paper, we present Crossroads, an interactive social game which makes active listening fun by inviting players to co-create images about one another’s personal experiences. Deployed through a tablet-mobile web app, players take turns acting in ‘listener roles’ to generate AI images, and eventually uncover a collective picture along a “crossroad” shaped map. An initial mixed-method evaluation with 36 users demonstrates that players find the experience highly engaging and feel especially heard during in-game conversations. This work contributes a novel game which uses AI to mediate empathetic dialogue, and surfaces questions about the trade-offs of gamifying listening. CHI EA ’25, Yokohama, Japan

OpenMC Interpretation of FNS SINBAD Shielding Benchmark Experiments

Thu, 02 Jan 2025 00:00:00 GMT

OpenMC Interpretation of FNS SINBAD Shielding Benchmark Experiments Ebiwonjumi, Bamidele; Segantin, Stefano; Peterson, Ethan The Fusion Neutron Source (FNS) clean benchmark experiments on tungsten, vanadium, and beryllium assemblies from the SINBAD (Shielding Integral Benchmark Archive and Database) are analyzed to experimentally validate OpenMC (version 0.14.1-dev) fusion neutronics capabilities. The assemblies were irradiated with a 14-MeV deuterium-tritium neutron source. Neutron spectra, photon spectra, reaction rates, gamma heating rates (GHRs), and tritium production rates (TPRs) are compared to measured data in the experimental assemblies and MCNP-6.2 results. In the tungsten case, slight overestimations of the experimental data were observed in the neutron spectra, and the photon spectra agreed well with the experiments. Most of the GHRs agreed with the measured data within the range of experimental uncertainty in the tungsten and vanadium assemblies. In the vanadium assembly, the calculated neutron spectra underestimated the experiments in the low energy region while the photon spectra were well calculated when compared to experiments. The most noticeable discrepancies with experimental data in the gamma heating were observed at detector positions closest to the source. For the reaction rates, notable discrepancies with experimental data were seen at the front and rear of the assemblies. Compared to experiments, the OpenMC neutron spectra were well predicted in the beryllium assembly, whereas the calculated fission reaction rate and TPRs overestimated the experiments, an observation similar to that which has been reported by other authors. The average, overall calculation-to-experiment ratio (C/E) over nine TPR and seven GHR measurements were 1.03 ± 0.20 and 0.95 ± 0.14, respectively. In the case of verification, the OpenMC results of the benchmark calculations indicated comparable accuracy to MCNP-6.2. In general, the validation exercise showed that OpenMC can be used to analyze the fusion neutronics shielding benchmark problems.

SoK: Acoustic Side Channels

Wed, 26 Nov 2025 00:00:00 GMT

SoK: Acoustic Side Channels Wang, Ping; Nagaraja, Shishir; Bourquard, Aur?lien; Gao, Haichang; Yan, Jeff Acoustic side channels (ASCs) have been discovered for several decades, highlighting the tangible security risks posed by unintended sound emissions from computing and electronic systems. Their existence has drawn considerable attention from researchers, driving rapid progress in both attack methodologies and defense mechanisms across a wide range of scenarios. In this paper, we provide a state-of-the-art analysis of ASCs, covering all the significant academic research in the area. First, we clarify existing ambiguities and conceptual confusion, proposing a clear definition of ASC. Second, we analyse the characteristics of known ASCs, discuss their security implications, and propose the first taxonomy. Next, we summarize attack techniques, discuss countermeasures, and identify areas for future research. We also link side channels and inverse problems, two fields that appear to be completely isolated from each other but have deep connections.

Umm Kamel’s Affair: How Infidelity Liberated the Night Sky in Jabal ‘Amil

Tue, 02 Jan 2024 00:00:00 GMT

Umm Kamel’s Affair: How Infidelity Liberated the Night Sky in Jabal ‘Amil Nahleh, Mohamad Weakened by the expansion of several imperial and colonial projects, the inhabitants of Jabal ‘Amil survived as second-class citizens, severed from the urban expression of Lebanese nationalism, and having to formulate their identity amid countless transgressions on their scholarship and literary production. It is thus in the spectacles of the universe and the mysteries of the cosmos that they inscribed fragments of their oral legacy, turning the night sky into an archive that no empire could burn or colonize. And yet it is light pollution, leaking from the same cities they were once forced to nourish, that quickly established itself as the main transgressor, clearing the faintest stories in their celestial library. Although distant manifestations of Islamic cosmology could no longer animate their rural nights, new alterations in the sky after dark, no matter how violent, have proven worthy carri-ers of their modern myths and legends. And it is onto the loudest object in their polluted sky, the Israeli reconnaissance drone IAI Searcher MK, that they grafted the tale of their legendary matriarch Umm Kamel. I argue that Umm Kamel’s physical and symbolic ascent into the sky was orchestrated by a modern generation of ‘Amilis whose infidelity to the celestial stories authored by their ancestors fortified their ability to transform the combined pressures of pollution and colonization. United by their efforts to forge new imaginaries around a starless night, they invite reflection on the possibility (and responsibility) of confronting the sky we have together inherited rather than lamenting the one we have lost. In tracing Umm Kamel’s transformation from figure to constellation, I contend that their cosmic interventions set the stage for new alliances between design and darkness, and ultimately, for a more expanded imagination of night design, particularly within the context of the climate crisis.

Ophthalmology Optical Coherence Tomography Databases for Artificial Intelligence Algorithm: A Review

Tue, 02 Apr 2024 00:00:00 GMT

Ophthalmology Optical Coherence Tomography Databases for Artificial Intelligence Algorithm: A Review Restrepo, David; Quion, Justin Michael; Do Carmo Novaes, Frederico; Azevedo Costa, Iago Diogenes; Vasquez, Constanza; Bautista, Alyssa Nicole; Quiminiano, Ellaine; Lim, Patricia Abigail; Mwavu, Roger; Celi, Leo Anthony; Nakayama, Luis Filipe BACKGROUND: Imaging plays a pivotal role in eye assessment. With the introduction of advanced machine learning and artificial intelligence (AI), the focus has shifted to imaging datasets in ophthalmology. While disparities and health inequalities hidden within data are well-documented, the ophthalmology field faces specific challenges to the creation and maintenance of datasets. Optical Coherence Tomography (OCT) is useful for the diagnosis and monitoring of retinal pathologies, making it valuable for AI applications. This review aims to identify and compare the landscape of publicly available optical coherence tomography databases for AI applications. METHODS: We conducted a literature review on OCT and AI articles with publicly accessible datasets, using PubMed, Scopus, and Web of Science databases. The review retrieved 183 articles, and after full-text analysis, 50 articles were included. From the included articles were identified 8 publicly available OCT datasets, focusing on patient demographics and clinical details for thorough assessment and comparison. RESULTS: The resulting datasets encompass 154,313 images collected from Spectralis, Cirrus HD, Topcon 3D, and Bioptigen devices. These datasets included normal exams, age-related macular degeneration, and diabetic maculopathy, among others. Comprehensive demographic information is available in one dataset and the USA is the most represented population. DISCUSSION: Current publicly available OCT databases for AI applications exhibit limitations, stemming from their non-representative nature and the lack of comprehensive demographic information. Limited datasets hamper research and equitable AI development. To promote equitable AI algorithmic development in ophthalmology, there is a need for the creation and dissemination of more representative datasets.

Market Design for Capacity Sharing in Networks

Fri, 21 Nov 2025 00:00:00 GMT

Market Design for Capacity Sharing in Networks Amin, Saurabh; Jaillet, Patrick; Pulyassary, Haripriya; Wu, Manxi We study a market mechanism that sets edge prices to incentivize strategic agents to efficiently share limited network capacity. In this market, agents form coalitions, with each coalition sharing a unit capacity of a selected route and making payments to cover edge prices. Our focus is on the existence and computation of market equilibrium, where challenges arise from the interdependence between coalition formation among strategic agents with heterogeneous preferences and route selection that induces a network flow under integral capacity constraints. To address this interplay between coalition formation and network capacity utilization, we introduce a novel approach based on combinatorial auction theory and network flow theory. We establish sufficient conditions on the network topology and agents' preferences that guarantee both the existence and polynomial-time computation of a market equilibrium. Additionally, we identify a particular market equilibrium that maximizes utilities for all agents and is equivalent to the classical Vickrey-Clarke-Groves mechanism. Furthermore, we extend our results to multi-period settings and general networks, showing that when the sufficient conditions are not met, an equilibrium may still exist but requires more complex, path-based pricing mechanisms that set differentiated prices based on agents' preference parameters.

Forage: Understanding RAG-based Sensemaking for Community Conversations

Fri, 25 Apr 2025 00:00:00 GMT

Forage: Understanding RAG-based Sensemaking for Community Conversations Schroeder, Hope; Beeferman, Doug; Detwiller, Maya; Dimitrakopoulou, Dimitra; Roy, Deb We introduce Forage, a RAG-based and LLM-augmented search engine, which we apply to the problem of sensemaking for community conversation data. We report on formative user studies introducing Forage to two distinct user groups: NPR journalists and municipal staff in the city of Durham, North Carolina. We taxonomize the query types users make with the tool, use cases that include synthesizing insights across conversations and finding content about a particular subject. We find that users tend to gravitate towards using the system for synthesis more than for pure search. We report on challenges and opportunities surfaced by performing sensemaking with an open-ended interface like Forage, such as the benefits of finding content quickly, but also the challenges users face interacting with a system in natural language. Insights from this formative study confirm the usefulness of Forage for sensemaking, but also make follow-up work, such as systematically evaluating system performance and developing appropriate design, urgent. CHI EA ’25, Yokohama, Japan

Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation

Sun, 01 Sep 2024 00:00:00 GMT

Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation Jackson, Ilya; Ivanov, Dmitry; Dolgui, Alexandre; Namdar, Jafar This research examines the transformative potential of artificial intelligence (AI) in general and Generative AI (GAI) in particular in supply chain and operations management (SCOM). Through the lens of the resource-based view and based on key AI capabilities such as learning, perception, prediction, interaction, adaptation, and reasoning, we explore how AI and GAI can impact 13 distinct SCOM decision-making areas. These areas include but are not limited to demand forecasting, inventory management, supply chain design, and risk management. With its outcomes, this study provides a comprehensive understanding of AI and GAI's functionality and applications in the SCOM context, offering a practical framework for both practitioners and researchers. The proposed framework systematically identifies where and how AI and GAI can be applied in SCOM, focussing on decision-making enhancement, process optimisation, investment prioritisation, and skills development. Managers can use it as a guidance to evaluate their operational processes and identify areas where AI and GAI can deliver improved efficiency, accuracy, resilience, and overall effectiveness. The research underscores that AI and GAI, with their multifaceted capabilities and applications, open a revolutionary potential and substantial implications for future SCOM practices, innovations, and research.

Remote Direct Code Execution

Mon, 17 Nov 2025 00:00:00 GMT

Remote Direct Code Execution Huang, Yibo; Qiu, Yiming; Ding, Daqian; Kon, Patrick Tser Jern; Zhang, Yiwen; Mao, Yuzhou; Bhatnagar, Archit; Chowdhury, Mosharaf; Devadas, Srinivas; Xing, Jiarong; Chen, Ang We propose remote direct code execution (RDX), which elevates the power of RDMA from memory access to code execution. We target runtime extension frameworks such as Wasm filters, BPF programs, and UDF functions, where RDX enables an agentless architecture that unlocks capabilities such as fast extension injection, update consistency guarantees, and minimal resource contention. We outline the roadmap for RDX around a new CodeFlow abstraction, encompassing programming remote extensions, exposing management stubs, remotely validating and JIT compiling code, seamlessly linking code to local context, managing remote extension state, and synchronizing code to targets. The case studies and initial results demonstrate the feasibility of RDX and its potential to spark the next wave of RDMA innovations. HotNets ’25, College Park, MD, USA

User Adoption of Intelligent Environments: A Review of Technology Adoption Models, Challenges, and Prospects

Fri, 16 Feb 2024 00:00:00 GMT

User Adoption of Intelligent Environments: A Review of Technology Adoption Models, Challenges, and Prospects FakhrHosseini, Shabnam; Chan, Kathryn; Lee, Chaiwoo; Jeon, Myounghoon; Son, Heesuk; Rudnik, John; Coughlin, Joseph Recent technological advancements have enabled the development of smarter (more automated) and more intelligent (adaptable) environments. To understand what factors lead users to reject or adopt Intelligent Environments (IEs), we reviewed nine prominent technology adoption theories. We conducted a literature review to investigate the acceptance and adoption of different types of IEs. We found that perceived usefulness, ease of use, perceived control or self-efficacy, affect and enjoyment, and perceived risks are the common factors across the studies explaining the adoption of IEs. However, shortcomings in the design and methods of the reviewed studies present major concerns in the generalizability and application of existing theories to emerging IEs. We identify eight lacunae in the existing literature and propose a new conceptual model for explaining the adoption of IEs. Through this study, we contribute to the formulation of the theoretical background for the successful introduction of IEs and their integration into users’ everyday life.

Safe and Secure Control of Connected and Automated Vehicles: An Event-Triggered Control Approach using Trust-Aware Robust Control Barrier Functions

Tue, 18 Nov 2025 00:00:00 GMT

Safe and Secure Control of Connected and Automated Vehicles: An Event-Triggered Control Approach using Trust-Aware Robust Control Barrier Functions Ahmad, H M SABBIR; Sabouni, Ehsan; Xiao, Wei; Cassandras, Christos; Li, Wenchao We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to safely navigate through a conflict area (e.g., traffic intersections, merging roadways, roundabouts). Previous studies have shown that such a network can be targeted by adversarial attacks causing traffic jams or safety violations resulting in collisions. We focus on attacks targeting the V2X communication network used to share vehicle data and consider as well uncertainties due to noise in sensor measurements and communication channels. To combat these, motivated by recent work on the safe control of CAVs, we propose a trust-aware robust event-triggered decentralized control and coordination framework that can provably guarantee safety. We maintain a trust metric for each vehicle in the network computed based on their behavior and used to balance the tradeoff between conservativeness (when deeming every vehicle as untrustworthy) while guaranteeing safety and performance. It is important to highlight that our framework is invariant to the specific choice of the trust framework. Based on this framework, we propose an attack detection and mitigation scheme which has twofold benefits: (i) the trust framework is immune to false positives, and (ii) it provably guarantees safety against false positive cases which may arise from a poor choice of trust framework. We use extensive simulations in SUMO and CARLA to validate the theoretical guarantees and demonstrate the efficacy of our proposed scheme to detect and mitigate adversarial attacks. The code for the simulated scenarios can be found in this \href{https://github.com/SabbirAhmad26/Trust_based_CBF}{\textit{\underline{link}}}.

Three-dimensional, soft magnetic-cored solenoids via multi-material extrusion

Tue, 20 Feb 2024 00:00:00 GMT

Three-dimensional, soft magnetic-cored solenoids via multi-material extrusion Cañada, Jorge; Kim, Hyeonseok; Velásquez-García, Luis Fernando This study reports fully 3D-printed, three-dimensional, soft magnetic-cored solenoids that generate three times the largest magnetic fields previously reported from 3D-printed solenoids. The devices are fabricated on a customised, multi-material 3D printer that can extrude both filaments and pellets. Three different kinds of materials are employed to manufacture the reported soft magnetic-cored solenoids: pure PLA (dielectric portions), PLA doped with copper particles (electrically conductive structures), and nylon or PLA doped with metallic particles (soft magnetic cores). Via manufacturing optimisation, the reported devices are 33% smaller and can withstand about twice the current, generating three times more magnetic field. The 3D-printed solenoids generate Gauss-level magnetic fields while drawing tens-of-milliamps currents and can be readily used to implement fully 3D-printed induction sensors. The results of this work extend the state of the art in 3D-printed electronics, enabling the creation of more complex and capable solenoids for in-situ manufactured and in-space manufactured electromagnetic systems.

The Churns and Turns of HCI: Which CHI Papers Make the Most Impact in an Ever-growing Sea of HCI Publications

Fri, 25 Apr 2025 00:00:00 GMT

The Churns and Turns of HCI: Which CHI Papers Make the Most Impact in an Ever-growing Sea of HCI Publications Kaltenhauser, Annika; Sch?ning, Johannes; Churchill, Elizabeth; Ishii, Hiroshi; Mekler, Elisa; Shneiderman, Ben The ACM Conference on Human Factors in Computing Systems (CHI) is the premier venue for research in Human-Computer Interaction (HCI). 11,290 full papers have been published and collectively cited almost one million times. Highly cited papers undoubtedly represent influential work, affecting the creation of review standards and conference submission and acceptance practices within and beyond CHI. However, the factors contributing to high citation counts and what constitutes a highly cited CHI paper remain largely unclear. In this panel discussion, we will engage the CHI community in exploring the relationship between paper characteristics, citation numbers, and effective impact on HCI as a discipline, and on HCI as an influential endeavour in technology design and development. To ground this discussion, we present findings from a literature review of the 100 most cited CHI full papers, looking at past and present fields and subfields of influence. We will also share insights from HCI experts. Our goals are to shed light on the meaning of impactful work at CHI and in HCI more broadly, to reflect on key trends in HCI over the years, and to discuss themes that have driven pivotal shifts in HCI research. We will lead the conversation toward a deeper understanding of citation practices, the role of citations in focusing and driving HCI research, and the implications of citation when it comes to shaping what is considered impactful HCI. CHI EA ’25, Yokohama, Japan

Safeguards and Security for High-Burnup TRISO Pebble Bed Spent Fuel and Reactors

Fri, 02 Aug 2024 00:00:00 GMT

Safeguards and Security for High-Burnup TRISO Pebble Bed Spent Fuel and Reactors Forsberg, Charles; Kadak, Andrew Several high-temperature thermal neutron–spectrum pebble bed reactors are being commercialized. China has started up two helium-cooled pebble bed high-temperature reactors. In the United States, the X-Energy helium-cooled and the Kairos Power salt-cooled pebble bed high-temperature reactors will produce spent nuclear fuel (SNF) with burnups exceeding 150 000 MWd per tonne. The reactor fuel in each case consists of small spherical graphite pebbles (4 to 6 cm in diameter) containing thousands of small TRISO (microspheric tri-structural isotropic) fuel particles embedded in the fuel of zone these pebbles. The unique isotopic, chemical, and physical characteristics of this high-burnup SNF create a technical case to eliminate safeguards based on the low risk for use in nuclear weapons, while maintaining safeguards in terms of risk for use in radiological weapons. These safeguards could be reduced to the simple counting and monitoring of pebbles in storage. Alternatively, there is the option to create a special category with reduced requirements for this SNF in storage, transport, and disposal. No safeguards would be required for a repository with only this type of SNF. Reactor safeguards are required for fresh fuel, partly burnt fuel, and to identify unconventional pebbles with depleted uranium or other materials that might be used to create weapons-useable materials.

Constrained Tabular Diffusion for Finance

Fri, 14 Nov 2025 00:00:00 GMT

Constrained Tabular Diffusion for Finance Cardei, Michael; Munoz, Jose; Barrera, Oscar; Chandrahas, Shreyas; Saha, Partha Generative models in finance face the dual challenge of producing realistic data while satisfying strict regulatory and economic objectives, a requirement that standard tabular diffusion models cannot provide. To address this difficulty, we introduce Constrained Tabular Diffusion for Finance (CTDF), a novel integration of sampling-time feasibility operations with mixed-type tabular diffusion in financial applications. By incorporating a training-free feasibility operator into the reverse‑diffusion sampling loop, CTDF enforces hard constraints for applications such as simulation, legal compliance, and extrapolation. Extensive experiments on large-scale financial datasets demonstrate zero constraint violations and improvement in scarce data utility. CTDF establishes a robust method for generating trustworthy and compliant synthetic data, opening new avenues for rigorous generative modeling and analysis in the financial domain. 6th ACM International Conference on AI in Finance (ICAIF ’25), November 15–18, 2025, Singapore, Singapore

A Bayesian sampling framework for constrained optimisation of build layouts in additive manufacturing

Sat, 17 Aug 2024 00:00:00 GMT

A Bayesian sampling framework for constrained optimisation of build layouts in additive manufacturing Kim, Suh In; Gee, Kaitlyn; Hart, A John In additive manufacturing processes such as laser powder bed fusion, the build orientation and packing of components affect the required support structures, the number of parts in each build, and the surface roughness of the printed parts, among other factors. Maximising the packing density while minimising the build height can increase effective machine utilisation and decrease per-part cost. Yet, the build layout optimisation problem is highly nonlinear and difficult to solve using human intuition, so a systematic algorithm approach is required. Here, we present and demonstrate a voxel-based analysis method with Bayesian optimisation for determining component build orientation in additive manufacturing. We introduce selected case studies incorporating exemplary process attributes of laser powder bed fusion, including the determination of orientation and packing configurations based on support removal and tool-accessibility constraints.

A rapid simple point-of-care assay for the detection of SARS-CoV-2 neutralizing antibodies

Thu, 11 Nov 2021 00:00:00 GMT

A rapid simple point-of-care assay for the detection of SARS-CoV-2 neutralizing antibodies Kongsuphol, Patthara; Jia, Huan; Cheng, Hoi Lok; Gu, Yue; Shunmuganathan, Bhuvaneshwari DO; Chen, Ming Wei; Lim, Sing Mei; Ng, Say Yong; Tambyah, Paul Ananth; Nasir, Haziq; Gao, Xiaohong; Tay, Dousabel; Kim, Seunghyeon; Gupta, Rashi; Qian, Xinlei; Kozma, Mary M; Purushotorman, Kiren; McBee, Megan E; MacAry, Paul A; Sikes, Hadley D; Preiser, Peter R Background Neutralizing antibodies (NAbs) prevent pathogens from infecting host cells. Detection of SARS-CoV-2 NAbs is critical to evaluate herd immunity and monitor vaccine efficacy against SARS-CoV-2, the virus that causes COVID-19. All currently available NAb tests are lab-based and time-intensive. Method We develop a 10 min cellulose pull-down test to detect NAbs against SARS-CoV-2 from human plasma. The test evaluates the ability of antibodies to disrupt ACE2 receptor— RBD complex formation. The simple, portable, and rapid testing process relies on two key technologies: (i) the vertical-flow paper-based assay format and (ii) the rapid interaction of cellulose binding domain to cellulose paper. Results Here we show the construction of a cellulose-based vertical-flow test. The developed test gives above 80% sensitivity and specificity and up to 93% accuracy as compared to two current lab-based methods using COVID-19 convalescent plasma. Conclusions A rapid 10 min cellulose based test has been developed for detection of NAb against SARS-CoV-2. The test demonstrates comparable performance to the lab-based tests and can be used at Point-of-Care. Importantly, the approach used for this test can be easily extended to test RBD variants or to evaluate NAbs against other pathogens.

Developing a SARS-CoV-2 Antigen Test Using Engineered Affinity Proteins

Wed, 11 Aug 2021 00:00:00 GMT

Developing a SARS-CoV-2 Antigen Test Using Engineered Affinity Proteins Kim, Seunghyeon; Yee, Emma; Miller, Eric A; Hao, Yining; Tay, Dousabel MY; Sung, Ki-Joo; Jia, Huan; Johnson, Joseph M; Saeed, Mohsan; Mace, Charles R; Yüksel Yurt, Deniz; Sikes, Hadley D The ongoing COVID-19 pandemic has clearly established how vital rapid, widely accessible diagnostic tests are in controlling infectious diseases and how difficult and slow it is to scale existing technologies. Here, we demonstrate the use of the rapid affinity pair identification via directed selection (RAPIDS) method to discover multiple affinity pairs for SARS-CoV-2 nucleocapsid protein (N-protein), a biomarker of COVID-19, from in vitro libraries in 10 weeks. The pair with the highest biomarker sensitivity was then integrated into a 10 min, vertical-flow cellulose paper test. Notably, the as-identified affinity proteins were compatible with a roll-to-roll printing process for large-scale manufacturing of tests. The test achieved 40 and 80 pM limits of detection in 1× phosphate-buffered saline (mock swab) and saliva matrices spiked with cell-culture-generated SARS-CoV-2 viruses and is also capable of detection of N-protein from characterized clinical swab samples. Hence, this work paves the way toward the mass production of cellulose paper-based assays which can address the shortages faced due to dependence on nitrocellulose and current manufacturing techniques. Further, the results reported herein indicate the promise of RAPIDS and engineered binder proteins for the timely and flexible development of clinically relevant diagnostic tests in response to emerging infectious diseases.

Archaeology of Self: Reflexivity in Data Activism to Address Systemic Injustices

Tue, 04 Nov 2025 00:00:00 GMT

Archaeology of Self: Reflexivity in Data Activism to Address Systemic Injustices Walker, Raechel; Cruse, Brady; Cora, Aisha; Rogers, Kantwon; D'Ignazio, Catherine; Brion-Meisels, Gretchen; Breazeal, Cynthia Traditional data science education often neglects the importance of identity and sociopolitical context—especially for African American students whose lived experiences and cultural insights are essential for building justice centered technologies. This paper presents findings from the Data Activism Program, which integrated Dr. Yolanda Sealey-Ruiz’s Archaeology of Self™ framework to foster critical self-reflection and racial identity development among African American high school and college students. Through technical training in data science, art-based learning, and partnerships with social justice organizations, students engaged in reflexive practices that positioned them as active agents in challenging systemic oppression. Interviews reveal that the Archaeology of Self™ deepened students’ reflexivity skills and strengthened their sound racial identity, enabling them to interrogate bias within themselves and the data science process. We argue that embedding frameworks such as the Archaeology of Self™ into algorithmic design offers a concrete, transferable method for operationalizing reflexivity in data science and AI. This study contributes to the AI and data science community by offering actionable strategies to center identity and power in AI development. EAAMO ’25, Pittsburgh, PA, USA

Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs

Mon, 10 Nov 2025 00:00:00 GMT

Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs Lee, Yongjae; Mehrasa, Nazanin; Choi, Chanyeol; Chen, Chung-Chi; Mehta, Dhagash; Zohren, Stefan; Kim, Yoon; Lee, Chulheum; Lee, Yeonhee; Oh, Eunsook The finance sector is seeing a rapid increase in the application of machine learning and AI, with Large Language Models (LLMs), ESG (Environmental, Social, and Governance) investing, and AI Safety significantly reshaping the field. This workshop focuses on how these advancements intersect with core financial AI applications. We will foster interdisciplinary discussion on applying LLMs to finance, addressing challenges in multilingual and non-English markets like Korea. The event will also highlight the integration of ESG signals into algorithmic decision-making and explore AI Safety, emphasizing reliability, fairness, and explainability for AI systems in regulated financial environments. By bringing together experts from academia, industry, and regulatory bodies, the workshop aims to stimulate discussions on practical issues, ethical dilemmas, and cutting-edge research shaping financial AI's future. We welcome submissions that combine technical rigor with societal relevance in AI-driven financial decisions. CIKM ’25, Seoul, Republic of Korea

Design and Fabrication of Hybrid Functional Identities for Mechanical Elements

Fri, 25 Apr 2025 00:00:00 GMT

Design and Fabrication of Hybrid Functional Identities for Mechanical Elements AlAlawi, Marwa My PhD research explores the simultaneous integration of mechanical and electrical functionalities in mechanical components such as gears, linkages, and springs, which I define as "hybrid functional identities." The focus is on transforming these components into non-intrusive sensors and active elements that maintain structural integrity while providing electrical capabilities like sensing, energy harvesting, and communication. I establish a framework for hybrid functional identities by examining common mechanical elements and their associated motions—rotational, linear, and reciprocal—along with force-based interactions like stretching, compression, and torsion. This analysis identifies essential electrical functionalities that complement these mechanical behaviors. Building on this foundation, I investigate modular mechanical building blocks that support diverse mechanical and electrical interaction primitives using a unified geometric structure. Ultimately, I aim to create an interconnected system where hybrid mechanical-electrical components function autonomously and communicate through an embedded wireless network. CHI EA ’25, Yokohama, Japan

Connecting through Comics: Design and Evaluation of Cube, an Arts-Based Digital Platform for Trauma-Impacted Youth

Fri, 02 May 2025 00:00:00 GMT

Connecting through Comics: Design and Evaluation of Cube, an Arts-Based Digital Platform for Trauma-Impacted Youth Kumar, Ila; Shen, Jocelyn; Ferguson, Craig; Picard, Rosalind This paper explores the design, development and evaluation of a digital platform that aims to assist young people who have experienced trauma in understanding and expressing their emotions and fostering social connections. Integrating principles from expressive arts and narrative-based therapies, we collaborate with lived experts to iteratively design a novel, user-centered digital tool for young people to create and share comics that represent their experiences. Specifically, we conduct a series of nine workshops with N=54 trauma-impacted youth and young adults to test and refine our tool, beginning with three workshops using low-fidelity prototypes, followed by six workshops with Cube, a web version of the tool. A qualitative analysis of workshop feedback and empathic relations analysis of artifacts provides valuable insights into the usability and potential impact of the tool, as well as the specific needs of young people who have experienced trauma. Our findings suggest that the integration of expressive and narrative therapy principles into Cube can offer a unique avenue for trauma-impacted young people to process their experiences, more easily communicate their emotions, and connect with supportive communities. We end by presenting implications for the design of social technologies that aim to support the emotional well-being and social integration of youth and young adults who have faced trauma.

The Structure of Cross-National Collaboration in Open-Source Software Development

Mon, 10 Nov 2025 00:00:00 GMT

The Structure of Cross-National Collaboration in Open-Source Software Development Xu, Henry; Yu, Katy; He, Hao; Fang, Hongbo; Vasilescu, Bogdan; Park, Patrick Open-source software (OSS) development platforms, such as GitHub, expand the potential for cross-national collaboration among developers by lowering the geographic, temporal, and coordination barriers that limited software innovation in the past. However, research has shown that the technological affordances that facilitate cross-national collaboration do not uniformly benefit all countries. Using the GitHub Innovation Graph dataset, which aggregates the complete cross-country collaborations among the entire population of GitHub developers, we present quantitative evidence of deep-seated religious and cultural affinities, shared colonial histories, and geopolitical factors structuring the collaborations between non-U.S. country pairs that become visible when the overarching dominance of the U.S. is removed from the data. This study highlights the opportunities to develop decentralizing strategies to facilitate new collaborations between developers in non-U.S. countries, thereby fostering the development of novel, innovative solutions. More generally, this study also underscores the importance of contextualizing user behavior and knowledge management in information systems with long-term, macro-social conditions in which these systems are inextricably embedded. CIKM ’25, Seoul, Republic of Korea

Partition–diffusion–reaction bounds for thin-film membrane formation kinetics

Sat, 15 Nov 2025 00:00:00 GMT

Partition–diffusion–reaction bounds for thin-film membrane formation kinetics Deshmukh, Akshay; Elimelech, Menachem; Lienhard, John H. New membrane chemistries and structures have rapidly developed over the last ten years, driven by applications ranging from critical metals separations and carbon capture to highly chlorine-resistant reverse-osmosis membranes. The thin selective layer at the heart of reverse osmosis and nanofiltration membranes is typically fabricated using interfacial synthesis, with multifunctional aqueous-phase monomers and organicphase monomers. Here, we develop a physics-based model of partition, diffusion, and reaction dynamics during the early stages of interfacial synthesis. These processes critically impact membrane structure and performance. By solving the resulting partial differential equations numerically and with analytical approximations, we demonstrate that the planar reaction rate is initially limited by the partitioning and diffusion of the aqueous-phase reactant into the organic phase. Later, finite reactant availability and aqueous-phase diffusion become limiting. Through a combination of nondimensionalization, parameter mapping, and property prediction, we develop a framework that spans a wide parameter space in reactant chemistry, solvent and support layer choice, and initial reactant concentrations. We demonstrate that the planar reaction rate and dynamics are strongly affected by the partition coefficient of the aqueous reactant, which varies rapidly with changes in reactant and solvent chemistry. The influence of diffusion variations is more limited. This tractable, physics-based model enables the rapid quantification of monomer and solvent impact on interfacial synthesis, which is essential for the rational development of new high-performance thin-film composite membranes.

Finger stick blood test to assess postvaccination SARS-CoV-2 neutralizing antibody response against variants

Sat, 22 Jan 2022 00:00:00 GMT

Finger stick blood test to assess postvaccination SARS-CoV-2 neutralizing antibody response against variants Lim, Sing Mei; Cheng, Hoi Lok; Jia, Huan; Kongsuphol, Patthara; D/O Shunmuganathan, Bhuvaneshwari; Chen, Ming Wei; Ng, Say Yong; Gao, Xiaohong; Turaga, Shuvan Prashant; Heussler, Sascha P; Somani, Jyoti; Sengupta, Sharmila; Tay, Dousabel MY; McBee, Megan E; Young, Barnaby E; MacAry, Paul A; Sikes, Hadley D; Preiser, Peter R There is clinical need for a quantifiable point-of-care (PoC) SARS-CoV-2 neutralizing antibody (nAb) test that is adaptable with the pandemic's changing landscape. Here, we present a rapid and semi-quantitative nAb test that uses finger stick or venous blood to assess the nAb response of vaccinated population against wild-type (WT), alpha, beta, gamma, and delta variant RBDs. It captures a clinically relevant range of nAb levels, and effectively differentiates prevaccination, post first dose, and post second dose vaccination samples within 10 min. The data observed against alpha, beta, gamma, and delta variants agrees with published results evaluated in established serology tests. Finally, our test revealed a substantial reduction in nAb level for beta, gamma, and delta variants between early BNT162b2 vaccination group (within 3 months) and later vaccination group (post 3 months). This test is highly suited for PoC settings and provides an insightful nAb response in a postvaccinated population.

Rapid Evaluation of Vaccine Booster Effectiveness against SARS-CoV-2 Variants

Wed, 07 Sep 2022 00:00:00 GMT

Rapid Evaluation of Vaccine Booster Effectiveness against SARS-CoV-2 Variants Cheng, Hoi Lok; Lim, Sing Mei; Jia, Huan; Chen, Ming Wei; Ng, Say Yong; Gao, Xiaohong; Somani, Jyoti; Sengupta, Sharmila; Tay, Dousabel MY; Chua, Patrina WL; R., Abirami; Ling, Sharon YH; McBee, Megan E; Young, Barnaby E; Sikes, Hadley D; Preiser, Peter R As the COVID-19 pandemic continues, countries around the world are switching toward vaccinations and boosters to combat the pandemic. However, waning immunity against SARS-CoV-2 wild-type (WT) and variants have been widely reported. Booster vaccinations have shown to be able to increase immunological protection against new variants; however, the protection observed appears to decrease quickly over time suggesting a second booster shot may be appropriate. Moreover, heterogeneity and waning of the immune response at the individual level was observed suggesting a more personalized vaccination approach should be considered. To evaluate such a personalized strategy, it is important to have the ability to rapidly evaluate the level of neutralizing antibody (nAbs) response against variants at the individual level and ideally at a point of care setting. Here, we applied the recently developed cellulose pulled-down virus neutralization test (cpVNT) to rapidly assess individual nAb levels to WT and variants of concerns in response to booster vaccination. Our findings confirmed significant heterogeneity of nAb responses against a panel of SARS-CoV-2 variants, and indicated a strong increase in nAb response against variants of concern (VOCs) upon booster vaccination. For instance, the nAb response against current predominant omicron variant was observed with medians of 88.1% (n = 6, 95% CI = 73.2% to 96.2%) within 1-month postbooster and 70.7% (n = 22, 95% CI = 66.4% to 81.8%) 3 months postbooster. Our data show a point of care (POC) test focusing on nAb response levels against VOCs can guide decisions on the potential need for booster vaccinations at individual level. Importantly, it also suggests the current booster vaccines only give a transient protective response against some VOC and new more targeted formulations of a booster vaccine against specific VOC may need to be developed in the future. IMPORTANCE Vaccination against SARS-CoV-2 induces protection through production of neutralization antibodies (nAb). The level of nAb is a major indicator of immunity against SARS-CoV-2 infection. We developed a rapid point-of-care test that can monitor the nAb level from a drop of finger stick blood. Here, we have implemented the test to monitor individual nAb level against wild-type and variants of SARS-CoV-2 at various time points of vaccination, including post-second-dose vaccination and postbooster vaccination. Huge diversity of nAb levels were observed among individuals as well as increment in nAb levels especially against Omicron variant after booster vaccination. This study evaluated the performance of this point-of-care test for personalized nAb response tracking. It verifies the potential of using a rapid nAb test to guide future vaccination regimens at both the individual and population level.

Tumor-localized catalases can fail to alter tumor growth and transcriptional profiles in subcutaneous syngeneic mouse tumor models

Tue, 01 Aug 2023 00:00:00 GMT

Tumor-localized catalases can fail to alter tumor growth and transcriptional profiles in subcutaneous syngeneic mouse tumor models Sheen, Allison; Agarwal, Yash; Cheah, Keith M; Cowles, Sarah C; Stinson, Jordan A; Palmeri, Joseph R; Sikes, Hadley D; Wittrup, K Dane Catalase is an antioxidant enzyme that catalyzes the rapid conversion of hydrogen peroxide to water and oxygen. Use of catalase as a cancer therapeutic has been proposed to reduce oxidative stress and hypoxia in the tumor microenvironment, both activities which are hypothesized to reduce tumor growth. Furthermore, exposing murine tumors to exogenous catalase was previously reported to have therapeutic benefit. We studied the therapeutic effect of tumor-localized catalases with the aim to further elucidate the mechanism of action. To do this, we engineered two approaches to maximize intratumoral catalase exposure: 1) an injected extracellular catalase with enhanced tumor retention, and 2) tumor cell lines that over-express intracellular catalase. Both approaches were characterized for functionality and tested for therapeutic efficacy and mechanism in 4T1 and CT26 murine syngeneic tumor models. The injected catalase was confirmed to have enzyme activity >30,000 U/mg and was retained at the injection site for more than one week in vivo. The engineered cell lines exhibited increased catalase activity and antioxidant capacity, with catalase over-expression that was maintained for at least one week after gene expression was induced in vivo. We did not observe a significant difference in tumor growth or survival between catalase-treated and untreated mice when either approach was used. Finally, bulk RNA sequencing of tumors was performed, comparing the gene expression of catalase-treated and untreated tumors. Gene expression analysis revealed very few differentially expressed genes as a result of exposure to catalase and notably, we did not observe changes consistent with an altered state of hypoxia or oxidative stress. In conclusion, we observe that sustained intratumoral catalase neither has therapeutic benefit nor triggers significant differential expression of genes associated with the anticipated therapeutic mechanism in the subcutaneous syngeneic tumor models used. Given the lack of effect observed, we propose that further development of catalase as a cancer therapeutic should take these findings into consideration.

Optical Detection of Interleukin-6 Using Liquid Janus Emulsions Using Hyperthermophilic Affinity Proteins

Thu, 22 Aug 2024 00:00:00 GMT

Optical Detection of Interleukin-6 Using Liquid Janus Emulsions Using Hyperthermophilic Affinity Proteins Chen, Michelle; Corless, Elliot I; Engelward, Bevin P; Swager, Timothy M; Sikes, Hadley D. When equal volumes of two immiscible liquids are mixed (e.g., a hydrocarbon and a fluorocarbon), Janus droplets can form in an aqueous solution. In a gravity-aligned Janus droplet, the boundary between the two phases is flat and thus optically transparent when viewed from above. When tipped due to interactions with an analyte (i.e., agglutination), the resulting change in refraction and reflection yields an optical signal that can be detected and quantified. This study reports the detection and quantitation of interleukin-6 (IL-6) using emulsions functionalized at the hydrocarbon:aqueous interface with engineered proteins that bind IL-6 at high affinity and specificity. Hyperthermophilic affinity proteins (rcSso7d) are derived from thermophiles, giving them excellent thermal stability. Two rcSso7d affinity protein variants were synthesized with a noncanonical azide-functionalized amino acid to enable click chemistry to novel polymeric anchors embedded in the hydrocarbon phase. The two binding proteins recognize different epitopes, enabling the detection of both monomeric and dimeric IL-6 via agglutination. It is noteworthy that the rsSso7d protein variants, in addition to having superior thermal stability and facile recombinant synthesis in E. coli, show superior performance when compared to commercial antibodies for IL-6.

Point-of-need diagnostics in a post-Covid world: an opportunity for paper-based microfluidics to serve during syndemics

Wed, 01 Jan 2025 00:00:00 GMT

Point-of-need diagnostics in a post-Covid world: an opportunity for paper-based microfluidics to serve during syndemics Tsaloglou, Maria-Nefeli; Christodouleas, Dionysios C; Milette, Jonathan; Milkey, Kendall; Romine, Isabelle C; Im, Judy; Lathwal, Shefali; Selvam, Duraipandian Thava; Sikes, Hadley D; Whitesides, George M Zoonotic outbreaks present with unpredictable threats to human health, food production, biodiversity, national security and disrupt the global economy. The COVID-19 pandemic—caused by zoonotic coronavirus, SARS-CoV2— is the most recent upsurge of an increasing trend in outbreaks for the past 100 years. This year, emergence of avian influenza (H5N1) is a stark reminder of the need for national and international pandemic preparedness. Tools for threat reduction include consistent practices in reporting pandemics, and widespread availability of accurate detection technologies. Wars and extreme climate events redouble the need for fast, adaptable and affordable diagnostics at the point of need. During the recent pandemic, rapid home tests for SARS-CoV-2 proved to be a viable functional model that leverages simplicity. In this perspective, we introduce the concept of syndemnicity in the context of infectious diseases and point-of-need healthcare diagnostics. We also provide a brief state-of-the-art for paper-based microfluidics. We illustrate our arguments with a case study for detecting brucellosis in cows. Finally, we conclude with lessons learned, challenges and opportunities for paper-based microfluidics to serve point-of-need healthcare diagnostics during syndemics.

Faster search for tensor decomposition over finite fields

Mon, 10 Nov 2025 00:00:00 GMT

Faster search for tensor decomposition over finite fields Yang, Jason We present an 𝑂 ∗ (|F| min{𝑅, Í 𝑑≥2 𝑛𝑑 }+(𝑅−𝑛0 ) (Í 𝑑≠0 𝑛𝑑 ) )-time algorithm for determining whether the rank of a concise tensor 𝑇 ∈ F 𝑛0×···×𝑛𝐷−1 is ≤ 𝑅, assuming 𝑛0 ≥ · · · ≥ 𝑛𝐷−1 and 𝑅 ≥ 𝑛0. For 3-dimensional tensors, we have a second algorithm running in 𝑂 ∗ (|F| 𝑛0+𝑛2+(𝑅−𝑛0+1−𝑟∗ ) (𝑛1+𝑛2 )+𝑟 2 ∗ ) time, where 𝑟∗ := j 𝑅 𝑛0 k + 1. Both algorithms use polynomial space and improve on our previous work, which achieved running time 𝑂 ∗ (|F| 𝑛0+(𝑅−𝑛0 ) (Í 𝑑 𝑛𝑑 ) ). ISSAC ’25, Guanajuato, Mexico

Human-AI Interaction for Augmented Reasoning: Improving Human Reflective and Critical Thinking with Artificial Intelligence

Fri, 25 Apr 2025 00:00:00 GMT

Human-AI Interaction for Augmented Reasoning: Improving Human Reflective and Critical Thinking with Artificial Intelligence Danry, Valdemar; Pataranutaporn, Pat; Cui, Christopher; Hung, Jui-Tse; Blanchard, Lancelot; Bu?inca, Zana; Tan, Chenhao; Starner, Thad; Maes, Pattie AI-Augmented Reasoning systems are cognitive assistants that support human reasoning by providing AI-based feedback that can help users improve their critical reasoning skills. Made possible with new techniques like argumentation mining, fact-checking, crowdsourcing, attention nudging, and large language models, AI augmented reasoning systems can provide real-time feedback on logical reasoning, help users identify and avoid flawed arguments and misinformation, suggest counter-arguments, provide evidence-based explanations, and foster deeper reflection. The goal of this workshop is to bring together researchers from AI, HCI, cognitive and social science to discuss recent advances in AI-augmented reasoning, to identify open problems in this area, and to cultivate an emerging community on this important topic. CHI EA ’25, Yokohama, Japan

Speech to Reality: On-Demand Production using Natural Language, 3D Generative AI, and Discrete Robotic Assembly

Wed, 19 Nov 2025 00:00:00 GMT

Speech to Reality: On-Demand Production using Natural Language, 3D Generative AI, and Discrete Robotic Assembly Kyaw, Alexander Htet; Smith, Miana; Jeon, Se Hwan; Gershenfeld, Neil We present a system that transforms speech into physical objects using 3D generative AI and discrete robotic assembly. By leveraging natural language, the system makes design and manufacturing more accessible to people without expertise in 3D modeling or robotic programming. While generative AI models can produce a wide range of 3D meshes, AI-generated meshes are not directly suitable for robotic assembly or account for fabrication constraints. To address this, we contribute a workflow that integrates natural language, 3D generative AI, geometric processing, and discrete robotic assembly. The system discretizes the AI-generated geometry and modifies it to meet fabrication constraints such as component count, overhangs, and connectivity to ensure feasible physical assembly. The results are demonstrated through the assembly of various objects, ranging from chairs to shelves, which are prompted via speech and realized within 5 minutes using a robotic arm. SCF ’25, Cambridge, MA, USA

MechStyle: Augmenting Generative AI with Mechanical Simulation to Create Stylized and Structurally Viable 3D Models

Wed, 19 Nov 2025 00:00:00 GMT

MechStyle: Augmenting Generative AI with Mechanical Simulation to Create Stylized and Structurally Viable 3D Models Faruqi, Faraz; Abdel-Rahman, Amira; Tejedor, Leandra; Nisser, Martin; Li, Jiaji; Phadnis, Vrushank; Jampani, Varun; Gershenfeld, Neil; Hofmann, Megan; Mueller, Stefanie Recent developments in Generative AI enable creators to stylize 3D models based on text prompts. These methods change the 3D model geometry, which can compromise the model’s structural integrity once fabricated. We present MechStyle, a system that enables creators to stylize 3D printable models while preserving their structural integrity. MechStyle accomplishes this by augmenting the Generative AI-based stylization process with feedback from a Finite Element Analysis (FEA) simulation. As the stylization process modifies the geometry to approximate the desired style, feedback from the FEA simulation reduces modifications to regions with increased stress. We evaluate the effectiveness of FEA simulation feedback in the augmented stylization process by comparing three stylization control strategies. We also investigate the time efficiency of our approach by comparing three adaptive scheduling strategies. Finally, we demonstrate MechStyle’s user interface that allows users to generate stylized and structurally viable 3D models and provide five example applications. SCF ’25, Cambridge, MA, USA

AI-assisted sensemaking: Human-AI collaboration for the analysis and interpretation of recorded facilitated conversations

Fri, 25 Apr 2025 00:00:00 GMT

AI-assisted sensemaking: Human-AI collaboration for the analysis and interpretation of recorded facilitated conversations Kabbara, Jad; Phan, Thanh-Mai; Rakhilin, Marina; Detwiller, Maya; Dimitrakopoulou, Dimitra; Roy, Deb In light of growing toxic polarization and societal fragmentation often fueled by social media, we are designing alternative communication spaces we refer to as dialogue networks—networks of people engaged in recorded small-group prompted dialogue. We introduce the dialogue network framework and our use of tools powered by large language models that assist humans in the analysis and interpretation of themes and patterns across conversations which we refer to as sensemaking. We pilot case studies in collaboration with community partners using a prototype AI-assisted sensemaking tool. Insights from these pilots can inform the use of AI for human-led community engagement processes. CHI EA ’25, Yokohama, Japan

$HealthGenie:$ A Knowledge-Driven LLM Framework for Tailored Dietary Guidance

Mon, 10 Nov 2025 00:00:00 GMT

$HealthGenie:$ A Knowledge-Driven LLM Framework for Tailored Dietary Guidance Gao, Fan; Zhao, Xinjie; Xia, Ding; Zhou, Zhongyi; Yang, Rui; Lu, Jinghui; Jiang, Hang; Park, Chanjun; Li, Irene Seeking dietary guidance often requires navigating complex nutritional knowledge while considering individual health needs. To address this, we present HealthGenie, an interactive platform that leverages the interpretability of knowledge graphs (KGs) and the conversational power of large language models (LLMs) to deliver tailored dietary recommendations alongside integrated nutritional visualizations for fast, intuitive insights. Upon receiving a user query, HealthGenie performs intent refinement and maps user's needs to a curated nutritional knowledge graph. The system then retrieves and visualizes relevant subgraphs, while offering detailed, explainable recommendations. Users can interactively adjust preferences to further tailor results. A within-subject study and quantitative analysis show that HealthGenie reduces cognitive load and interaction effort while supporting personalized, health-aware decision-making. CIKM ’25, Seoul, Republic of Korea

TinkerXR: In-Situ, Reality-Aware CAD and 3D Printing Interface for Novices

Wed, 19 Nov 2025 00:00:00 GMT

TinkerXR: In-Situ, Reality-Aware CAD and 3D Printing Interface for Novices Arslan, O?uz; Akdo?an, Artun; Dogan, Mustafa Doga Despite the growing accessibility of augmented reality (AR) for visualization, existing computer-aided design (CAD) systems remain confined to traditional screens or require complex setups or predefined parameters, limiting immersion and accessibility for novices. We present TinkerXR, an open-source AR interface enabling in-situ design and fabrication through Constructive Solid Geometry (CSG) modeling. TinkerXR operates solely with a headset and 3D printer, allowing users to design directly in and for their physical environments. By leveraging spatial awareness, depth occlusion, recognition of physical constraints, reference objects, and hand movement controls, TinkerXR enhances realism, precision, and ease of use. Its AR-based workflow integrates design and 3D printing with a drag-and-drop interface for printers’ virtual twins. A user study comparing TinkerXR with Tinkercad shows that TinkerXR offers novices higher accessibility, engagement, and ease of use. Participants highlighted how designing directly in physical space made the process more intuitive. By bridging the gap between digital creation and physical output, TinkerXR aims to transform everyday spaces into expressive creative studios. We release TinkerXR as open source1 to encourage further exploration of accessible, spatially grounded CAD tools. SCF ’25, Cambridge, MA, USA

Hierarchical Discrete Lattice Assembly: An Approach for the Digital Fabrication of Scalable Macroscale Structures

Wed, 19 Nov 2025 00:00:00 GMT

Hierarchical Discrete Lattice Assembly: An Approach for the Digital Fabrication of Scalable Macroscale Structures Smith, Miana; Richard, Paul; Kyaw, Alexander; Gershenfeld, Neil Although digital fabrication processes at the desktop scale have become proficient and prolific, systems aimed at producing larger-scale structures are still typically complex, expensive, and unreliable. In this work, we present an approach for the fabrication of scalable macroscale structures using simple robots and interlocking lattice building blocks. A target structure is first voxelized so that it can be populated with an architected lattice. These voxels are then grouped into larger interconnected blocks, which are produced using standard digital fabrication processes, leveraging their capability to produce highly complex geometries at a small scale. These blocks, on the size scale of tens of centimeters, are then fed to mobile relative robots that are able to traverse over the structure and place new blocks to form structures on the meter scale. To facilitate the assembly of large structures, we introduce a live digital twin simulation tool for controlling and coordinating assembly robots that enables both global planning for a target structure and live user design, interaction, or intervention. To improve assembly throughput, we introduce a new modular assembly robot, designed for hierarchical voxel handling. We validate this system by demonstrating the voxelization, hierarchical blocking, path planning, and robotic fabrication of a set of meter-scale objects. SCF ’25, Cambridge, MA, USA

Are Crypto Ecosystems (De)centralizing? A Framework for Longitudinal Analysis

Mon, 24 Nov 2025 00:00:00 GMT

Are Crypto Ecosystems (De)centralizing? A Framework for Longitudinal Analysis Ju, Harang; Valavi, Eshan; Kumar, Madhav; Aral, Sinan Blockchain technology relies on decentralization to resist faults and attacks while operating without trusted intermediaries. Although industry experts have touted decentralization as central to their promise and disruptive potential, it is still unclear whether the crypto ecosystems built around blockchains are becoming more or less decentralized over time. As crypto plays an increasing role in facilitating economic transactions and peer-to-peer interactions, measuring their decentralization becomes even more essential.We thus propose a systematic framework for measuring the decentralization of crypto ecosystems over time and compare commonly used decentralization metrics. We applied this framework to seven prominent blockchains, across five distinct subsystems and across their lifetime for over 15 years. Our analysis revealed that while crypto has largely become more decentralized over time, recent trends show a shift toward centralization in the consensus layer, NFT marketplaces, and developers. Our framework and results inform researchers, policymakers, and practitioners about the design, regulation, and implementation of crypto ecosystems and provide a systematic, replicable foundation for future studies.

Multimodal AI for Human Sensing and Interaction

Fri, 25 Apr 2025 00:00:00 GMT

Multimodal AI for Human Sensing and Interaction Liang, Paul Pu; Ahuja, Karan; Luo, Yiyue A significant body of HCI research today focuses on applying AI to sense, learn, and interact with humans through a wide range of wearable and ubiquitous sensors. These methods typically involve learning features from multimodal sensory data using AI methods. To aid HCI researchers who want to apply AI to their sensing problems, this course will cover the fundamental challenges and approaches in multimodal AI for human sensing and interaction. It is planned for 3 parts, one given by each organizer. The first covers the foundations of multimodal AI, studying how AI systems can represent, combine, and learn information from many interconnected sensory inputs. The second part discusses the practice of multimodal AI for human sensing, covering the latest methods for cross-modal learning across diverse sensors, human-centered application domains, and real-world concerns around their usage. The final part covers the hardware, fabrication, and data collection challenges that must be tackled to deploy these multimodal AI systems in the real world. By the end of this course, attendees should understand the fundamental principles and challenges of multimodal AI, identify the right AI approaches for their problems, prototype basic hardware systems for efficient and robust sensing, be aware of real-world concerns around ethics, interpretability, and privacy, and appreciate the range of human-centered applications enabled by multimodal AI and sensing. CHI EA ’25, Yokohama, Japan

Deep-Time Architecture: Building as Material-Event

Sat, 02 Jan 2021 00:00:00 GMT

Deep-Time Architecture: Building as Material-Event Alonso, Cristina Parreño Despite our tendency to conceive, perceive, and represent buildings as static objects, buildings are, in their abundant reality, matter and energy in flux. As Heraclitus famously remarked in his panta rhei (πάντα ῥεῖ,): “everything flows.”1 Buildings are no different, and they need to be better thought through as entities in motion. In architectural literature, many voices have challenged the prevailing notion of the building as a static object. Bruno Latour, for instance, claims that a building is rather “a moving project, and that even once it has been built, it ages, it is transformed by its users, modified by all of what happens inside and outside, and that it will pass or be renovated, adulterated and transformed beyond recognition.”2 Another attempt to express architecture’s fluidity is Bernard Tschumi’s triad, “space, event and movement,” with which he aimed to expand what constitutes building beyond a static object and form: “There is no space without event, no architecture without movement.”3 And here we must add that there is no movement without time—and further, that given enough time, even a solid-like material (think of a building here) flows.

Involuntary vs. voluntary flexible work: insights for scholars and stakeholders

Thu, 08 Aug 2019 00:00:00 GMT

Involuntary vs. voluntary flexible work: insights for scholars and stakeholders Kaduk, Anne; Genadek, Katie; Kelly, Erin L; Moen, Phyllis Building on insights from the early stages of our research partnership with a U.S. Fortune 500 organization, we came to differentiate between voluntary and involuntary schedule variability and remote work. This differentiation underscores the complexity behind flexible schedules and remote work, especially among white-collar, salaried professionals. We collected survey data among the partner firm's information technology (IT) workforce to evaluate whether these forms of flexibility had different implications for workers, as part of the larger Work, Family, and Health Network Study. We find that a significant minority of these employees report working variable schedules and working at home involuntarily. Involuntary variable schedules are associated with greater work-to-family conflict, stress, burnout, turnover intentions, and lower job satisfaction in models that adjust for personal characteristics, job, work hours, family demands, and other factors. Voluntary remote work, in contrast, is protective and more common in this professional sample. Employees working at least 20% of their hours at home and reporting moderate or high choice over where they work have lower stress and intentions to leave the firm. These findings point to the importance of both stakeholders and scholars distinguishing between voluntary and involuntary forms of flexibility, even in a relatively advantaged workforce.

Machine learning demand forecasting and supply chain performance

Tue, 04 Aug 2020 00:00:00 GMT

Machine learning demand forecasting and supply chain performance Feizabadi, Javad In many supply chains, firms staged in upstream of the chain suffer from variance amplification emanating from demand information distortion in a multi-stage supply chain and, consequently, their operation inefficiency. Prior research suggest that employing advanced demand forecasting, such as machine learning, could mitigate the effect and improve the performance; however, it is less known what is the extent and magnitude of savings as tangible supply chain performance outcomes. In this research, hybrid demand forecasting methods grounded on machine learning i.e. ARIMAX and Neural Network is developed. Both time series and explanatory factors are feed into the developed method. The method was applied and evaluated in the context of functional product and a steel manufacturer. The statistically significant supply chain performance improvement differences were found across traditional and ML-based demand forecasting methods. The implications for the theory and practice are also presented.

The future of sperm: a biovariability framework for understanding global sperm count trends

Mon, 10 May 2021 00:00:00 GMT

The future of sperm: a biovariability framework for understanding global sperm count trends Boulicault, Marion; Perret, Meg; Galka, Jonathan; Borsa, Alex; Gompers, Annika; Reiches, Meredith; Richardson, Sarah The past 50 years have seen heated debate in the reproductive sciences about global trends in human sperm count. In 2017, Levine and colleagues published the largest and most methodologically rigorous meta-regression analysis to date and reported that average total sperm concentration among men from ‘Western’ countries has decreased by 59.3% since 1973, with no sign of halting. These results reverberated in the scientific community and in public discussions about men and masculinity in the modern world, in part because of scientists’ public-facing claims about the societal implications of the decline of male fertility. We find that existing research follows a set of implicit and explicit assumptions about how to measure and interpret sperm counts, which collectively form what we term the Sperm Count Decline hypothesis (SCD). Using the study by Levine and colleagues, we identify weaknesses and inconsistencies in the SCD, and propose an alternative framework to guide research on sperm count trends: the Sperm Count Biovariability hypothesis (SCB). SCB asserts that sperm count varies within a wide range, much of which can be considered non-pathological and species-typical. Knowledge about the relationship between individual and population sperm count and life-historical and ecological factors is critical to interpreting trends in average sperm counts and their relationships to health and fertility.

Estimating Pedestrian Flows on Street Networks

Sat, 02 Oct 2021 00:00:00 GMT

Estimating Pedestrian Flows on Street Networks Sevtsuk, Andres City governments and planners alike commonly seek to increase pedestrian activity on city streets as part of broader sustainability, community building, and economic development strategies. Though walkability has received ample attention in planning literature, most planners still lack practical methods for predicting how development proposals could affect pedestrian activity on specific streets or public spaces at different times of the day. Cities typically require traffic impact assessments (TIAs) but not pedestrian impact assessments. In this study I present a methodology for estimating pedestrian trip generation and distribution between detailed origins and destinations in both existing and proposed built environments. Using the betweenness index from network analysis, I introduce a number of methodological improvements that allow the index to model pedestrian trips with parameters and constraints to account for pedestrian behavior in different settings. I demonstrate its application in the Kendall Square area of Cambridge (MA), where estimated foot traffic is compared during lunch and evening peak periods with observed pedestrian counts. The proposed approach can be particularly useful for TIAs, neighborhood plans, and large-scale development projects, where pedestrian flow estimates can be used to guide pedestrian infrastructure and safety improvements and public space investments or for locating pedestrian priority streets during the COVID-19 pandemic.

Understanding individuals with spinal cord injury’s self-care practices: a technology probe study to promote pressure relief adherence

Wed, 02 Oct 2024 00:00:00 GMT

Understanding individuals with spinal cord injury’s self-care practices: a technology probe study to promote pressure relief adherence Oh, Hannah Hye Yeon; Pontis, Sheila Pressure reliefs (PRs) are self-care practices essential for individuals with spinal cord injury (SCI) to prevent life-threatening pressure injuries (PIs). Despite the benefits, individuals often do not do these exercises at home, leading to increased patient morbidity and mortality. To examine how digital technology could improve this population's adherence to PR exercises, we conducted a technology probe study with five individuals with SCI over ten consecutive business days. A chat-based intervention was created to send user-scheduled PR reminders, which were personalized with visual elements and progress trackers. Participants were interviewed before and after interacting with the probe to better understand their experiences with PIs and PR practices. Results shed light on specific factors that may impact individuals with SCI's behaviours towards PRs and four considerations to design a customisable reminder intervention: (1) easy to use and friendly technology, (2) design-your-own- schedule feature, (3) communication style feature, and (4) dialogue support features. Personalisation supported with gamified visual progress tracking and motivational messages emerged as a strong strategy to increase PR adherence. Both sets of findings expand upon the human-computer interaction (HCI) literature for mobile health tools that encourage self-care practices; in particular, to the specific needs of individuals with SCI and the use of visual elements to increase engagement.

Health and toxicity in content moderation: the discursive work of justification

Tue, 12 Dec 2023 00:00:00 GMT

Health and toxicity in content moderation: the discursive work of justification Gibson, Anna D.; Docherty, Niall; Gillespie, Tarleton Within academia, industry, and government, the terms ‘health’ and ‘toxicity’ are widely used to describe and justify decisions around online content and its removal. However, the meanings of these terms are assumed to be self-evident and therefore are rarely examined. This article turns a critical eye to the health and toxicity metaphor to unpack its hidden political work. We trace the metaphor through three different discourses: the historical political economy of the term, the usage by cultural elites in the last two decades, and finally through its contemporary instrumental usage by volunteer content moderators on Facebook. By linking these discourses together, we argue that the metaphor of health and toxicity serves as a means for justification and legitimacy under contemporary neoliberalized orders that typically chafe at modes of public intervention and the language of democratic statecraft. Rather than elucidating the challenges of online content, we find that the metaphor often serves to obfuscate or sidestep the hardest problems in democratic governance. This analysis therefore has practical significance for researchers, policymakers, journalists, and other speakers that publicly traffic in this discourse at large.

Balancing Covariates in Randomized Experiments with the Gram–Schmidt Walk Design

Tue, 01 Oct 2024 00:00:00 GMT

Balancing Covariates in Randomized Experiments with the Gram–Schmidt Walk Design Harshaw, Christopher; Sävje, Fredrik; Spielman, Daniel A; Zhang, Peng The design of experiments involves a compromise between covariate balance and robustness. This article provides a formalization of this tradeoff and describes an experimental design that allows experimenters to navigate it. The design is specified by a robustness parameter that bounds the worst-case mean squared error of an estimator of the average treatment effect. Subject to the experimenter’s desired level of robustness, the design aims to simultaneously balance all linear functions of potentially many covariates. Less robustness allows for more balance. We show that the mean squared error of the estimator is bounded in finite samples by the minimum of the loss function of an implicit ridge regression of the potential outcomes on the covariates. Asymptotically, the design perfectly balances all linear functions of a growing number of covariates with a diminishing reduction in robustness, effectively allowing experimenters to escape the compromise between balance and robustness in large samples. Finally, we describe conditions that ensure asymptotic normality and provide a conservative variance estimator, which facilitate the construction of asymptotically valid confidence intervals. Supplementary materials for this article are available online.

From natural language to simulations: applying AI to automate simulation modelling of logistics systems

Fri, 16 Feb 2024 00:00:00 GMT

From natural language to simulations: applying AI to automate simulation modelling of logistics systems Jackson, Ilya; Jesus Saenz, Maria; Ivanov, Dmitry Our research strives to examine how simulation models of logistics systems can be produced automatically from verbal descriptions in natural language and how human experts and artificial intelligence (AI)-based systems can collaborate in the domain of simulation modelling. We demonstrate that a framework constructed upon the refined GPT-3 Codex is capable of generating functionally valid simulations for queuing and inventory management systems when provided with a verbal explanation. As a result, the language model could produce simulation models for inventory and process control. These results, along with the rapid improvement of language models, enable a significant simplification of simulation model development. Our study offers guidelines and a design of a natural language processing-based framework on how to build simulation models of logistics systems automatically, given the verbal description. In generalised terms, our work offers a technological underpinning of human-AI collaboration for the development of simulation models.

HiTop 2.0: combining topology optimisation with multiple feature size controls and human preferences

Sun, 31 Dec 2023 00:00:00 GMT

HiTop 2.0: combining topology optimisation with multiple feature size controls and human preferences Schiffer, Gillian; Ha, Dat Quoc; Carstensen, Josephine V Topology optimisation is a computational design approach that generates high-performing, efficient structures uniquely suited to a design engineer’s goal. However, there exist two major obstacles to the accessibility, or ease of use, of topology optimisation: expensive computational costs and users’ binary decision between personal intuition and the algorithm’s result. Human-informed topology optimisation, or HiTop, presents an alternative approach to topology optimisation when a user lacks access to a high-performance computer or knowledge of code parameters. HiTop 2.0 prompts users to interactively identify a region of interest in the preliminary design and modify the size of the solid and/or void features. The novel contribution of this paper implements multi-phase minimum and maximum solid feature size controls in HiTop 2.0, and demonstrates 2D and 3D benchmark examples, including test cases that show how the user can interactively enhance issues related to eigenvalues, stress, and energy absorption, while solving the minimum compliance problem.

Integrated urban heat sinks for low-carbon neighbourhoods: dissipating heat to the ground and sky through building structures

Sun, 04 May 2025 00:00:00 GMT

Integrated urban heat sinks for low-carbon neighbourhoods: dissipating heat to the ground and sky through building structures Gascón Alvarez, Eduardo; Feickert, Kiley; Ismail, Mohamed A; Mueller, Caitlin T; Norford, Leslie K In a global context of simultaneous urbanization and rising ambient temperatures, it is imperative to design heat-resilient and material-efficient neighbourhoods that respond to the pressing demand for housing with minimal environmental impact. With this goal in mind, the work presented here focuses on the integration of heat dissipation systems within structural building components, introducing a novel framework for their systems-level simulation and design. Two well-studied, low-cost systems (shallow geothermal and night-sky cooling) are modelled within a parametric design workflow that combines bottom-up structural embodied carbon calculations with annual building energy simulations that account for heat sink availability. The proposed method results in a fast and reliable early-stage design tool that allows urban planners, policymakers, and designers to evaluate the suitability of available heat dissipation technologies across climates and urban morphologies. This paper analyzes specifically the multi-domain performance of a hypothetical urban geometry within three different cooling-dominated locations (Algiers, Cairo, and Bangkok).

China’s Potential Lessons from Ukraine for Conflict over Taiwan

Mon, 03 Jul 2023 00:00:00 GMT

China’s Potential Lessons from Ukraine for Conflict over Taiwan Taylor Fravel, M What lessons for a conflict over Taiwan might China be learning from Russia’s invasion of Ukraine and the global responses to the war? And what are the strategic implications of these lessons? To answer these questions, I examine how the war in Ukraine may be shaping China’s assessments of the political, military and economic costs of military action against Taiwan, and how these assessments may influence China’s decision to use force against Taiwan.

BoundarEase: Fostering Constructive Community Engagement to Inform More Equitable Student Assignment Policies

Fri, 02 May 2025 00:00:00 GMT

BoundarEase: Fostering Constructive Community Engagement to Inform More Equitable Student Assignment Policies Overney, Cassandra; Moe, Cassandra; Chang, Alvin; Gillani, Nabeel Public school districts across the United States (US) play a pivotal role in shaping access to quality education through their student assignment policies—most prominently, school attendance boundaries. Community engagement processes for changing such policies, however, are often opaque, cumbersome, and highly polarizing—hampering equitable access to quality schools in ways that can perpetuate disparities in achievement and future life outcomes. In this paper, we describe a collaboration with a large US public school district serving nearly 150,000 students to design and evaluate a new sociotechnical system, “BoundarEase”, for fostering more constructive community engagement around changing school attendance boundaries. Through a formative study with 16 community members, we first identify several frictions in existing community engagement processes during boundary planning, like individualistic over collective thinking; a failure to understand and empathize with different community members when considering policy impacts; and challenges in accessing and understanding the impacts of boundary changes. We then use these frictions to inspire the design and development of BoundarEase, a web platform that allows community members to explore and offer feedback on potential boundaries based on their preferences. A user study with 12 community members reveals that BoundarEase prompts reflection among community members on how policies might impact families beyond their own, and increases transparency around the details of policy proposals. Our paper offers education researchers insights into the challenges and opportunities involved in community engagement for designing student assignment policies; human-computer interaction researchers a case study of how new sociotechnical systems might help mitigate polarization in local policymaking; and school districts a practical tool they might use to facilitate community engagement to foster more equitable student assignment policies. Cassandra Overney, Cassandra Moe, Alvin Chang, and Nabeel Gillani. 2025. BoundarEase: Fostering Constructive Community Engagement to Inform More Equitable Student Assignment Policies. Proc. ACM Hum.-Comput. Interact. 9, 2, Article CSCW040 (May 2025), 37 pages.

Multi-objective Evolutionary Learning for Near Pareto-Optimal Optimization of Solar Deployment

Tue, 11 Nov 2025 00:00:00 GMT

Multi-objective Evolutionary Learning for Near Pareto-Optimal Optimization of Solar Deployment Sigrist, Cooper; Li, Archimedes; Zhang, Alice; Lechowicz, Adam; Bashir, Noman; Lertsaroj, Pichsinee; Bahlous-Boldi, Ryan; Hajiesmaili, Mohammad Existing residential rooftop photovoltaic (PV) installations in the United States are inequitable, as they are concentrated in high-income neighborhoods, and carbon-inefficient because they are often not located in electric grids dominated by fossil-fuel generators. Prior work, however, shows that prioritizing socioeconomic equity can also significantly increase the carbon efficiency of new installations. In this paper, we formalize the problem of site selection for rooftop PV installations as a multi-objective optimization problem, with metrics including energy generation, carbon offsetting, and demographic equity. We introduce a novel method called Evolutionary Value Assignment (EVA) that uses a neural network trained via evolutionary learning to select ideal sites for deployment. We evaluate our proposed approach in a case study using a dataset of U.S. solar generation and demographic information. Compared to projections of current installation trends, our method improves Carbon Efficiency by 43%, Income Equity by 41%, and Racial Equity by 24%, while increasing Energy Generation Potential by up to 10%. Therefore, our optimized placement can achieve the estimated carbon offset needed for net-zero emissions from electricity generation earlier than current deployment trends. BUILDSYS ’25, Golden, CO, USA

Robust and expert-agnostic digital twin calibration via ensemble learning and Bayesian optimization

Tue, 11 Nov 2025 00:00:00 GMT

Robust and expert-agnostic digital twin calibration via ensemble learning and Bayesian optimization Zhan, Sicheng; Cui, Bosen Digital twins have emerged as a critical tool in tackling climate change. Considering the data scarcity of complex systems, a promising approach to developing digital twins involves combining physics-based models with data assimilation. However, model calibration remains challenging due to uncertainties in both the physical models and observational data, and the reliance on domain knowledge. In this study, we develop an ensemble learning-based approach that aggregates sub-models with diversified calibration configurations. The proposed method streamlines calibration without expert-driven parameter screening and improves the digital twin's extrapolation capability, enabling more robust predictive applications. We demonstrate the effectiveness of our approach by calibrating the energy model of an office building, significantly reducing the extrapolation error and the associated risks. To the best of our knowledge, this is the first study to facilitate the calibration of physics-based models using ensemble learning, especially in the parameter space. BUILDSYS ’25, Golden, CO, USA

Talk to the Hand: an LLM-powered Chatbot with Visual Pointer as Proactive Companion for On-Screen Tasks

Fri, 25 Apr 2025 00:00:00 GMT

Talk to the Hand: an LLM-powered Chatbot with Visual Pointer as Proactive Companion for On-Screen Tasks Prasongpongchai, Thanawit; Pataranutaporn, Pat; Lertsutthiwong, Monchai; Maes, Pattie This paper presents Pointer Assistant, a novel human-AI interaction technique for on-screen tasks. The design features a chatbot displayed as an extra mouse pointer, alongside the user’s, which proactively gives feedback on user actions while directing them to relevant areas on the screen and responding to the user’s direct chat messages. The effectiveness of the design’s key characteristics, pointer form and proactivity, was investigated in a study involving 220 participants in a financial budget planning task. Results demonstrated that the pointer design and interaction reduced task load while improving satisfaction with the experience, and increased the number of budget categories ideated during the task compared to the traditional passive chat log design. Participants viewed Pointer Assistant as a fun, innovative, and helpful visual guide while noting that its assertiveness can be improved. Future developments could offer even further enhancements to the user experience of human-AI collaboration and task outcomes. CHI ’25, Yokohama, Japan

WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures

Wed, 19 Nov 2025 00:00:00 GMT

WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures Faruqi, Faraz; Paonaskar, Josha; Schuler, Riley; Prevey, Aiden; Taylor, Carson; Tak, Anika; Guinto, Anthony; Shilamkar, Eeshani; Cheenaruenthong, Natarith; Nisser, Martin This paper introduces WireBend-kit, a desktop wirebending machine and computational design tool for creating 3D wireframe structures. Combined, they allow users to rapidly and inexpensively create custom 3D wireframe structures from aluminum wire. Our design tool is implemented in freely available software and allows users to generate virtual wireframe designs and assess their fabricability. A path-planning procedure automatically converts the wireframe design into fabrication instructions for our machine while accounting for material elasticity and kinematic error sources. The custom machine costs $293 in parts and can form aluminum wire into 3D wireframe structures through an ordered sequence of feed, bend, and rotate instructions. Our technical evaluation reveals our system’s ability to overcome odometrically accumulating errors inherent to wirebending in order to produce accurate 3D structures from inexpensive hardware. Finally, we provide application examples demonstrating the design space enabled by Wirebend-kit. SCF ’25, Cambridge, MA, USA

Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments

Mon, 23 Jun 2025 00:00:00 GMT

Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments Gosciak, Jennah; Balagopalan, Aparna; Ouyang, Derek; Koenecke, Allison; Ghassemi, Marzyeh; Ho, Daniel Prior work has documented widespread racial and ethnic inequities across sectors, such as healthcare, finance, and technology. Across all of these domains, conducting disparity assessments at regular time intervals is critical for surfacing potential biases in decision-making and improving outcomes across demographic groups. Because disparity assessments fundamentally depend on the availability of demographic information, their efficacy is limited by the availability and consistency of available demographic identifiers. While prior work has considered the impact of missing data on fairness, little attention has been paid to the role of delayed demographic data. Delayed data, while eventually observed, might be missing at the critical point of monitoring and action – and delays may be unequally distributed across groups in ways that distort disparity assessments. We characterize such impacts in healthcare, using electronic health records of over 5M patients across primary care practices in all 50 states. Our contributions are threefold. First, we document the high rate of race and ethnicity reporting delays in a healthcare setting and demonstrate widespread variation in rates at which demographics are reported across different groups. Second, through a set of retrospective analyses using real data, we find that such delays impact disparity assessments and hence conclusions made across a range of consequential healthcare outcomes, particularly at more granular levels of state-level and practice-level assessments. Third, we find limited ability of conventional methods that impute missing race in mitigating the effects of reporting delays on the accuracy of timely disparity assessments. Our insights and methods generalize to many domains of algorithmic fairness where delays in the availability of sensitive information may confound audits, thus deserving closer attention within a pipeline-aware machine learning framework. FAccT ’25, Athens, Greece

Securing Cryptographic Software via Typed Assembly Language

Sat, 22 Nov 2025 00:00:00 GMT

Securing Cryptographic Software via Typed Assembly Language Song, Shixin; Dong, Tingzhen; Nwabueze, Kosi; Zanders, Julian; Erbsen, Andres; Chlipala, Adam; Yan, Mengjia Authors of cryptographic software are well aware that their code should not leak secrets through its timing behavior, and, until 2018, they believed that following industry-standard constant-time coding guidelines was sufficient. However, the revelation of the Spectre family of speculative execution attacks injected new complexities. To block speculative attacks, prior work has proposed annotating the program's source code to mark secret data, with hardware using this information to decide when to speculate (i.e., when only public values are involved) or not (when secrets are in play). While these solutions are able to track secret information stored on the heap, they suffer from limitations that prevent them from correctly tracking secrets on the stack, at a cost in performance. This paper introduces SecSep, a transformation framework that rewrites assembly programs so that they partition secret and public data on the stack. By moving from the source-code level to assembly rewriting, SecSep is able to address limitations of prior work. The key challenge in performing this assembly rewriting stems from the loss of semantic information through the lengthy compilation process. The key innovation of our methodology is a new variant of typed assembly language (TAL), Octal, which allows us to address this challenge. Assembly rewriting is driven by compile-time inference within Octal. We apply our technique to cryptographic programs and demonstrate that it enables secure speculation efficiently, incurring a low average overhead of 1.2%. CCS ’25, Taipei

Study on LLMs for Promptagator-Style Dense Retriever Training

Mon, 10 Nov 2025 00:00:00 GMT

Study on LLMs for Promptagator-Style Dense Retriever Training Gwon, Daniel; Jedidi, Nour; Lin, Jimmy Promptagator demonstrated that Large Language Models (LLMs) with few-shot prompts can be used as task-specific query generators for fine-tuning domain-specialized dense retrieval models. However, the original Promptagator approach relied on proprietary and large-scale LLMs which users may not have access to or may be prohibited from using with sensitive data. In this work, we study the impact of open-source LLMs at accessible scales (≤14B parameters) as an alternative. Our results demonstrate that open-source LLMs as small as 3B parameters can serve as effective Promptagator-style query generators. We hope our work will inform practitioners with reliable alternatives for synthetic data generation and give insights to maximize fine-tuning results for domain-specific applications. Our code is available at https://www.github.com/mitll/promptodile CIKM ’25, Seoul, Republic of Korea

One-Sided Bounded Noise: Theory, Optimization Algorithms and Applications

Sat, 22 Nov 2025 00:00:00 GMT

One-Sided Bounded Noise: Theory, Optimization Algorithms and Applications Xiao, Hanshen; Wan, Jun; Shi, Elaine; Devadas, Srinivas We investigate the optimal trade-off between utility and privacy using one-sided perturbation. Unlike conventional privacy-preserving statistical releases, randomization for obfuscating side-channel information is often constrained by infrastructure limitations. In practical scenarios, these constraints may only allow positive and bounded perturbations. For example, extending processing time or sending and storing dummy messages/data is typically feasible. However, implementing modifications in the opposite direction is challenging due to restrictions imposed by hardware capacity, communication protocols, and data management systems. In this paper, we establish the foundation of the positive noise mechanism within three semantic privacy frameworks: Differential Privacy (DP), Maximal Leakage (MaxL), and Probably Approximately Correct (PAC) Privacy. We then present a series of results that characterize or approximate the optimal one-sided noise distribution, subject to a second-moment budget and a bounded maximal magnitude. Building on this theoretical foundation, we develop efficient tools to solve the underlying optimization problems. Through experiments conducted in various scenarios, we demonstrate that existing techniques, such as Truncated Biased Laplace noise, are often suboptimal and result in excessive performance degradation. For instance, in an anonymous communication system with a 250K message budget, our optimized DP noise mechanism achieves a 21× reduction in dummy messages and an 18× reduction in dummy message latency overhead compared to traditional methods. CCS ’25, Taipei, Taiwan

TH-Wood: Developing Thermo-Hygro-Coordinating Driven Wood Actuators to Enhance Human-Nature Interaction

Fri, 25 Apr 2025 00:00:00 GMT

TH-Wood: Developing Thermo-Hygro-Coordinating Driven Wood Actuators to Enhance Human-Nature Interaction Wang, Guanyun; Chen, Chuang; Jin, Xiao; Chen, Yulu; Zheng, Yangweizhe; Zhen, Qianzi; Zhang, Yang; Li, Jiaji; Yang, Yue; Tao, Ye; Luo, Shijian; Sun, Lingyun Wood has become increasingly applied in shape-changing interfaces for its eco-friendly and smart responsive properties, while its applications face challenges as it remains primarily driven by humidity. We propose TH-Wood, a biodegradable actuator system composed of wood veneer and microbial polymers, driven by both temperature and humidity, and capable of functioning in complex outdoor environments. This dual-factor-driven approach enhances the sensing and response channels, allowing for more sophisticated coordinating control methods. To assist in designing and utilizing the system more effectively, we developed a structure library inspired by dynamic plant forms, conducted extensive technical evaluations, created an educational platform accessible to users, and provided a design tool for deformation adjustments and behavior previews. Finally, several ecological applications demonstrate the potential of TH-Wood to significantly enhance human interaction with natural environments and expand the boundaries of human-nature relationships. CHI ’25, Yokohama, Japan

From blades to tracks: a case study in structural reuse of curved surfaces for circular design

Wed, 19 Nov 2025 00:00:00 GMT

From blades to tracks: a case study in structural reuse of curved surfaces for circular design Pupping, Jesse; Riso, Marzia; Popescu, Mariana; Bousseau, Adrien; Joustra, Jelle We explore the fabrication of curved surfaces by reusing panels extracted from decommissioned wind turbine blades, using cycling pumptracks as a case study. We first present real-world prototypes of pumptrack modules that we manufactured to evaluate the practicality of this reuse scenario and to define the boundary conditions for harvesting blade panels and assembling a track. We then propose an algorithm to optimize the segmentation of a wind turbine blade into quadrilateral panels whose sides fall within a small set of compatible boundaries. These panels form a library of modules that designers can connect side by side to create pumptracks of various lengths and curvatures. Together, these contributions provide a proof-of-concept of how computer-aided design and manufacturing can support circular design through the reuse of curved surfaces.

Fintech Innovation in China

Tue, 23 Sep 2025 00:00:00 GMT

Fintech Innovation in China Cusumano, Michael This column discusses innovation in payment platforms in China and what Western central banks and governments might learn. Private Chinese companies led in the introduction of the mobile payment systems Alipay and WeChat Pay, using QR codes, and most transactions in the country are now digital. China also has banned private crypto currencies and stablecoins and introduced a public digital currency and payment system using crypto technology. However, it has been very difficult to get users to switch to the new central bank digital currency, despite aggressive promotions, subsidies, and mandates. China's experience suggests that other central banks around the world will have difficulty introducing their own digital currencies and competing with private stablecoins and cryptocurrencies as well as other private digital payment platforms.

The Stable Marriage Problem and Sudoku

Wed, 07 Aug 2024 00:00:00 GMT

The Stable Marriage Problem and Sudoku Borodin, Matvey; Chen, Eric; Duncan, Aidan; Khovanova, Tanya; Litchev, Boyan; Liu, Jiahe; Moroz, Veronika; Qian, Matthew; Raghavan, Rohith; Rastogi, Garima; Voigt, Michael Are you having trouble getting married? These days, there are lots of products on the market for dating, from apps to websites and matchmakers, but we know a simpler way! That’s right—your path to coupled life isn’t through Tinder; it’s through Sudoku! Read our fabulous paper, where we explore the Stable Marriage Problem to help you find happiness and stability in marriage through math. As a bonus, you get two Sudoku puzzles with a new flavor.

How Medical Technologies Materialize Oppression

Mon, 03 Apr 2023 00:00:00 GMT

How Medical Technologies Materialize Oppression Boulicault, Marion Biomedical practice can encode and perpetuate oppressive ideologies. This encoding and perpetuation, scholars like Liao and Carbonell (Citation2023) convincingly argue, can occur not only via social practices, but also through medical technologies themselves. In other words, medical technologies can “materialize oppression”: they can be biased in a way that systematically “reflects and perpetuates unjust power relations” (Liao and Carbonell Citation2023, 9). In this paper, I examine how medical technologies materialize oppression, offering a preliminary, non-exhaustive taxonomy of the mechanisms of this materialization. While scholars like Liao and Carbonell focus primarily on physical medical instruments, I offer new examples that illustrate these mechanisms at work, focusing on medical data classification technologies and infrastructures. A clearer view of how these mechanisms operate suggests possibilities for building technologies that liberate rather than oppress.

Wild Wood Gridshells: Mixed-Reality Construction of Nonstandard Wood

Mon, 03 Jul 2023 00:00:00 GMT

Wild Wood Gridshells: Mixed-Reality Construction of Nonstandard Wood Cousin, Tim; Alkhayat, Latifa; Pearl, Natalie; Dewart, Christopher B; Mueller, Caitlin Irregular wood is often downcycled despite having significant embedded strength. Reintegrating this wood into structural assemblies can improve material efficiency in the built environment. This work implemented material logic in a design-to-fabrication workflow for building structures using bifurcated tree branches to leverage this potential (Figure 1). This process is demonstrated through the design and construction of a prototype. A user-oriented computational interface is proposed that manages irregular geometries, matching and optimization algorithms, and structural simulation for design iteration. The demonstrated workflow, which concludes with augmented reality (AR) assisted fabrication, facilitates designing with varying materials, enabling upcycling a wide range of nonstandard building elements. At scale, this methodology can significantly reduce the environmental impact of construction.

MiNav: Autonomous Drone Navigation Indoors using Millimeter-Waves

Wed, 03 Sep 2025 00:00:00 GMT

MiNav: Autonomous Drone Navigation Indoors using Millimeter-Waves Lam, Maisy; Herrera, Joshua; Afzal, Sayed Saad; Zhou, Kaichen; Adib, Fadel We present the design, implementation, and evaluation of MiNav, a system capable of accurate, efficient and fully autonomous drone navigation in challenging indoor environments, including those where vision-based systems fail. MiNav builds on recent literature in millimeter-wave (mmWave) backscatter localization and makes the leap to full end-to-end autonomous mmWave-based navigation. MiNav leverages a mmWave radar mounted on a drone and one or more mmWave backscatter tags deployed in the environment. To enable autonomous navigation, our design introduces key innovations. First, MiNav derives a novel Joint DOP-SNR formulation to probabilistically model uncertainty in localization, and uses this uncertainty to generate an RF-Navigation Map that maximizes the accuracy and reliability of mmWave backscatter localization throughout an environment. It then applies a RF-aware Autonomous Path Planning technique that jointly optimizes for navigation efficiency and localization performance. We built an end-to-end real-time implementation of MiNav consisting of a custom built drone and mmWave backscatter tags. We tested it in practical indoor environments. We run over 165 successful autonomous missions across different tag deployments and demonstrate a median 3D navigation error of 9.1 cm. Our results also show that in comparison to baseline implementations that rely on more classical uncertainty metrics, MiNav achieves a 20% increase in navigation reliability and nearly 3x improvement in self-tracking in millimeter-wave backscatter localization. Finally, we demonstrate first of its kind capabilities, such as fully autonomous, end-to-end mmWave-based drone navigation and path planning in featureless and dark environments. Demo video: http://y2u.be/EpnWibRcxBI

A Civics Lesson for Corporations Seeking to Join a University Community of Innovation

Mon, 30 Oct 2023 00:00:00 GMT

A Civics Lesson for Corporations Seeking to Join a University Community of Innovation Wright, Randall S. Civics, according to Merriam-Webster(2023), is “a social science dealing withthe rights and duties of citizens.”We’ve reached an inflection point.The headline of the July 2023 edi-tion of University-Industry EngagementAdvisor (Lewis 2023) reads “Beforesigning off on strategic partnerships,experts stress value of solid due dili-gence process.”

Artificial intelligence for telemedicine diabetic retinopathy screening: a review

Tue, 12 Dec 2023 00:00:00 GMT

Artificial intelligence for telemedicine diabetic retinopathy screening: a review Nakayama, Luis Filipe; Zago Ribeiro, Lucas; Novaes, Frederico; Miyawaki, Isabele Ayumi; Miyawaki, Andresa Emy; de Oliveira, Juliana Angélica Estevão; Oliveira, Talita; Malerbi, Fernando Korn; Regatieri, Caio Vinicius Saito; Celi, Leo Anthony; Silva, Paolo S PURPOSE: This study aims to compare artificial intelligence (AI) systems applied in diabetic retinopathy (DR) teleophthalmology screening, currently deployed systems, fairness initiatives and the challenges for implementation. METHODS: The review included articles retrieved from PubMed/Medline/EMBASE literature search strategy regarding telemedicine, DR and AI. The screening criteria included human articles in English, Portuguese or Spanish and related to telemedicine and AI for DR screening. The author's affiliations and the study's population income group were classified according to the World Bank Country and Lending Groups. RESULTS: The literature search yielded a total of 132 articles, and nine were included after full-text assessment. The selected articles were published between 2004 and 2020 and were grouped as telemedicine systems, algorithms, economic analysis and image quality assessment. Four telemedicine systems that perform a quality assessment, image preprocessing and pathological screening were reviewed. A data and post-deployment bias assessment are not performed in any of the algorithms, and none of the studies evaluate the social impact implementations. There is a lack of representativeness in the reviewed articles, with most authors and target populations from high-income countries and no low-income country representation. CONCLUSIONS: Telemedicine and AI hold great promise for augmenting decision-making in medical care, expanding patient access and enhancing cost-effectiveness. Economic studies and social science analysis are crucial to support the implementation of AI in teleophthalmology screening programs. Promoting fairness and generalizability in automated systems combined with telemedicine screening programs is not straightforward. Improving data representativeness, reducing biases and promoting equity in deployment and post-deployment studies are all critical steps in model development.

The Removal Chain & Sentient Life Cycles

Mon, 03 Jul 2023 00:00:00 GMT

The Removal Chain & Sentient Life Cycles Schrage, Leonard; Duarte, Fábio; Ratti, Carlo As our cities are growing, managing waste is becoming increasingly challenging. Global plastic waste is set to almost triple by 2060 (OECD Citation2020) while recycling rates are staying below expectations. At the same time, landfills are being relocated away from cities, reaching their maximum capacities, or forced to shut down due to contamination with hazardous materials. As waste management infrastructure is increasingly removed from urban areas, we are becoming further disconnected from its ubiquitous, indispensable, yet invisible life of its own. In recent years, supply chain issues have been an omnipresent reflection of our consumerist reality. For example, when the Ever Given—one of the largest container ships in the world—got stuck in the Suez Canal in 2021 (Chellel et al. Citation2021), we were reminded that our globalized goods travel a long way around the world before they arrive at our doorstep. Still, we tend to forget that there is a life after the supply. On a planet with finite resources and growing piles of (hazardous) trash, we need to look further than the obvious. We urgently need to embrace a circular economy to combat the climate crisis. And to do so, we need to mind both the supply and removal chains.

A two-level machine learning approach for predicting thermal striping in T-junctions with upstream elbow

Sun, 02 Jun 2024 00:00:00 GMT

A two-level machine learning approach for predicting thermal striping in T-junctions with upstream elbow Wang, Yu-Jou; Baglietto, Emilio; Shirvan, Koroush Thermal striping is a phenomenon characterized by oscillatory mixing of non-isothermal streams, which is commonly seen in industrial processes such as nuclear coolant piping, petrochemical plants and liquefied natural gas transportation. The oscillatory mixing of hot and cold fluid can produce thermal field fluctuations and pose a potential risk of high-cycle thermal fatigue failures. Predicting and evaluating spatiotemporal fluctuations in thermal striping often requires high resolution and massive computational power. Although there have been extensive studies using machine learning algorithms on surrogate modeling, research focused on spatiotemporal fluctuation predictions is very limited. Due to the high dimensionality, it often requires complex algorithms with a large amount of high-fidelity training data, which limits the adoption of such methods for industrial applications. In this research, a two-level machine learning framework based on turbulence coherent structures is proposed and its application to a practical problem is demonstrated. The two-level design leverages vortex identification and local bias correction techniques, efficiently reducing the number of full-order simulations required for training. In the first level, well-organized coherent structures are extracted by performing Proper Orthogonal Decomposition on local parameters and then a tree-based machine-learning model is used to down-select the reference structures for the field reconstruction. In the second level, a parameterized convolution neural network is trained to predict the bias introduced by reference structures approximation. The demonstration of the methodology shows that the method can accurately capture the fluctuation frequencies and amplitudes of the spatiotemporal fields in a highly variational setting. Based on the vortex identification method, the methodology is expected to be applicable to general phenomenon driven by large coherent structures.

A Dual-Branch Coupled Fourier Neural Operator for High-Resolution Multi-Phase Flow Modeling in Porous Media

Sat, 22 Nov 2025 00:00:00 GMT

A Dual-Branch Coupled Fourier Neural Operator for High-Resolution Multi-Phase Flow Modeling in Porous Media Al Hashim, Hassan; Elyas, Odai; Williams, John This paper investigates a physics-informed surrogate modeling framework for multi-phase flow in porous media based on the Fourier Neural Operator. Traditional numerical simulators, though accurate, suffer from severe computational bottlenecks due to fine-grid discretizations and the iterative solution of highly nonlinear partial differential equations. By parameterizing the kernel integral directly in Fourier space, the operator provides a discretization-invariant mapping between function spaces, enabling efficient spectral convolutions. We introduce a Dual-Branch Adaptive Fourier Neural Operator with a shared Fourier encoder and two decoders: a saturation branch that uses an inverse Fourier transform followed by a multilayer perceptron and a pressure branch that uses a convolutional decoder. Temporal information is injected via Time2Vec embeddings and a causal temporal transformer, conditioning each forward pass on step index and time step to maintain consistent dynamics across horizons. Physics-informed losses couple data fidelity with residuals from mass conservation and Darcy pressure, enforcing the governing constraints in Fourier space; truncated spectral kernels promote generalization across meshes without retraining. On SPE10-style heterogeneities, the model shifts the infinity-norm error mass into the 10−2 to 10−1 band during early transients and sustains lower errors during pseudo-steady state. In zero-shot three-dimensional coarse-to-fine upscaling from 30 ×110 ×5 to 60 ×220 ×5, it attains 𝑅2 =0.90, RMSE = 4.4 ×10−2, and MAE = 3.2 ×10−2, with more than 90% of voxels below five percent absolute error across five unseen layers, while the end-to-end pipeline runs about three times faster than a full-order fine-grid solve and preserves water-flood fronts and channel connectivity. Benchmarking against established baselines indicates a scalable, high-fidelity alternative for high-resolution multi-phase flow simulation in porous media.

Unveiling IPv6 Scanning Dynamics: A Longitudinal Study Using Large Scale Proactive and Passive IPv6 Telescopes

Thu, 04 Sep 2025 00:00:00 GMT

Unveiling IPv6 Scanning Dynamics: A Longitudinal Study Using Large Scale Proactive and Passive IPv6 Telescopes Tanveer, Hammas Bin; Chan, Echo; Mok, Ricky K. P.; Kappes, Sebastian; Richter, Philipp; Gasser, Oliver; Ronan, John; Berger, Arthur; Claffy, kc We introduce new tools and vantage points to develop and integrate proactive techniques to attract IPv6 scan traffic, thus enabling its analysis. By deploying the largest-ever IPv6 proactive telescope in a production ISP network, we collected over 600M packets of unsolicited traffic from 1.9k Autonomous Systems in 10 months. We characterized the sources of unsolicited traffic, evaluated the effectiveness of five major features across the network stack, and inferred scanners' sources of target addresses and their strategies.

HARMONY: A Scalable Distributed Vector Database for High-Throughput Approximate Nearest Neighbor Search

Tue, 23 Sep 2025 00:00:00 GMT

HARMONY: A Scalable Distributed Vector Database for High-Throughput Approximate Nearest Neighbor Search Xu, Qian; Zhang, Feng; Li, Chengxi; Cao, Lei; Chen, Zheng; Zhai, Jidong; Du, Xiaoyong Approximate Nearest Neighbor Search (ANNS) is essential for various data-intensive applications, including recommendation systems, image retrieval, and machine learning. Scaling ANNS to handle billions of high-dimensional vectors on a single machine presents significant challenges in memory capacity and processing efficiency. To address these challenges, distributed vector databases leverage multiple nodes for the parallel storage and processing of vectors. However, existing solutions often suffer from load imbalance and high communication overhead, primarily due to traditional partition strategies that fail to effectively distribute the workload. In this paper, we introduce Harmony, a distributed ANNS system that employs a novel multi-granularity partition strategy, combining dimension-based and vector-based partition. This strategy ensures a balanced distribution of computational load across all nodes while effectively minimizing communication costs. Furthermore, Harmony incorporates an early-stop pruning mechanism that leverages the monotonicity of distance computations in dimensionbased partition, resulting in significant reductions in both computational and communication overhead. We conducted extensive experiments on diverse real-world datasets, demonstrating that Harmony outperforms leading distributed vector databases, achieving 4.63× throughput on average in four nodes and 58% performance improvement over traditional distribution for skewed workloads.

Kernel Extension DSLs Should Be Verifier-Safe!

Mon, 08 Sep 2025 00:00:00 GMT

Kernel Extension DSLs Should Be Verifier-Safe! Solleza, Franco; Adam, Justus; Crotty, Andrew; Narayan, Akshay; Schwarzkopf, Malte; Tatbul, Nesime eBPF allows developers to write safe operating system extensions, but writing these extensions remains challenging because it requires detailed knowledge of both the extension's domain and eBPF's programming interface. Most importantly, the extension must pass the eBPF verifier. This paper argues that DSLs for extensions should guarantee verifier-safety: valid DSL programs should result in eBPF code that always passes the verifier. This avoids complex debugging and the need for extension developers to be eBPF experts. We show that three existing DSLs for different domains are compatible with verifier-safety. Beyond verifier-safety, practical extension DSLs must also achieve good performance. Inspired by database query optimization, we sketch an approach to creating DSL-specific optimizers capable of maintaining verifier-safety. A preliminary evaluation shows that optimizing verifier-safe extension performance is feasible. eBPF ’25, September 8–11, 2025, Coimbra, Portugal

Experiencing EmbedNet: Embedding self-sensing to 3D casting objects

Sat, 27 Sep 2025 00:00:00 GMT

Experiencing EmbedNet: Embedding self-sensing to 3D casting objects Liu, Fangzheng; Dementyev, Artem; Wicaksono, Irmandy; Paradiso, Joseph This paper introduces EmbedNet, a method for integrating dense sensor networks into casting objects. With EmbedNet, sensor nodes are seamlessly incorporated into casting objects during fabrication. The process involves extruding base materials like silicone rubber or liquid plastic and a custom-designed sensor strip using a hand-held extruder into a mold tailored to specific applications. The base material mixes with the sensor strip in the mold, and upon curing, the result is an object with a defined shape housing a sensor network. EmbedNet employs a small Host node to access sensor data from all nodes on the strip. Each sensor node is self-contained and provides status indications through an onboard RGB LED. The Host connects with all sensor nodes using just three wires: power, ground, and data. This one-wire communication is facilitated through a custom-designed software serial port for each sensor node. The paper showcases various applications of EmbedNet, including wearables, home sensing, and entertainment devices. UIST Adjunct ’25, Busan, Republic of Korea

Demonstrating NeuroFlux: A Non-Invasive Peripheral Magnetic Stimulation Device for Multimodal Haptic Feedback

Sat, 27 Sep 2025 00:00:00 GMT

Demonstrating NeuroFlux: A Non-Invasive Peripheral Magnetic Stimulation Device for Multimodal Haptic Feedback Huang, Bingjian; Chin, Sam; Wigdor, Daniel; Paradiso, Joseph We demonstrate NeuroFlux, a wearable armband that delivers multimodal haptic feedback through non-invasive peripheral magnetic stimulation. Unlike conventional haptic devices limited to either tactile or kinesthetic modalities, NeuroFlux stimulates peripheral nerves to independently evoke both muscle movements and localized skin sensations. Our system features a custom-designed control circuit and a multi-coil armband, enabling precise, real-time control of stimulation location and intensity. This hardware innovation significantly expands the design space of haptic feedback by bridging kinesthetic and tactile modalities through a single, compact device. In our demonstration, participants will experience a wide range of magnetically induced haptic sensations, including independent stimulation of muscular and cutaneous nerves in the forearm. The setup includes interactive tasks that showcase NeuroFlux’s ability to generate diverse haptic effects such as finger flexion, wrist movement, as well as immersive virtual reality object interactions. By offering hands-on exposure to peripheral magnetic stimulation, we aim to spark new research directions in multimodal haptic feedback and make neural stimulation more accessible to the HCI community. UIST Adjunct ’25, Busan, Republic of Korea

Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking

Tue, 22 Apr 2025 00:00:00 GMT

Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking De, Soham; Bakker, Michiel; Baxter, Jay; Saveski, Martin X's Community Notes, a crowd-sourced fact-checking system, allows users to annotate potentially misleading posts. Notes rated as helpful by a diverse set of users are prominently displayed below the original post. While demonstrably effective at reducing misinformation's impact when notes are displayed, there is an opportunity for notes to appear on many more posts: for 91% of posts where at least one note is proposed, no notes ultimately achieve sufficient support from diverse users to be shown on the platform. This motivates the development of Supernotes: AI-generated notes that synthesize information from several existing community notes and are written to foster consensus among a diverse set of users. Our framework uses an LLM to generate many diverse Supernote candidates from existing proposed notes. These candidates are then evaluated by a novel scoring model, trained on millions of historical Community Notes ratings, selecting candidates that are most likely to be rated helpful by a diverse set of users. To test our framework, we ran a human subjects experiment in which we asked participants to compare the Supernotes generated by our framework to the best existing community notes for 100 sample posts. We found that participants rated the Supernotes as significantly more helpful, and when asked to choose between the two, preferred the Supernotes 75.2% of the time. Participants also rated the Supernotes more favorably than the best existing notes on quality, clarity, coverage, context, and argumentativeness. Finally, in a follow-up experiment, we asked participants to compare the Supernotes against LLM-generated summaries and found that the participants rated the Supernotes significantly more helpful, demonstrating that both the LLM-based candidate generation and the consensus-driven scoring play crucial roles in creating notes that effectively build consensus among diverse users. WWW ’25, Sydney, NSW, Australia

I Feel Your Pain: a Haptic Interface for Improving Pain Literacy

Sat, 27 Sep 2025 00:00:00 GMT

I Feel Your Pain: a Haptic Interface for Improving Pain Literacy Yin, Peggy; Chen, Sofia; Chang, Ethan There is no sensation more universal and misunderstood than pain. While pain presents itself in nearly every eukaryotic organism, it remains one of the most elusive disease states to express, let alone treat. Here, we introduce Pain by Numbers, a haptic, immersive storytelling interface that facilitates user recognition and communication of low-to-medium-intensity pain, in order to improve pain literacy for patients, physicians, and society-at-large. UIST Adjunct ’25, Busan, Republic of Korea

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank

Tue, 22 Apr 2025 00:00:00 GMT

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank Loveland, Donald; Wu, Xinyi; Zhao, Tong; Koutra, Danai; Shah, Neil; Ju, Mingxuan Collaborative Filtering (CF) methods dominate real-world recommender systems given their ability to learn high-quality, sparse ID-embedding tables that effectively capture user preferences. These tables scale linearly with the number of users and items, and are trained to ensure high similarity between embeddings of interacted user-item pairs, while maintaining low similarity for non-interacted pairs. Despite their high performance, encouraging dispersion for non-interacted pairs necessitates expensive regularization (e.g., negative sampling), hurting runtime and scalability. Existing research tends to address these challenges by simplifying the learning process, either by reducing model complexity or sampling data, trading performance for runtime. In this work, we move beyond model-level modifications and study the properties of the embedding tables under different learning strategies. Through theoretical analysis, we find that the singular values of the embedding tables are intrinsically linked to different CF loss functions. These findings are empirically validated on real-world datasets, demonstrating the practical benefits of higher stable rank -- a continuous version of matrix rank which encodes the distribution of singular values. Based on these insights, we propose an efficient warm-start strategy that regularizes the stable rank of the user and item embeddings. We show that stable rank regularization during early training phases can promote higher-quality embeddings, resulting in training speed improvements of up to 65.9%. Additionally, stable rank regularization can act as a proxy for negative sampling, allowing for performance gains of up to 21.2% over loss functions with small negative sampling ratios. Overall, our analysis unifies current CF methods under a new perspective -- their optimization of stable rank -- motivating a flexible regularization method that is easy to implement, yet effective at enhancing CF systems. WWW ’25, April 28-May 2, 2025, Sydney, NSW, Australia

Unified and Generalizable Reinforcement Learning for Facility Location Problems on Graphs

Tue, 22 Apr 2025 00:00:00 GMT

Unified and Generalizable Reinforcement Learning for Facility Location Problems on Graphs Guo, Wenxuan; Wang, Runzhong; Xu, Yanyan; Jin, Yaohui Facility location problems on graphs are ubiquitous in the real world and hold significant importance, yet their resolution is often impeded by NP-hardness. MIP solvers can find the optimal solutions but fail to handle large instances, while algorithm efficiency has a higher priority in cases of emergency. Recently, machine learning methods have been proposed to tackle such classical problems with fast inference, but they are limited to the myopic constructive pattern and only consider simple cases in Euclidean space. This paper introduces a unified and generalizable approach to tackle facility location problems on weighted graphs with deep reinforcement learning, demonstrating a keen awareness of complex graph structures. Striking a harmonious balance between solution quality and running time, our method stands out with superior efficiency and steady performance. Our model trained on small graphs is highly scalable and consistently generates high-quality solutions, achieving a speedup of more than 2000 times to Gurobi on instances with 1000 nodes. The experiments on Shanghai road networks further demonstrate its practical value in solving real-world problems. The source codes are available at https://github.com/AryaGuo/PPO-swap. WWW ’25, Sydney, NSW, Australia

Paratrouper: Exploratory Creation of Character Cast Visuals Using Generative AI

Fri, 25 Apr 2025 00:00:00 GMT

Paratrouper: Exploratory Creation of Character Cast Visuals Using Generative AI Leong, Joanne; Ledo, David; Driscoll, Thomas; Grossman, Tovi; Fitzmaurice, George; Anderson, Fraser Great characters are critical to the success of many forms of media, such as comics, games, and films. Designing visually compelling casts of characters requires significant skill and consideration, and there is a lack of specialized tools to support this endeavor. We investigate how AI-driven image-generation techniques can empower creatives to explore a variety of visual design possibilities for individual and groups of characters. Informed by interviews with character designers, Paratrouper is a multi-modal system that enables creating and experimenting with multiple permutations for character casts and visualizing them in various contexts as part of a holistic approach to design. We demonstrate how Paratrouper supports different aspects of the character design process, and share insights from its use by eight creators. Our work highlights the interplay between creative agency and serendipity, as well as the visual interrelationships among character aesthetics. Joanne Leong, David Ledo, Thomas Driscoll, Tovi Grossman, George Fitzmaurice, and Fraser Anderson. 2025. Paratrouper: Exploratory Creation of Character Cast Visuals Using Generative AI. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). Association for Computing Machinery, New York, NY, USA, Article 189, 1–20.

FiberCircuits: A Miniaturization Framework To Manufacture Fibers That Embed Integrated Circuits

Sat, 27 Sep 2025 00:00:00 GMT

FiberCircuits: A Miniaturization Framework To Manufacture Fibers That Embed Integrated Circuits Honnet, Cedric; Babatain, Wedyan; Luo, Yiyue; Kilic Afsar, Ozgun; Bensahel, Chloe; Nicita, Sarah; Zhu, Yunyi; Danielescu, Andreea; Gershenfeld, Neil; Paradiso, Joseph UIST ’25, Busan, Republic of Korea

FIP: Endowing Robust Motion Capture on Daily Garment by Fusing Flex and Inertial Sensors

Fri, 25 Apr 2025 00:00:00 GMT

FIP: Endowing Robust Motion Capture on Daily Garment by Fusing Flex and Inertial Sensors Zheng, Ruonan; Fang, Jiawei; Yao, Yuan; Gao, Xiaoxia; Zuo, Chengxu; Guo, Shihui; Luo, Yiyue What if our clothes could capture our body motion accurately? This paper introduces Flexible Inertial Poser (FIP), a novel motion-capturing system using daily garments with two elbow-attached flex sensors and four Inertial Measurement Units (IMUs). To address the inevitable sensor displacements in loose wearables which degrade joint tracking accuracy significantly, we identify the distinct characteristics of the flex and inertial sensor displacements and develop a Displacement Latent Diffusion Model and a Physics-informed Calibrator to compensate for sensor displacements based on such observations, resulting in a substantial improvement in motion capture accuracy. We also introduce a Pose Fusion Predictor to enhance multimodal sensor fusion. Extensive experiments demonstrate that our method achieves robust performance across varying body shapes and motions, significantly outperforming SOTA IMU approaches with a 19.5% improvement in angular error, a 26.4% improvement in elbow angular error, and a 30.1% improvement in positional error. FIP opens up opportunities for ubiquitous human-computer interactions and diverse interactive applications such as Metaverse, rehabilitation, and fitness analysis. Our project page can be seen at Flexible Inertial Poser. CHI ’25, Yokohama, Japan

GPU-accelerated dynamic nonlinear optimization with ExaModels and MadNLP

Wed, 26 Feb 2025 00:00:00 GMT

GPU-accelerated dynamic nonlinear optimization with ExaModels and MadNLP Pacaud, François; Shin, Sungho We investigate the potential of Graphics Processing Units (GPUs) to solve large-scale nonlinear programs with a dynamic structure. Using ExaModels, a GPU-accelerated automatic differentiation tool, and the interior-point solver MadNLP, we significantly reduce the time to solve dynamic nonlinear optimization problems. The sparse linear systems formulated in the interior-point method is solved on the GPU using a hybrid solver combining an iterative method with a sparse Cholesky factorization, which harness the newly released NVIDIA cuDSS solver. Our results on the classical distillation column instance show that despite a significant pre-processing time, the hybrid solver allows to reduce the time per iteration by a factor of $\mathbf{2 5}$ for the largest instance. 2024 IEEE 63rd Conference on Decision and Control (CDC), Milan, Italy, 2024

Scalable Primal Decomposition Schemes for Large-Scale Infrastructure Networks

Sun, 01 Jun 2025 00:00:00 GMT

Scalable Primal Decomposition Schemes for Large-Scale Infrastructure Networks Engelmann, Alexander; Shin, Sungho; Pacaud, François; Zavala, Victor M The operation of large-scale infrastructure networks requires scalable optimization schemes. To guarantee safe system operation, a high degree of feasibility in a small number of iterations is important. Decomposition schemes can help to achieve scalability. In terms of feasibility, however, classical approaches, such as the alternating direction method of multipliers (ADMMs), often converge slowly. In this work, we present primal decomposition schemes for hierarchically structured strongly convex quadratic programs. These schemes offer high degrees of feasibility in a small number of iterations in combination with global convergence guarantees. We benchmark their performance against the centralized off-the-shelf interior-point solver Ipopt and ADMM on problems with up to 300 000 decision variables and constraints. We find that the proposed approaches solve problems as fast as Ipopt, but with reduced communication and without requiring a full model exchange. Moreover, the proposed schemes achieve a higher accuracy than ADMM.

Coplanarity of rooted spanning-tree vectors

Fri, 05 Dec 2025 00:00:00 GMT

Coplanarity of rooted spanning-tree vectors Polettini, Matteo; Harunari, Pedro E.; Cengio, Sara D.; Lecomte, Vivien Employing a recent technology of tree surgery, we prove a “deletion–constriction” formula for products of rooted spanning-trees on weighted directed graphs that generalizes deletion–contraction on undirected graphs. The formula implies that, letting τ x ∅ , τ x + , and τ x - be the rooted spanning-tree polynomials obtained, respectively, by removing both directed edges between two vertices, or by forcing the tree to pass through either edge, the vectors ( τ x ∅ , τ x + , τ x - ) are coplanar for all roots x . We deploy the result to give an alternative derivation of a recently found mutual linearity of stationary currents of Markov chains. We generalize deletion–constriction and current linearity for two pairs of edges and conjecture that similar results may hold for arbitrary subsets of edges.

Search for the decay B0 → ϕϕ

Wed, 03 Dec 2025 00:00:00 GMT

Search for the decay B0 → ϕϕ Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; Aleksiejunas, R. A search for the decay B0 → ϕϕ is made using pp collision data collected with the LHCb detector at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb−1. No significant signal is observed, and an upper limit on the branching fraction of 1.3 (1.4) × 10−8 at 90 (95)% confidence level is set. This result supersedes the previous LHCb study and improves the upper limit by a factor of two.

Regulating Sommerfeld resonances for multi-state systems and higher partial waves

Wed, 03 Dec 2025 00:00:00 GMT

Regulating Sommerfeld resonances for multi-state systems and higher partial waves Parikh, Aditya; Sato, Ryosuke; Slatyer, Tracy R. Long-range attractive interactions between dark matter particles can significantly enhance their annihilation, particularly at low velocities. This “Sommerfeld enhancement” is typically computed by evaluating the deformation of the two-particle wavefunction due to the long-range potential, while ignoring the physics associated with the annihilation, and then scaling the appropriate annihilation matrix elements by factors that depend on the wavefunction in the limit where the particles approach zero relative separation. It has long been recognized that this approach is a valid approximation only in the limit where the annihilation rate is small, and breaks down in the regime where the enhanced annihilation rate approaches the unitarity bound, in which case ignoring the impact of the annihilation physics on the two-particle wavefunction cannot be justified and leads to apparent violations of unitarity. In the case where the physics relevant to annihilation occurs at a parametrically shorter distance scale (higher energy scale) compared with the long-range potential, we provide a simple prescription for correcting the Sommerfeld enhancement for the effects of the short-range physics, valid for all partial waves and for systems where multiple states are coupled by the long-range potential.

A field guide to event-shape observables using optimal transport

Tue, 02 Dec 2025 00:00:00 GMT

A field guide to event-shape observables using optimal transport Cesarotti, Cari; LeBlanc, Matt We lay out the phenomenological behavior of event-shape observables evaluated by solving optimal transport problems between collider events and reference geometries — which we name manifold distances — to provide guidance regarding their use in future studies. This discussion considers several choices related to the metric used to quantify these distances. We explore the differences between the various options, for the first time using a combination of analytical studies and simulated minimum-bias and multi-jet events. Making judicious choices when defining the metric and reference geometry can improve sensitivity to interesting signal features and reduce sensitivity to non-perturbative effects in QCD. The goal of this article is to provide a ‘field guide’ that can inform how choices made when defining a manifold distance can be tailored for the analysis at-hand.

Search for the lepton-flavour-violating decays B0 → K*0τ±e∓

Wed, 26 Nov 2025 00:00:00 GMT

Search for the lepton-flavour-violating decays B0 → K*0τ±e∓ Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. A first search at LHCb for the lepton-flavour-violating decays B0 → K*0τ±e∓ is presented. The analysis is performed using a sample of proton-proton collision data, collected with the LHCb detector at a centre-of-mass energy of 13 TeV between 2016 and 2018, corresponding to an integrated luminosity of 5.4 fb−1. No significant signal is observed, and upper limits on the branching fractions are determined to be B B 0 → K ∗ 0 τ − e + < 5.9 7.1 × 10 − 6 and B B 0 → K ∗ 0 τ + e − < 4.9 5.9 × 10 − 6 at the 90% (95%) confidence level. These results correspond to the current most stringent upper limits for b → sτl transitions.

Guidelines for environmental life cycle assessment of cultivated meat

Wed, 03 Dec 2025 00:00:00 GMT

Guidelines for environmental life cycle assessment of cultivated meat Blackstone, Nicole T.; Pavlova, Anisiya; Trinidad, Kirsten R.; Nikkhah, Amin; Sinke, Pelle; Heller, Martin; Duncan-Duggal, Joe; Ridoutt, Brad; Smetana, Sergiy; Makov, Tamar; Shabtai, Shira Purpose Cultivated meat is produced by growing animal cells in vitro without using, or reducing the use of, animals for meat, poultry, or seafood production. Responsibly and consistently investigating the environmental impacts of cultivated meat is essential to provide reliable performance benchmarks and realistic comparisons with animal-based production systems. In this contribution, we provide technical, actionable guidelines for conducting life cycle assessments (LCAs) of cultivated meat and highlight further research needs for the field. Methods We assembled a global team of recognized and active scientists in cultivated meat LCA, livestock systems LCA, and ISO LCA standards to develop this set of guidelines using a workshop (in person and online) and online meetings, as well as asynchronous feedback, to reach consensus. Results and discussion These guidelines provide specifications throughout the four phases of LCA, from goal definition to the interpretation of LCA results. Data gaps, including the availability and quality of feed or food-grade culture media component inventories, are among the areas highlighted for further exploration. Conclusion We invite LCA practitioners to apply these guidelines when investigating cultivated meat systems to increase the consistency and reliability of environmental impact evaluations for these emerging products.

Sharp Bound for the Erdős–Straus Non-averaging Set Problem

Wed, 03 Dec 2025 00:00:00 GMT

Sharp Bound for the Erdős–Straus Non-averaging Set Problem Pham, Huy T.; Zakharov, Dmitrii A set of integers A is non-averaging if there is no element a in A which can be written as an average of a subset of A not containing a . We show that the largest non-averaging subset of { 1 , … , n } has size n 1 / 4 + o ( 1 ) , thus solving the Erdős–Straus problem. We also determine the largest size of a non-averaging set in a d -dimensional box for any fixed d . Our main tool includes the structure theorem for the set of subset sums due to Conlon, Fox and the first author, together with a result about the structure of a point set in nearly convex position.

Seasonal variations of the atmospheric muon neutrino spectrum measured with IceCube

Mon, 01 Dec 2025 00:00:00 GMT

Seasonal variations of the atmospheric muon neutrino spectrum measured with IceCube IceCube Collaboration This study presents an analysis of seasonal variations in the atmospheric muon neutrino flux, using 11.3 years of data from the IceCube Neutrino Observatory. By leveraging a novel spectral unfolding method, we explore the energy range from 125 GeV to 10 TeV for zenith angles from 90 ∘ to 110 ∘ , corresponding to the Antarctic atmosphere. Our findings reveal that the differential measurement of the amplitudes of the seasonal variation is consistent with an energy-dependent decrease reaching ( - 4.5 ± 1.2)% during Austral winter and increase to (+ 3.9 ± 1.3)% during Austral summer relative to the annual average at 10 TeV. While the unfolded flux exceeds the model predictions by up to 30%, the differential measurement of the seasonal to annual average flux remains unaffected. The measured seasonal variations of the muon neutrino spectrum are consistent with theoretical predictions using the MCEq code and the NRLMSISE-00 atmospheric model.

Capacity lower bound for the Ising perceptron

Sun, 23 Feb 2025 00:00:00 GMT

Capacity lower bound for the Ising perceptron Ding, Jian; Sun, Nike We consider the Ising perceptron with gaussian disorder, which is equivalent to the discrete cube { - 1 , + 1 } N intersected by M random half-spaces. The perceptron’s capacity is the largest integer M N for which the intersection is nonempty. It is conjectured by Krauth and Mézard (1989) that the (random) ratio M N / N converges in probability to an explicit constant α ⋆ ≐ 0.83 . Kim and Roche (1998) proved the existence of a positive constant γ such that γ ⩽ M N / N ⩽ 1 - γ with high probability; see also Talagrand (1999). In this paper we show that the Krauth–Mézard conjecture α ⋆ is a lower bound with positive probability, under the condition that an explicit univariate function S ⋆ ( λ ) is maximized at λ = 0 . Our proof is an application of the second moment method to a certain slice of perceptron configurations, as selected by the so-called TAP (Thouless, Anderson, and Palmer, 1977) or AMP (approximate message passing) iteration, whose scaling limit has been characterized by Bayati and Montanari (2011) and Bolthausen (2012).

Tackling the UK’s regional economic inequality: binding constraints and avenues for policy intervention

Mon, 14 Aug 2023 00:00:00 GMT

Tackling the UK’s regional economic inequality: binding constraints and avenues for policy intervention Stansbury, Anna; Turner, Dan; Balls, Ed We analyse binding constraints to productivity growth in the UK’s regions outside London and the greater South East. These analyses challenge a number of common arguments about the UK’s regional economic inequality problem. We find little evidence consistent with the hypotheses (i) that low shares of university graduates remain the primary constraint on growth for the UK’s regions; (ii) that there is a generalised issue with access to finance for firms outside the South East; or (iii) that low or falling regional migration rates are to blame for the persistence of the UK’s regional economic inequalities. Instead, we find evidence consistent with (i) a specific relative shortage of STEM degrees; (ii) binding transport infrastructure constraints within major non-London conurbations; (iii) a failure of public innovation policy to support clusters beyond the South East, in particular through the regional distribution of public support for Research and Development (R&D); and (iv) missed opportunities for higher internal mobility due to London’s overheating housing market. We also find some suggestive evidence consistent with constraints on access to early-stage equity financing for high-growth-potential SMEs in certain regions.

Chile’s Inclusion Law: the arduous drive to regulate an unequal education system, 2006–19

Wed, 16 Apr 2025 00:00:00 GMT

Chile’s Inclusion Law: the arduous drive to regulate an unequal education system, 2006–19 Cummings, Peter MM; Mizala, Alejandra; Schneider, Ben Ross Chile’s Inclusion Law, passed in 2015, significantly increased government regulation of one of the most privatised education systems in the world and provided major redistributive benefits. How did Chile’s government succeed in passing and implementing this legislation in the face of a powerful and cohesive opposition? Our study finds that student protesters served as the initial impetus, shaping the education debate and increasing the political salience and urgency of education reform. In line with power resource theory, other left movement organisations and voters used their power to support redistributive education reform, and Bachelet’s centre-left coalition followed through on its mandate by proposing the Inclusion Law. Also, a well-connected policy network helped articulate problems with the status quo and shaped the specifics of the education bill. To develop this argument, the paper draws on historical information on the student movement in Chile, quantitative data on education stakeholder appearances in the press, public opinion surveys, and detailed analysis of the 13-month legislative proceedings – to explain the law’s passage in congress. To underscore the significance of the Inclusion Law and to contextualise the Chilean case, the paper also compares Chile to other countries with nation-wide school choice systems.

Bayesian Network–Based Fault Diagnostic System for Nuclear Power Plant Assets

Sat, 04 Mar 2023 00:00:00 GMT

Bayesian Network–Based Fault Diagnostic System for Nuclear Power Plant Assets Zhao, Xingang; Wang, Xinyan; Golay, Michael W Future advances in nuclear power technologies call for enhanced operator advice and autonomous control capabilities that can leverage simpler designs and increased safety features to reduce reliance on human labor. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for the plant structures, systems, and components (SSCs) of interest. The primary goal is to aid plant personnel in (1) deducing the probabilistic performance status of the monitored SSCs and (2) detecting impending faults/failures. The task of estimating conditional failure probability is a bidirectional inference problem, and a logical approach is to use the Bayesian network (BN) method. As a knowledge-based explainable artificial intelligence tool and a probabilistic graphical model, BN offers reasoning capability under uncertainty, graphical representation emulating physical behavior of the target SSC, and interpretability of the model structure and results. This paper provides a systematic overview of the BN technique and the software tools for implementing BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgment can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. The focus is on failure-prone and risk-important balance of plant assets, especially for cases with strong operator involvement. Two example case studies on the failure of (1) a centrifugal pump and (2) an electric motor are conducted to demonstrate the usefulness and technical feasibility of the proposed BN-based fault diagnostic system using an expert system shell.

Your body tells more than words – predicting perceived meeting productivity through body signals

Sun, 03 Mar 2024 00:00:00 GMT

Your body tells more than words – predicting perceived meeting productivity through body signals Zeyda, Maximilian; Stracke, Selina; Knipfer, Kristin; Gloor, Peter A The productivity of work meetings is mostly assessed through post-hoc questionnaires. These questionnaires are impractical as they require additional time after the meeting has ended. Thus, measuring meeting productivity in a non-intrusive manner is of practical and theoretical importance. Extending research on physiological arousal and the healthy physiological variability thesis to the context of work meetings, we take a novel approach and investigate whether physiological arousal and the variability in implicit body signals of meeting participants (heart rate, arm movements, and speech intensity) can be accurate predictors of perceived meeting productivity. In a preliminary field study, we used smartwatches and tracked the body signals of 16 team members in 26 team meetings. The perceived meeting productivity was assessed at the end of the meetings. Partly supporting our assumptions, multilevel analysis showed that the variance in arm acceleration was a significant predictor of perceived meeting productivity. Further, using a random forest classifier, we accurately predicted perceived meeting productivity in roughly 60% of the cases with body signals. This study adds to previous work on meeting effectiveness by tapping into the potential of wearables to provide valid information about perceived meeting productivity. Cultivating our findings, we discuss lessons learned for future research.

Phonon Sampling Method for Inelastic Thermal Neutron Scattering Events

Thu, 03 Aug 2023 00:00:00 GMT

Phonon Sampling Method for Inelastic Thermal Neutron Scattering Events Trainer, Amelia; Forget, Benoit Accurate representation of thermal neutron scattering in Monte Carlo transport simulations requires that the molecular vibrations of the target material be accounted for. Historically, this has been achieved by precomputing large multidimensional tables that are a function of temperature and the cosine of the scattering angle, as well as incoming and outgoing neutron energy. Most commonly used sampling techniques for thermal neutron scattering rely on large multidimensional tables, where higher resolution results in an increase in required memory and attempts to reduce memory can result in grid coarseness errors. An alternative sampling method is introduced here that is a significant departure from precomputed tables and instead relies on a more physical model of the scattering behavior. The phonon sampling method classifies neutron scattering events by the number of phonons excited/de-excited during the scattering collision. In doing so, energy exchange may be obtained via rejection sampling, and an analytical representation of the momentum exchange is obtained. This sampling method has been tested on graphite, yttrium hydride, and uranium nitride, and preliminary implementation of the phonon sampling method shows accurate results for angular and energy distributions, though resulting in up to a 40% slowdown in overall calculation time. This notable slowdown is countered, however, by a large reduction in storage (over 99% reduction compared to standard multidimensional tables).

Assessment of Engineering Turbulence Models in Buoyant Diabatic Turbulent Flow

Tue, 02 Jul 2024 00:00:00 GMT

Assessment of Engineering Turbulence Models in Buoyant Diabatic Turbulent Flow Wiser, Ralph; Baglietto, Emilio Turbulent heat transfer in buoyancy-dominated flows is a challenging problem for computational fluid dynamics (CFD). Many authors attribute model error in these conditions to the Reynolds analogy. We leverage a brand-new direct numerical simulation database to evaluate the performance of several popular turbulence models in buoyant diabatic channel flow. We find that heat transfer results are relatively accurate, with a Nusselt number error less than 20%. However, the turbulent flow solution is very inaccurate, with wall shear overpredicted by up to 100%. This indicates significant turbulence model error in such flows. We determined that the dominant sources of model error are missing physics in the algebraic Reynolds stress framework and the simple buoyancy production term used in industrial CFD. We suggest that future modeling efforts focus on these two sources of model error. We demonstrate that the Reynolds analogy is not the dominant source of model error.

The insurgent smart city: How a social movement created an alternative imaginary of the smart city

Mon, 17 Jul 2023 00:00:00 GMT

The insurgent smart city: How a social movement created an alternative imaginary of the smart city Stokols, Andrew Urban scholars have critiqued smart cities for their association with neoliberal governance, narrow focus on quantifiable aspects of urban systems, and failure to incorporate citizens’ needs or aspirations. The “smart city” remains a contested concept and as such is subject to reappropriation. Here, I analyze the case of an urban social movement, the 2019–2020 Hong Kong Anti-ELAB protests, as an alternative, “insurgent smart city.” Following from an earlier network analysis of Telegram channels used during the protests, I show how the communications system underpinning much of the protest action simultaneously enabled coordination while also remaining open to grassroots decision-making and innovations of new protest formats as the movement responded to countertactics of the state and police. Telegram channels linked neighborhood-based organizing to the citywide movement. These actions not only emulated but also inverted top-down visions of a total urban information system underpinning many smart city projects. Framing the Hong Kong Anti-ELAB protests as an insurgent smart city offers an alternative sociotechnical imaginary of what smart cities could be, and raises possibilities for an “insurgent digital citizenship” as an alternative to both state and platform-mediated forms of digital citizenship.

The evolution of global cybersecurity norms in the digital age: A longitudinal study of the cybersecurity norm development process

Fri, 03 May 2024 00:00:00 GMT

The evolution of global cybersecurity norms in the digital age: A longitudinal study of the cybersecurity norm development process Madnick, Benjamin; Huang, Keman; Madnick, Stuart Developing cybersecurity norms and global normative cybersecurity behaviors play an increasingly critical role in global cybersecurity governance. This paper takes a longitudinal approach to analyze cybersecurity norms development activities during the period 1997–2020. A total of 206 individual cases were collected, and 233 individual cybersecurity norms were identified and compiled into 25 subject categories. Categorizing the norm subjects alongside the frequency of cases and norms identified each year allowed for a longitudinal view of cyber norm activities and the evolution in developments over these years. This examination enables us to categorize cybersecurity norms, including their dynamic focus and evolution patterns. By studying those viewed as “successful,” we gain guidance regarding the construction of global cybersecurity governance in the digital age.

Anthropology Has One Job (On Genocide in the United States)

Mon, 02 Jan 2023 00:00:00 GMT

Anthropology Has One Job (On Genocide in the United States) Lowry, David Shane In an introductory anthropology course, the instructor might provide a definition of anthropology similar to this: “Anthropology is the most scientific of the humanities, and it is the most humanistic of the sciences.” If something like that is said, it stems from a statement in Anthropology, a 1964 book by famed anthropologist Eric Wolf in which he attempted to define the discipline. Wolf’s approach came at a time when many anthropologists were attempting to intervene in the historical telling of the world.Footnote1 In particular, Wolf argued that non-Europeans were also participants in global, colonial processes. The value of Wolf’s voice—indeed, the value of most anthropology at the time—was that it offered a wide-scale view of human events for which the anthropologist was merely an observer, hence not responsible.

Online Bidding under RoS Constraints without Knowing the Value

Tue, 22 Apr 2025 00:00:00 GMT

Online Bidding under RoS Constraints without Knowing the Value Vijayan, Sushant; Feng, Zhe; Padmanabhan, Swati; Shanmugam, Karthikeyan; Suggala, Arun; Wang, Di We consider the problem of bidding in online advertising, where an advertiser aims to maximize value while adhering to budget and Return-on-Spend (RoS) constraints. Unlike prior work that assumes knowledge of the value generated by winning each impression (e.g., conversions), we address the more realistic setting where the advertiser must simultaneously learn the optimal bidding strategy and the value of each impression opportunity. This introduces a challenging exploration-exploitation dilemma: the advertiser must balance exploring different bids to estimate impression values with exploiting current knowledge to bid effectively. To address this, we propose a novel Upper Confidence Bound (UCB)-style algorithm that carefully manages this trade-off. Via a rigorous theoretical analysis, we prove that our algorithm achieves Õ(₲T log(|B|T) ) regret and constraint violation, where T is the number of bidding rounds and B is the domain of possible bids. This establishes the first optimal regret and constraint violation bounds for bidding in the online setting with unknown impression values. Moreover, our algorithm is computationally efficient and simple to implement. We validate our theoretical findings through experiments on synthetic data, demonstrating that our algorithm exhibits strong empirical performance compared to existing approaches. WWW ’25, April 28–May 2, 2025, Sydney, NSW, Australia.

Tactile Vega-Lite: Rapidly Prototyping Tactile Charts with Smart Defaults

Fri, 25 Apr 2025 00:00:00 GMT

Tactile Vega-Lite: Rapidly Prototyping Tactile Charts with Smart Defaults Chen, Mengzhu (Katie); Pedraza Pineros, Isabella; Satyanarayan, Arvind; Zong, Jonathan Tactile charts are essential for conveying data to blind and low vision (BLV) readers but are difficult for designers to construct. Non-expert designers face barriers to entry due to complex guidelines, while experts struggle with fragmented and time-consuming workflows that involve extensive customization. Inspired by formative interviews with expert tactile graphics designers, we created Tactile Vega-Lite (TVL): an extension of Vega-Lite that offers tactile-specific abstractions and synthesizes existing guidelines into a series of smart defaults. Predefined stylistic choices enable non-experts to produce guideline-compliant tactile charts quickly. Expert users can override defaults to tailor customizations for their intended audience. In a user study with 12 tactile graphics creators, we show that Tactile Vega-Lite enhances flexibility and consistency by automating tasks like adjusting spacing and translating braille while accelerating iterations through pre-defined textures and line styles. Through expert critique, we also learn more about tactile chart design best practices and design decisions. CHI ’25, Yokohama, Japan

Toward Everyday Perceptual and Physiological Augmentation

Sat, 27 Sep 2025 00:00:00 GMT

Toward Everyday Perceptual and Physiological Augmentation Tao, Yujie; Gemicioglu, Tan; Chin, Sam; Huang, Bingjian; Brooks, Jas; Follmer, Sean; Lopes, Pedro; Nanayakkara, Suranga Human senses are fundamental to how we interpret and interact with the world. Computing devices are increasingly coupled with the human sensory system through interfaces such as smart glasses, earbuds, and wristbands. This opens up opportunities to dynamically mediate, modify, and augment perceptual experiences and physiological processes through multisensory stimulation. These devices go beyond assistive technologies designed for individuals with sensory impairments (e.g., hearing aids) and are now available for everyday use. Applications range from enriching immersive entertainment experiences to supporting well-being through multisensory interventions. The UIST community has been a key venue for introducing many proof-of-concept prototypes in multisensory stimulation. However, gaps remain in systematically understanding how such technologies can be designed, studied, and contextualized in long-term, everyday use. This workshop will examine barriers to transitioning prototypes from proof-of-concepts into systems for real-world use. The session will feature keynote talks, demo sessions, and an interactive device-swap activity where participants exchange and wear different devices during the afternoon session, and conclude with an open discussion to develop implementation frameworks. UIST Adjunct ’25, Busan, Republic of Korea

GyFoam: Fabricating Lattice Foam with Customizable Stiffness through Uniform Expansion

Sat, 27 Sep 2025 00:00:00 GMT

GyFoam: Fabricating Lattice Foam with Customizable Stiffness through Uniform Expansion Wang, Guanyun; Chen, Haotian; Wang, Yufeng; Li, Songyun; Tao, Yue; Qi, Fanke; Cao, Lizhuo; Jin, Xiao; Tao, Ye; Li, Jiaji We present GyFoam, a fabrication method integrating foam material with lattice structure to enable controlled and uniform expansion, which supports high-quality forming in appearance and customizable stiffness in function, using standard 3D printers, filaments, commercially available Thermo-Expandable Microspheres and silicone. To achieve customizable stiffness, we propose two methods: modifying material concentration and adjusting lattice structural parameters. Additionally, we propose three shape control strategies for creating complex shapes: bending, wavy edges, and internal doming. Furthermore, a user-friendly design tool is established for users to construct lattice structures, preview basic deformation, and generate mold models for printing. Finally, through a series of applications, we validate GyFoam’s practical usage of fabricating large objects, wearable products, enabling flexible interactions and creating aesthetic designs. UIST ’25, Busan, Republic of Korea

EmbroChet: A Hybrid Textile Fabrication Approach for 3D Personalized Handicraft via Heat-Shrinking

Sat, 27 Sep 2025 00:00:00 GMT

EmbroChet: A Hybrid Textile Fabrication Approach for 3D Personalized Handicraft via Heat-Shrinking Wang, Guanyun; Wang, Zhiqi; Li, Fanyu; Liu, Qinyang; Dong, Tianshu; Hong, Zixiang; Li, Xinyi; Zhu, Kuangqi; Li, Jiaji; Zhao, Xiaoliang; Tao, Ye We propose EmbroChet, a hybrid approach that bridges digital fabrication and textile craftsmanship, empowering individuals unfamiliar with intricate craft techniques to design and fabricate 3D textile handicrafts intuitively. EmbroChet allows the creation of handicrafts by embroidering chain stitches (a fundamental embroidery technique) onto a heat-shrinkable film, which subsequently self-transforms from a 2D composite to a 3D textile through a freely controllable heating triggering process. Through a single stitch type, the method enables custom designs and intricate geometries to be achieved without complex manual skills that often requires expertise between different stitch knowledge. To better demonstrate EmbroChet, we propose a design tool that includes shape-changing libraries to assist users in customizing 3D shapes. The evaluation demonstrates its unique strength in balancing geometric complexity and textile softness. Furthermore, our workshop verifies the feasibility of EmbroChet, exploring its potential for personalized textile fabrication, and synergizing the precision of digital fabrication with the tactile artistry of textile craftsmanship. UIST ’25, Busan, Republic of Korea

Meta-antenna: Mechanically Frequency Reconfigurable Metamaterial Antennas

Sat, 27 Sep 2025 00:00:00 GMT

Meta-antenna: Mechanically Frequency Reconfigurable Metamaterial Antennas AlAlawi, Marwa; Zheng, Regina; Ahn, Sooyeon; Yan, Katherine; Sethapakdi, Ticha; Zhu, Junyi; Mueller, Stefanie We introduce Meta-antenna, a design and fabrication pipeline for creating frequency reconfigurable antennas while making use of a single type of mechanical metamaterial structure. Unlike traditional static antenna systems with fixed radiation patterns and frequency responses per geometry, Meta-antenna leverages mechanical reconfiguration to alter the radiation and geometry characteristics of the antenna, making it more versatile for sensing and communication. Meta-antenna provides a design space of resonance frequency from 500 MHz to 6.3 GHz (≥ 10dB) upon the structure’s compression, bending, or rotation. Additionally, we provide an Ansys-based editor that allows users to generate metamaterial antenna geometries and simulate their resonance frequency. We also provide a code template for Meta-antenna based sensing interactions. Our technical evaluation demonstrates that our fabricated Meta-antenna structures remain functional even after 10,000 compression cycles. Finally, we contribute three example applications showcasing Meta-antenna’s potential in adaptive personal devices, smart home systems, and tangible user interfaces. UIST ’25, Busan, Republic of Korea

Computational Tailor-Making for Personalized, Shape-changing, and Sustainable Fabrics

Sat, 27 Sep 2025 00:00:00 GMT

Computational Tailor-Making for Personalized, Shape-changing, and Sustainable Fabrics Narumi, Koya; Hirose, Yuichi; Lee, Hsuanling; Larsson, Maria; He, Liang; Leake, Mackenzie; Forman, Jack; Farahi, Behnaz; Yao, Lining; Igarashi, Takeo Fabrics are fundamental elements of our daily lives, which are woven, knitted, or embroidered into diverse products like clothing and furniture. Recent advances in materials science and digital fabrication have enabled us to fabricate personalized and responsive fabric products computationally and interactively, which we call “computational tailor-making.” In this workshop, we will build an interdisciplinary network of researchers on computational tailor-making and discuss (1) computational fabric design, (2) novel fabric fabrication tools, (3) shape-changing fabrics, and (4) sustainable fabric production, from the viewpoint of HCI. The workshop session will help attendees build a shared vision, recognize potential challenges, find unexpected solutions and ideas, collaborate beyond disciplines, and explore the possible connection to industries. UIST Adjunct ’25, Busan, Republic of Korea

Ori-TENG: 3D Printed Origami Tessellations as Triboelectric Nanogenerators for Self-powered Sensing and Energy Harvesting

Sat, 27 Sep 2025 00:00:00 GMT

Ori-TENG: 3D Printed Origami Tessellations as Triboelectric Nanogenerators for Self-powered Sensing and Energy Harvesting AlAlawi, Marwa; Wang, Kexin; Zheng, Regina; Chan, Adelene; Feick, Martin; Mueller, Stefanie We introduce Ori-TENG, a design and fabrication framework for 3D printed origami tessellations that function as triboelectric sensors and energy harvesters. Ori-TENG structures are 3D printed flat in a single step, then folded, with internal electrical routing optimized for both folding mechanics and triboelectric performance. UIST Adjunct ’25, Busan, Republic of Korea

GreenMix: Energy-Efficient Serverless Computing via Randomized Sketching on Asymmetric Multi-Cores

Sat, 15 Nov 2025 00:00:00 GMT

GreenMix: Energy-Efficient Serverless Computing via Randomized Sketching on Asymmetric Multi-Cores Basu Roy, Rohan; Patel, Tirthak; Li, Baolin; Samsi, Siddharth; Gadepally, Vijay; Tiwari, Devesh GreenMix is motivated by the renewed interest in asymmetric multi-core processors and the emergence of the serverless computing model. Asymmetric multi-cores offer better energy and performance trade-offs by placing different core types on the same die. However, existing serverless scheduling techniques do not leverage these benefits. GreenMix is the first serverless work to reduce energy and serverless keep-alive costs while meeting QoS targets by leveraging asymmetric multi-cores. GreenMix employs randomized sketching, tailored for serverless execution and keep-alive, to perform within 10% of the optimal solution in terms of energy efficiency and keep-alive cost reduction. GreenMix’s effectiveness is demonstrated through evaluations on clusters of ARM big.LITTLE and Intel Alder Lake asymmetric processors. It outperforms competing state-of-the-art schedulers, offering a novel approach for energy-efficient serverless computing. SC ’25, St Louis, MO, USA

Scalable and Low Power Localization for Underwater Robots

Fri, 21 Nov 2025 00:00:00 GMT

Scalable and Low Power Localization for Underwater Robots Afzal, Sayed Saad; Rademacher, Jack; Chen, Weitung; Wang, Purui; Adib, Fadel Localization is a critical task for underwater robots, yet today’s underwater localization systems are limited by their accuracy, scalability, and/or energy consumption (i.e., longevity). We present the design, implementation, and evaluation of EchoBLUE– an accurate, scalable, and low-power localization system for underwater robots. In EchoBLUE, an underwater robot transmits SONARstyle (FMCW) signals, and leverages ultra-low power underwater backscatter nodes as location anchors. EchoBLUE’s design introduces two key innovations. The first is a novel doppler compensation mechanism that enables it to accurately self-localize under mobility: the technique employs a cross-chirp mechanism that exploits the quad-band nature of the resulting backscatter response to overcome the rangedoppler ambiguity. Second, it introduces the first semi-active retrodirective underwater backscatter design and uses it for location anchors; this design achieves wide bandwidth to backscatter the full FMCW signal, enabling fine-grained localization. We implemented a proof of concept prototype of EchoBLUE by building a base station mounted on a BlueROV2 underwater robot and custom-designed low-power retrodirective location anchors deployed in a pool. Our evaluation across 700 real-world trials demonstrates that EchoBLUE achieves a median 3D localization accuracy of 28 cm and 90th percentile of 48 cm. Moreover, these anchors consume only 740 𝜇𝑊 for semi-active backscatter, paving the way for truly low-power and scalable underwater localization.

A polyurethane-urea elastomer at low to extreme strain rates

Fri, 15 Sep 2023 00:00:00 GMT

A polyurethane-urea elastomer at low to extreme strain rates Lee, Jaehee; Veysset, David; Hsieh, Alex J; Rutledge, Gregory C; Cho, Hansohl A finite strain nonlinear constitutive model is presented to study the extreme mechanical behavior of a polyurethane-urea (PUU) well suited for many engineering applications. The micromechanically- and thermodynamically based constitutive model captures salient features in resilience and dissipation in the material from low to extreme strain rates. The extreme deformation features are further elucidated by laser-induced micro-particle impact tests for the material, where an ultrafast strain rate ( > 1 0 6 s−1) incurs. Numerical simulations for the strongly inhomogeneous deformation events are in good agreement with the experimental data, supporting the predictive capabilities of the constitutive model for the extreme deformation features of the PUU material over at least 9 orders of magnitude in strain rates ( 1 0 − 3 to 1 0 6 s−1).

Molecular simulation of flow-enhanced nucleation of polyethylene crystallites in biaxial flows

Wed, 17 Apr 2024 00:00:00 GMT

Molecular simulation of flow-enhanced nucleation of polyethylene crystallites in biaxial flows Gangal, Chinmay S; Rutledge, Gregory C Flow-enhanced nucleation (FEN) of n-pentacontahectane (C150) under biaxial extensional flows of varying strain rate ratios is studied using nonequilibrium molecular dynamics simulation. The nucleation rates thus calculated are used to test previously published FEN models based on invariants of the conformation tensor of Kuhn segments and the extra stress tensor. Models based on the conformation tensor provide a more accurate description of FEN observed in biaxial flow simulations than those based on the extra stress tensor. In addition, the formation of nematic domains previously reported to be stabilized by shear or extensional flow is absent in equibiaxial flows. However, such domains do form in non-equibiaxial flows, and nucleation occurs in these domains preferentially. The shape and orientation of nuclei formed under biaxial flows of various strengths and strain rate ratios are also reported.

Cholesterol Nanofiber Patches with Sustainable Oil Delivery Eliminate Inflammation in Atopic Skin

Fri, 12 Jul 2024 00:00:00 GMT

Cholesterol Nanofiber Patches with Sustainable Oil Delivery Eliminate Inflammation in Atopic Skin Sroczyk, Ewa A; Tarasiuk, Aleksandra; Talar, Marcin; Rutledge, Gregory C; Makaro, Adam; Misztal, Zofia; Wołyniak, Maria; Berniak, Krzysztof; Sałaga, Maciej; Fichna, Jakub; Stachewicz, Urszula Atopic skin is dry and itchy and lacks integrity. Impaired skin barrier results from altered lipid composition of the skin. A crucial skin lipid, cholesterol, provides flexibility and homeostasis of the cell membranes' lipid bilayer. Cholesterol-based creams and natural oils, especially blackcurrant seed oil, are beneficial for skin care as they hydrate the skin and improve its integrity. The major atopic symptom, skin dryness, can be overcome by the application of porous patches enhanced with cholesterol and natural oil. The base of the patches is constructed of polyimide (PI) nanofibers with cholesterol coatings and externally added blackcurrant seed oil. The presence of cholesterol in PI mats hinders the passage of oil through the patches to the skin, resulting in sustained and prolonged skin hydration. The theoretical and numerical investigations of oil dynamics in porous mats confirmed the experimental results, showing a prolonged skin hydration effect up to 6 h. Additionally, as demonstrated by in vivo tests on atopic mice, cholesterol patches lower serum immunoglobulin E levels and expression of proinflammatory cytokines in the skin, thereby accelerating skin healing. Our results hold great promise for the long-term application of the patches in atopic dermatitis treatment.

The Polls and the U.S. Presidential Election in 2020 …. and 2024

Tue, 30 May 2023 00:00:00 GMT

The Polls and the U.S. Presidential Election in 2020 …. and 2024 Barnett, Arnold; Sarfati, Arnaud Arguably, the single greatest determinant of U.S. public policy is the identity of the president. And if trusted, polls not only provide forecasts about presidential-election outcomes but can act to shape those outcomes. Looking ahead to the 2024 U.S. presidential election and recognizing that polls before the 2020 presidential election were sharply criticized, we consider whether such harsh assessments are warranted. Initially, we explore whether such polls as processed by the sophisticated aggregator FiveThirtyEight successfully forecast actual 2020 state-by-state outcomes. We evaluate FiveThirtyEight’s forecasts using customized statistical methods not used previously, methods that take account of likely correlations among election outcomes in similar states. We find that, taken together, the pollsters and FiveThirtyEight did an excellent job in predicting who would win in individual states, even those “tipping point” states where forecasting is more difficult. However, we also find that FiveThirtyEight underestimated Donald Trump’s vote shares by state to a modest but statistically significant extent. We further consider how the polls performed when the more primitive aggregator Real Clear Politics combined their results, and then how well single statewide polls performed without aggregation. It emerges that both Real Clear Politics and the individual polls fared surprisingly well.

The Profession’s Vanguards: Arab Architects and Regional Architectural Exchange, 1900–50

Wed, 19 Jul 2023 00:00:00 GMT

The Profession’s Vanguards: Arab Architects and Regional Architectural Exchange, 1900–50 Abusaada, Nadi Writings on architecture in the Middle East during the first half of the twentieth century have often focused on the legacies of colonial architects and planners in shaping Middle Eastern cities and built environments. Contrarily, this article focuses on the overlooked history of the first milieu of trained Arab architects in Middle East, focusing on Palestine, Syria, Lebanon and Egypt. Examining unstudied historical materials and archives, it maps out the trajectories of individual architects as well as the architectural profession more generally in this period of rapid change. It is divided into three main sections that highlight this: first, architecture’s transition from the Ottoman guild system to its professionalisation by the turn of the century; second, the mobility of architectural knowledge and expertise in the Arab region following the First World War; finally, the development of a new institutionalised architectural culture that sought to cultivate bonds between Arab architects not only in their individual countries, but also regionally throughout the Arab world towards the mid-twentieth century.

Fossil fuel divestment and public climate change policy preferences: an experimental test in three countries

Sun, 26 Feb 2023 00:00:00 GMT

Fossil fuel divestment and public climate change policy preferences: an experimental test in three countries Schwartz, Joshua A.; Lendway, Paul; Nuri, Abolfazl Divestment is a prominent strategy championed by activists to induce positive social change. For example, the current fossil fuel divestment movement includes over 1,500 institutions that control $40 trillion in assets. A primary pathway through which divestment is theorized to be effective is by influencing public beliefs and policy preferences, thus pressuring policymakers to take action. However, prior research only tests this argument via qualitative case studies. We assess the impact of exposure to information about fossil fuel divestment on public opinion through the use of national survey experiments in three major greenhouse gas emitters: the U.S., India, and South Africa. We find surprisingly little evidence that exposure to information about the fossil fuel divestment movement can increase public support for policies that address climate change. Our findings suggest that divestment movements may be less effective at changing beliefs and policy preferences than previously realized.

“Sculptress Interprets Land’s Spirit”: Elizabeth Wyn Wood, the Group of Seven, and analogy as equivalence

Tue, 26 Sep 2023 00:00:00 GMT

“Sculptress Interprets Land’s Spirit”: Elizabeth Wyn Wood, the Group of Seven, and analogy as equivalence Nikčević, Hana Canadian sculptor Elizabeth Wyn Wood (1903–66), best known for her modernist landscape sculptures, has since the inception of her artistic career been compared, through analogy, with the Group of Seven (fl. 1920–33), Canada’s enduringly famous and overtly nationalistic collective of modernist landscape painters. Critics claimed that Wood “achieved for sculpture what the Group of Seven achieved for painting” and, occasionally, invoked specific Group artists, dubbing Wood the “Lawren Harris of sculpture.” Analogizing across disciplines, the Wood/Group likening appears to posit a formal comparison in gendered language: the Group’s bold, decorative portrayals of the northern Ontario “wilderness” find clear visual comparands in Wood’s abstracted compositions of the same region. In this article, however, I demonstrate that the apparently visual basis for the comparison is inextricable from the textual discourse fundamental to Canadian art in the early twentieth century and beyond; it is only through analyzing this discourse that an understanding of the Wood/Group analogy can be reached. The Group ostensibly pioneered the first genuine Canadian landscape aesthetic; through immersing himself in the land, the mythology went, the Canadian artist learned to paint Canada on its own terms. This landscape artist-as-woodsman myth was a form of settler indigenization by which Canada laid cultural claim to colonized land. Analogy frames Wood as not an epigone but an equal of the Group: in producing organically, anew, a genuine Canadian landscape aesthetic for sculpture, Wood “achieved for sculpture what the Group of Seven achieved for painting”—its deployment as a medium in the service of Canada’s land claim.

A Landscape “Difficult to Describe”: The Model Village and the Capital City

Wed, 22 Mar 2023 00:00:00 GMT

A Landscape “Difficult to Describe”: The Model Village and the Capital City Springstubb, Phoebe In mid-twentieth-century Punjab, grassroots development projects sought to modernize the countryside by decentralizing power to villages. The capital city Chandigarh, built in the same period, seems to represent the opposite: a national symbol of a newly independent India’s centralized power. Yet, this article argues, rural and urban were reciprocal and volatile counterparts. Through the work of M.S. Randhawa, it reorients analysis of Chandigarh to reveal how the materiality of landscape itself was a medium for territorial planning, indelibly linking—and managing the distinctions between—city and countryside. A botanist and civil servant, Randhawa used landscape to realize modernizing agendas and to constrain social change in projects from model villages and a “bioaesthetic” plan for the city to new land-grant universities that ushered in the Green Revolution’s industrialized agriculture. His work offers a revisionist history of development’s practitioners and periodization. It shows how an uneven fabric of late-colonial rural uplift shaped the contours of postcolonial, state-directed agrarian transformation. Following the civil servant in the landscape, this article calls for the grounding of abstract theories like development and state formation in histories of their local inflections.

Policy Search through Genetic Programming and LLM-assisted Curriculum Learning

Fri, 31 Oct 2025 00:00:00 GMT

Policy Search through Genetic Programming and LLM-assisted Curriculum Learning Jorgensen, Steven; Nadizar, Giorgia; Pietropolli, Gloria; Manzoni, Luca; Medvet, Eric; O'Reilly, Una-May; Hemberg, Erik Curriculum learning (CL) consists in using a diverse set of user-provided test cases, with varying levels of difficulty and organized in a suitable progression, for learning a policy. The quality of test cases is important to allow optimization techniques as genetic programming (GP) to solve policy search problems. In this work, we evaluate large language models (LLMs) as providers of test cases for GP-based policy search. We consider two policy search tasks, a single-player and a multi-player game, and four LLMs differing in complexity and specialization, which we prompt in order to generate suitable test cases for the two games. We experimentally assess the intrinsic quality of LLM-generated test cases and their utility when inserted in a curriculum consumed by a GP optimization. We evaluate the robustness of the approach with respect to the way cases are scheduled in curricula and with respect to the policy representation, for which we use both graphs and linear programs evolved by GP. We observe that the effectiveness of LLM-assisted CL depends on both the choice of LLM and the design of the prompting and scheduling strategies. These findings highlight important considerations for leveraging LLMs in automated curriculum design for GP-based optimization.

Robust Biharmonic Skinning Using Geometric Fields

Tue, 28 Oct 2025 00:00:00 GMT

Robust Biharmonic Skinning Using Geometric Fields Dodik, Ana; Sitzmann, Vincent; Solomon, Justin; Stein, Oded Bounded bihramonic weights are a popular tool used to rig and deform characters for animation, to compute reduced-order simulations, and to define feature descriptors for geometry processing. They necessitate tetrahedralizing the volume bounded by the surface, introducing the possibility of meshing artifacts or tetrahedralization failure. We introduce a mesh-free and robust automatic skinning technique that generates weights comparable to the current state of the art, but works reliably even on open surfaces, triangle soups, and point clouds where current methods fail. We achieve this through the use of a specialized Lagrangian representation enabled by the advent of hardware ray-tracing, which circumvents the need for finite elements while optimizing the biharmonic energy and enforcing boundary conditions. The flexibility of our formulation allows us to integrate artistic control through weight painting during the optimization. We offer a thorough qualitative and quantitative evaluation of our method.

SquareLoop: Explore Optimal Authentication Block Strategy for ML

Sat, 18 Oct 2025 00:00:00 GMT

SquareLoop: Explore Optimal Authentication Block Strategy for ML Strzeszynski, Jan; Tong, Jianming; Lee, Kyungmi; Xiong, Nathan; Parashar, Angshuman; Emer, Joel; Krishna, Tushar; Yan, Mengjia Off-chip memory in ML accelerators is vulnerable to both hardware and software attack, which needs encryption and authentication. Precise performance modeling of it requires (1) representation of authentication blocks (AuthBlock) to cover the full design space of shapes and orientations, and (2) precise memory behavior modeling, as encryption and authentication mainly increase memory traffic. This paper introduces 𝑆 2Loop, a framework that resolves these challenges by introducing (1) flexible, all-level partitioning based AuthBlocks for ensuring full coverage of the entire design space, (2) a realistic layout-based memory model, and (3) an Mapping-LayoutAuthentication co-search algorithm to explore the drastic combinatorial design space to figure out optimal mapping, layout, and AuthBlock shape choice for multi-layer workloads. SquareLoop’s detailed memory model helps find better mapping to achieve 1.32× speedup on ResNet18 compared to the SotA SecureLoop, and our latency predictions are validated to within 7.3% of an RTL implementation. 𝑆 2𝐿𝑜𝑜𝑝 also achieve up-to 1.08×/1.82× overall speedup for authenticated ResNet18/MobileNet-V3 on various accelerators with AuthBlock and Mapping co-searching. We open-source 𝑆 2Loop to provide a powerful and validated tool for designing efficient, secure accelerators at https://github.com/maeri-project/squareloop. HASP 2025, Seoul, Republic of Korea

A Close Look at RMP Entry Caching and Its Security Implications in SEV-SNP

Sat, 18 Oct 2025 00:00:00 GMT

A Close Look at RMP Entry Caching and Its Security Implications in SEV-SNP Bagia, Alexis; Ulitzsch, Vincent; Trujillo, Dani?l; Li, Mengyuan; Yan, Mengjia; Seifert, Jean-Pierre AMD’s Secure Encrypted Virtualization (SEV) technology is a pivotal component in AMD server processors that boosts cloud computing security. It achieves this by offering transparent memory encryption and managing keys for protecting virtual machines (VMs), independently of the hypervisor’s trustworthiness. The latest iteration, SEV-Secure Nested Paging (SEV-SNP), introduces memory integrity protection through a data structure called the Reverse Map Table (RMP), which maps system physical addresses to guest physical addresses and tracks ownership of physical pages. The RMP is maintained in a dedicated region in DRAM. As every memory write triggers a check against an RMP entry, caching RMP entries is crucial to alleviating the RMP’s performance impact. However, caching may create new security challenges, as it can introduce new microarchitectural side-channels. In addition, maintaining cache coherence is crucial for the RMP’s security guarantees. However, so far, neither the details of the RMP’s caching behavior nor its security implications have been explored. This paper aims to fill this gap by conducting a systematic study of the RMP’s caching behavior. Through reverse engineering, we identify that the RMP is not only cached in the TLB, but also in the L1D and L2 data cache. Interestingly, this caching depends on the access type on Zen 5. We also uncover the mechanisms by which cache coherence across the TLB is enforced. We find that each update to the RMP table triggers a global TLB flush across all cores. Finally, we present several potential security implications and demonstrate that an attacker can exploit RMP’s caching to leak physical address information. A user process can leak 6 bits of the Physical Frame Number (PFN) of its pages via the L1D cache within 2.5 µs per page, with success rates of 97 % (Zen 4) and 99 % (Zen 3 and Zen 5).

Guarding LLM-aided Software Transformation Tasks via Component Exoskeletons

Mon, 13 Oct 2025 00:00:00 GMT

Guarding LLM-aided Software Transformation Tasks via Component Exoskeletons Lamprou, Evangelos; Kalhauge, Christian; Rinard, Martin; Vasilakis, Nikos Large language models (LLMs) are achieving state-of-the-art results across a wide variety of software transformation tasks---including translating across languages and lifting opaque software components to high-level languages. Unfortunately, their results are often subtly incorrect, insecure, or underperformant---affecting the widespread deployment of these LLM-driven techniques in settings that go beyond the narrow scope of academic papers. This paper posits that such widespread deployment crucially depends on developing appropriate model guardrails for safeguarding the results of the transformation process. Such guardrails can be supported by component exoskeletons, tunable partial specifications extracted mostly automatically from the original, pre-transformed component. Exoskeletons serve as component projections that supplement, and often go through, the entire transformation process, confirming that the new, transformed component meets the original specifications. They show promise on several real-world scenarios and unearth exciting research directions. PACMI ’25, October 13-16, 2025, Seoul, Republic of Korea

The Continuous Tensor Abstraction: Where Indices Are Real

Thu, 09 Oct 2025 00:00:00 GMT

The Continuous Tensor Abstraction: Where Indices Are Real Won, Jaeyeon; Ahrens, Willow; Collin, Teodoro Fields; Emer, Joel S.; Amarasinghe, Saman This paper introduces the continuous tensor abstraction, allowing indices to take real-number values (e.g., A[3.14]). It also presents continuous tensor algebra expressions, such as Cx,y = Ax,y ∗ Bx,y, where indices are defined over a continuous domain. This work expands the traditional tensor model to include continuous tensors. Our implementation supports piecewise-constant tensors, on which infinite domains can be processed in finite time. We also introduce a new tensor format for efficient storage and a code generation technique for automatic kernel generation. For the first time, our abstraction expresses domains like computational geometry and computer graphics in the language of tensor programming. Our approach demonstrates competitive or better performance to hand-optimized kernels in leading libraries across diverse applications. Compared to hand-implemented libraries on a CPU, our compiler-based implementation achieves an average speedup of 9.20× on 2D radius search with ∼60× fewer lines of code (LoC), 1.22× on genomic interval overlapping queries (with ∼18× LoC saving), and 1.69× on trilinear interpolation in Neural Radiance Field (with ∼6× LoC saving).

A Domain-Specific Probabilistic Programming Language for Reasoning about Reasoning (Or: A Memo on memo)

Thu, 09 Oct 2025 00:00:00 GMT

A Domain-Specific Probabilistic Programming Language for Reasoning about Reasoning (Or: A Memo on memo) Chandra, Kartik; Chen, Tony; Tenenbaum, Joshua B.; Ragan-Kelley, Jonathan The human ability to think about thinking ("theory of mind") is a fundamental object of study in many disciplines. In recent decades, researchers across these disciplines have converged on a rich computational paradigm for modeling theory of mind, grounded in recursive probabilistic reasoning. However, practitioners often find programming in this paradigm challenging: first, because thinking-about-thinking is confusing for programmers, and second, because models are slow to run. This paper presents memo, a new domain-specific probabilistic programming language that overcomes these challenges: first, by providing specialized syntax and semantics for theory of mind, and second, by taking a unique approach to inference that scales well on modern hardware via array programming. memo enables practitioners to write dramatically faster models with much less code, and has already been adopted by several research groups.

Pyrosome: Verified Compilation for Modular Metatheory

Thu, 09 Oct 2025 00:00:00 GMT

Pyrosome: Verified Compilation for Modular Metatheory Jamner, Dustin; Kammer, Gabriel; Nag, Ritam; Chlipala, Adam We present Pyrosome, a generic framework for modular language metatheory that embodies a novel approach to extensible semantics and compilation, implemented in Coq. Common techniques for semantic reasoning are often tied to the specific structures of the languages and compilers that they support. Contextual equivalence is difficult to work with directly, and both logical relations and transition system-based approaches typically fix a specific notion of effect globally. While modular transition systems have been effective in imperative settings, they are suboptimal for functional code. These limitations restrict the extension and composition of semantics in these systems. In Pyrosome, verified compilers are fully extensible, meaning that to extend a language simply requires defining and verifying the compilation of the new feature, reusing the old correctness theorem for all other cases. The novel enabling idea is an inductive formulation of equivalence preservation that supports the addition of new rules to the source language, target language, and compiler. Pyrosome defines a formal, deeply embedded notion of programming languages with semantics given by dependently sorted equational theories, so all compiler-correctness proofs boil down to type-checking and equational reasoning. We support vertical composition of any compilers expressed in our framework in addition to feature extension. Since our design requires compilers to support open programs, our correctness guarantees support linking with any target code of the appropriate type. As a case study, we present a multipass compiler from System F with simple references, through CPS translation and closure conversion. Specifically, we demonstrate how we can build such a compiler incrementally by starting with a compiler for simply typed lambda-calculus and adding natural numbers, the unit type, recursive functions, and a global heap, then extending judgments with a type environment and adding type abstraction, all while reusing the original theorems. We also present a linear version of the simply typed CPS pass and compile a small imperative language to the simply typed target to show how Pyrosome handles substructural typing and imperative features.

What You See Is What It Does: A Structural Pattern for Legible Software

Thu, 09 Oct 2025 00:00:00 GMT

What You See Is What It Does: A Structural Pattern for Legible Software Meng, Eagon; Jackson, Daniel The opportunities offered by LLM coders (and their current limitations) demand a reevaluation of how software is structured. Software today is often “illegible”—lacking a direct correspondence between code and observed behavior—and insufficiently modular, leading to a failure of three key requirements of robust coding: incrementality (the ability to deliver small increments by making localized changes), integrity (avoiding breaking prior increments) and transparency (making clear what has changed at build time, and what actions have happened at runtime). A new structural pattern offers improved legibility and modularity. Its elements are concepts and synchronizations: fully independent services and event-based rules that mediate between them. A domain-specific language for synchronizations allows behavioral features to be expressed in a granular and declarative way (and thus readily generated by an LLM). A case study of the RealWorld benchmark is used to illustrate and evaluate the approach. Onward! ’25, Singapore, Singapore

Gauguin, Descartes, Bayes: A Diurnal Golem’s Brain

Thu, 09 Oct 2025 00:00:00 GMT

Gauguin, Descartes, Bayes: A Diurnal Golem’s Brain Chandra, Kartik; Liu, Amanda; Ragan-Kelley, Jonathan; Tenenbaum, Joshua B. A "quine" is a deterministic program that prints itself. In this essay, I will show you a "gauguine": a probabilistic program that infers itself. A gauguine is repeatedly asked to guess its own source code. Initially, its chances of guessing correctly are of course minuscule. But as the gauguine observes more and more of its own previous guesses, it detects patterns of behavior and gains information about its inner workings. This information allows it to bootstrap self-knowledge, and ultimately discover its own source code. We will discuss how—and why—we might write a gauguine, and what we stand to learn by constructing one. Onward! ’25, Singapore, Singapore

Low-Fidelity vs. High-Fidelity Spatial Design in Virtual Reality for Non-professionals

Tue, 29 Oct 2024 00:00:00 GMT

Low-Fidelity vs. High-Fidelity Spatial Design in Virtual Reality for Non-professionals Wei, Lan; Dai, Chenyue; Peng, Xuening; Tong, Xin; Liu, Can In spatial design, non-professionals lack effective hands-on opportunities to participate in the design process. Although VR platforms can support spatial design with immersive interaction, existing tools simply provide high-fidelity 3D objects for users to choose and place around. Low-fidelity design approach is rarely supported, nor investigated in this context. In this work, we present a user study comparing low-fidelity and high-fidelity spatial design in VR. Eighteen participants were recruited to use both versions of a prototype with varied geometric fidelity to complete home designs. Their design outcome and intent was evaluated by professional designers. Our findings show, the low-fidelity version allowed participants to think more openly and creatively, leading to a more holistic expression of their design intent and needs, while the high-fidelity version promoted users’ thinking of realistic scenarios. We discuss the design implications and how they can be combined in co-design activities. CHCHI 2024, Shenzhen, China

Trans Data: A Research and Design Agenda from Trans Activists' Transformative Data Science

Thu, 16 Oct 2025 00:00:00 GMT

Trans Data: A Research and Design Agenda from Trans Activists' Transformative Data Science Stevens, Nikko; D'Ignazio, Catherine; Doğan, Amelia Trans activists play a deeply important role in caring for and advocating for the transgender community using data. Through an interview study with 16 trans activists working in trans-led and trans-serving organizations in the United States, we document how they use restorative/transformative data science processes of resolving, researching, recording, and refusing and using data. We incorporate their data practices with trans technology and trans competent interaction design approaches to propose a research agenda for trans data: materially improve trans lives, cross data boundaries, and constantly engage in power analysis. We expound on how a trans data research agenda can benefit data advocacy and CSCW research and design.

Techno-economic analysis and life cycle assessment for catalytic fast pyrolysis of mixed plastic waste

Mon, 05 Jun 2023 00:00:00 GMT

Techno-economic analysis and life cycle assessment for catalytic fast pyrolysis of mixed plastic waste Yadav, Geetanjali; Singh, Avantika; Dutta, Abhijit; Uekert, Taylor; DesVeaux, Jason S; Nicholson, Scott R; Tan, Eric CD; Mukarakate, Calvin; Schaidle, Joshua A; Wrasman, Cody J; Carpenter, Alberta C; Baldwin, Robert M; Román-Leshkov, Yuriy; Beckham, Gregg T yrolysis of waste plastics has gained interest as a candidate chemical recycling technology. To examine the potential of this approach, we conducted a techno-economic analysis (TEA) and life cycle assessment (LCA) of a conceptual catalytic fast pyrolysis (CFP) facility that converts 240 metric tons/day of mixed plastic waste. The modeled base case predicts the minimum selling price (MSP) of a benzene, toluene, and xylenes (BTX) mixture at $1.07 per kg when co-products are sold at their average market prices. We predict that the aromatic product stream can be cost-competitive with virgin BTX mixtures ($0.68/kg) if the mixed waste plastics are available for less than $0.10/kg or if crude oil prices exceed $60/barrel. Moreover, we estimate that CFP-based conversion of waste plastics can reduce the total supply chain energy use by 24% but with a 2.4-fold increase in greenhouse gas (GHG) emissions per kilogram of BTX, relative to incumbent manufacturing process. Sensitivity analysis highlights that feedstock cost, co-product selling prices, capital cost for product separations, and operating costs are key cost drivers. Further, we examine three additional CFP processes that differ in product composition, namely naphtha, and a case where the products are rich in either C2–C4 olefins or BTX aromatic hydrocarbons. Whereas the MSP of naphtha ($2.18/kg) is ∼4-fold higher than virgin naphtha, both the olefin-rich and aromatics-rich product cases exhibit a potential reduction in MSP up to 40%, with a 21%–45% reduction in total supply chain energy and 2.2–3.8-fold increase in GHG emissions relative to incumbent manufacturing processes. LCA predicts that the CFP process exhibits lower fossil fuel depletion than virgin manufacturing across all cases as well as lower acidification, ozone depletion, and smog formation for select cases, but high utility and feedstock preparation requirements result in poorer performance across other metrics. Overall, this study highlights important process parameters for improving CFP of mixed waste plastics from economic and environmental perspectives.

Togedule: Scheduling Meetings with Large Language Models and Adaptive Representations of Group Availability

Thu, 16 Oct 2025 00:00:00 GMT

Togedule: Scheduling Meetings with Large Language Models and Adaptive Representations of Group Availability Song, Jaeyoon; Ashktorab, Zahra; Malone, Thomas Scheduling is a perennial-and often challenging-problem for many groups. Existing tools are mostly static, showing an identical set of choices to everyone, regardless of the current status of attendees' inputs and preferences. In this paper, we propose Togedule, an adaptive scheduling tool that uses large language models to dynamically adjust the pool of choices and their presentation format. With the initial prototype, we conducted a formative study (N=10) and identified the potential benefits and risks of such an adaptive scheduling tool. Then, after enhancing the system, we conducted two controlled experiments, one each for attendees and organizers (total N=66). For each experiment, we compared scheduling with verbal messages, shared calendars, or Togedule. Results show that Togedule significantly reduces the cognitive load of attendees indicating their availability and improves the speed and quality of the decisions made by organizers.

Core‐passivation: A concept for stable core‐shell nanoparticles in aqueous electrocatalysis

Thu, 19 Jan 2023 00:00:00 GMT

Core‐passivation: A concept for stable core‐shell nanoparticles in aqueous electrocatalysis Göhl, Daniel; Paciok, Paul; Wang, Zhenshu; Kang, Jin Soo; Heggen, Marc; Mayrhofer, Karl JJ; Román‐Leshkov, Yuriy; Ledendecker, Marc The stability of nanoparticles is a major challenge in thermal and electrocatalysis. This is especially true for core‐shell nanoparticles where only a few monolayers of noble metal protect the usually non‐noble core material. In this work, we utilize the practical nobility concept to engineer stable core‐shell nanoparticles with a self‐passivating core material. Specifically, tantalum carbide as core material in combination with a 1–3 monolayer thick platinum shell exhibits exceptional stability in aqueous media. The core‐shell catalyst shows no sign of structural changes after 10,000 degradation cycles up to 1.0 VRHE. Due to the efficient passivation of tantalum carbide at the solid/liquid interface, the dissolution reduces by a factor of eight compared to bare Pt. Our findings confirm that passivating core materials are highly beneficial for the stabilization of core‐shell nanomaterials in aqueous media. They open up new ways for the rational design of cost‐efficient but stable non‐noble core – platinum shell nanoparticles where harsh, oxidizing conditions are employed.

Interdependence of Solvent and Catalyst Selection on Low Pressure Hydrogen-Free Reductive Catalytic Fractionation

Mon, 13 Mar 2023 00:00:00 GMT

Interdependence of Solvent and Catalyst Selection on Low Pressure Hydrogen-Free Reductive Catalytic Fractionation Facas, Gregory G; Brandner, David G; Bussard, Jeremy R; Román-Leshkov, Yuriy; Beckham, Gregg T Hydrogen-free reductive catalytic fractionation (RCF) is a promising method to produce aromatic compounds directly from native biomass without the use of external hydrogen gas. In this work, we show that by using high boiling point diols as a solvent in hydrogen-free RCF, reaction pressures can be reduced by an order of magnitude compared to conventional RCF with methanol and hydrogen gas, while still producing appreciable aromatic monomer yields. Importantly, the use of diols with secondary alcohol functional groups increases hydrogenation activity on Ru/C, Pt/C, and Ni/C, measured by the yield of aromatic compounds with saturated propyl side chains, compared to processing in ethylene glycol, indicating that the choice of solvent and catalyst together can be tuned to control product selectivity of aromatic monomers in RCF.

Propylene Metathesis over Molybdenum Silicate Microspheres with Dispersed Active Sites

Wed, 20 Sep 2023 00:00:00 GMT

Propylene Metathesis over Molybdenum Silicate Microspheres with Dispersed Active Sites Skoda, David; Zhu, Ran; Hanulikova, Barbora; Styskalik, Ales; Vykoukal, Vit; Machac, Petr; Simonikova, Lucie; Kuritka, Ivo; Poleunis, Claude; Debecker, Damien P; Román-Leshkov, Yuriy In this work, we demonstrate that amorphous and porous molybdenum silicate microspheres are highly active catalysts for heterogeneous propylene metathesis. Homogeneous molybdenum silicate microspheres and aluminum-doped molybdenum silicate microspheres were synthesized via a nonaqueous condensation of a hybrid molybdenum biphenyldicarboxylate-based precursor solution with (3-aminopropyl)triethoxysilane. The as-prepared hybrid metallosilicate products were calcined at 500 °C to obtain amorphous and porous molybdenum silicate and aluminum-doped molybdenum silicate microspheres with highly dispersed molybdate species inserted into the silicate matrix. These catalysts contain mainly highly dispersed MoOx species, which possess high catalytic activity in heterogeneous propylene metathesis to ethylene and butene. Compared to conventional silica-supported MoOx catalysts prepared via incipient wetness impregnation (MoIWI), the microspheres with low Mo content (1.5–3.6 wt %) exhibited nearly 2 orders of magnitude higher steady-state propylene metathesis rates at 200 °C, approaching site time yields of 0.11 s–1.

Accessing monomers from lignin through carbon–carbon bond cleavage

Fri, 04 Oct 2024 00:00:00 GMT

Accessing monomers from lignin through carbon–carbon bond cleavage Palumbo, Chad T; Ouellette, Erik T; Zhu, Jie; Román-Leshkov, Yuriy; Stahl, Shannon S; Beckham, Gregg T Lignin, the heterogeneous aromatic macromolecule found in the cell walls of vascular plants, is an abundant feedstock for the production of biochemicals and biofuels. Many valorization schemes rely on lignin depolymerization, with decades of research focused on accessing monomers through C–O bond cleavage, given the abundance of β–O–4 bonds in lignin and the large number of available C–O bond cleavage strategies. Monomer yields are, however, invariably lower than desired, owing to the presence of recalcitrant C–C bonds whose selective cleavage remains a major challenge in catalysis. In this Review, we highlight lignin C–C cleavage reactions, including those of linkages arising from biosynthesis (β–1, β–5, β–β and 5–5) and industrial processing (5–CH2–5 and α–5). We examine multiple approaches to C–C cleavage, including homogeneous and heterogeneous catalysis, photocatalysis and biocatalysis, to identify promising strategies for further research and provide guidelines for definitive measurements of lignin C–C bond cleavage.

Direct propylene epoxidation via water activation over Pd-Pt electrocatalysts

Thu, 04 Jan 2024 00:00:00 GMT

Direct propylene epoxidation via water activation over Pd-Pt electrocatalysts Chung, Minju; Maalouf, Joseph H; Adams, Jason S; Jiang, Chenyu; Román-Leshkov, Yuriy; Manthiram, Karthish Direct electrochemical propylene epoxidation by means of water-oxidation intermediates presents a sustainable alternative to existing routes that involve hazardous chlorine or peroxide reagents. We report an oxidized palladium-platinum alloy catalyst (PdPtOx/C), which reaches a Faradaic efficiency of 66 ± 5% toward propylene epoxidation at 50 milliamperes per square centimeter at ambient temperature and pressure. Embedding platinum into the palladium oxide crystal structure stabilized oxidized platinum species, resulting in improved catalyst performance. The reaction kinetics suggest that epoxidation on PdPtOx/C proceeds through electrophilic attack by metal-bound peroxo intermediates. This work demonstrates an effective strategy for selective electrochemical oxygen-atom transfer from water, without mediators, for diverse oxygenation reactions.

Interaction Configurations and Prompt Guidance in Conversational AI for Question Answering in Human-AI Teams

Thu, 16 Oct 2025 00:00:00 GMT

Interaction Configurations and Prompt Guidance in Conversational AI for Question Answering in Human-AI Teams Song, Jaeyoon; Ashktorab, Zahra; Pan, Qian; Dugan, Casey; Geyer, Werner; Malone, Thomas Understanding the dynamics of human-AI interaction in question answering is crucial for enhancing collaborative efficiency. Extending from our initial formative study, which revealed challenges in human utilization of conversational AI support, we designed two configurations for prompt guidance: a Nudging approach, where the AI suggests potential responses for human agents, and a Highlight strategy, emphasizing crucial parts of reference documents to aid human responses. Through two controlled experiments, the first involving 31 participants and the second involving 106 participants, we compared these configurations against traditional human-only approaches, both with and without AI assistance. Our findings suggest that effective human-AI collaboration can enhance response quality, though merely combining human and AI efforts does not ensure improved outcomes. In particular, the Nudging configuration was shown to help improve the quality of the output when compared to AI alone. This paper delves into the development of these prompt guidance paradigms, offering insights for refining human-AI collaborations in conversational question-answering contexts and contributing to a broader understanding of human perceptions and expectations in AI partnerships.

Pushing on an Open Door: Japan’s Evolutionary Security Posture

Thu, 13 Jul 2023 00:00:00 GMT

Pushing on an Open Door: Japan’s Evolutionary Security Posture Heginbotham, Eric; Leiter, Samuel; Samuels, Richard J At the 2022 Shangri-La Dialogue, Japan’s Prime Minister Fumio Kishida warned defense ministers from across the Indo-Pacific region that “Ukraine today may be East Asia tomorrow.” Russia’s war of aggression and China’s tacit support for the invasion have amplified the urgency of the threat posed by China’s economic and military rise and have informed material changes to Japanese defense policy.

Dissecting User Experience of Social Virtual Reality: A Tale of Five Platforms

Thu, 16 Oct 2025 00:00:00 GMT

Dissecting User Experience of Social Virtual Reality: A Tale of Five Platforms Cheng, Ruizhi; Li, Jie; Chen, Songqing; Han, Bo Social virtual reality (VR) has the potential to replace conventional online social media by offering quasi-realworld social experiences. As such, it has been extensively examined by the research community. However, existing studies fall short of providing a comprehensive understanding of how different aspects of social VR platforms interact to affect user experience. Motivated by this limitation, we conduct a user study with Oculus Quest 2 headsets and dissect the user experience on five social VR platforms. We evenly and randomly divide 42 participants into short-term (spending 10–30 minutes/platform) and long-term (spending at least 120 minutes/platform) groups. Besides employing surveys and interviews, we measure the frame rate and resolution of these platforms and explore how various factors interplay to influence the user experience of social VR. Our findings reveal that the frame rate, resolution, and interactive events of social VR platforms have a more significant impact on the experience of long-term users compared to short-term users. The scalability limitations of these platforms, as evidenced by decreased frame rates with the increasing number of concurrent users, result in an increased prevalence of motion sickness among long-term users, negatively impacting their overall experience. Moreover, the absence of highly interactive events also deteriorates their overall experience, and the low resolution combined with the lack of interactive events further decreases their sense of social presence. Additionally, our study demonstrates several common limitations negatively affecting the experience of both long-term and short-term users. For example, the harassment prevention mechanisms on all five platforms are inadequate, and being harassed has a detrimental effect on users’ overall experience and sense of social presence. The avatar embodiment of investigated platforms has limited contribution to users’ sense of social presence, mainly due to the lack of realism and full-body tracking. Our findings call for more research in scalability support, motion sickness relief, interactive event design, harassment prevention, and avatar development for improving social VR platforms in the future.

Investigation of critical heat flux enhancement on nanoengineered surfaces in pressurized subcooled flow boiling using infrared thermometry

Tue, 28 Mar 2023 00:00:00 GMT

Investigation of critical heat flux enhancement on nanoengineered surfaces in pressurized subcooled flow boiling using infrared thermometry Wang, Chi; Su, Guanyu; Akinsulire, Olorunsola; Zhang, Limiao; Rahman, Md Mahamudur; Bucci, Matteo Enhancing the flow boiling critical heat flux (CHF) is beneficial to the economics and safety margins of many industrial applications cooled by boiling heat transfer. While many studies have shown that surfaces with hydrophilic nanoscale and micro-scale features can enhance CHF in pool boiling, it is still not clear how these engineered surfaces affect the CHF in subcooled flow boiling at ambient pressure, let alone high-pressure conditions. Here, two nano-engineered surfaces, i.e., a surface coated with a porous layer of hydrophilic silica nanoparticles and a surface coated with zinc oxide nanowires, were tested. Flow boiling tests with a 10 K subcooling and a mass flux of 1000 kg/(m2·s) were conducted at 1 bar and 4 bars using infrared thermometry diagnostics. At 1 bar, the CHF enhancement is around 15% for both coatings. At 4 bars, the CHF enhancement is around 17% for the nanowire surface, and around 25% for the nano-porous surface. Infrared thermometry measurements reveal that the CHF enhancement comes from an increase of both two-phase heat transfer and single-phase heat transfer mechanisms, which is due to a change of bubble dynamics on the nanoengineered surfaces. It is also shown that the boiling crisis can be predicted using a percolation model based on Monte Carlo (MC) simulations.

Connecting Digitalization and Sustainability: Proptech in the Real Estate Operations and Management

Thu, 27 Apr 2023 00:00:00 GMT

Connecting Digitalization and Sustainability: Proptech in the Real Estate Operations and Management Tan, Zhengzhen; Miller, Norm G. Digitalization of building operations and maintenance enable real-time monitoring, optimization, and automation for environment sustainability. Proptech startups are important change agents in accelerating building digitalization. While many researchers analyze economic and environmental savings from deployment of digital technology, far less attention has been devoted to challenges for proptech startups to transform efficiency gains into viable businesses. We analyze the Unissu global proptech startup database to reveal the scope and competitive landscape of proptech solutions. We conduct interviews with building owners/operators to understand what impedes the adoption of proptech solutions. Despite rapid growth, ongoing challenges remain for sustainability-focused proptech firms with three adoption barriers: (1) integration of the technology stacks; (2) integration of technology stacks with business processes; and (3) integration of owner/operators and the occupants’ solutions. Proptech with applications that work with existing infrastructure or provide more complete holistic solutions with extensive capital reserves, are more likely to survive. Other pathways include having data standardization and security protocols in place; technology partnership with technology incumbents; and effective communication with owners/operators to fill the knowledge gap. Findings can provide insights to emerging digital proptech startups as they spearhead market adoption in the real estate sector and monetize the sustainability value creation.

Driver response and recovery following automation initiated disengagement in real-world hands-free driving

Wed, 29 Mar 2023 00:00:00 GMT

Driver response and recovery following automation initiated disengagement in real-world hands-free driving Gershon, Pnina; Mehler, Bruce; Reimer, Bryan Objective Advanced driver assistance systems are increasingly available in consumer vehicles, making the study of drivers’ behavioral adaptation and the impact of automation beneficial for driving safety. Concerns over driver’s being out-of-the-loop, coupled with known limitations of automation, has led research to focus on time-critical, system-initiated disengagements. This study used real-world data to assess drivers’ response to, and recovery from, automation-initiated disengagements by quantifying changes in visual attention, vehicle control, and time to steady-state behaviors. Methods Fourteen drivers drove for one month each a Cadillac CT6 equipped with Super Cruise (SC), a partial automation system that, when engaged, enables hands-free driving. The vehicles were instrumented with data acquisition systems recording driving kinematics, automation use, GPS, and video. The dataset included 265 SC-initiated disengagements identified across 5,514 miles driven with SC. Results Linear quantile mixed-effects models of glance behavior indicated that following SC-initiated disengagement, the proportions of glances to the Road decreased (Q50Before=0.91, Q50After=0.69; Q85Before=1.0, Q85After=0.79), the proportions of glances to the Instrument Cluster increased (Q50Before=0.14, Q50After=0.25; Q85Before=0.34, Q85After=0.45), and mean glance duration to the Road decreased by 4.86 sec in Q85. Multinomial logistic regression mixed-models of glance distributions indicated that the number of transitions between glance locations following disengagement increased by 43% and that glances were distributed across fewer locations. When driving hands-free, take over time was significantly longer (2.4 sec) compared to when driving with at least one hand on the steering wheel (1.8 sec). Analysis of moment-to-moment distributional properties of visual attention and steering wheel control following disengagement indicated that on average it took drivers 6.1 sec to start the recovery of glance behavior to the Road and 1.5 sec for trend-stationary proportions of at least one hand on the steering wheel. Conclusions Automation-initiated disengagements triggered substantial changes in driver glance behavior including shorter on-road glances and frequent transitions between Road and Instrument Cluster glance locations. This information seeking behavior may capture drivers’ search for information related to the disengagement or the automation state and is likely shaped by the automation design. The study findings can inform the design of more effective driver-centric information displays for smoother transitions and faster recovery.

Lessons in Sanctions-Proofing from Russia

Tue, 04 Apr 2023 00:00:00 GMT

Lessons in Sanctions-Proofing from Russia Glenn, Caileigh Government actors and other observers across Europe and the United States called the multilateral sanctions imposed on Russia in early 2022 “unprecedented.”Footnote1 Even Russian President Vladimir Putin acknowledged their severity when he stressed “the need to counter economic restrictions that were imposed on us, which are truly unprecedented without any exaggeration.”Footnote2 Part of the response to the Russian invasion of Ukraine, these financial and trade sanctions—imposed on Russia by Western governments—target key firms in the financial and energy sectors, debt financing, technology, Russia’s foreign currency reserves, and more recently, most Russian oil and transportation insurers.

Why Haven’t We Applied the Lessons from Lean to Innovation?

Thu, 20 Apr 2023 00:00:00 GMT

Why Haven’t We Applied the Lessons from Lean to Innovation? Wright, Randall S. Yes, I know. People have been doingLean innovation—increasing efficiencyby capturing customer feedback earlyand often and minimizing waste in theproduct development cycle—for the last10 years.I’m not talking about applying Leanprinciples to innovation. I’m talkingabout how American business leadershad the humility to admit their firmsneeded to learn Lean from Japaneseculture to master globally competitiveoperations, and why they need now tolearn innovation from the culture ofuniversities to master globally compet-itive innovation.

Becoming Infrastructure: A Critical Realist Account of the Evolution of DHIS2 as Digital Public Health Infrastructure in Sierra Leone

Thu, 16 Oct 2025 00:00:00 GMT

Becoming Infrastructure: A Critical Realist Account of the Evolution of DHIS2 as Digital Public Health Infrastructure in Sierra Leone Ndubuisi-Obi, Innocent; Chen, Nuole; Tsai, Lily Today, the District Health Information System 2 (DHIS2) has become the de-facto standard for open-source health management information systems and Sierra Leone's status as the first country in sub-Saharan Africa to implement DHSI2 makes it a productive place for researchers interested in understanding the end-to-end process of infrastructuring in a low-resource bureaucratic setting. In this article, we examine its design, implementation, and maintenance in Sierra Leone over a period of 14 years - from 2008 to 2022. We present an intensive case study discretized by three morphogenetic cycles (decentralization, centralization, and fragmentation) and furnished with explanatory account's of DHIS2's evolution using a critical realist research methodology to describe the emergence of DHIS2 as digital public health infrastructure. These accounts highlight the structural and cultural systems of DHIS2, their elaborations, and their interaction with agents over successive periods of DHIS2's evolution. Our study finds that, despite its continued use in Sierra Leone, the increasing generativity in the structural and cultural systems of DHSI2 and Sierra Leone’s public health system engenders a persistent instability that requires continuous resolution. Though we find that extant literature aids in our understanding of DHIS2’s evolution, we proffer two mechanisms, infrastructural capture and socio-technical debt, which aid our explanation of events observed in our case study. Our work makes a case for more ontologically-diverse theorizing of bureaucracy-aware computing systems.

Factorization in additive monoids of evaluation polynomial semirings

Thu, 01 Jun 2023 00:00:00 GMT

Factorization in additive monoids of evaluation polynomial semirings Ajran, Khalid; Bringas, Juliet; Li, Bangzheng; Singer, Easton; Tirador, Marcos For a positive real α, we can consider the additive submonoid M of the real line that is generated by the nonnegative powers of α. When α is transcendental, M is a unique factorization monoid. However, when α is algebraic, M may not be atomic, and even when M is atomic, it may contain elements having more than one factorization (i.e., decomposition as a sum of irreducibles). The main purpose of this paper is to study the phenomenon of multiple factorizations inside M. When α is algebraic but not rational, the arithmetic of factorizations in M is highly interesting and complex. In order to arrive to that conclusion, we investigate various factorization invariants of M, including the sets of lengths, sets of Betti elements, and catenary degrees. Our investigation gives continuity to recent studies carried out by Chapman et al. in 2020 and by Correa-Morris and Gotti in 2022.

The Argentella scandal: why French officials did not make Corsica a nuclear test site in 1960

Mon, 17 Apr 2023 00:00:00 GMT

The Argentella scandal: why French officials did not make Corsica a nuclear test site in 1960 Cooper, Austin R. Top French officials made plans in early 1960 to transform an abandoned silver mine in Corsica, called the Argentella Massif, into an underground site for nuclear explosions. By June 1960, they had canceled these plans. This article shows how a mass movement on the Mediterranean island forced their hand, and it explains why Corsicans of diverse political affiliations took to the streets. The Argentella project—and the health, environmental, and strategic risks that it entailed—looked in Corsica like evidence that Paris saw the islanders as second-class citizens, even residents of an internal colony. French police intelligence, which maintained surveillance on the Corsican anti-nuclear movement, feared that this movement might have drawn inspiration from the contemporaneous struggle for national liberation in Algeria, where French nuclear explosions began. The Argentella protests illustrated national disagreements about French nuclear ambitions that previous scholarship, proposing official consensus, has minimized. They show how, in a nuclear-armed democracy, local officials, political activists, and ordinary citizens can shape nuclear-weapons policy. But Corsican anti-nuclear action in 1960 did not demand disarmament. These protests also illuminate a longer trajectory in French nuclear history, which involved atmospheric explosions in colonized territories in Algeria and Polynesia until the 1970s, despite local and international resistance.

Towards Foundation Model for Spatiotemporal Data Analysis

Tue, 14 Oct 2025 00:00:00 GMT

Towards Foundation Model for Spatiotemporal Data Analysis Wu, Yuankai; Chen, Xinyu; Zhuang, Dingyi Spatiotemporal data modeling has long been a fundamental task across disciplines such as climate & environmental science, and transportation engineering. A typical goal is to estimate unknown information at specific spatiotemporal points based on partially observed data—for example, interpolating weather conditions at unmeasured locations, reconstructing missing historical records, or forecasting the future trajectories of financial markets. These are all core tasks within the broader scope of spatiotemporal modeling. This tutorial (1 hours) introduces a cohesive view of spatiotemporal data modeling, tracing the evolution from traditional statistical approaches to modern deep learning paradigms. We begin by revisiting Kriging and time series decomposition to highlight the essential assumptions and strengths of these classical methods. Next, we explore low-rank matrix and tensor completion techniques, which leverage the structured patterns of spatiotemporal data. We then elaborate on spatiotemporal graph neural networks, which characterize complex dependencies by integrating graph structures with dynamic temporal features. Finally, we discuss recent advances in applying large foundation models to spatiotemporal tasks, including their capabilities and current limitations. Throughout the tutorial, we emphasize how lessons from traditional methods—such as the importance of locality, periodicity, and smoothness priors—can inspire new directions for developing and fine-tuning foundation models in the spatiotemporal domain. We conclude by outlining key challenges and opportunities in bridging classical wisdom with emerging AI capabilities. SSTD ’25, Osaka, Japan

Gender gaps in South Korea’s labour market: children explain most of the gender employment gap, but little of the gender wage gap

Wed, 03 May 2023 00:00:00 GMT

Gender gaps in South Korea’s labour market: children explain most of the gender employment gap, but little of the gender wage gap Stansbury, Anna; Kirkegaard, Jacob Funk; Dynan, Karen South Korea’s gender wage and employment gaps are among the largest in the OECD. Using labour force survey data over 2010–19, we estimate gender wage and employment gaps, and child earnings penalties, for women aged 25–54. We show (i) that the large gender gaps in South Korea’s labour market are mostly not a function of differential sorting by gender along education, occupation, or industry lines, (ii) that caring for children (and, perhaps increasingly, for the elderly) is the major factor inhibiting women’s labour force participation, and (iii) that large gender wage gaps exist even for women without care responsibilities. These findings suggest that improving opportunities for work–family balance is crucial to helping increase women’s labour force participation, but may do little to close gender wage gaps: other major obstacles also appear to stand in the way of Korean women’s full inclusion in the labour force.

Madman or Mad Genius? The International Benefits and Domestic Costs of the Madman Strategy

Thu, 04 May 2023 00:00:00 GMT

Madman or Mad Genius? The International Benefits and Domestic Costs of the Madman Strategy Schwartz, Joshua A. According to the “Madman Theory” outlined by Daniel Ellsberg and Thomas C. Schelling, and embraced by Presidents Richard Nixon and Donald Trump, being perceived as mad can help make seemingly incredible threats—such as starting a nuclear war—more credible. However, recent research has largely concluded that the Madman Theory does not work. In this study, I theorize that the international benefits of the Madman Theory have been underestimated, but also that there are significant domestic barriers associated with adopting such a strategy that undermine its effectiveness. Through a series of five novel survey experiments, I find evidence that perceived madness provides limited advantages in coercive bargaining vis-à-vis foreign adversaries, but it also entails significant domestic costs that potentially erode its efficacy. Overall, this study provides clearer support for the Madman Theory than most previous literature has found, but also breaks new theoretical ground by analyzing the domestic politics of perceived madness.

Purrfect Pitch: Exploring Pitch Interval Learning through an Audio-Haptic Interface

Thu, 09 Oct 2025 00:00:00 GMT

Purrfect Pitch: Exploring Pitch Interval Learning through an Audio-Haptic Interface Chin, Sam; Fang, Cathy Mengying; Singh, Nikhil; Ibrahim, Ibrahim; Paradiso, Joe; Maes, Pattie We introduce Purrfect Pitch, a system consisting of a wearable haptic device and a custom-designed learning interface for musical ear training. We focus on the ability to identify pitch intervals (sequences of two musical notes), a perceptually ambiguous task that usually requires rote training. With our system, users hear two tones while simultaneously receiving two corresponding vibrotactile stimuli on the back. Providing haptic feedback on the back makes the auditory distance between tones salient, and the back-worn design is comfortable and unobtrusive. During training, users receive multi-sensory feedback from our system and input their guessed interval value on our web-based learning interface. Our study with 18 participants shows that our system enables novice learners to identify intervals more accurately and consistently than those who only received audio feedback, even after removing the haptic feedback. We also share further insights on designing a multisensory learning system. AHs 2025, Masdar City, Abu Dhabi, United Arab Emirates

Teaching AI to Feel: A Collaborative, Full-Body Exploration of Emotive Communication

Mon, 27 Oct 2025 00:00:00 GMT

Teaching AI to Feel: A Collaborative, Full-Body Exploration of Emotive Communication Lemus, Lissette; Pilcher, Kris; Sprengel, Holger; Sabater-Mir, Jordi; Tütüncü, Esen K. Commonaiverse is an interactive installation exploring human emotions through full-body motion tracking and real-time AI feedback. Participants engage in three phases: Teaching, Exploration and the Cosmos Phase, collaboratively expressing and interpreting emotions with the system. The installation integrates MoveNet for precise motion tracking and a multi-recommender AI system to analyze emotional states dynamically, responding with adaptive audiovisual outputs. By shifting from top-down emotion classification to participant-driven, culturally diverse definitions, we highlight new pathways for inclusive, ethical affective computing. We discuss how this collaborative, out-of-the-box approach pushes multimedia research beyond single-user facial analysis toward a more embodied, co-created paradigm of emotional AI. Furthermore, we reflect on how this reimagined framework fosters user agency, reduces bias, and opens avenues for advanced interactive applications. MM ’25, October 27–31, 2025, Dublin, Ireland

Personalized Animations for Affective Feedback: Generative AI Helps to Visualize Skin Conductance

Sun, 26 Oct 2025 00:00:00 GMT

Personalized Animations for Affective Feedback: Generative AI Helps to Visualize Skin Conductance Scheirer, Jocelyn; Picard, Rosalind; Cantrell, Aubrey Biofeedback interfaces traditionally rely on abstract visualizations, tones, or haptics to convey physiological states—but these often lack personal relevance, emotional salience, and engagement. In this paper, we present a novel system that bridges wearable sensing and generative AI to create real-time, personalized animated biofeedback experiences. Users describe emotionally meaningful objects or scenes to a language model in our system, which outputs generate customized Processing animations. These animations are then dynamically driven by electrodermal activity (EDA) signals from a wrist sensor. We co-design and evaluate the system with autistic adults, many of whom have unique “special interests” that are likely to engage them more than a one-sized-fits-all visualization. Many of these individuals also have difficulty with interoception -- feeling or sensing their own internal and physiological state changes. We built this tool to transform passive physiological monitoring into an interactive multimedia experience, where the visual representation of the body is authored by the user. We introduce a prompt-engineered GPT-based interface that streamlines code generation, sensor mapping, and iterative refinement, requiring no prior coding expertise. The technical pipeline we built includes signal filtering, dynamic parameter mapping, and natural language-based customization— delivering a real-time, visually immersive feedback loop. We report on initial case studies with 12 autistic adults using the system, which highlight both the expressive potential and individual variability of user responses, reinforcing the need for adaptable multimedia frameworks in health technologies. By merging realtime physiological data with generative animation and natural language interaction, this work expands the creative frontier of personalized affective biofeedback. We also address ethical challenges arising from using AI with physiological sensors. MRAC '25, October 27–28, 2025, Dublin, Ireland

Hands-on Strategies for Teaching Social and Societal Impacts of Computing

Tue, 21 Oct 2025 00:00:00 GMT

Hands-on Strategies for Teaching Social and Societal Impacts of Computing Kurkovsky, Stan; Nnamani, Manee Ngozi; Hunter, Aaron; Sobomehin, Olatunde; Braught, Grant; Goldweber, Michael The topic of hands-on strategies for teaching the social and societal impacts of computing is of growing interest to the computer science education community because it addresses a critical gap in traditional CS curricula [7]. While technical skills remain central, educators increasingly recognize the need to prepare students for the ethical, social, and human-centered challenges posed by modern computing technologies. From AI-driven decision-making to digital accessibility and data privacy, computing profoundly affects individuals and communities, making it essential for students to engage with these issues through experiential learning [12]. Different viewpoints on this topic emerge based on pedagogical approaches, disciplinary perspectives, and technological optimism or skepticism. Some educators advocate for integrating servicelearning and community-based projects, arguing that real-world engagement fosters empathy and ethical awareness. Others emphasize case studies and simulations, providing structured exposure to societal challenges without the unpredictability of external partnerships. Additionally, viewpoints may diverge on the role of AI: while some see AI tools as an opportunity to enhance social good, others worry they may exacerbate biases and reduce human agency in computing. Despite these differences, there is broad agreement that computing education must go beyond technical training to include a deeper understanding of computing’s role in society. CompEd 2025, October 21–25, 2025, Gaborone, Botswana

Analysis of Driver and Pedestrian Gesture Use in the Boston Area. Automated Vehicles May Need More Than Kinematics in Ambiguous Situations

Wed, 08 Oct 2025 00:00:00 GMT

Analysis of Driver and Pedestrian Gesture Use in the Boston Area. Automated Vehicles May Need More Than Kinematics in Ambiguous Situations Weibert, Alexander; Manstetten, Dietrich; Reimer, Bryan; Gershon, Pnina; Mehler, Bruce; Abdenebaoui, Larbi; Hatice Şahin, İppoliti Roadways, despite their formal regulations, are dynamic spaces where humans interact beyond formal rules to resolve conflicts. In ambiguous situations, the right of way is often unclear. Self-driving vehicles in urban traffic introduce challenges to their coexistence with humans, indicating a need for greater social awareness in these vehicles. To investigate social interactions among roadway users, we analyzed a naturalistic driving dataset focusing on instances where drivers yielded to pedestrians, by noting gestures. Video analysis showed that gestures were more common in ambiguous situations than in regulated scenarios. Drivers used gestures to navigate the right of way efficiently, while pedestrians used them to express gratitude. These findings highlight the importance of understanding social expressions in designing socially aware self-driving vehicles. AutomotiveUI Adjunct ’25, Brisbane, QLD, Australia

Characterizing and Optimizing Realistic Workloads on a Commercial Compute-in-SRAM Device

Fri, 17 Oct 2025 00:00:00 GMT

Characterizing and Optimizing Realistic Workloads on a Commercial Compute-in-SRAM Device Zhang, Niansong; Zhu, Wenbo; Golden, Courtney; Ilan, Dan; Chen, Hongzheng; Batten, Christopher; Zhang, Zhiru Compute-in-SRAM architectures offer a promising approach to achieving higher performance and energy efficiency across a range of data-intensive applications. However, prior evaluations have largely relied on simulators or small prototypes, limiting the understanding of their real-world potential. In this work, we present a comprehensive performance and energy characterization of a commercial compute-in-SRAM device, the GSI APU, under realistic workloads. We compare the GSI APU against established architectures, including CPUs and GPUs, to quantify its energy efficiency and performance potential. We introduce an analytical framework for general-purpose compute-in-SRAM devices that reveals fundamental optimization principles by modeling performance trade-offs, thereby guiding program optimizations. Exploiting the fine-grained parallelism of tightly integrated memory-compute architectures requires careful data management. We address this by proposing three optimizations: communicationaware reduction mapping, coalesced DMA, and broadcast-friendly data layouts. When applied to retrieval-augmented generation (RAG) over large corpora (10GB–200GB), these optimizations enable our compute-in-SRAM system to accelerate retrieval by 4.8×–6.6× over an optimized CPU baseline, improving end-to-end RAG latency by 1.1×–1.8×. The shared off-chip memory bandwidth is modeled using a simulated HBM, while all other components are measured on the real compute-in-SRAM device. Critically, this system matches the performance of an NVIDIA A6000 GPU for RAG while being significantly more energy-efficient (54.4×-117.9× reduction). These findings validate the viability of compute-in-SRAM for complex, real-world applications and provide guidance for advancing the technology. MICRO ’25, Seoul, Republic of Korea

Voice to Vision: A Sociotechnical System for Transparent Civic Decision-Making

Fri, 17 Oct 2025 00:00:00 GMT

Voice to Vision: A Sociotechnical System for Transparent Civic Decision-Making Hughes, Margaret; Overney, Cassandra; Kamra, Ashima; Tepale, Jasmin; Hamby, Elizabeth; Jasim, Mahmood; Roy, Deb Communities frequently report sending feedback “into a void” during community engagement processes like neighborhood planning, creating a critical disconnect between public input and decision-making. Voice to Vision addresses this gap with a sociotechnical system that comprises three integrated components: a flexible data architecture linking community input to planning outputs, a sensemaking interface for planners to analyze and synthesize feedback, and a community-facing platform that makes the entire engagement process transparent. By creating a shared information space between stakeholders, our system demonstrates how structured data and specialized interfaces can foster cooperation across stakeholder groups, while addressing tensions in accessibility and trust formation. Our CSCW demonstration will showcase this system’s ability to transform opaque civic decision-making processes into collaborative exchanges, inviting feedback on its potential applications beyond urban planning. CSCW Companion ’25, Bergen, Norway

Augmenting Collaborative Problem-Solving: Exploring the Design and Use of GenAI for Groupwork

Fri, 17 Oct 2025 00:00:00 GMT

Augmenting Collaborative Problem-Solving: Exploring the Design and Use of GenAI for Groupwork Johnson, Janet; Rick, Steven; Gr?nb?k, Jens Emil; Wong, Emily; Yin, Ming; Nebeling, Michael; Klein, Mark; Ackerman, Mark; Malone, Thomas Complex problem-solving and creative work in the real world are rarely individual endeavors and typically unfold within teams and group settings. While advancements in generative artificial intelligence (GenAI) have shown promise in augmenting creativity and productivity, these tools are primarily designed for individual use and overlook group dynamics and the collaborative aspects of teamwork. This workshop will provide a platform for researchers and practitioners to explore the design of future human-AI groups across four key themes: (1) the role of GenAI in group settings, (2) collaborative and multimodal interactions with GenAI, (3) evaluating GenAI’s influence within groups and designing for appropriate reliance, and (4) evolving group practices in the presence of GenAI. We hope to build a community and construct alignment across participants around how to pursue research that understands how GenAI can augment, undermine, or bring new practices to collaborative settings and groupwork. CSCW Companion ’25, Bergen, Norway

Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC

Wed, 26 Nov 2025 00:00:00 GMT

Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC CMS Collaboration We propose a neural network training method capable of accounting for the effects of systematic variations of the data model in the training process and describe its extension towards neural network multiclass classification. The procedure is evaluated on the realistic case of the measurement of Higgs boson production via gluon fusion and vector boson fusion in the τ τ decay channel at the CMS experiment. The neural network output functions are used to infer the signal strengths for inclusive production of Higgs bosons as well as for their production via gluon fusion and vector boson fusion. We observe improvements of 12 and 16% in the uncertainty in the signal strengths for gluon and vector-boson fusion, respectively, compared with a conventional neural network training based on cross-entropy.

Designs Related Through Projective and Hopf Maps

Fri, 28 Nov 2025 00:00:00 GMT

Designs Related Through Projective and Hopf Maps Lindblad, Ayodeji We verify a construction which, for K the reals, complex numbers, quaternions, or octonions, builds a spherical t-design by placing a spherical t-design on each K -projective or K -Hopf fiber associated to the points of a ⌊ t / 2 ⌋ -design on a quotient projective space K P n ≠ O P 2 or sphere. This generalizes work of König and Kuperberg, who verified the K = C case of the projective settings, and of Okuda, who (inspired by independent observation of this construction by Cohn, Conway, Elkies, and Kumar) verified the K = C case of the generalized Hopf settings.

A generative deep learning approach to de novo antibiotic design

Thu, 16 Oct 2025 00:00:00 GMT

A generative deep learning approach to de novo antibiotic design Krishnan, Aarti; Anahtar, Melis N.; Valeri, Jacqueline A.; Jin, Wengong; Donghia, Nina M.; Sieben, Leif; Luttens, Andreas; Zhang, Yu; Modaresi, Seyed Majed; Hennes, Andrew; Fromer, Jenna; Bandyopadhyay, Parijat; Chen, Jonathan C.; Rehman, Danyal; Desai, Ronak; Edwards, Paige; Lach, Ryan S.; Aschtgen, Marie-Stéphanie; Gaborieau, Margaux; Gaetani, Massimiliano; Palace, Samantha G.; Omori, Satotaka; Khonde, Lutete; Moroz, Yurii S.; Blough, Bruce; Jin, Chunyang; Loh, Edmund; Grad, Yonatan H.; Saei, Amir Ata; Coley, Connor W.; Wong, Felix; Collins, James J. The antimicrobial resistance crisis necessitates structurally distinct antibiotics. While deep learning approaches can identify antibacterial compounds from existing libraries, structural novelty remains limited. Here, we developed a generative artificial intelligence framework for designing de novo antibiotics through two approaches: a fragment-based method to comprehensively screen >107 chemical fragments in silico against Neisseria gonorrhoeae or Staphylococcus aureus, subsequently expanding promising fragments, and an unconstrained de novo compound generation, each using genetic algorithms and variational autoencoders. Of 24 synthesized compounds, seven demonstrated selective antibacterial activity. Two lead compounds exhibited bactericidal efficacy against multidrug-resistant isolates with distinct mechanisms of action and reduced bacterial burden in vivo in mouse models of N. gonorrhoeae vaginal infection and methicillin-resistant S. aureus skin infection. We further validated structural analogs for both compound classes as antibacterial. Our approach enables the generative deep-learning-guided design of de novo antibiotics, providing a platform for mapping uncharted regions of chemical space.

Frontiers of biological material intelligence

Wed, 26 Nov 2025 00:00:00 GMT

Frontiers of biological material intelligence Marom, Lee; Buehler, Markus J. Biological materials exhibit a form of intelligence that enables them to sense, adapt, and self-optimize in response to their environments. Unlike synthetic materials, which are often designed for singular, static functions, natural material systems integrate sensing, memory, and feedback directly into their architectures. As industries face increasing demands for resilience, sustainability, and efficiency, the development of intelligent materials has become a promising step toward the future of material innovation. Advances in artificial intelligence and machine learning, along with mathematical frameworks spanning graph theory and category theory, provide powerful tools to uncover the underlying design principles of intelligent biological materials. Simultaneously, digital fabrication methods, including additive manufacturing and biofabrication, allow the scalable realization of adaptive material systems. As the integration of deep biological insight, computational modeling, and advanced fabrication continues to evolve, it sets the stage for a profound shift in how we conceive, create, and deploy materials. Advancing this convergence will accelerate the development of intelligent systems that are capable of autonomous adaptation, long-term resilience, and embedded functionality across scales and environments.

Leveraging community engagement and human-centered design to develop multilevel implementation strategies to enhance adoption of a health equity intervention

Mon, 24 Nov 2025 00:00:00 GMT

Leveraging community engagement and human-centered design to develop multilevel implementation strategies to enhance adoption of a health equity intervention Price, Maggi A.; Mulkern, Patrick J.; Condon, Madelaine; Rakhilin, Marina; Johansen, Kara; Lyon, Aaron R.; Saldana, Lisa; Pachankis, John; Woodward, Sue A.; Roeder, Kathryn M.; Moran, Lyndsey R.; Jerskey, Beth A. Background Health equity intervention implementation (which promotes positive health outcomes for populations experiencing disproportionately worse health) is often impeded by health-equity-specific barriers like provider bias; few studies demonstrate how to overcome these barriers through implementation strategies. An urgent health equity problem in the U.S. is the mental health of transgender youth. To address this, we developed Gender-Affirming Psychotherapy (GAP), a health equity intervention comprising best-practice mental health care for transgender youth. This paper details the identification of implementation determinants and the development of targeted strategies to promote provider adoption of GAP. Methods This study represents part of a larger study of mental health provider adoption of GAP. Here we describe the first 2 stages of the 3-stage community-engaged and human-centered design process – Discover, Design/Build, and Test – to identify implementation determinants of adoption and develop implementation strategies with transgender youth, their parents, and mental health providers. This process involved collecting data via focus groups, design meetings, usability testing, and champion meetings. Data were analyzed using rapid and conventional content analysis. Qualitative coding of implementation determinants was guided by the Health Equity Implementation Framework, and implementation strategy coding was facilitated by the ERIC Implementation Strategy Compilation. Results We identified 15 determinants of GAP adoption, and all were specific to the transgender population (e.g., inclusive record system, anti-transgender attitudes). Seventeen implementation strategies were recommended and 12 were developed, collectively addressing all identified determinants. Most strategies were packaged into an online self-paced mental health provider training (implementation intervention) with 6 training tools. Additional inner-setting strategies were designed to support training uptake (e.g., mandate training) and GAP adoption (e.g., change record system). Conclusions Community-engaged and human-centered design methods can identify health equity intervention implementation determinants and develop targeted strategies. We highlight five generalizable takeaways for health equity implementation scientists: (1) implementer bias may be a key barrier, (2) experience with the health equity population may be an important facilitator, (3) stakeholder stories may be an effective training tool, (4) inner-setting-level implementation strategies may be necessary, and (5) teaching implementers how to build implementation strategies can overcome resource-constraints. Trial registration November 11, 2022; NCT05626231.

Breeding of microbiomes conferring salt tolerance to plants

Thu, 27 Nov 2025 00:00:00 GMT

Breeding of microbiomes conferring salt tolerance to plants Guilherme Pereira, Caio; Edwards, Joseph A.; Khasanova, Albina; Carlson, Alexis; Brisson, Vanessa; Schaefer, Estelle; Glavina del Rio, Tijana; Tringe, Susannah; Vogel, John P.; Des Marais, David L.; Juenger, Thomas E.; Mueller, Ulrich G. Background Microbiome breeding through host-mediated selection is a technique to artificially select for microbiomes conferring beneficial properties to plants. Using a systematic selection protocol that maximises the heritability of microbiome effects, transmission fidelity, and microbiome stability through multiple selection cycles, we previously developed root-associated microbial communities conferring sodium and aluminium tolerance to Brachypodium distachyon, a model for cereal crops. Here, we explore the physiological mechanisms underlying our selected microbiomes’ effect on plant fitness and analyse how our selection protocol shaped the composition and structure of these microbiomes. We analysed the effects of our selected microbiomes on plant fitness and tissue-nutrient concentration, then used 16S rRNA amplicon sequencing to examine microbial community composition and co-occurrence network patterns. Results Our sodium-selected microbiomes reduced leaf sodium concentration by ~ 50%, whereas the aluminium-selected microbiomes had no effect on leaf-tissue nutrient concentration, suggesting different mechanisms underlying the microbiome-mediated stress tolerance. By testing the selected microbiomes in a cross-fostering experiment, we show that our artificially selected microbiomes attained (a) ecological robustness contributing to transplantability (i.e. inheritance) of microbiome-encoded effects between plants; and (b) network features identifying key bacteria promoting salt-stress tolerance. Conclusions Combined, these findings elucidate critical mechanisms underlying host-mediated artificial selection as a framework to breed microbiomes with targeted benefits for plants under salt stresses, with significant implications for sustainable agriculture.

Measurement of ψ(2S) to J/ψ cross-section ratio as function of multiplicity in pPb collisions at √sNN = 8.16 TeV

Wed, 26 Nov 2025 00:00:00 GMT

Measurement of ψ(2S) to J/ψ cross-section ratio as function of multiplicity in pPb collisions at √sNN = 8.16 TeV Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; Alessio, F.; The LHCb collaboration The production ratio of ψ(2S) to J/ψ charmonium states is presented as a function of multiplicity in proton-lead collisions at a centre-of-mass energy of s NN = 8.16 TeV, for both prompt and nonprompt sources. The total luminosity recorded by the LHCb experiment corresponds to 13.6 nb−1 for pPb collisions and 20.8 nb−1 for Pbp collisions, where the first particle corresponds to the particle traveling towards the detector. Measurements are performed in the dimuon final state at forward (backward) centre-of-mass rapidity, with respect to the proton direction, 1.5 < y* < 4.0 (−5.0 < y* < −2.5) for pPb (Pbp) collisions. A multiplicity dependence of the prompt production ratio is observed in pPb collisions, whereas no dependence is found in nonprompt production, nor in either prompt or nonprompt production in Pbp collisions. These results suggest that in the Pb-going direction additional suppression mechanisms beyond comover effects may be present, possibly related to the formation of quark-gluon plasma. This highlights a transition from small to large collision systems and provides important insight into the suppression of charmonia in proton-nucleus collisions.

CURENet: combining unified representations for efficient chronic disease prediction

Thu, 27 Nov 2025 00:00:00 GMT

CURENet: combining unified representations for efficient chronic disease prediction Dao, Cong-Tinh; Phan, Nguyen M. T.; Ding, Jun-En; Wu, Chenwei; Restrepo, David; Luo, Dongsheng; Zhao, Fanyi; Liao, Chun-Chieh; Peng, Wen-Chih; Wang, Chi-Te; Chen, Pei-Fu; Chen, Ling; Ju, Xinglong; Liu, Feng; Hung, Fang-Ming Electronic health records (EHRs) are designed to synthesize diverse data types, including unstructured clinical notes, structured lab tests, and time-series visit data. Physicians draw on these multimodal and temporal sources of EHR data to form a comprehensive view of a patient’s health, which is crucial for informed therapeutic decision-making. Yet, most predictive models fail to fully capture the interactions, redundancies, and temporal patterns across multiple data modalities, often focusing on a single data type or overlooking these complexities. In this paper, we present CURENet, a multimodal model (Combining Unified Representations for Efficient chronic disease prediction) that integrates unstructured clinical notes, lab tests, and patients’ time-series data by utilizing large language models (LLMs) for clinical text processing and textual lab tests, as well as transformer encoders for longitudinal sequential visits. Curenet has been capable of capturing the intricate interaction between different forms of clinical data and creating a more reliable predictive model for chronic illnesses. We evaluated CURENet using the public MIMIC-III and private FEMH datasets, where it achieved over 94% accuracy in predicting the top 10 chronic conditions in a multi-label framework. Our findings highlight the potential of multimodal EHR integration to enhance clinical decision-making and improve patient outcomes.

Effective field theory factorization for diffraction

Tue, 25 Nov 2025 00:00:00 GMT

Effective field theory factorization for diffraction Lee, Kyle; Schindler, Stella T.; Stewart, Iain W. We derive a factorization formula for coherent and incoherent ep diffraction using the soft collinear effective theory, utilizing multiple power expansion parameters to handle different kinematic regions. This goes beyond the known hard-collinear diffractive factorization to address the small-x Regge dynamics and Pomeron exchange from first principles. The effective field theory analysis also uncovers and factorizes an important irreducible incoherent background generated by color-nonsinglet exchange, dubbed “quasi-diffraction”, for which we calculate the associated Sudakov suppression. For unpolarized scattering we show that there are four diffractive structure functions at leading power, and point out the importance of studying F 3 , 4 D through asymmetries, in addition to F 2 , L D . For the quasi-diffractive background, we make model independent predictions for ratios of the corresponding structure functions in a perturbative kinematic region. Our analysis also makes predictions for six leading-power spin-dependent structure functions. Finally, we provide connections to diffractive parton distributions, and assess the Ingelman-Schlein model. Our work lays a path for further QCD-based studies of diffraction.

Coherent photoproduction of ρ0, ω and excited vector mesons in ultraperipheral PbPb collisions

Tue, 18 Nov 2025 00:00:00 GMT

Coherent photoproduction of ρ0, ω and excited vector mesons in ultraperipheral PbPb collisions Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. The invariant-mass distribution for the coherent photoproduction of dipions in ultraperipheral PbPb collisions is measured using data, corresponding to an integrated luminosity of 224.6 ± 9.6μb−1, collected by the LHCb experiment in 2018 at a nucleon-nucleon centre-of-mass energy s NN = 5.02 TeV. In the mass range from 400 to 1200 MeV, the results are consistent with previous experiments, with the spectrum dominated by the ρ0 meson, which interferes with a nonresonant component, together with a smaller ω meson contribution. In an extended mass range up to 2300 MeV, models previously used do not fit the data and a consistent description requires the introduction of two resonances at masses of 1350 ± 20 MeV and 1790 ± 20 MeV with widths of about 300 MeV. The cross-section for each meson is measured differentially in twelve bins of rapidity from 2.05 to 4.90. The ρ0 cross-section increases with rapidity from about 400 to 600 mb and is measured with a typical precision of 8%, while the cross-section times branching fraction for the ω, ρ′ and ρ′′, with the statistical precision of the data, do not have a pronounced rapidity dependence and are between 0.5 and 1.5mb, with uncertainties up to 30%. A large nuclear suppression is observed for the ρ0 meson compared to expectations based on photoproduction on the proton that use the impulse approximation. Significant suppression is also observed compared to that predicted by elastic scattering described in the Glauber approach, or with the addition of inelastic scattering in a Gribov-Glauber model.

Forcing with Invariant Measures

Mon, 24 Nov 2025 00:00:00 GMT

Forcing with Invariant Measures Ackerman, Nathanael; Freer, Cameron; Golshani, Mohammad; Mirabi, Mostafa; Patel, Rehana This paper introduces a model-theoretic generalization of the notion of forcing with random reals, in which forcing gives rise to random generic structures. Specifically, we consider forcing with κ -Borel probability measures on the space of L -structures with a (possibly uncountable) infinite set X, focusing on those that are invariant under the action of the symmetric group Sym ( X ) . We demonstrate how any Sym ( X ) -invariant measure where X is countable can be uniquely extended to a Sym ( Y ) -invariant measure where Y is uncountable, and prove that forcing with such measures satisfies the countable chain condition. We also show that we can uniformly distinguish between these random generic structures and the Cohen generic structures that arise from forcing with a strong Fraïssé class: There is a κ -Borel set of low complexity that contains every Cohen generic structure that is not highly homogeneous but contains no random generic structure, implying that a structure that is not highly homogeneous cannot be both Cohen generic and random generic. Finally, we answer an open question of Kostana in the case of ω 1 , by establishing a connection between forcing with a strong Fraïssé class and Cohen forcing.

Gnotobiotic growth and phosphorus limitation of Arabidopsis thaliana and co-occurring microbes on phosphated iron oxides

Thu, 27 Nov 2025 00:00:00 GMT

Gnotobiotic growth and phosphorus limitation of Arabidopsis thaliana and co-occurring microbes on phosphated iron oxides Mackie, Amanda M.; Schuler, Christopher J.; McRose, Darcy L. The macronutrient phosphorus is vital for sustaining cellular processes in all life forms. Due to its frequent adsorption on iron minerals, phosphorus bioavailability is low in many soils. While the abiotic adsorption of phosphate on iron minerals has been well studied, the direct effects of this process on bioavailability to plants and microbes has not been thoroughly investigated in a simplified laboratory system. We developed a hydroponic growth system that uses hydrous ferric oxide (HFO) to induce phosphorus limitation and can enable both plant and microbial cultivation as well as gnotobiotic co-culture. We demonstrate that this system can be used for phosphorus-limited growth of the model plant Arabidopsis thaliana as well as two root-associated bacterial isolates (from the genera Rhizobium and Pseudomonas). Elemental analysis of phosphorus and iron concentration in A. thaliana shoots reveals that the addition of increasing amounts of HFO leads to a progressive decrease in phosphorus concentration but does not affect iron quotas. We also report that phosphorus concentrations in both bacterial isolates decrease when cultivated in media supplemented with HFO. We further show that A. thaliana can be co-cultured with a Rhizobium isolate in our phosphorus-limited hydroponic system with bacteria relying on plant photosynthate as their sole carbon source. Our work provides a controlled demonstration of the effects of mineral adsorption on phosphorus bioavailability and a tool for further investigation of how plants and microbes access phosphorus in the environment.

Beyond submodular maximization via one-sided smoothness

Mon, 24 Nov 2025 00:00:00 GMT

Beyond submodular maximization via one-sided smoothness Ghadiri, Mehrdad; Santiago, Richard; Shepherd, Bruce The multilinear framework for submodular maximization was developed to achieve a tight 1 - 1 / e approximation for maximizing a monotone submodular function subject to a matroid constraint, including as special case the submodular welfare problem. The framework has a continuous optimization step (solving the multilinear extension of a submodular function) and a rounding part (rounding a fractional solution to an integral one). We extend both parts to provide a framework for a wider array of applications. The continuous part works for a more general class of continuous functions parameterized by a new smoothness parameter σ . A twice differential function F is called σ -one-sided-smooth ( σ -OSS) if its second derivatives are bounded as follows: 1 2 u T ∇ 2 F ( x ) u ≤ σ · ‖ u ‖ 1 ‖ x ‖ 1 u T ∇ F ( x ) for all u , x ≥ 0 , x ≠ 0 . For σ = 0 this includes previously studied continuous DR-Submodular functions as well as quadratics defined by copositive matrices. We give a modification of the continuous greedy algorithm which finds a solution for maximizing a monotone σ -OSS F over a polytope in the non-negative orthant; the solution approximates the optimum to within factors which are functions of σ which depend on additional properties. Interestingly, σ -OSS functions arise as the multilinear extensions of set functions associated with several well-studied diversity maximization problems: max f ( S ) = ∑ i , j ∈ S A ij : | S | ≤ k . For instance, when A ij defines a σ -semi-metric, its extension is σ -OSS. In these settings, we also develop rounding schemes to approximate the discrete problem.

Shotgun Metagenomics of Gastric Biopsies Reveals Compositional and Functional Microbiome Shifts in High- and Low-Gastric-Cancer-Risk Populations from Colombia, South America

Mon, 27 Feb 2023 00:00:00 GMT

Shotgun Metagenomics of Gastric Biopsies Reveals Compositional and Functional Microbiome Shifts in High- and Low-Gastric-Cancer-Risk Populations from Colombia, South America Mannion, Anthony; Sheh, Alexander; Shen, Zeli; Dzink-Fox, JoAnn; Piazuelo, M Blanca; Wilson, Keith T; Peek, Richard; Fox, James G Along with Helicobacter pylori infection, the gastric microbiota is hypothesized to modulate stomach cancer risk in susceptible individuals. Whole metagenomic shotgun sequencing (WMS) is a sequencing approach to characterize the microbiome with advantages over traditional culture and 16S rRNA sequencing including identification of bacterial and non-bacterial taxa, species/strain resolution, and functional characterization of the microbiota. In this study, we used WMS to survey the microbiome in extracted DNA from antral gastric biopsy samples from Colombian patients residing in the high-risk gastric cancer town Túquerres (n = 10, H. pylori-positive = 7) and low-risk town of Tumaco (n = 10, H. pylori-positive = 6). Kraken2/Bracken was used for taxonomic classification and abundance. Functional gene profiles were inferred by InterProScan and KEGG analysis of assembled contigs and gene annotation. The most abundant taxa represented bacteria, non-human eukaryota, and viral genera found in skin, oral, food, and plant/soil environments including Staphylococus, Streptococcus, Bacillus, Aspergillus, and Siphoviridae. H. pylori was the predominant taxa present in H. pylori-positive samples. Beta diversity was significantly different based on H. pylori-status, risk group, and sex. WMS detected more bacterial taxa than 16S rRNA sequencing and aerobic, anaerobic, and microaerobic culture performed on the same gastric biopsy samples. WMS identified significant differences in functional profiles found between H. pylori-status, but not risk or sex groups. H. pylori-positive samples were significantly enriched for H. pylori-specific genes including virulence factors such as vacA, cagA, and urease, while carbohydrate and amino acid metabolism genes were enriched in H. pylori-negative samples. This study shows WMS has the potential to characterize the taxonomy and function of the gastric microbiome as risk factors for H. pylori-associated gastric disease. Future studies will be needed to compare and validate WMS versus traditional culture and 16S rRNA sequencing approaches for characterization of the gastric microbiome.

Resonance Scattering Treatment with the Windowed Multipole Formalism

Sun, 03 Mar 2024 00:00:00 GMT

Resonance Scattering Treatment with the Windowed Multipole Formalism Ridley, Gavin; Forget, Benoit; Burke, Timothy A new method for directly sampling the resonance upscattering effect is presented. Alternatives have relied on inefficient rejection sampling techniques or large tabular storage of relative velocities. None of these approaches, which require pointwise energy data, are particularly well suited to the windowed multipole cross-section representation. The new method, called multipole analytic resonance scattering, overcomes these limitations by inverse transform sampling from the target relative velocity distribution where the cross section is expressed in the multipole formalism. The closed-form relative speed distribution contains a novel special function we deem the incomplete Faddeeva function, and we present the first results on its efficient numerical evaluation.

Assessing the Structure-Based Turbulence Model Performance for Thermal Striping Applications Using Symmetric Jet Experiments

Tue, 02 Jul 2024 00:00:00 GMT

Assessing the Structure-Based Turbulence Model Performance for Thermal Striping Applications Using Symmetric Jet Experiments Pham, Monica; Petrov, Victor; Manera, Annalisa; Baglietto, Emilio Turbulent mixing of coolant streams can result in an oscillatory mixing phenomenon called thermal striping. These fluctuations have the potential to lead to anticipated thermal fatigue failures in advanced nuclear reactors. To predict thermal striping, robust and computationally affordable modeling tools that are capable of accurately representing complex turbulence are needed. Hybrid turbulence approaches, such as detached-eddy simulation and scale-adaptive simulation, have shown some success in resolving complex unsteady turbulence for massively separated flows, however the applicability of these models to internal flows is limited. A STRUCTure-based (STRUCT) second-generation Unsteady Reynolds-Averaged Navier–Stokes turbulence model was recently proposed at the Massachusetts Institute of Technology to robustly extend the applicability of hybrid closures. In this work, the STRUCT model is evaluated using experimental data taken at the Reactor Cavity Cooling System separate-effects test facility at the University of Michigan. The experiments observed the interaction of parallel symmetric rectangular jets, and include measurements for mean profiles of velocity and Reynolds stresses. In the present work, the simulation results are assessed against mean profiles of velocity and Reynolds stresses, demonstrating the ability to reproduce the unsteadiness of the jets in close agreement with the measurements at considerably reduced computational cost.

Deep-learning models for forecasting financial risk premia and their interpretations

Fri, 12 May 2023 00:00:00 GMT

Deep-learning models for forecasting financial risk premia and their interpretations Lo, Andrew W; Singh, Manish The measurement of financial risk premia, the amount that a risky asset will outperform a risk-free one, is an important problem in asset pricing. The noisiness and non-stationarity of asset returns makes the estimation of risk premia using machine learning (ML) techniques challenging. In this work, we develop ML models that solve the problems associated with risk premia forecasting by separating risk premia prediction into two independent tasks, a time series model and a cross-sectional model, and using neural networks with skip connections to enable their deep neural network training. These models are tested robustly with different metrics, and we observe that our models outperform several existing standard ML models. A known issue with ML models is their ‘black box’ nature, i.e. their opaqueness to interpretability. We interpret these deep neural networks using local approximation-based techniques that provide explanations for our model's predictions.

Machine Learning Distinguishes Plant Bioelectric Recordings with and Without Nearby Human Movement

Sat, 15 Nov 2025 00:00:00 GMT

Machine Learning Distinguishes Plant Bioelectric Recordings with and Without Nearby Human Movement Gloor, Peter A.; Weinbeer, Moritz Background: Quantitatively detecting whether plants exhibit measurable bioelectric differences in the presence of nearby human movement remains challenging, in part because plant signals are low-amplitude, slow, and easily confounded by environmental factors. Methods: We recorded bioelectric activity from 2978 plant samples across three species (basil, salad, tomato) using differential electrode pairs (leaf and soil electrodes) sampling at 142 Hz. Two trained performers executed three specific eurythmic gestures near experimental plants while control plants remained isolated. Random Forest and Convolutional Neural Network classifiers were applied to distinguish the control from treatment conditions using engineered features including spectral, temporal, wavelet, and frequency domain characteristics. Results: Random Forest classification achieved 62.7% accuracy (AUC = 0.67) distinguishing differences in recordings collected near a moving human from control conditions, representing a statistically significant 12.7 percentage point improvement over chance. Individual performer signatures were detectable with 68.2% accuracy, while plant species classification achieved only 44.5% accuracy, indicating minimal species-specific artifacts. Temporal analysis revealed that the plants with repeated exposure exhibited consistently less negative bioelectric amplitudes compared to single-exposure plants. Innovation: We introduce a data-driven approach that pairs standardized, short-window bioelectric recordings with machine-learning classifiers (Random Forest, CNN) to test, in an exploratory manner, whether plant signals differ between human-moving-nearby and isolation conditions. Conclusions: Plants exhibit modest but statistically detectable bioelectric differences in the presence of nearby human movement. Rather than attributing these differences to eurythmic movement itself, the present design can only demonstrate that plant recordings collected within ~1 m of a moving human differ, modestly but statistically, from recordings taken ≥3 m away. The underlying biophysical pathways and specific contributing factors (airflow, VOCs, thermal plumes, vibration, electromagnetic fields) remain unknown. These results should therefore be interpreted as exploratory correlations, not mechanistic evidence of gesture-specific plant sensing.

Analysis of Regional Surface CO2 Fluxes Using the MEGA Satellite Data Assimilation System

Thu, 13 Nov 2025 00:00:00 GMT

Analysis of Regional Surface CO2 Fluxes Using the MEGA Satellite Data Assimilation System Hu, Liting; Hu, Xiaoyi; Jiang, Fei; He, Wei; Deng, Zhu; Fang, Shuangxi; Fang, Xuekun Understanding the dynamics of terrestrial carbon sources and sinks is crucial for addressing climate change, yet significant uncertainties remain at regional scales. We developed the Monitoring and Evaluation of Greenhouse gAs Flux (MEGA) inversion system with satellite data assimilation and applied it to China using OCO-2 V11.1r XCO2 retrievals. Our results show that China’s terrestrial ecosystems acted as a carbon sink of 0.28 ± 0.15 PgC yr−1 during 2018–2023, consistent with other inversion estimates. Validation against surface CO2 flask measurements demonstrated significant improvement, with RMSE and MAE reduced by 30%–46% and 24–44%, respectively. Six sets of prior sensitivity experiments conclusively demonstrated the robustness of MEGA. In addition, this study is the first to systematically compare model-derived and observation-based background fields in satellite data assimilation. Ten sets of background sensitivity experiments revealed that model-based background fields exhibit superior capability in resolving seasonal flux dynamics, though their performance remains contingent on three key factors: (1) initial fields, (2) flux fields, and (3) flux masks (used to control regional flux switches). These findings highlight the potential for further refinement of the atmospheric inversion system.

ZeoSyn: A Comprehensive Zeolite Synthesis Dataset Enabling Machine-Learning Rationalization of Hydrothermal Parameters

Wed, 06 Mar 2024 00:00:00 GMT

ZeoSyn: A Comprehensive Zeolite Synthesis Dataset Enabling Machine-Learning Rationalization of Hydrothermal Parameters Pan, Elton; Kwon, Soonhyoung; Jensen, Zach; Xie, Mingrou; Gómez-Bombarelli, Rafael; Moliner, Manuel; Román-Leshkov, Yuriy; Olivetti, Elsa Zeolites, nanoporous aluminosilicates with well-defined porous structures, are versatile materials with applications in catalysis, gas separation, and ion exchange. Hydrothermal synthesis is widely used for zeolite production, offering control over composition, crystallinity, and pore size. However, the intricate interplay of synthesis parameters necessitates a comprehensive understanding of synthesis-structure relationships to optimize the synthesis process. Hitherto, public zeolite synthesis databases only contain a subset of parameters and are small in scale, comprising up to a few thousand synthesis routes. We present ZeoSyn, a dataset of 23,961 zeolite hydrothermal synthesis routes, encompassing 233 zeolite topologies and 921 organic structure-directing agents (OSDAs). Each synthesis route comprises comprehensive synthesis parameters: 1) gel composition, 2) reaction conditions, 3) OSDAs, and 4) zeolite products. Using ZeoSyn, we develop a machine learning classifier to predict the resultant zeolite given a synthesis route with >70% accuracy. We employ SHapley Additive exPlanations (SHAP) to uncover key synthesis parameters for >200 zeolite frameworks. We introduce an aggregation approach to extend SHAP to all building units. We demonstrate applications of this approach to phase-selective and intergrowth synthesis. This comprehensive analysis illuminates the synthesis parameters pivotal in driving zeolite crystallization, offering the potential to guide the synthesis of desired zeolites. The dataset is available at https://github.com/eltonpan/zeosyn_dataset.

One-Pot Synthesis of CHA/ERI-Type Zeolite Intergrowth from a Single Multiselective Organic Structure-Directing Agent

Wed, 13 Mar 2024 00:00:00 GMT

One-Pot Synthesis of CHA/ERI-Type Zeolite Intergrowth from a Single Multiselective Organic Structure-Directing Agent Kwon, Soonhyoung; Bello-Jurado, Estefanía; Ikonnikova, Evgeniia; Lee, Hwajun; Schwalbe-Koda, Daniel; Corma, Avelino; Willhammar, Tom; Olivetti, Elsa A; Gomez-Bombarelli, Rafael; Moliner, Manuel; Román-Leshkov, Yuriy We report the one-pot synthesis of a chabazite (CHA)/erionite (ERI)-type zeolite intergrowth structure characterized by adjustable extents of intergrowth enrichment and Si/Al molar ratios. This method utilizes readily synthesizable 6-azaspiro[5.6]dodecan-6-ium as the exclusive organic structure-directing agent (OSDA) within a potassium-dominant environment. High-throughput simulations were used to accurately determine the templating energy and molecular shape, facilitating the selection of an optimally biselective OSDA from among thousands of prospective candidates. The coexistence of the crystal phases, forming a distinct structure comprising disk-like CHA regions bridged by ERI-rich pillars, was corroborated via rigorous powder X-ray diffraction and integrated differential-phase contrast scanning transmission electron microscopy (iDPC S/TEM) analyses. iDPC S/TEM imaging further revealed the presence of single offretite layers dispersed within the ERI phase. The ratio of crystal phases between CHA and ERI in this type of intergrowth could be varied systematically by changing both the OSDA/Si and K/Si ratios. Two intergrown zeolite samples with different Si/Al molar ratios were tested for the selective catalytic reduction (SCR) of NO_x with NH₃, showing competitive catalytic performance and hydrothermal stability compared to that of the industry-standard commercial NH₃-SCR catalyst, Cu-SSZ-13, prevalent in automotive applications. Collectively, this work underscores the potential of our approach for the synthesis and optimization of adjustable intergrown zeolite structures, offering competitive alternatives for key industrial processes.

Recommendations for improving rigor and reproducibility in site specific characterization

Wed, 01 May 2024 00:00:00 GMT

Recommendations for improving rigor and reproducibility in site specific characterization Wrasman, Cody J; Bell, Alexis T; Chandler, Bert D; Harris, James W; Kwon, Stephanie; Ball, Madelyn R; Krishna, Siddarth H; Khatib, Sheima J; Bollini, Praveen; Román-Leshkov, Yuriy; “Bean” Getsoian, Andrew; Weber, Robert S; Lercher, Johannes A; Liu, Dongxia; Resasco, Daniel E; Bates, Jason S; Hall, Jacklyn N; Lebrón-Rodríguez, Edgard A; Paz Herrera, Laura; Notestein, Justin M; Schaidle, Joshua A Heterogeneous catalysis is driven by the interaction of reactant molecules and the catalyst surface. The locus of this interaction as well as the surrounding ensemble of atoms is referred to as the catalyst active site. Active site characterization attempts to distinguish active catalytic sites from inactive surface sites, to elucidate the structural and chemical nature of active sites, and to quantify active site concentration. Numerous techniques have been demonstrated to provide compositional and structural information about the active sites within a catalyst. However, each technique has its own limitations and experimental pitfalls that can lead to data misinterpretation or irreproducible results. This work aims to provide an overview of the types of data that can be collected, to outline common experimental challenges and how to avoid them, and to assemble relevant references for the most used active site characterization techniques. More broadly, we aim to outline best practices for researchers to collect, interpret, and report active site characterization data in a way that provides the most benefit to the broader catalysis community. Increasing the rigor and reproducibility of active site characterization offers a strategy to better link properties with catalytic performance and to enable the community to develop consensus concerning these relationships.

Design and Validation of a High-Throughput Reductive Catalytic Fractionation Method

Wed, 05 Jun 2024 00:00:00 GMT

Design and Validation of a High-Throughput Reductive Catalytic Fractionation Method Kenny, Jacob K; Neefe, Sasha R; Brandner, David G; Stone, Michael L; Happs, Renee M; Kumaniaev, Ivan; Mounfield, William P; Harman-Ware, Anne E; Devos, Katrien M; Pendergast, Thomas H; Medlin, J Will; Román-Leshkov, Yuriy; Beckham, Gregg T Reductive catalytic fractionation (RCF) is a promising method to extract and depolymerize lignin from biomass, and bench-scale studies have enabled considerable progress in the past decade. RCF experiments are typically conducted in pressurized batch reactors with volumes ranging between 50 and 1000 mL, limiting the throughput of these experiments to one to six reactions per day for an individual researcher. Here, we report a high-throughput RCF (HTP-RCF) method in which batch RCF reactions are conducted in 1 mL wells machined directly into Hastelloy reactor plates. The plate reactors can seal high pressures produced by organic solvents by vertically stacking multiple reactor plates, leading to a compact and modular system capable of performing 240 reactions per experiment. Using this setup, we screened solvent mixtures and catalyst loadings for hydrogen-free RCF using 50 mg poplar and 0.5 mL reaction solvent. The system of 1:1 isopropanol/methanol showed optimal monomer yields and selectivity to 4-propyl substituted monomers, and validation reactions using 75 mL batch reactors produced identical monomer yields. To accommodate the low material loadings, we then developed a workup procedure for parallel filtration, washing, and drying of samples and a ¹H nuclear magnetic resonance spectroscopy method to measure the RCF oil yield without performing liquid-liquid extraction. As a demonstration of this experimental pipeline, 50 unique switchgrass samples were screened in RCF reactions in the HTP-RCF system, revealing a wide range of monomer yields (21-36%), S/G ratios (0.41-0.93), and oil yields (40-75%). These results were successfully validated by repeating RCF reactions in 75 mL batch reactors for a subset of samples. We anticipate that this approach can be used to rapidly screen substrates, catalysts, and reaction conditions in high-pressure batch reactions with higher throughput than standard batch reactors.

Electrifying Hydroformylation Catalysts Exposes Voltage-Driven C–C Bond Formation

Wed, 19 Jun 2024 00:00:00 GMT

Electrifying Hydroformylation Catalysts Exposes Voltage-Driven C–C Bond Formation Zeng, Joy S; Cosner, Emma L; Delgado-Kukuczka, Spencer P; Jiang, Chenyu; Adams, Jason S; Román-Leshkov, Yuriy; Manthiram, Karthish Electrochemical reactions can access a significant range of driving forces under operationally mild conditions and are thus envisioned to play a key role in decarbonizing chemical manufacturing. However, many reactions with well-established thermochemical precedents remain difficult to achieve electrochemically. For example, hydroformylation (thermo-HFN) is an industrially important reaction that couples olefins and carbon monoxide (CO) to make aldehydes. However, the electrochemical analogue of hydroformylation (electro-HFN), which uses protons and electrons instead of hydrogen gas, represents a complex C-C bond-forming reaction that is difficult to achieve at heterogeneous electrocatalysts. In this work, we import Rh-based thermo-HFN catalysts onto electrode surfaces to unlock electro-HFN reactivity. At mild conditions of room temperature and 5 bar CO, we achieve Faradaic efficiencies of up to 15% and turnover frequencies of up to 0.7 h^-1. This electro-HFN rate is an order of magnitude greater than the corresponding thermo-HFN rate at the same catalyst, temperature, and pressure. Reaction kinetics and operando X-ray absorption spectroscopy provide evidence for an electro-HFN mechanism that involves distinct elementary steps relative to thermo-HFN. This work demonstrates a step-by-step experimental strategy for electrifying a well-studied thermochemical reaction to unveil a new electrocatalyst for a complex and underexplored electrochemical reaction.

Enabling Lignin Valorization Through Integrated Advances in Plant Biology and Biorefining

Mon, 22 Jul 2024 00:00:00 GMT

Enabling Lignin Valorization Through Integrated Advances in Plant Biology and Biorefining Dixon, Richard A; Puente-Urbina, Allen; Beckham, Gregg T; Román-Leshkov, Yuriy Despite lignin having long been viewed as an impediment to the processing of biomass for the production of paper, biofuels, and high-value chemicals, the valorization of lignin to fuels, chemicals, and materials is now clearly recognized as a critical element for the lignocellulosic bioeconomy. However, the intended application for lignin will likely require a preferred lignin composition and form. To that end, effective lignin valorization will require the integration of plant biology, providing optimal feedstocks, with chemical process engineering, providing efficient lignin transformations. Recent advances in our understanding of lignin biosynthesis have shown that lignin structure is extremely diverse and potentially tunable, while simultaneous developments in lignin refining have resulted in the development of several processes that are more agnostic to lignin composition. Here, we review the interface between in planta lignin design and lignin processing and discuss the advances necessary for lignin valorization to become a feature of advanced biorefining.

Reducing Solvent Consumption in Reductive Catalytic Fractionation through Lignin Oil Recycling

Wed, 14 Aug 2024 00:00:00 GMT

Reducing Solvent Consumption in Reductive Catalytic Fractionation through Lignin Oil Recycling Jang, Jun Hee; Callejón Álvarez, Júlia; Neuendorf, Quinn S; Román-Leshkov, Yuriy; Beckham, Gregg T Reductive catalytic fractionation (RCF) enables the simultaneous valorization of lignin and carbohydrates in lignocellulosic biomass through solvent-based lignin extraction, followed by depolymerization and catalytic stabilization of the extracted lignin. Process modeling has shown that the use of exogenous organic solvent in RCF is a challenge for economic and environmental feasibility, and previous works proposed that lignin oil, a mixture of lignin-derived monomers and oligomers produced by RCF, can be used as a cosolvent in RCF. Here, we further explore the potential of RCF solvent recycling with lignin oil, extending the feasible lignin oil concentration in the solvent to 100 wt %, relative to the previously demonstrated 0-19 wt % range. Solvents containing up to 80 wt % lignin oil exhibited 83-93% delignification, comparable to 83% delignification with a methanol-water mixture, and notably, using lignin oil solely as a solvent achieved 67% delignification in the absence of water. In additional experiments, applying the RCF solvent recycling approach to ten consecutive RCF reactions resulted in a final lignin oil concentration of 11 wt %, without detrimental impacts on lignin extraction, lignin oil molar mass distribution, aromatic monomer selectivity, and cellulose retention. Overall, this work further demonstrates the potential for using lignin oil as an effective cosolvent in RCF, which can reduce the burden on downstream solvent recovery.

A Career in Catalysis: Mark E. Davis

Fri, 23 Aug 2024 00:00:00 GMT

A Career in Catalysis: Mark E. Davis Arhancet, Juan P; Chen, Cong-Yan; Cybulskis, Viktor J; Gounder, Rajamani; Hong, Suk Bong; Jones, Christopher W; Kang, Jong Hun; Kubota, Yoshihiro; Lee, Hyunjoo; Orazov, Marat; Román-Leshkov, Yuriy; Schmidt, Joel E Mark E. Davis led an independent research program from 1981 to 2023, beginning at the Virginia Polytechnic Institute and State University (VPI) and then transitioning to the California Institute of Technology (Caltech). His research program was marked by exceptional creativity, breadth, and depth. With classical training in reaction engineering, Davis developed expertise in experimental heterogeneous catalysis and led work in this discipline for more than 40 years. His name is synonymous with zeolites, and today, he is one of the most widely recognized experts in zeolite synthesis, characterization, and catalysis in the world. Early work at the VPI focused on zeolites and catalysis with supported metal coordination complexes. His creativity was evident at the earliest stages of his career, with the development of supported aqueous phase catalysts and the world’s first crystalline, extra-large pore molecular sieve, both reported in the late 1980s. A move to Caltech saw a significant expansion of his zeolite synthesis program and the rapid acceleration of a multidecade collaboration with Dr. Stacey I. Zones of Chevron. At Caltech, his work expanded to include studies of molecular recognition and catalysis with organic/inorganic hybrid materials, and he developed a large, parallel program in drug delivery. His work on catalysis heavily emphasized zeolite catalysis, including major thrusts on the conversion of sugars in the liquid phase and methanol in the gas phase. Numerous new zeolites and molecular sieves were discovered throughout the four decades of the Davis laboratory, highlighted by a successful, multidecade quest to prepare a chiral zeolite with enantioselective catalytic properties. Davis is one of the most decorated researchers of the last four decades. He is one of only 21 living people currently elected to all of the US National Academies (Engineering, Science, Medicine) and elected as a Fellow of the National Academy of Inventors. He was the first engineer to win the NSF’s Alan T. Waterman Award and is one of only two researchers (to date) to win the International Zeolite Association’s Donald Breck Award twice (1989, 2019). Awards from the ACS (Ipatieff, Murphree, and Somorjai Awards), AIChE (Colburn, Professional Progress Awards), and North American Catalysis Society (Emmett Award) are among his accolades.

Plant Bioelectrical Signals for Environmental and Emotional State Classification

Wed, 05 Nov 2025 00:00:00 GMT

Plant Bioelectrical Signals for Environmental and Emotional State Classification Gloor, Peter A. In this study, we present a pilot investigation using a single Purple Heart plant (Tradescantia pallida) to explore whether bioelectrical signals for dual-purpose classification tasks: environmental state detection and human emotion recognition. Using an AD8232 ECG sensor at 400 Hz sampling rate, we recorded 3 s bioelectrical signal segments with 1 s overlap, converting them to mel-spectrograms for ResNet18 CNN (Convolutional Neural Network) classification. For lamp on/off detection, we achieved 85.4% accuracy with balanced precision (0.85–0.86) and recall (0.84–0.86) metrics across 2767 spectrogram samples. For human emotion classification, our system achieved optimal performance at 73% accuracy with 1 s lag, distinguishing between happy and sad emotional states across 1619 samples. These results should be viewed as preliminary and exploratory, demonstrating feasibility rather than definitive evidence of plant-based emotion sensing. Replication across plants, days, and experimental sites will be essential to establish robustness. The current study is limited by a single-plant setup, modest sample size, and reliance on human face-tracking labels, which together preclude strong claims about generalizability.

Within-Subtype HIV-1 Polymorphisms and Their Impacts on Intact Proviral DNA Assay (IPDA) for Viral Reservoir Quantification

Fri, 31 Oct 2025 00:00:00 GMT

Within-Subtype HIV-1 Polymorphisms and Their Impacts on Intact Proviral DNA Assay (IPDA) for Viral Reservoir Quantification Arikatla, Mohith Reddy; Mathad, Jyoti S.; Reddy, Kavidha; Reddy, Nicole; Ndung’u, Thumbi; Dupnik, Kathryn M.; Lee, Guinevere Q. The Intact Proviral DNA Assay (IPDA) is widely used to quantify genome-intact HIV proviruses in people living with HIV, but viral sequence diversity has been observed to cause assay failures due to primer/probe mismatches. Adapted for subtype C, IPDA-BC is a modified version of the IPDA validated on South African HIV-1 subtype C. India is also impacted by subtype C, but IPDA performance within-subtype across geographical regions is not well studied. We analyzed Indian (IN) and South African (ZA) subtype C sequences in silico, hypothesizing that IPDA-BC may underperform with IN viruses. Primer/probe binding was predicted using three increasingly stringent nucleotide mismatch criteria, whose sensitivity and specificity were evaluated against experimental IPDA outcomes. Phylogenetic analyses confirmed that IN and ZA subtype C sequences form distinct clusters with significant compartmentalization (p < 0.003). Across criteria, up to 6–10% decreases in primer/probe binding were observed in IN versus ZA, with the env forward primer being the most affected. These criteria showed low sensitivity (18–53%) and variable specificity (67–100%) in predicting experimental outcomes. In conclusion, even within subtype, HIV-1 variation across geographical regions may impact IPDA performance, underscoring the need for improved predictive models to guide assay design for global HIV cure research.

An Investigation of the Modulating Effects of Sensory Stimulation and Transcranial Magnetic Stimulation on Memory-Related Brain Activity

Fri, 31 Oct 2025 00:00:00 GMT

An Investigation of the Modulating Effects of Sensory Stimulation and Transcranial Magnetic Stimulation on Memory-Related Brain Activity Nikolin, Stevan; Wang, Matthew; Moffa, Adriano; Huang, Haijing; Xu, Mei; Pande, Siddhartha Raj; Martin, Donel Background/Objectives: As the global population ages, the prevalence of disorders associated with memory dysfunction (e.g., Alzheimer’s disease) continues to increase. There is a need for novel interventions that can enhance memory and support affected individuals. Non-invasive brain stimulation provides a promising approach to engage circuits within the hippocampal network, a group of brain regions critical for episodic memory, and thereby improve cognition. Methods: Twenty healthy participants completed a single-blind, within-subject crossover study over four sessions. In each session, they received one of four interventions whilst viewing pictures of real-world objects: 40 Hz synchronised audiovisual stimulation (AVS), theta burst stimulation (TBS), a combination of synchronised 5 Hz repetitive transcranial magnetic stimulation with AVS (rTMS + AVS), or sham rTMS. Electroencephalography (EEG) was recorded to measure associated brain activity changes. Following each intervention, participants completed a recognition memory task. Results: Mixed-effect repeated measure models (MRMMs) revealed no significant differences in recognition memory performance or theta (5 Hz) activity across conditions. However, both TBS and rTMS + AVS significantly increased gamma (40 Hz) activity compared to sham rTMS, and TBS induced a widespread increase in theta-gamma phase-amplitude coupling during picture viewing. Conclusions: While the neuromodulatory interventions did not enhance memory performance, the observed increase in gamma activity, particularly following rTMS-based stimulation, suggests potential engagement of neural processes associated with memory. These findings warrant further investigation into the role of gamma oscillations in memory and cognitive enhancement.

Shaping In-Vehicle Behaviours through Activity-Centered Design

Wed, 08 Oct 2025 00:00:00 GMT

Shaping In-Vehicle Behaviours through Activity-Centered Design Patel, Ankit; Gershon, Pnina; Habibovic, Azra; Novakazi, Fjoll?; Akahoshi, Sakura; Alsaid, Areen; Cha, Kyungjoo In today’s fast-paced society, most individuals commute either by personal vehicle or public transportation. User preferences and requirements are crucial, with design playing a significant role. The nature of design should be such that it is both inclusive and assimilative, and its purpose is to propel innovation and progress while also improving the quality of life of the user. That is why a general focus was given to the user-centered design approach while developing vehicles, especially, cabin (cockpit) design. With prioritizing the user activities, it is interesting to explore how users’ experience and behavior vary through the application of different design approaches. Nevertheless, existing literature has significantly overlooked the impact of design approaches on “human activity". Therefore, the main objective of the workshop is to examine the relationships between activity-centered design and user behavior. AutomotiveUI Adjunct ’25, Brisbane, QLD, Australia

Scale, Engage, or Both?: Potential and Perils of Applying Large Language Models in Interview and Conversation-Based Research

Fri, 17 Oct 2025 00:00:00 GMT

Scale, Engage, or Both?: Potential and Perils of Applying Large Language Models in Interview and Conversation-Based Research Hwang, Angel Hsing-Chi; Aubin Le Qu?r?, Marianne; Schroeder, Hope; Cuevas, Alejandro; Dow, Steven; Kapania, Shivani; Rho, Eugenia An increasing number of studies apply tools powered by large language models (LLMs) to interview and conversation-based research, one of the most commonly used research methods in CSCW. This panel invites the CSCW community to critically debate the role of LLMs in reshaping interview-based methods. We aim to explore how these tools might (1) address persistent challenges in conversation-based research, such as limited scalability and participant engagement, (2) introduce novel methodological possibilities, and (3) surface additional practical, technical, and ethical concerns. The panel discussion will be grounded on the panelists’ prior experience applying LLMs to their own interview and conversation-based research. We ask whether LLMs offer unique advantages to enhance interview research, beyond automating certain aspects of the research process. Through this discussion, we encourage researchers to reflect on how applying LLM tools may require rethinking research design, conversational protocols, and ethical practices. CSCW Companion ’25, Bergen, Norway

Yeast Display Reveals Plentiful Mutations That Improve Fusion Peptide Vaccine-Elicited Antibodies Beyond 59% HIV-1 Neutralization Breadth

Mon, 27 Oct 2025 00:00:00 GMT

Yeast Display Reveals Plentiful Mutations That Improve Fusion Peptide Vaccine-Elicited Antibodies Beyond 59% HIV-1 Neutralization Breadth França, Camila T; Pletnev, Sergei; Madan, Bharat; Katsamba, Phinikoula S; McKee, Krisha; Morano, Nicholas C; Zhang, Baoshan; Bahna, Fabiana; Bylund, Tatsiana; Lin, Bob C; Louder, Mark K; Mannepalli, Seetha; Nimrania, Rajani; O’Dell, Sijy; Doria-Rose, Nicole A; Kwong, Peter D; Shapiro, Lawrence; Sheng, Zizhang; Zhou, Tongqing; DeKosky, Brandon J Background/Objectives: Vaccine elicitation of antibodies with high HIV-1 neutralization breadth is a long-standing goal. Recently, the induction of such antibodies has been achieved at the fusion peptide site of vulnerability. Questions remain, however, as to how much anti-fusion peptide antibodies can be improved and whether their neutralization breadth and potency are sufficient to prevent HIV-1 infection. Methods: Here, we use yeast display coupled with deep mutational screening and biochemical and structural analyses to study the improvement of the best fusion peptide-directed, vaccine-elicited antibody, DFPH_a.01, with an initial 59% breadth. Results: Yeast display identified both single and double mutations that improved recognition of HIV-1 envelope trimers. We characterized two paratope-distal light chain (LC) mutations, S10R and S59P, which together increased breadth to 63%. Biochemical analysis demonstrated DFPH-a.01_10R59P-LC, and its component mutations, to have increased affinity and stability. Cryo-EM structural analysis revealed elbow-angle influencing by S10R-LC and isosteric positioning by S59P-LC as explanations for enhanced breadth, affinity, and stability. Conclusions: These results, along with another antibody with enhanced performance (DFPH-a.01_1G10A56K-LC with 64% breadth), suggest that mutations improving DFPH_a.01 are plentiful, an important vaccine insight.

A Probabilistic Perspective on Tiling Sparse Tensor Algebra

Fri, 17 Oct 2025 00:00:00 GMT

A Probabilistic Perspective on Tiling Sparse Tensor Algebra Sharma, Ritvik; Xue, Zi Yu; Zhang, Nathan; Lacouture, Rubens; Kjolstad, Fredrik; Achour, Sara; Horowitz, Mark Sparse tensor algebra computations are often memory-bound due to irregular access patterns and low arithmetic intensity. We present D2T2 (Data-Driven Tensor Tiling), a framework that optimizes static coordinate-space tiling schemes to minimize memory traffic by identifying and leveraging relevant high-level statistics from input operands. For a given tensor algebra computation, D2T2 collects statistics from input tensors, builds a probability distribution-based model of the tensor computation, and uses it to predict traffic for various tiling configurations. It searches over tile shape and size configurations to minimize total traffic. We evaluate D2T2 against Tailors and DRT, two state of the art tiling schemes for sparse tensor algebra. We find that D2T2 achieves, on average, a 2.54 × speedup over Tailors and a 1.13× lower memory bandwidth compared to DRT for sparse-sparse matrix multiplication (SpMSpM). We also achieve 1.22–48.94× lower bandwidth for SpMSpM and up to 34.31× lower bandwidth for tensor operations (TTM and MTTKRP) than conservative static tiling schemes. Unlike prior tiling techniques, D2T2 is deployable without specialized hardware support. On Opal, a 16nm sparse tensor algebra accelerator, D2T2 generated tiling configurations that achieve 1.23–3.34 × speedups compared to their original hand-tuned configurations. MICRO ’25, Seoul, Republic of Korea

HapticHearing: A Haptic Feedback System for Complementing Auditory Speech Perception for Mild-to-Moderate Hearing Loss

Wed, 22 Oct 2025 00:00:00 GMT

HapticHearing: A Haptic Feedback System for Complementing Auditory Speech Perception for Mild-to-Moderate Hearing Loss Chin, Sam; Fitz-Gibbon, Emmie; Huang, Bingjian; Paradiso, Joseph Age-related hearing loss is often caused by cochlear hair cell degradation. This creates a challenge for hearing aids, which rely on sound amplification. Once hearing ability in a specific frequency is lost, amplification alone provides little benefit. Previous haptic systems have tried to solve this with complete sensory substitution, converting audio signals like phonemes to tactile patterns. However, these systems require significant amount of time to learn, and induce high cognitive load in haptic perception. Our system, HapticHearing, takes an alternative approach of leveraging a user’s residual hearing and complementing it with tactile feedback. We present a custom multi-actuator haptic device, designed to translate phonemic information from speech into tactile patterns that are customized to a user’s hearing loss and speech perception abilities. The system consists of a microphone for speech capture, four-band energy envelope extraction with vowel embedding, a custom USB-to-haptic driver PCB, and wearable devices containing eight vibrotactile actuators that deliver personalized tactile feedback based on the user’s audiogram. Psychophysical validation (n=9) showed neck-worn devices achieved better spatial localization (67% vs 53%) while while bracelet and necklace devices had lower detection thresholds than over-ear (thresholds 0.09 vs 0.18). ASSETS ’25, Denver, CO, USA

Resonance: Drawing from Memories to Imagine Positive Futures through AI-Augmented Journaling

Thu, 09 Oct 2025 00:00:00 GMT

Resonance: Drawing from Memories to Imagine Positive Futures through AI-Augmented Journaling Zulfikar, Wazeer; Chiaravalloti, Treyden; Shen, Jocelyn; Picard, Rosalind; Maes, Pattie People inherently use experiences of their past while imagining their future, a capability that plays a crucial role in mental health. Resonance is an AI-powered journaling tool designed to augment this ability by offering AI-generated, action-oriented suggestions for future activities based on the user’s own past memories. Suggestions are offered when a new memory is logged and are followed by a prompt for the user to imagine carrying out the suggestion. In a two-week randomized controlled study (N=55), we found that using Resonance significantly improved mental health outcomes, reducing the users’ PHQ8 scores, a measure of current depression, and increasing their daily positive affect, particularly when they would likely act on the suggestion. Notably, the effectiveness of the suggestions was higher when they were personal, novel, and referenced the user’s logged memories. Finally, through open-ended feedback, we discuss the factors that encouraged or hindered the use of the tool. AHs 2025, Masdar City, Abu Dhabi, United Arab Emirates

A11yShape: AI-Assisted 3-D Modeling for Blind and Low-Vision Programmers

Wed, 22 Oct 2025 00:00:00 GMT

A11yShape: AI-Assisted 3-D Modeling for Blind and Low-Vision Programmers Zhang, Zhuohao (Jerry); Li, Haichang; Yu, Chun Meng; Faruqi, Faraz; Xie, Junan; Kim, Gene; Fan, Mingming; Forbes, Angus; Wobbrock, Jacob; Guo, Anhong; He, Liang Building 3-D models is challenging for blind and low-vision (BLV) users due to the inherent complexity of 3-D models and the lack of support for non-visual interaction in existing tools. To address this issue, we introduce A11yShape, a novel system designed to help BLV users who possess basic programming skills understand, modify, and iterate on 3-D models. A11yShape leverages LLMs and integrates with OpenSCAD, a popular open-source editor that generates 3-D models from code. Key functionalities of A11yShape include accessible descriptions of 3-D models, version control to track changes in models and code, and a hierarchical representation of model components. Most importantly, A11yShape employs a cross-representation highlighting mechanism to synchronize semantic selections across all model representations—code, semantic hierarchy, AI description, and 3-D rendering. We conducted a multi-session user study with four BLV programmers, where, after an initial tutorial session, participants independently completed 12 distinct models across two testing sessions, achieving results that aligned with their own satisfaction. The result demonstrates that participants were able to comprehend provided 3-D models, as well as independently create and modify 3-D models—tasks that were previously impossible without assistance from sighted individuals. ASSETS ’25, Denver, CO, USA

Benthic: Perceptually Congruent Structures for Accessible Charts and Diagrams

Wed, 22 Oct 2025 00:00:00 GMT

Benthic: Perceptually Congruent Structures for Accessible Charts and Diagrams Mei⁎, Catherine; Pollock⁎, Josh; Hajas, Daniel; Zong, Jonathan; Satyanarayan, Arvind Graphical representations — such as charts and diagrams — have a visual structure that communicates the relationship between visual elements. For instance, we might consider two elements to be connected when there is a line or arrow between them, or for there to be a part-to-whole relationship when one element is contained within the other. Yet, existing screen reader solutions rarely surface this structure for blind and low-vision readers. Recent approaches explore hierarchical trees or adjacency graphs, but these structures capture only parts of the visual structure — containment or direct connections, respectively. In response, we present Benthic, a system that supports perceptually congruent screen reader structures, which align screen reader navigation with a graphic’s visual structure. Benthic models graphical representations as hypergraphs: a relaxed tree structure that allows a single hyperedge to connect a parent to a set of children nodes. In doing so, Benthic is able to capture both hierarchical and adjacent visual relationships in a manner that is domain-agnostic and enables fluid (i.e., concise and reversible) traversal. To evaluate Benthic, we conducted a study with 15 blind participants who were asked to explore two kinds of graphical representations that have previously been studied with sighted readers. We find that Benthic’s perceptual congruence enabled flexible, goal-driven exploration and supported participants in building a clear understanding of each diagram’s structure. ASSETS ’25, Denver, CO, USA

Quartz: A Reconfigurable, Distributed-Memory Accelerator for Sparse Applications

Fri, 17 Oct 2025 00:00:00 GMT

Quartz: A Reconfigurable, Distributed-Memory Accelerator for Sparse Applications Golden, Courtney; Feldmann, Axel; Emer, Joel; Sanchez, Daniel Iterative sparse matrix computations lie at the heart of many scientific computing and graph analytics algorithms. On conventional systems, their irregular memory accesses and low arithmetic intensity create challenging memory bandwidth bottlenecks. To overcome such bottlenecks, distributed-SRAM architectures are structured as an array of tiles, each with a processing element (PE) and a small local memory, to achieve very high aggregate memory bandwidth. However, current distributed-SRAM architectures suffer from either poor programmability due to over-specialized PEs or poor compute performance due to inefficient general-purpose PEs. We propose Quartz, a new architecture that uses short dataflow tasks and reconfigurable PEs in a distributed-SRAM system to deliver both high performance and high programmability. Unlike traditional sparse CGRAs or on-die reconfigurable engines, Quartz allows reconfigurable compute to be highly utilized and scaled by (1) providing high memory bandwidth to each processing element and (2) introducing a task-level dataflow execution model that fits this new setting. Our execution model dynamically reconfigures each tile’s PE in response to inter-tile messages to execute tasks on local data. This execution model enables fine-grained data partitioning across tiles. To make execution efficient, we explore novel data partitioning techniques that use graph and hypergraph partitioning to minimize network traffic and balance load in the face of both static-static and static-dynamic operand sparsity. To ensure programmability, we show how a wide range of Einsum-expressible computations and flexible data distributions can be systematically captured in small tasks for execution on Quartz. Quartz’s architecture, data partitioning techniques, and programming model together achieve gmean 21.4 × speedup over a prior state-of-the-art system for six different iterative sparse applications from scientific computing and graph analytics. MICRO ’25, Seoul, Republic of Korea

Converting Spatial to Social: Using Persistent Homology to Understand Social Groups

Sun, 12 Oct 2025 00:00:00 GMT

Converting Spatial to Social: Using Persistent Homology to Understand Social Groups Chen, Valerie; Liang, Claire; Shah, Julie; Andrist, Sean In social settings, people display sophisticated spatial behaviors—for example, one might naturally enter into a conversation by sidling up to a group. Artificial agents will need the ability to reason about spatial representations of social information to understand not only how social groups form, but also how to interact within and around them. Leveraging the insight that people reason about shared space topologically rather than geometrically, we employ techniques from applied topology to introduce a new method for social group analysis that improves quantifiability and enables rigorous analysis of social group structure. We present a novel topological mathematical formalism called the social simplicial complex that provides an equivalence relation for socially analogous configurations of people and is provably robust against small perturbations and noise. Moreover, this formalism suggests quantifiable metrics to assess the confidence of social group existence and the social closeness of people within groups. We further use this formalism to introduce an open-source toolkit for evaluating possible models of social relationships, which we name the Social Topological Analysis (SoTA) Toolkit. Finally, we explore algebraic topology’s potential to serve more generally as a powerful tool for multi-modal social data processing, and its possibilities for further applications in social-spatial analysis. ICMI ’25, Canberra, ACT, Australia

LLMs in Citation Intent Classification: Progress, Precision, and Reproducibility Challenges

Tue, 21 Oct 2025 00:00:00 GMT

LLMs in Citation Intent Classification: Progress, Precision, and Reproducibility Challenges Fogelson, Alex; Thompson, Neil; Trišović, Ana Understanding the intent behind scientific citations is critical for advancing scholarly search and knowledge mapping. This paper reflects on the methodological use of large language models (LLMs) for multi-class citation intent classification. Our experiments evaluating a diverse range of models and approaches reveal striking disagreement among state-of-the-art (SotA) systems. This inconsistency suggests that citation intent classification remains a challenging task for LLMs raising questions about the robustness, reliability and replicability of current methods. Moreover, our findings highlight a concerning dependency on proprietary LLMs that, even with access to compute resources, were necessary to achieve sufficient accuracy. This introduces new challenges, as silent updates, lack of versioning, and opaque training pipelines pose threats to methodological transparency and long-term reproducibility in LLMenabled research. ACM REP ’25, Vancouver, BC, Canada

Ancestral Technology: Inside Colombia’s Hidden Technological Landscape

Thu, 30 Oct 2025 00:00:00 GMT

Ancestral Technology: Inside Colombia’s Hidden Technological Landscape Reynolds-Cuellar, Pedro Luz Marina Burgos’ fingers moved deliberately across the threads, constructing a tšombiach—a ceremonial sash commonly used to protect and strengthen the body. “This is the frog; to us, it represents fertility,” she explained, pointing to an emerging pattern. “This is the sun. Families weave it differently. This is how the tšombiach helps us tell our own story.” What I witnessed in this Colombian village was not simply craft—it was a technology for encoding and transmitting intergenerational knowledge. Passing most of my time between MIT and Harvard created a sense of technology as merely technical or socio-technical systems serving as a means to undetermined progress that only a few seem able to influence or have power over. A sense of relentless push towards the new, often at the expense of the old. Learning from Luz Marina, a traditional weaver from the Quillasinga Indigenous people, helped me make sense of radically different technological values, motivations and purposes. She is part of a centuries-long tradition of sustaining technologies designed for a different purpose entirely: cultural preservation. These technological systems solve immediate problems while maintaining the social fabric that makes problem-solving possible across generations. During five years of fieldwork in Colombia’s rural communities —ultimately leading to my doctoral dissertation— I encountered technologies that function according to entirely different logics than those driving “modern” narratives of innovation. I began —along with my collaborators in Colombia— conceptualizing these as “ancestral technologies”: forms of world-making —some of which take the form of artifacts— that primarily support cultural cohesion, remain rooted in specific geographies and carry their history through collective memory. Unlike modern technologies optimized for profit, efficiency or scale, these ancestral systems optimize for continuity and collective meaning. In an era when predictive technology sells the fantasy that unlimited computational power must be our goal as a society, perhaps the question is not whether we can build more powerful systems, but whether we can build systems that help us preserve what matters most.

Asymmetric linker generates intrinsically disordered metal–organic framework with local MOF-74 structure

Thu, 14 Aug 2025 00:00:00 GMT

Asymmetric linker generates intrinsically disordered metal–organic framework with local MOF-74 structure Dinakar, Bhavish; Oppenheim, Julius J; Vandone, Marco; Torres, Juan F; Iliescu, Andrei; Yang, Zhentao; Román-Leshkov, Yuriy; Dincă, Mircea Here, we report an intrinsically disordered MOF in the MOF-74 family, Mg2x(as-dobpdc) (as-dobpdc4 = 30 ,4-dioxidobiphenyl-3,40 -dicarboxylate). Despite the absence of crystallinity, this material exhibits local ordering consistent with that of its crystalline isomers, maintains porosity, and exhibits a high density of open metal sites.

Sustainable aviation fuels from biomass and biowaste via bio- and chemo-catalytic conversion: Catalysis, process challenges, and opportunities

Sun, 01 Jun 2025 00:00:00 GMT

Sustainable aviation fuels from biomass and biowaste via bio- and chemo-catalytic conversion: Catalysis, process challenges, and opportunities Zhang, Junyan; Webber, Matthew S; Pu, Yunqiao; Li, Zhenglong; Meng, Xianzhi; Stone, Michael L; Wei, Bingqing; Wang, Xueqi; Yuan, Sainan; Klein, Bruno; Seemala, Bhogeswararao; Wyman, Charles E; Ramasamy, Karthikeyan K; Thorson, Mike; Langholtz, Matthew H; Heyne, Joshua S; Koishybay, Aibolat; Adhikari, Shiba; Cao, Sufeng; Sutton, Andrew D; Tuskan, Gerald A; Román-Leshkov, Yuriy; Ragauskas, Arthur J; Ling, Tao; Davison, Brian H Sustainable aviation fuel (SAF) production from biomass and biowaste streams is an attractive option for decarbonizing the aviation sector, one of the most-difficult-to-electrify transportation sectors. Despite ongoing commercialization efforts using ASTM-certified pathways (e.g., lipid conversion, Fischer–Tropsch synthesis), production capacities are still inadequate due to limited feedstock supply and high production costs. New conversion technologies that utilize lignocellulosic feedstocks are needed to meet these challenges and satisfy the rapidly growing market. Combining bio- and chemo-catalytic approaches can leverage advantages from both methods, i.e., high product selectivity via biological conversion, and the capability to build C-C chains more efficiently via chemical catalysis. Herein, conversion routes, catalysis, and processes for such pathways are discussed, while key challenges and meaningful R&D opportunities are identified to guide future research activities in the space. Bio- and chemo-catalytic conversion primarily utilize the carbohydrate fraction of lignocellulose, leaving lignin as a waste product. This makes lignin conversion to SAF critical in order to utilize whole biomass, thereby lowering overall production costs while maximizing carbon efficiencies. Thus, lignin valorization strategies are also reviewed herein with vital research areas identified, such as facile lignin depolymerization approaches, highly integrated conversion systems, novel process configurations, and catalysts for the selective cleavage of aryl C–O bonds. The potential efficiency improvements available via integrated conversion steps, such as combined biological and chemo-catalytic routes, along with the use of different parallel pathways, are identified as key to producing all components of a cost-effective, 100% SAF.

Methods for Carbon Mass Closure in Polyolefin Hydrocracking

Thu, 24 Jul 2025 00:00:00 GMT

Methods for Carbon Mass Closure in Polyolefin Hydrocracking Brenner, Anna E; Drake, Griffin; Beckham, Gregg T; Román-Leshkov, Yuriy Heterogeneous catalytic hydrocracking of polyolefins is a promising approach for the processing of postconsumer plastics, but product quantification methods remain inconsistent across the literature. In systems that generate a large fraction of vapor-phase products, typical product capture methods can result in large carbon balance deficits, exceeding 50%, compromising reported yields and selectivities. Here, we identify the major sources of product loss and develop enhanced capture methods to improve the quantification accuracy. Seven supplemental techniques were evaluated, targeting either increased vapor recovery (by increasing the volatility or system volume) or enhanced retention in the liquid phase (by decreasing volatility). Among these, a flow collection approach using a continuous helium sweep and downstream gas sampling bag capture yielded the highest recovery, achieving a 96 ± 9.2% carbon balance closure. We show that the efficacy of these methods is strongly dependent on product distribution. In general, solvent addition was most effective when condensable species dominate the product distribution, while flow collection was preferred when both condensable species and light gases are present in high concentrations. These results highlight the need for method-specific workup strategies and demonstrate that no single protocol is universally optimal. We provide general guidelines for selecting and implementing robust product capture techniques, enabling accurate yield and selectivity determinations in polyolefin hydrocracking systems.

Lignin Extraction and Condensation as a Function of Temperature, Residence Time, and Solvent System in Flow-through Reactors

Fri, 01 Aug 2025 00:00:00 GMT

Lignin Extraction and Condensation as a Function of Temperature, Residence Time, and Solvent System in Flow-through Reactors Brandner, David G; Gracia Vitoria, Jaime; Kenny, Jacob K; Bussard, Jeremy R; Jang, Jun Hee; Woodworth, Sean P; Vanbroekhoven, Karolien; Román-Leshkov, Yuriy; Beckham, Gregg T Solvolytic extraction of lignin from biomass is a critical step in lignin-first biorefining, including the reductive catalytic fractionation (RCF) process. Key to optimal RCF processing is the ability to rapidly extract lignin from biomass at high delignification extents and transfer the lignin molecules to a catalyst surface in a time frame that minimizes lignin condensation reactions. Here, we use a flow-through reactor to study the effects of temperature (175-250 °C), residence time (9 to 36 min), and solvent composition (methanol and methanol-water) on lignin extraction and condensation. We evaluated three metrics at each condition: total delignification, delignification rate, and extent of condensation, the latter measured by a decrease in monomer yield for batch hydrogenolysis reactions of solvolysis liquor compared to batch RCF reactions. We observe that delignification is predominantly determined by temperature, while residence time dictates the lignin condensation extent. Moreover, the extent of both extraction and condensation increased in the methanol-water solvent system compared to that in the methanol system. Lignin extracted in methanol is stable up to 18-min residence times at or below 225 °C, while a majority of the lignin extracted in methanol-water is condensed with a 9-min residence time at 200 °C. These results can inform reactor designs and solvent selection for lignin-first biorefining processes that aim to physically separate the biomass and catalyst.

The legacy of Rudolf Nieuwenhuys in perspective

Mon, 24 Nov 2025 00:00:00 GMT

The legacy of Rudolf Nieuwenhuys in perspective Pignatelli, Michele; Rockland, Kathleen S. Professor Nieuwenhuys is among the great neuroanatomists and a historical figure of the later 20th and early 21st centuries. His legacy is manifold. There is the tangible legacy of the multiple scientific volumes, at once physical and conceptual entities. There is the generational legacy of handed-on scientific and intellectual traditions, and there is the legacy of specific scientific directions. In this brief Commentary, we highlight just two examples of his scientific contributions.

Some Advice on Sustainability: ‘I Would Never Get into a Business I Did Not Really Understand’

Tue, 01 Nov 2022 00:00:00 GMT

Some Advice on Sustainability: ‘I Would Never Get into a Business I Did Not Really Understand’ Wright, Randall S. My father, Chester S. Wright, was a business executive. He was president of two manufacturing companies and a member of the board of directors of four others. As a young boy, I remember him coming home from work in a big, black Chrysler Imperial—a “company car”—fitted out with shining chromium bumpers and gleaming radiator grill. After a wonderful home-cooked dinner my mother always made for my father, my two sisters, and me, he and I would head out in the Imperial to Gray’s Drug Store so he could buy House of Windsor cigars, and we could pick up the latest copies of Popular Mechanics, Popular Science, and Mechanix Illustrated.

The 5-methylcytosine DNA glycosylase ROS1 prevents paternal genome hypermethylation in Arabidopsis endosperm

Thu, 18 Sep 2025 00:00:00 GMT

The 5-methylcytosine DNA glycosylase ROS1 prevents paternal genome hypermethylation in Arabidopsis endosperm Hemenway, Elizabeth A.; Gehring, Mary Background DNA methylation patterning is a consequence of opposing activities of DNA methyltransferases and DNA demethylases. In many plant and animal species, reproduction is a period of significant epigenome lability. In flowering plants, two distinct female gametes, the egg cell and the central cell, are fertilized to produce the embryo and the endosperm of the seed. The endosperm is an unusual tissue, exemplified by triploidy and reduced DNA methylation. In Arabidopsis thaliana, a 5-methylcytosine DNA glycosylase, DME, demethylates regions of the central cell genome, leading to methylation differences between maternally- and paternally-inherited endosperm genomes after fertilization. Expression of DME in the central cell is required for gene imprinting, or parent-of-origin specific gene expression, in endosperm. DME is part of a four member gene family in Arabidopsis that includes ROS1, DML2, and DML3. It is unknown whether any of the other DNA glycosylases are required for endosperm methylation patterning. Results Using whole-genome methylation profiling, we identify ROS1 target regions in the endosperm. We show that ROS1 prevents hypermethylation of paternally-inherited alleles in the endosperm at regions that lack maternal or paternal allele methylation in wild-type endosperm. Additionally, we demonstrate that at many ROS1 target regions the maternal alleles are demethylated by DME. Conclusions ROS1 promotes epigenetic symmetry between parental genomes in the endosperm by preventing CG methylation gain on the paternal genome. We conclude that ROS1 and DME act in a parent-of-origin-specific manner at shared endosperm targets, and consider possible implications for the evolution of imprinting mechanisms.

Players chatter and dice clatter: exploring sonic power relations in posthuman game-based learning ecologies

Fri, 28 Oct 2022 00:00:00 GMT

Players chatter and dice clatter: exploring sonic power relations in posthuman game-based learning ecologies Woods, Peter J; Jones, Karis Responding to both recent interest in sound within qualitative education research and sound studies literature that conceptualizes sound as a posthuman technology, we use this paper to explore the following research questions: How does sound both enact and unveil posthuman learning ecologies? And how can education scholars engage sound within posthuman research? Through a posthuman framework, we position noise as an analytical tool for exploring and unveiling more-than-human relations. We then draw parallels between posthuman qualitative research into sound (via noise) and the ideological foundation of experimental music, a musical tradition deeply invested in working with sound as an agentic actor. Within this alignment, we propose using graphic scores to transcribe sonic data without reinscribing humanist research aims. To illustrate, we provide a micro-analysis of preservice teachers engaged in a role-playing game activity and uncover the ways sound asserts its agency within learning ecologies.

Palonosetron, a 5-HT3 Receptor Antagonist, Induces G1 Cell Cycle Arrest and Autophagy in Gastric Cancer Cells

Wed, 15 Oct 2025 00:00:00 GMT

Palonosetron, a 5-HT3 Receptor Antagonist, Induces G1 Cell Cycle Arrest and Autophagy in Gastric Cancer Cells Yoo, Young Chul; Lin, Lin; Lee, Sihak; Shin, Yeeun Rachel; Oh, Ju Eun; Kim, Na Young Serotonin or 5-hydroxytryptamine (5-HT) has been implicated in promoting cancer cell growth by acting on 5-HT receptors, such as 5-HT1 and 5-HT2 receptors. However, the role of 5-HT3 receptor antagonists in gastric cancer cell lines remains unclear. This study aimed to evaluate the effect of 5-HT3 receptor antagonists (ondansetron, palonosetron, and ramosetron) on cancer cell growth using AGS and MKN-1 cell lines, as well as the xenograft mouse model. All the three antagonists inhibited cell proliferation, migration, and colony formation in AGS cells. Specifically, palonosetron induced G1 cell cycle arrest, autophagy, and phosphorylation of GSK3β, along with increased expression of p27, p53, and LC3B. In vivo studies demonstrated that palonosetron reduced tumor growth and modulated pro-inflammatory cytokines—tumor necrosis factor alpha, interleukin 6, and interleukin 1β. These findings suggest that 5-HT3 receptor antagonists, especially palonosetron, exert anti-tumor effects in gastric cancer through G1 cell cycle regulation and immunomodulation. The results position palonosetron as a promising lead for further preclinical development in gastric cancer.

50 years of nanomechanics: Scale-bridging mechanistic insights through the looking glass

Mon, 17 Nov 2025 00:00:00 GMT

50 years of nanomechanics: Scale-bridging mechanistic insights through the looking glass Han, Seung M.; Gianola, Daniel S.; Portela, Carlos M.; Sebastiani, Marco; Kirchlechner, Christoph Historical and recent advances in the field of nanomechanics, ranging from the early development of nanoindentation to recent advances in artificial intelligence- and machine learning-based characterization and modeling are covered in this article. Early advances were motivated by thin-film mechanics challenges driven by the microelectronics industry. In the ensuing years, different methodologies for probing mechanical properties at length scales relevant to a myriad of applications and materials systems have been developed, coupled with a variety of in situ testing methods that shed insights into new mechanisms. Built upon the knowledge base from nanomechanics, new mechanical metamaterials with otherwise unachievable material properties have been discovered, and new methods in testing and analyzing properties for extreme conditions have been recently reported. This article discusses the journey that the nanomechanics community has gone through over the past 50 years and shares the scale-bridging mechanistic insights through the looking glass.

Sustainable Synthesis of CoFe2O4/Fe2O3 Catalyst for Hydrogen Generation from Sodium Borohydride Hydrolysis

Wed, 01 Oct 2025 00:00:00 GMT

Sustainable Synthesis of CoFe2O4/Fe2O3 Catalyst for Hydrogen Generation from Sodium Borohydride Hydrolysis Teixeira, Lucas Tonetti; Medeiros, Marcos; Liu, Liying; Park, Vinicius Novaes; Valente-Rodriguez, Célio; Letichevsky, Sonia; Fajardo, Humberto Vieira; de Siqueira, Rogério Navarro Correia; Maia da Costa, Marcelo Eduardo Huguenin; Botelho Junior, Amilton Barbosa Hydrogen has been explored as a greener alternative for greenhouse gas emissions reduction. Sodium borohydride (NaBH4) is a favorable hydrogen carrier due to its high hydrogen content, safe handling, and rapid hydrogen release. This work presents a novel synthesis of the catalyst CoFe2O4/Fe2O3 using nanocellulose fibers (TCNF) as reactive templates for metal adsorption and subsequent calcination. The resulting material was tested for H2 production from basic NaBH4 aqueous solutions (10–55 °C). The catalyst’s composition is 74.8 wt% CoFe2O4, 25 wt% Fe2O3, and 0.2 wt% Fe2(SO4)3 with agglomerated spheroidal particles (15–20 nm) and homogeneous Fe and Co distribution. The catalyst produced 1785 mL of H2 in 15 min at 25 °C (50 mg catalyst, 4.0% NaBH4, and 2.5 wt% NaOH), close to the stoichiometric maximum (2086 mL). The maximum H2 generation rate (HGR) reached 3.55 L min−1 gcat−1 at 40 °C. Activation energies were determined using empirical (38.4 ± 5.3 kJ mol−1) and Langmuir–Hinshelwood (L–H) models (42.2 ± 5.8 kJ mol−1), consistent with values for other Co-ferrite catalysts. Kinetic data fitted better to the L–H model, suggesting that boron complex adsorption precedes H2 evolution.

On the potential of microtubules for scalable quantum computation

Wed, 19 Nov 2025 00:00:00 GMT

On the potential of microtubules for scalable quantum computation Mavromatos, Nick E.; Mershin, Andreas; Nanopoulos, Dimitri V. We examine the quantum coherence properties of tubulin heterodimers arranged into the protofilaments of cytoskeletal microtubules. In the physical model proposed by the authors, the microtubule interiors are treated as high-Q quantum electrodynamics (QED) cavities that can support decoherence-resistant entangled states under physiological conditions, with decoherence times of the order of O ( 10 - 6 ) s. We identify strong electric dipole interactions between tubulin dimers and ordered water dipole quanta within the microtuble interior as the mechanism responsible for the extended coherence times. Classical nonlinear (pseudospin) σ -models describing solitonic excitations are reinterpreted as emergent quantum-coherent—or possibly pointer—states, arising from incomplete collapse of dipole-aligned quantum states. These solitons mediate dissipation-free energy transfer along microtubule filaments. We discuss logic-gate-like behaviour facilitated by microtubule-associated proteins, and outline how such structures may enable scalable, ambient-temperature quantum computation, with the fundamental unit of information storage realized as a quDit encoded in the tubulin dipole state. We further describe a process akin to “decision-making” that emerges following an external stimulus, whereby optimal, energy-loss-free signal and information transport pathways are selected across the microtubular network. Finally, we propose experimental approaches—including Rabi-splitting spectroscopy and entangled surface plasmon probes—to validate the use of biomatter as a substrate for scalable quantum computation.

Can Artificial Intelligence Improve the Appropriate Use and Decrease the Misuse of REBOA?

Thu, 25 Sep 2025 00:00:00 GMT

Can Artificial Intelligence Improve the Appropriate Use and Decrease the Misuse of REBOA? Bokenkamp, Mary; Ma, Yu; Dorken-Gallastegi, Ander; Proaño-Zamudio, Jefferson A; Gebran, Anthony; Velmahos, George C; Bertsimas, Dimitris; Kaafarani, Haytham MA Background: The use of resuscitative endovascular balloon occlusion of the aorta (REBOA) for control of noncompressible torso hemorrhage remains controversial. We aimed to utilize a novel and transparent/interpretable artificial intelligence (AI) method called Optimal Policy Trees (OPTs) to improve the appropriate use and decrease the misuse of REBOA in hemodynamically unstable blunt trauma patients. Methods: We trained and then validated OPTs that “prescribe” REBOA in a 50:50 split on all hemorrhagic shock blunt trauma patients in the 2010–2019 ACS-TQIP database based on rates of survival. Hemorrhagic shock was defined as a systolic blood pressure ≤90 on arrival or a transfusion requirement of ≥4 units of blood in the first 4 h of presentation. The expected 24 h mortality rate following OPT prescription was compared to the observed 24 h mortality rate in patients who were or were not treated with REBOA. Results: Out of 4.5 million patients, 100,615 were included, and 803 underwent REBOA. REBOA patients had a higher rate of pelvic fracture, femur fracture, hemothorax, pneumothorax, and thoracic aorta injury (p < 0.001). The 24 h mortality rate for the REBOA vs. non-REBOA group was 47% vs. 21%, respectively (p < 0.001). OPTs resulted in an 18% reduction in 24 h mortality for REBOA and a 0.8% reduction in non-REBOA patients. We specifically divert the misuse of REBOA by recommending against REBOA in cases where it leads to worse outcomes. Conclusions: This proof-of-concept study shows that interpretable AI models can improve mortality in unstable blunt trauma patients by optimizing the use and decreasing the misuse of REBOA. To date, these models have been used to predict outcomes, but their groundbreaking use will be in prescribing interventions and changing outcomes.

Ultra-High Resolution 9.4T Brain MRI Segmentation via a Newly Engineered Multi-Scale Residual Nested U-Net with Gated Attention

Wed, 24 Sep 2025 00:00:00 GMT

Ultra-High Resolution 9.4T Brain MRI Segmentation via a Newly Engineered Multi-Scale Residual Nested U-Net with Gated Attention Kalluvila, Aryan; Patel, Jay B.; Johnson, Jason M. A 9.4T brain MRI is the highest resolution MRI scanner in the public market. It offers submillimeter brain imaging with exceptional anatomical detail, making it one of the most powerful tools for detecting subtle structural changes associated with neurological conditions. Current segmentation models are optimized for lower-field MRI (1.5T–3T), and they struggle to perform well on 9.4T data. In this study, we present the GA-MS-UNet++, the world’s first deep learning-based model specifically designed for 9.4T brain MRI segmentation. Our model integrates multi-scale residual blocks, gated skip connections, and spatial channel attention mechanisms to improve both local and global feature extraction. The model was trained and evaluated on 12 patients in the UltraCortex 9.4T dataset and benchmarked against four leading segmentation models (Attention U-Net, Nested U-Net, VDSR, and R2UNet). The GA-MS-UNet++ achieved a state-of-the-art performance across both evaluation sets. When tested against manual, radiologist-reviewed ground truth masks, the model achieved a Dice score of 0.93. On a separate test set using SynthSeg-generated masks as the ground truth, the Dice score was 0.89. Across both evaluations, the model achieved an overall accuracy of 97.29%, precision of 90.02%, and recall of 94.00%. Statistical validation using the Wilcoxon signed-rank test (p < 1 × 10−5) and Kruskal–Wallis test (H = 26,281.98, p < 1 × 10−5) confirmed the significance of these results. Qualitative comparisons also showed a near-exact alignment with ground truth masks, particularly in areas such as the ventricles and gray–white matter interfaces. Volumetric validation further demonstrated a high correlation (R2 = 0.90) between the predicted and ground truth brain volumes. Despite the limited annotated data, the GA-MS-UNet++ maintained a strong performance and has the potential for clinical use. This algorithm represents the first publicly available segmentation model for 9.4T imaging, providing a powerful tool for high-resolution brain segmentation and driving progress in automated neuroimaging analysis.

De novo design of a two-step approach targeting Claudin-6 for enhanced drug delivery to solid tumors

Thu, 20 Nov 2025 00:00:00 GMT

De novo design of a two-step approach targeting Claudin-6 for enhanced drug delivery to solid tumors Yan, Jiayao; Zhong, Liqing; Chen, Xiaotong; Li, Lin; Liu, Fangcen; Lei, Lei; An, Mengchao; Wei, Xiao; Wang, Ying; Chen, Tianran; Guo, Jingyi; Shao, Jie; Yu, Xiaoxiao; Zhao, Yingjie; Li, Rutian; Liu, Qin Background Although antibody-conjugated drugs have achieved success in clinical practice for cancer treatment, challenges remain in developing a highly efficient drug delivery system with specific accumulation in tumors and reduction in side effects. With improved pharmacokinetics, strong covalent bonding and quick binding reactions, a pre-targeting approach via molecular pairs represents an attractive platform for two-step delivery system construction. Methods Bioinformatics and immunohistochemistry assays were performed to assess Claudin-6 (CLDN6) as a highly specific tumor target in solid tumors. A phage-displayed library was used to screen and optimize anti-CLDN6 designed ankyrin repeat proteins (DARPins), which were incorporated into a two-step delivery system based on SpyTag/SpyCatcher. Fluorescent staining, flow cytometry and near-infrared imaging were performed to assess the tumor-targeting ability and biodistribution of this delivery system. The cytotoxic drug, Monomethyl auristatin E (MMAE), was conjugated with the delivery system to evaluate its anti-tumor efficacy and safety profile. Results Anti-CLDN6 DARPins exhibited specific binding to CLDN6+ cancer cells with high affinity instead of negative cells in vitro, ex vivo and in vivo. The DARPins-based two-step delivery system improved background clearance with a high signal-to-noise ratio, enhancing the specific accumulation of payloads in tumors. The cytotoxic drug delivered via the two-step system appeared superior to the one-step approach in IC50, biodistribution, and tumor growth inhibition. Conclusions Our study presented the de novo design of a two-step drug delivery system targeting Claudin-6 with enhanced anti-tumor efficacy and improved biosafety. These findings highlighted the potential of this approach to enhance the efficacy of tumor-targeting therapies and reduce adverse effects, paving the way for more effective cancer treatments.

How Does AI Transform Cyber Risk Management?

Tue, 23 Sep 2025 00:00:00 GMT

How Does AI Transform Cyber Risk Management? Zeijlemaker, Sander; Lemiesa, Yaphet K; Schröer, Saskia Laura; Abhishta, Abhishta; Siegel, Michael Digital transformation embeds smart cities, e-health, and Industry 4.0 into critical infrastructures, thereby increasing reliance on digital systems and exposure to cyber threats and boosting complexity and dependency. Research involving over 200 executives reveals that under rising complexity, only 15% of cyber risk investments are effective, leaving most organizations misaligned or vulnerable. In this context, the role of artificial intelligence (AI) in cybersecurity requires systemic scrutiny. This study analyzes how AI reshapes systemic structures in cyber risk management through a multi-method approach: literature review, expert workshops with practitioners and policymakers, and a structured kill chain analysis of the Colonial Pipeline attack. The findings reveal three new feedback loops: (1) deceptive defense structures that misdirect adversaries while protecting assets, (2) two-step success-to-success attacks that disable defenses before targeting infrastructure, and (3) autonomous proliferation when AI applications go rogue. These dynamics shift cyber risk from linear patterns to adaptive, compounding interactions. The principal conclusion is that AI both amplifies and mitigates systemic risk. The core recommendation is to institutionalize deception in security standards and address drifting AI-powered systems. Deliverables include validated systemic structures, policy options, and a foundation for creating future simulation models to support strategic cyber risk management investment.

Flex-Route Transit for Smart Cities: A Reinforcement Learning Approach to Balance Ridership and Performance

Tue, 16 Sep 2025 00:00:00 GMT

Flex-Route Transit for Smart Cities: A Reinforcement Learning Approach to Balance Ridership and Performance Rodriguez, Joseph; Koutsopoulos, Haris N.; Zhao, Jinhua A major challenge for modern transit systems relying on traditional fixed-route designs is providing broad accessibility to users. Flex-route transit can enhance accessibility in low-density areas, since it combines the directness of fixed-route transit with the coverage of on-demand mobility. Although deviating for optional pickups can increase ridership and transit accessibility, it also deteriorates the service performance for fixed-route riders. To balance this inherent trade-off, this paper proposes a reinforcement learning approach for deviation decisions. The proposed model is used in a case study of a proposed flex-route service in the city of Boston. The performance on competing objectives is evaluated for reward configurations that adapt to peak and off-peak scenarios. The analysis shows a significant improvement of our method compared to a heuristic derived from industry practice as a baseline. To evaluate robustness, we assess performance across scenarios with varying demand compositions (fixed and requested riders). The results show that the method achieves greater improvements than the baseline in scenarios with increased request ridership, i.e., where decision-making is more complex. Our approach improves service performance under dynamic demand conditions and varying priorities, offering a valuable tool for smart cities to operate flex-route services.

Search for a cH signal in the associated production of at least one charm quark with a Higgs boson in the diphoton decay channel in pp collisions at $$\sqrt{s}=13$$ TeV

Wed, 12 Nov 2025 00:00:00 GMT

Search for a cH signal in the associated production of at least one charm quark with a Higgs boson in the diphoton decay channel in pp collisions at $$\sqrt{s}=13$$ TeV Chekhovsky, V.; Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I. This paper presents the first search for a cH signal sensitive to the coupling of the charm quark (c) to the Higgs boson (H) in the associated production of at least one charm quark with a Higgs boson decaying to two photons. The results are based on a data set of proton-proton collisions at a center-of-mass energy of 13 TeV collected with the CMS experiment at the LHC, corresponding to an integrated luminosity of 138 fb−1. Assuming the standard model (SM) rates for all other Higgs boson production processes, the observed (expected) upper limit at 95% confidence level on the cH signal strength is 243 (355) times the SM prediction. Under the same assumption, the observed (expected) allowed interval on the Higgs boson to charm quark coupling modifier, κc, is |κc| < 38.1 (|κc| < 72.5) at 95% confidence level.

A Bunch of Gaps: Factors Behind Service Reliability in Chicago’s High-Frequency Transit Network

Thu, 28 Aug 2025 00:00:00 GMT

A Bunch of Gaps: Factors Behind Service Reliability in Chicago’s High-Frequency Transit Network Rodriguez, Joseph; Koutsopoulos, Haris N.; Zhao, Jinhua Frequent transit services in urban areas have the potential to increase their accessibility to transit-dependent riders and reduce congestion by attracting new ridership through a modal shift. However, bus services operating in mixed traffic face operational challenges that reduce reliability and hinder their attractiveness. The sources of unreliability can range from local-level conditions, like the road infrastructure, to higher-level decisions, like the service plan. For the effective planning of improvement strategies, both scales of analysis must be considered. This paper uses a novel modeling framework to understand reliability by analyzing the route and segment factors separately. The Chicago Transit Authority (CTA) bus network is used as a case study for the analysis. The data reflect the operational, demand, and urban conditions of 50 high-frequency bus routes. At the route level, we use the coefficient of headway variation as the dependent variable and diverse route characteristics as explanatory variables. The results indicate that the most significant contributors to the variability of headways are variability in schedules and dispatching at terminals. It is also found that driver experience impacts reliability and that east–west routes are more unreliable than north–south routes. At the segment level, we use data from trips involved in bunching and gaps. As the dependent variable, a novel measure is formulated to capture how quickly bunching or gaps are formed. The bunching and gap events are treated as separate regression models. Findings suggest that link and dwell time variability are the most significant contributors to gap and bunching formation. In terms of infrastructure, bus lane segments reduce gap formations, and left turns increase bunching and gap formations. The insights presented can inform improvements in service and transit infrastructure planning to improve transit level of service (LOS) and support the future of sustainable, smart cities.

Oil Transport Simulation and Oil Consumption Prediction with a Physics-Based and Data-Driven Digital Twin Model for Internal Combustion Engines

Tue, 21 Oct 2025 00:00:00 GMT

Oil Transport Simulation and Oil Consumption Prediction with a Physics-Based and Data-Driven Digital Twin Model for Internal Combustion Engines Zhong, Xinlin; Tian, Tian Lubrication oil consumption (LOC) is one of the major sources of emissions from internal combustion (IC) engines; yet, analyzing and predicting it through modeling is challenging due to its multi-physics nature, which spans different time and length scales. In this work, a digital twin model is developed to simulate oil transport in the piston ring pack of IC engines and predict the resulting oil consumption with all major physical mechanisms considered. Three main contributors to LOC, namely, top ring up-scraping, oil vaporization on the liner, and reverse gas flows through the top ring gap, are included in the model. It was found that their behaviors are heavily dependent on the arrangement of the piston ring gaps. Therefore, with the ring rotation behavior still not resolved, the current model can predict the LOC range of a given engine profile. Results show that the predicted range can well encapsulate the experimentally measured LOC value.

LSM and CPT

Wed, 19 Nov 2025 00:00:00 GMT

LSM and CPT Seiberg, Nathan; Shao, Shu-Heng; Zhang, Wucheng We study a number of 1+1d lattice models with anti-unitary symmetries that simultaneously reflect space and reverse time. Some of these symmetries are anomalous, leading to Lieb-Schultz-Mattis-type constraints, thus excluding a trivially gapped phase. Examples include a mod 8 anomaly in the Majorana chain and various mod 2 anomalies in the spin chain. In some cases, there is an exact, non-anomalous lattice symmetry that flows in the continuum to CPT. In some other cases, the CPT symmetry of the continuum theory is emergent or absent. Depending on the model, the anomaly of the lattice model is matched in the continuum in different ways. In particular, it can be mapped to an emergent anomaly of an emanant symmetry.

A biomimetic chip to assess subcutaneous bioavailability of monoclonal antibodies in humans

Mon, 09 Oct 2023 00:00:00 GMT

A biomimetic chip to assess subcutaneous bioavailability of monoclonal antibodies in humans Chandran Suja, Vineeth; Qi, Qin M; Halloran, Kevin; Zhang, Jifeng; Shaha, Suyog; Prakash, Supriya; Kumbhojkar, Ninad; Deslandes, Antoine; Huille, Sylvain; Gokarn, Yatin R; Mitragotri, Samir Subcutaneous (subQ) injection is a common route for delivering biotherapeutics, wherein pharmacokinetics is largely influenced by drug transport in a complex subQ tissue microenvironment. The selection of good drug candidates with beneficial pharmacokinetics for subQ injections is currently limited by a lack of reliable testing models. To address this limitation, we report here a Subcutaneous Co-Culture Tissue-on-a-chip for Injection Simulation (SubCuTIS). SubCuTIS possesses a 3D coculture tissue architecture, and it allows facile quantitative determination of relevant scale independent drug transport rate constants. SubCuTIS captures key in vivo physiological characteristics of the subQ tissues, and it differentiates the transport behavior of various chemically distinct molecules. We supplemented the transport measurements with theoretical modeling, which identified subtle differences in the local absorption rate constants of seven clinically available mAbs. Accounting for first-order proteolytic catabolism, we established a mathematical framework to assess clinical bioavailability using the local absorption rate constants obtained from SubCuTIS. Taken together, the technology described here broadens the applicability of organs-on-chips as a standardized and easy-to-use device for quantitative analysis of subQ drug transport.

Nanoparticle-induced lipid membrane deformation influences the design of biomedicine

Tue, 21 Jul 2026 00:00:00 GMT

Nanoparticle-induced lipid membrane deformation influences the design of biomedicine Pincus, Isaac; Qi, Qin M Controlling the physicochemical properties of nanoparticles is important for their performance as drug carriers, pharmaceuticals, or imaging contrast agents in nanomedicine. Predictive models can accelerate experimental designs at reduced time and costs compared to a brute-force approach conventionally used. However, physical principles underlying particle-cell interactions are still poorly understood due to their large size contrast, hindering the model development. In this work, we describe a model that examines the interaction between multiple particles and the membrane of a mammalian cell or an artificial vesicle, thus influencing the outcomes of surface adsorption, detachment or uptake of particles. Compared to existing biophysical models on particle-membrane interactions accounting for membrane adhesion, stretching and bending energies, we make several important updates that are essential to reaching quantitative agreement with existing experimental data. Particle-induced membrane tension changes are crucial to the membrane deformation even at very low surface concentrations (0.1%); we explain this surprising finding using a new length scale previously neglected. Furthermore, a multi-step and non-equilibrium endocytosis mechanism is proposed in the absence of specific receptor-ligand interactions, inspired by recent experimental evidence on the dynamic regulation of membrane tension through the active transport of lipid molecules. We demonstrate the predictive power of our model in generating the adsorption isotherms and shear-induced particle detachment from cell surfaces and the size-dependent rate of particle uptake. Our research provides a framework to design tailor-made nanoparticles with controllable interaction outcomes with various cell types based on a quantitative and fundamental understanding.

Effective use of biosensors for high-throughput library screening for metabolite production

Wed, 04 Aug 2021 00:00:00 GMT

Effective use of biosensors for high-throughput library screening for metabolite production Kaczmarek, Jennifer A; Prather, Kristala LJ The development of fast and affordable microbial production from recombinant pathways is a challenging endeavor, with targeted improvements difficult to predict due to the complex nature of living systems. To address the limitations in biosynthetic pathways, much work has been done to generate large libraries of various genetic parts (promoters, RBSs, enzymes, etc.) to discover library members that bring about significantly improved levels of metabolite production. To evaluate these large libraries, high throughput approaches are necessary, such as those that rely on biosensors. There are various modes of operation to apply biosensors to library screens that are available at different scales of throughput. The effectiveness of each biosensor-based method is dependent on the pathway or strain to which it is applied, and all approaches have strengths and weaknesses to be carefully considered for any high throughput library screen. In this review, we discuss the various approaches used in biosensor screening for improved metabolite production, focusing on transcription factor-based biosensors.

A method for correcting the substructure of multiprong jets using the Lund jet plane

Mon, 10 Nov 2025 00:00:00 GMT

A method for correcting the substructure of multiprong jets using the Lund jet plane Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Damanakis, K.; Dragicevic, M.; Giordano, C.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R. Many analyses at the CERN LHC exploit the substructure of jets to identify heavy resonances produced with high momenta that decay into multiple quarks and/or gluons. This paper presents a new technique for correcting the substructure of simulated large-radius jets from multiprong decays. The technique is based on reclustering the jet constituents into several subjets such that each subjet represents a single prong, and separately correcting the radiation pattern in the Lund jet plane of each subjet using a correction derived from data. The data presented here correspond to an integrated luminosity of 138 fb−1 collected by the CMS experiment between 2016–2018 at a center-of-mass energy of 13 TeV. The correction procedure improves the agreement between data and simulation for several different substructure observables of multiprong jets. This technique establishes, for the first time, a robust calibration for the substructure of jets with four or more prongs, enabling future measurements and searches for new phenomena containing these signatures.

Inclusionary and Exclusionary Preferences: A Test of Three Cognitive Mechanisms

Sat, 22 Nov 2025 00:00:00 GMT

Inclusionary and Exclusionary Preferences: A Test of Three Cognitive Mechanisms Landau-Wells, Marika; Lydic, Kirsten O.; Kennedy, Joachim; Mittman, Benjamin G.; Thompson, Todd W.; Gupta, Akhil; Saxe, Rebecca Exclusionary social policies take a significant toll on the mental and physical health of targeted groups. Support for specific exclusionary policies does not always align with general antipathy towards the targeted group, however. Does support for specific exclusionary policies rely on particular thought processes (i.e., cognitive mechanisms)? Does opposition? We investigate these questions through the lens of “bathroom laws” across two studies. In Study 1, we use functional neuroimaging to test three candidate cognitive mechanisms from the literature: (1) threat-related emotions (e.g., fear, disgust) supporting exclusionary preferences; (2) mentalizing (e.g., empathy, perspective-taking) supporting inclusionary preferences; and (3) self-regulation (e.g., aligning one’s behavior with one’s goals) supporting inclusionary preferences. Consistent with the intergroup conflict and prejudice literatures, we find evidence of a motivated self-regulation mechanism in bathroom law opponents. In Study 2, we investigate a possible source of this motivation using text analysis of open-ended policy preference justifications. We find that bathroom law opponents link their policy preference to a small number of specific values, particularly autonomy of action. Taken together, these studies point to a value-driven, motivational account of inclusionary preferences that reconciles puzzling patterns of public opinion, offers new levers for tolerance interventions, and provides some insight into the brain-basis of political behavior.

Accelerated Bayesian Calibration and Uncertainty Quantification of RANS Turbulence Model Parameters for Stratified Atmospheric Boundary Layer Flows

Sat, 22 Nov 2025 00:00:00 GMT

Accelerated Bayesian Calibration and Uncertainty Quantification of RANS Turbulence Model Parameters for Stratified Atmospheric Boundary Layer Flows Shin, Ethan Y.; Howland, Michael F. In operational weather models, the effects of turbulence in the atmospheric boundary layer (ABL) on the resolved flow are modeled using turbulence parameterizations. These parameterizations typically use a predetermined set of model parameters that are tuned to limited data from canonical flows. Using these fixed parameters results in deterministic predictions that neglect uncertainty in the unresolved turbulence processes. In this study, we perform a machine learning-accelerated Bayesian inversion of a single-column model of the ABL. This approach is used to calibrate and quantify uncertainty in model parameters of Reynolds-averaged Navier–Stokes turbulence models. To verify the data-driven uncertainty quantification methodology, we test in an idealized setup in which a prescribed but unobserved set of parameters is learned from noisy approximations of the model output. Following this verification, we learn the parameters and their uncertainties in two different turbulence models conditioned on scale-resolving large-eddy simulation data over a range of ABL stabilities. We show how Bayesian inversion of a numerical model improves flow predictions by investigating the underlying mean momentum budgets. Further, we show that uncertainty quantification based on neutral ABL surface layer data recovers the relationships between parameters that have been predicted using theoretical modeling, but that learning the parameters based on stable ABL data or data from outside the surface layer can lead to different parameter relationships than neutral surface layer theory. Efforts to systematically reduce parameter uncertainty reveal that (1) sampling wind speed up to the ABL height can reduce uncertainty in key model parameters by up to $$84\%$$ , and (2) assimilating fluid flow quantities beyond first-order moment statistics can further reduce uncertainty in ways that baseline wind speed assimilation alone cannot achieve. The parameters learned using Bayesian uncertainty quantification generally yield lower error than standard deterministic parameters in out-of-sample tests and also provide uncertainty intervals on predictions.

Europa Clipper Magnetometer Boom Deployment: A First Look at the Magnetometer Observations of the Spacecraft and the Interplanetary Magnetic Field

Wed, 19 Nov 2025 00:00:00 GMT

Europa Clipper Magnetometer Boom Deployment: A First Look at the Magnetometer Observations of the Spacecraft and the Interplanetary Magnetic Field Cochrane, Corey J.; Joy, Steven P.; Korth, Haje; Biersteker, John B.; Blacksberg, Jordana; Bouchard, Michael; Contreras, Jacob; Dawson, Olivia R.; Khurana, Krishan K.; Murphy, Neil; Palm, Derek; Perley, Mitch O.; Pierce, David R.; Richter, Ingo; Russell, Christopher T. NASA’s Europa Clipper flagship mission is designed to investigate the habitability of Jupiter’s moon Europa. A key instrument aboard the spacecraft is the Europa Clipper Magnetometer (ECM), a suite of fluxgate magnetometer sensors deployed on a boom to minimize spacecraft-induced magnetic interference. The ECM investigation aims to characterize Europa’s induced magnetic field, offering constraints on the salinity, depth, and thickness of its subsurface ocean. This work presents the first in-flight ECM observations acquired during the magnetometer boom deployment and shortly thereafter. We show how these observations provide the requisite evidence needed to validate a successful deployment. We also demonstrate how these observations can be used to calibrate the sensor offsets and to develop new magnetic field models of the spacecraft of varying complexity, thus enabling the robust removal of the instrument’s zero-levels which is critical for achieving the mission’s science objectives. We finally share preliminary calibrated magnetometer observations acquired over a two-month period after deployment, revealing a very active interplanetary magnetic field characteristic of solar maximum.

Deuteron identification via time of flight with LHCb

Wed, 19 Nov 2025 00:00:00 GMT

Deuteron identification via time of flight with LHCb LHCb Collaboration It is shown that the timing capabilities of the LHCb detector operated during the LHC Run 2 can be used to identify light ion particles with momenta of a few GeV/c. This is achieved by estimating the particle time of flight through a newly developed technique. A dedicated reconstruction procedure and a neural-network-based estimator of the particle speed have been developed to enable deuteron identification by suppressing the abundant background from lighter particles. The performance of the identification procedure is demonstrated in a sample of proton-helium collisions at s NN = 110 GeV, where the production of deuteron and triton particles is observed. This novel approach opens the way to study deuteron and antideuteron production for different collision systems at different energy scales, exploiting the rich dataset collected by the LHCb experiment.

Confidently Comparing Estimates with the c-value

Fri, 24 Feb 2023 00:00:00 GMT

Confidently Comparing Estimates with the c-value Trippe, Brian L; Deshpande, Sameer K; Broderick, Tamara Modern statistics provides an ever-expanding toolkit for estimating unknown parameters. Consequently, applied statisticians frequently face a difficult decision: retain a parameter estimate from a familiar method or replace it with an estimate from a newer or more complex one. While it is traditional to compare estimates using risk, such comparisons are rarely conclusive in realistic settings. In response, we propose the “c-value” as a measure of confidence that a new estimate achieves smaller loss than an old estimate on a given dataset. We show that it is unlikely that a large c-value coincides with a larger loss for the new estimate. Therefore, just as a small p-value supports rejecting a null hypothesis, a large c-value supports using a new estimate in place of the old. For a wide class of problems and estimates, we show how to compute a c-value by first constructing a data-dependent high-probability lower bound on the difference in loss. The c-value is frequentist in nature, but we show that it can provide validation of shrinkage estimates derived from Bayesian models in real data applications involving hierarchical models and Gaussian processes. Supplementary materials for this article are available online.

Future circular collider feasibility study report

Mon, 17 Nov 2025 00:00:00 GMT

Future circular collider feasibility study report Benedikt, M.; Zimmermann, F.; Auchmann, B.; Bartmann, W.; Burnet, J. P.; Carli, C.; Chancé, A.; Craievich, P.; Giovannozzi, M.; Grojean, C.; Gutleber, J.; Hanke, K.; Henriques, A.; Janot, P.; Lourenço, C.; Mangano, M.; Otto, T.; Poole, J.; Rajagopalan, S.; Raubenheimer, T. In response to the 2020 Update of the European Strategy for Particle Physics, the Future Circular Collider (FCC) Feasibility Study was launched as an international collaboration hosted by CERN. This report describes the FCC integrated programme, which consists of two stages: an electron-positron collider (FCC-ee) in the first phase, serving as a high-luminosity Higgs, top, and electroweak factory; followed by a proton-proton collider (FCC-hh) at the energy frontier in the second phase. The FCC-ee is designed to operate at four key centre-of-mass energies: the Z pole, the WW pair production threshold, the ZH production peak, and the top/anti-top production threshold—each delivering the highest possible luminosities to four experiments. Over 15 years of operation, FCC-ee will produce more than 6 trillion Z bosons, 200 million WW pairs, nearly 3 million Higgs bosons, and 2 million top anti-top pairs. Precise energy calibration at the Z pole and WW threshold will be achieved through frequent resonant depolarisation of pilot bunches. The sequence of operation modes between the Z, WW, and ZH substages remains flexible. The FCC-hh will operate at a centre-of-mass energy of approximately 85 TeV—nearly an order of magnitude higher than the LHC—and is designed to deliver 5 to 10 times the integrated luminosity of the upcoming High-Luminosity LHC. Its mass reach for direct discovery extends to several tens of TeV. In addition to proton-proton collisions, the FCC-hh is capable of supporting ion-ion, ion-proton, and lepton-hadron collision modes. This second volume of the Feasibility Study Report presents the complete design of the FCC-ee collider, its operation and staging strategy, the full-energy booster and injector complex, required accelerator technologies, safety concepts, and technical infrastructure. It also includes the design of the FCC-hh hadron collider, development of high-field magnets, hadron injector options, and key technical systems for FCC-hh.

Nitrous Oxide Distributions in the Oxygenated Water Column of the Sargasso Sea

Thu, 15 Dec 2022 00:00:00 GMT

Nitrous Oxide Distributions in the Oxygenated Water Column of the Sargasso Sea Meyer, Annaliese C. S.; Cullen, Jay T.; Grundle, Damian S. This study presents dissolved nitrous oxide (N2O) concentrations in the water column at the Bermuda Atlantic Time-series Study (BATS) station and uses a subset of these measurements to estimate air-to-sea flux for four specific time points between September 2018 and June 2019. N2O concentrations at BATS were in the range of 4.0 nmol L−1–16.9 nmol L−1, with vertical profiles which were the mirror inverse of dissolved oxygen. Regardless of season, N2O concentration maxima were found within the oxygen minimum zone (OMZ). The highest maximum N2O values were observed in November and lowest in October. As the water column at BATS remains consistently at dissolved oxygen concentrations greater than 140 µmol L−1, and therefore aerobic, we assume that the bulk of N2O production occurs through nitrification. A nitrification source is supported by a correlation between excess N2O (ΔN2O) below the mixed layer, apparent oxygen utilization (AOU) and nitrate concentrations. We estimate a pooled average yield of 0.027% to 0.038% N2O from nitrification at BATS. Finally, estimates of air–sea exchange of N2O using regional average monthly wind speeds indicated that this region acts as a weak source or a sink of atmospheric N2O, and varies between months.

A holistic model for understanding the dynamics of outsourcing

Mon, 14 Feb 2022 00:00:00 GMT

A holistic model for understanding the dynamics of outsourcing Uygun, Yilmaz; Gotsadze, Nikoloz; Schupp, Florian; Gzirishvili, Lizi; Tindjou Nana, Brigitte Stephanie Outsourcing is a complex process as many external and internal factors that look convincing in the first place might, however, lead to a failure in the long run. Motivated by this, we wanted to get a holistic understanding of such outsourcing decisions. Thus, we created a comprehensive System Dynamics simulation model including all relevant variables to examine the dynamic nature of outsourcing in a holistic manner and over time that consists of more than 200 interrelated variables. Our results show, amongst others, that higher process specialisation that requires substantial investments by the supplier appears to be favourable for an outsourcing company and shifting a larger quantity to such a supplier achieves better cost savings and thus accounts for a better overall outsourcing result. On an operational level, we identified an innovation trap, a bargaining power shift, a plagiarism trap, and a knowledge trap. Based on that, we give specific managerial recommendations to tackles these aspects. We conclude that, amongst others, it is important for innovative companies with rather complex processes and parts to carefully plan which and how many employees to release so as not to lose the knowledge on those outsourced processes and parts.

Mediation and ANCOVA Models to Study the Influence of Solvent Retting Traits and Plant Physique on Bast Fiber Yield and Retting Time

Mon, 11 Jul 2022 00:00:00 GMT

Mediation and ANCOVA Models to Study the Influence of Solvent Retting Traits and Plant Physique on Bast Fiber Yield and Retting Time Shuvo, Ikra Iftekhar; Hoque, Md. Saiful; Khandakar, Lovely K. M. The study aims in applying two statistical tools to analyze the retting beha-vior of plant stems for extracting bast fibers for industrial applications. Atfirst, a mediation model is employed to investigate the first hypothesis of thiswork that involves studying the color response of the retted solvent asa function of retting time on the responsible variable, fiber yield (%).Statistically, there is a significant indirect effect of retting time on fiberyield (%) through retting trait (β = −0.0142, 95% C.I. [−0.0274, −0.0011]) –a statistical inference bolstered by the Sobel test result, confirming themediation effect (p-value = 0.0329 < 0.05; z-score = −2.1334; bootstrappingof 5000 resamples). Next, the second hypothesis of the current work involvesanalyzing the impact of stem form-factors on their retting time using thestatistical tool, ANCOVA. The partial- η2 indicates that cultivar treatmentaccounts for 30% variance of the retting time while controlling for the effectsof two covariates – diameter and length of the stems, in this case. Bycontrolling the Type-I error, Bonferroni and similar post-hoc tests also con-firm the statistical significance of cultivar categories pertaining to their meanretting time. Future work could focus on these underlying hypotheses andstudy the impact of microorganisms, environmental factors, and cultivartreatment variables on the retting time to optimize the overall fiber yieldand production process.

Improving Autistic Experiences in the Workplace: Key Factors and Actionable Steps

Wed, 24 Sep 2025 00:00:00 GMT

Improving Autistic Experiences in the Workplace: Key Factors and Actionable Steps Nishith, Shruti; O’Brien, Amanda M.; Li, Cindy; Bungert, Lindsay; Oddis, Kyle; Riddle, Joseph; Gabrieli, John D. E. Autistic adults have higher rates of unemployment and underemployment than non-autistic adults with and without disabilities. While previous work has highlighted factors specific to individuals and/or job sectors that serve as barriers or facilitators to autistic employment, the question of how to modify the workplace to best support autistic people remains under-researched. The present study utilized an ecological framework to investigate what workplace factors can be modified to improve autistic experiences and how these modifications may be enacted across different levels of workplace ecosystem to promote autistic success. Autistic participants (N = 85) across employment sectors provided quantitative ratings and written descriptions of positive and negative factors related to their workplace experiences. Quantitative and qualitative analyses were used to examine which factors and overarching principles most impact employment. Actionable strategies to modify these factors were derived from participant responses and validated by autistic collaborators and neuroinclusion experts. On average, participants rated task training as having the most positive, and mental health as having the most negative, impact on their employment. Participants described four themes (acceptance, communication, autonomy, accommodations) that can be embedded in the work environment to improve experiences. Steps to improve autistic employment that can be enacted by stakeholders across levels of the workplace experiences are provided. Autistic adults face multifaceted barriers to employment across levels of the workplace. Modifying the workplace itself, across multiple levels and stakeholders, may serve to improve autistic employment outcomes.

The Connectivity of Friends-and-Strangers Graphs on Complete Multipartite Graphs

Tue, 31 Dec 2024 00:00:00 GMT

The Connectivity of Friends-and-Strangers Graphs on Complete Multipartite Graphs Zhu, Honglin For simple graphs X and Y on n vertices, the friends-and-strangers graph FS ( X , Y ) is the graph whose vertex set consists of all bijections σ : V ( X ) → V ( Y ) , where two bijections σ and σ ′ are adjacent if and only if they agree on all but two adjacent vertices a , b ∈ V ( X ) such that σ ( a ) , σ ( b ) ∈ V ( Y ) are adjacent in Y. Resolving a conjecture of Wang, Lu, and Chen, we completely characterize the connectedness of FS ( X , Y ) when Y is a complete bipartite graph. We further extend this result to when Y is a complete multipartite graph. We also determine when FS ( X , Y ) has exactly two connected components where X is bipartite and Y is a complete bipartite graph.

Reducing Aerodynamic Interference Through Layout Optimization of Symmetrically Cambered Wingsails: A Comparative Study of In-Line and Parallel Configurations

Thu, 16 Oct 2025 00:00:00 GMT

Reducing Aerodynamic Interference Through Layout Optimization of Symmetrically Cambered Wingsails: A Comparative Study of In-Line and Parallel Configurations van Reen, Stephan; Lin, Jianfeng; Niu, Jiqiang; Sharpe, Peter; Li, Xiaodong; Yao, Hua-Dong Rigid wingsails are increasingly adopted for wind-assisted ship propulsion, with Symmetrically Cambered (SC) profiles identified as highly efficient for thrust generation. This study investigates installation layouts for multiple SC wingsails, focusing on aerodynamic interference that limits their performance. A fast 2D potential-flow panel method is employed and benchmarked against wind tunnel and 3D IDDES data. Two representative layouts are analyzed: triple-in-line (TL) and quad-in-parallel (QP). Layout optimization is performed using a genetic algorithm with distances between sails as design variables, constrained by the total installation span, at apparent wind angles (AWAs) of 60◦ , 90◦ , and 120◦ . Results show that thrust generation decreases progressively from upstream to downstream sails due to interference effects, with penalties of about 4–6% in the TL and up to 28% in the QP layout. The optimization improves performance only for the TL layout at 60◦ , while the QP layout shows negligible gains. Analysis of pressure distributions confirms that downstream sails suffer from reduced suction on the leading edge caused by upstream wakes. Overall, the TL layout demonstrates significantly higher aerodynamic reliability than the QP layout. These findings provide new insights into multi-sail configurations and highlight the importance of layout optimization in maximizing thrust efficiency.

A rapid experimental workflow for studying melt track scaling in laser powder bed fusion using high-precision metal template substrates

Thu, 26 Jun 2025 00:00:00 GMT

A rapid experimental workflow for studying melt track scaling in laser powder bed fusion using high-precision metal template substrates Weissbach, Reimar; Penny, Ryan W.; Hart, A. J. Development and qualification of process parameters in laser powder bed fusion (LPBF) involves many variables. At the outset of development, whether transferring known parameters to a new machine, or exploring a new material, single-track and single-layer experiments are a convenient means of down-selecting key variables and exploring parameter scaling behavior. We present an experimental workflow for single-layer LPBF experiments using high-precision metal template substrates, overcoming challenges with precision single-layer alignment in LPBF systems and enabling efficient processing and cross-sectional analysis. Templates are fabricated using chemical etching and machining, and are characterized using optical profilometry and X-ray transmission imaging of powder layers. Using the etched templates, a single-track parameter study is performed in SS316 including three powder layer thicknesses, and spanning common laser melting modes (lack-of-fusion, conduction, and keyhole mode). Analysis of melt track geometries using automated image processing allows a scaling law to be applied to define the process window, quantifying the amount of material added with increasing powder layer thickness. Single-track results are verified with raster scanning experiments, showing the potential to transfer single-track results to full LPBF builds.

Augmented intelligence should be good for medicine, if medicine is to remain good for us

Mon, 29 Sep 2025 00:00:00 GMT

Augmented intelligence should be good for medicine, if medicine is to remain good for us Idan, Daphna; Celi, Leo A.; Einav, Sharon; Frenkel, Amit Throughout history, the medical community has failed to address health disparities. Augmented intelligence (AI) is poised to cement these structural inequities permanently. The need to establish a triage process that ensures fair and equitable access to medical care, and to consider all patient populations equally researchable, should not overshadow the need to learn how best to exploit AI for furthering medical fairness and equity despite resource limitations. Open discussion of the shortcomings of medical AI, approaching medical AI development, testing, and implementation from a critical ethical perspective, constant testing and analysis of AI outputs, and human oversight in the loop constitute only the first part of ensuring augmented intelligence tools are equitably robust and free of bias.

Design Principles and Impact of a Learning Analytics Dashboard: Evidence from a Randomized MOOC Experiment

Mon, 27 Oct 2025 00:00:00 GMT

Design Principles and Impact of a Learning Analytics Dashboard: Evidence from a Randomized MOOC Experiment Borrella, Inma; Ponce-Cueto, Eva Learning Analytics Dashboards (LADs) are increasingly deployed to support self-regulated learning on online courses. Yet many existing dashboards lack strong theoretical grounding, contextual alignment, or actionable feedback, and some designs have been shown to inadvertently discourage learners through excessive social comparison or high inference costs. In this study, we designed and evaluated a LAD grounded in the COPES model of self-regulated learning and tailored to a credit-bearing Massive Open Online Course (MOOC) using a data-driven approach. We conducted a randomized controlled trial with 8745 learners, comparing a control group, a dashboard without feedback, and a dashboard with ARCS-framed actionable feedback. The results showed that the dashboard with feedback significantly increased learners’ likelihood of verification (i.e., paying for the certification track), with mixed effects on engagement and no measurable impact on final grades. These findings suggest that dashboards are not uniformly beneficial: while feedback-supported LADs can enhance motivation and persistence, dashboards that lack interpretive support may impose cognitive burdens without improving outcomes. This study contributes to the literature on learning analytics by (1) articulating the design principles for theoretically and contextually grounded LADs and (2) providing experimental evidence on their impact in authentic MOOC settings.

The Effect of IL-17A and Combined Mechanical Injury on Meniscal Tissue Integrity In Vitro

Fri, 24 Oct 2025 00:00:00 GMT

The Effect of IL-17A and Combined Mechanical Injury on Meniscal Tissue Integrity In Vitro Ahrens, Greta; Gellhaus, Florian; Weitkamp, Jan-Tobias; Behrendt, Peter; Cossais, François; Rolauffs, Bernd; Grodzinsky, Alan J; Kurz, Bodo Objectives: Meniscal integrity is crucial for knee joint stability and the prevention of osteoarthritis (OA) development. Recent studies suggested that mechanical overload and interleukin (IL)-17A may be important intertwined players in meniscal degeneration, but a direct impact of IL-17A on the meniscus has not been investigated. Therefore, the aim of this study was to analyze the effect of IL-17A on meniscal tissue with and without combined mechanical injury (MI). Methods: Meniscal explant disks (1 mm height, 3 mm diameter) were isolated from bovine menisci (preserving the native tibial superficial zone) and exposed to IL-17A [0–100 ng/mL] and/or MI (single compression, 50% strain, strain rate 1 mm/sec). After three days of incubation in a serum-free medium, the proteoglycan release (sGAG; DMMB assay), mRNA level of matrix-degrading enzymes (qRT-PCR), aggrecan degradation (NITEGE immunostaining), and cell death (histomorphometry of nuclear blebbing/apoptosis and condensed nuclei/unspecified cell death) were determined. Statistics: one- and two-way ANOVA with Tukey’s multiple comparisons or Kruskal– Wallis with post hoc testing. Results: IL-17A increased sGAG release in a dose-dependent significant manner. MI also induced the release of sGAG significantly, but the combination with IL-17A showed the highest levels. Both IL-17A and MI individually affected the mRNA levels for ADAMTS4 and MMP-13 slightly, but the combination of both particularly induced a significant increase in mRNA levels. Signals for the ADAMTS4-related aggrecan neoepitope NITEGE were elevated by IL-17A in superficial areas of the excised tissue and by MI in superficial and deeper areas. The combination of both stimuli intensified this signal further. MI increased the number of cells with condensed nuclei significantly and induced apoptosis in a small proportion of cells. IL-17A had no significant impact on the amount of condensed or apoptotic nuclei. Conclusions: Our findings emphasize an interaction between inflammatory cytokine IL-17A signaling and mechanical stress since IL17A induced matrix degeneration in meniscal tissue, which intensified in combination with a trauma. The latter might create a post-traumatic environment that promotes meniscal degeneration and subsequently osteoarthritis progression.

Molecular hallmarks of excitatory and inhibitory neuronal resilience to Alzheimer’s disease

Wed, 01 Oct 2025 00:00:00 GMT

Molecular hallmarks of excitatory and inhibitory neuronal resilience to Alzheimer’s disease Castanho, Isabel; Naderi Yeganeh, Pourya; Boix, Carles A.; Morgan, Sarah L.; Mathys, Hansruedi; Prokopenko, Dmitry; White, Bartholomew; Soto, Larisa M.; Pegoraro, Giulia Background A significant proportion of individuals maintain cognition despite extensive Alzheimer’s disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals could reveal therapeutic targets for AD. Methods This study defines molecular and cellular signatures of cognitive resilience by integrating bulk RNA and single-cell transcriptomic data with genetics across multiple brain regions. We analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk RNA sequencing (n = 631 individuals) and multiregional single-nucleus RNA sequencing (n = 48 individuals). Subjects were categorized into AD, resilient, and control based on β-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole-genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition. Results Transcriptomics and polygenic risk analysis position resilience as an intermediate AD state. Only GFAP and KLF4 expression distinguished resilience from controls at tissue level, whereas differential expression of genes involved in nucleic acid metabolism and signaling differentiated AD and resilient brains. At the cellular level, resilience was characterized by broad downregulation of LINGO1 expression and reorganization of chaperone pathways, specifically downregulation of Hsp90 and upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. MEF2C, ATP8B1, and RELN emerged as key markers of resilient neurons. Excitatory neuronal subtypes in the entorhinal cortex (ATP8B+ and MEF2Chigh) exhibited unique resilience signaling through activation of neurotrophin (BDNF-NTRK2, modulated by LINGO1) and angiopoietin (ANGPT2-TEK) pathways. MEF2C+ inhibitory neurons were over-represented in resilient brains, and the expression of genes associated with rare genetic variants revealed vulnerable somatostatin (SST) cortical interneurons that survive in AD resilience. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience. Conclusions We have defined molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preserved neuronal function, balanced network activity, and activation of neurotrophic survival signaling. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable interneurons likely provides compensation against AD-associated hyperexcitability. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

Nationwide Trends in Hospitalizations for Sudden Cardiac Arrest Before and During the COVID Outbreak

Wed, 22 Oct 2025 00:00:00 GMT

Nationwide Trends in Hospitalizations for Sudden Cardiac Arrest Before and During the COVID Outbreak Daoudi, Sarah; Furer, Ariel; John, Kevin; Chalhoub, Fadi; Chee, Jennifer; Infeld, Margaret; Elbaz-Greener, Gabby; Homoud, Munther; Udelson, James; Madias, Christopher; Rozen, Guy Background/Objectives: Sudden cardiac arrest (SCA) accounts for ~50% of cardiovascular mortality in the U.S. Cardiovascular complications are common in acute and post-acute COVID-19 infection. We aimed to examine nationwide trends in SCA-related hospitalizations in the United States before and during the COVID-19 outbreak. Methods: Using data from the National Inpatient Sample, we conducted a retrospective analysis of hospitalizations for SCA in the U.S. between 2016 and 2020. Sociodemographic and clinical characteristics and in-hospital mortality were compared between the pre-COVID (2016– 2019) and COVID (2020) eras. Multivariable analysis was performed to identify factors associated with mortality. Results: Among a weighted total of 153,100 SCA hospitalizations between 2016 and 2020, the median age was 65 years, 62.7% were male, and 66.6% were white. There was a trend towards fewer hospitalizations in 2020 compared to prior years (n = 28,585 vs. naverage = 32,129, p = 0.07). In-hospital mortality remained unchanged between the pre-COVID and COVID eras (47.7% vs. 47.3%, p = 0.66). Increased mortality was associated with female sex (OR: 1.21; 95% CI: 1.15–1.28; p < 0.001), non-white race (OR: 1.24; 95% CI: 1.15–1.28; p < 0.001), history of renal failure (OR: 1.08; 95% CI: 1.02–1.15; p = 0.007), and diabetes (OR: 1.32; 95% CI: 1.25–1.39; p < 0.001). In 2020, 1.5% of the study population was diagnosed with COVID-19 infection, which was found to be independently associated with increased in-hospital mortality (OR: 1.57; 95% CI: 1.27–1.95; p < 0.001). Conclusions: In 2020, there was a trend towards a decrease in hospitalizations for SCA, while COVID-19 infection was independently associated with higher in-hospital mortality among patients admitted with SCA.

Biosensor development for single-cell detection of glucuronate

Fri, 16 Jun 2023 00:00:00 GMT

Biosensor development for single-cell detection of glucuronate Nash, Jennifer Kaczmarek; Prather, Kristala LJ Recent work in biosensors has shown promise to enable high throughput searches through large genetic libraries. However, just as physiological limitations and lack of in-depth mechanistic knowledge can prevent us from achieving high titers in microbial systems; similar roadblocks can appear in the application of biosensors. Here, we characterized a previously developed transcription-factor (ExuR) based galacturonate biosensor for its other cognate ligand, glucuronate. Though we saw an ideal response to glucuronate from the biosensor in controlled and ideal experimental circumstances, these results began to deviate from a well-behaved system when we explored the application of the sensor to different MIOX homologs. Through modifications to circuit architecture and culture conditions, we were able to decrease this variation and use these more optimal conditions to apply the biosensor for the separation of two closely related MIOX homologs.

Strategies in engineering sustainable biochemical synthesis through microbial systems

Thu, 01 Aug 2024 00:00:00 GMT

Strategies in engineering sustainable biochemical synthesis through microbial systems Song, Yoseb; Prather, Kristala LJ Growing environmental concerns and the urgency to address climate change have increased demand for the development of sustainable alternatives to fossil-derived fuels and chemicals. Microbial systems, possessing inherent biosynthetic capabilities, present a promising approach for achieving this goal. This review discusses the coupling of systems and synthetic biology to enable the elucidation and manipulation of microbial phenotypes for the production of chemicals that can substitute for petroleum-derived counterparts and contribute to advancing green biotechnology. The integration of artificial intelligence with metabolic engineering to facilitate precise and data-driven design of biosynthetic pathways is also discussed, along with the identification of current limitations and proposition of strategies for optimizing biosystems, thereby propelling the field of chemical biology towards sustainable chemical production.

Covert reciprocals: a scope-based analysis of reciprocal alternations

Tue, 30 Sep 2025 00:00:00 GMT

Covert reciprocals: a scope-based analysis of reciprocal alternations Wehbe, Jad This paper argues that the class of predicates that participate in reciprocal alternations, like the seemingly 1-place predicate hug in Jane and Mary hugged, should in fact be analyzed as 2-place predicates with a covert reciprocal in object position. The main challenge for this analysis is that there are truth-conditional differences between covert reciprocals and their overt counterparts. Focusing on a few case studies, this paper will argue that these seemingly lexical differences can be reanalyzed in terms of scope, allowing the differences to be systematically predicted once appropriate scope restrictions on covert reciprocals are established. More specifically, I propose that covert reciprocals are simply reciprocals that have to be bound at the lowest possible scope position. I show that these seemingly 1-place predicates behave just like overt reciprocals, modulo the low-scope requirement, for example giving rise to homogeneity and non-maximality. I therefore conclude that in order to account systematically for these inferences, covert reciprocals (at least the case studies that the paper considers) must be treated as having the same LFs as low-scope overt reciprocals.

Robust resonant anomaly detection with NPLM

Sun, 28 Sep 2025 00:00:00 GMT

Robust resonant anomaly detection with NPLM Grosso, Gaia; Sengupta, Debajyoti; Golling, Tobias; Harris, Philip In this study, we investigate the application of the New Physics Learning Machine (NPLM) algorithm as an alternative to the standard CWoLa method with Boosted Decision Trees (BDTs), particularly for scenarios with rare signal events. NPLM offers an end-to-end approach to anomaly detection and hypothesis testing by utilizing an in-sample evaluation of a binary classifier to estimate a log-density ratio, which can improve detection performance without prior assumptions on the signal model. We examine two approaches: (1) a end-to-end NPLM application in cases with reliable background modelling and (2) an NPLM-based classifier used for signal selection when accurate background modelling is unavailable, with subsequent performance enhancement through a hyper-test on multiple values of the selection threshold. Our findings show that NPLM-based methods outperform BDT-based approaches in detection performance, particularly in low signal injection scenarios, while significantly reducing epistemic variance due to hyperparameter choices. This work highlights the potential of NPLM for robust resonant anomaly detection in particle physics, setting a foundation for future methods that enhance sensitivity and consistency under signal variability.

Tackling the Cardio-Kidney-Metabolic Burden in Cancer

Mon, 15 Sep 2025 00:00:00 GMT

Tackling the Cardio-Kidney-Metabolic Burden in Cancer Nahle, Tarek; Shah, Viraj; Kunhiraman, Harikrishnan H.; Makram, Omar M.; Ahmed, Ola; Yerraguntla, Sandeep; Gopu, Gaurav; Vy, Jenny; Singh, Shivam; Borse, Tanvi; Kalinsky, Kevin; Deswal, Anita; Sadler, Diego; Chitalia, Vipul; Weintraub, Neal L. Purpose of the Review This review aims to examine the clinical relevance of cardio-kidney-metabolic syndrome (CKMS) in oncology, highlighting its role as both a preexisting comorbidity and a consequence of cancer treatment. It aims to integrating CKMS staging into personalized cancer care. Recent Findings CKMS is a progressive syndrome marked by dysfunction across cardiovascular, renal, and metabolic systems. Cancer therapies—particularly hormonal agents, immune checkpoint inhibitors, and chemotherapeutics—can accelerate or reveal underlying CKMS through inflammatory and metabolic pathways. Early risk stratification based on CKMS stage enables more effective monitoring, referral, and therapeutic strategies. A stage-based, multidisciplinary approach tailored to cancer type and comorbidity burden is essential for optimizing outcomes. Summary With rising multimorbidity among cancer patients, recognizing and addressing CKMS is increasingly critical. Routine CKMS assessment in oncology offers a pathway for earlier intervention and potentially altering its course. A comprehensive, individualized care model based on CKS stage is necessary to mitigate CKMS-related complications and deliver high-quality, integrated cancer care.

Initial checkout of the Psyche electric propulsion system

Thu, 31 Jul 2025 00:00:00 GMT

Initial checkout of the Psyche electric propulsion system Snyder, John S.; Kelly, Charles L.; Garner, Charles; Bradley, Nicholas; Johnson, Ian; Corey, Ron; Ream, Jodie B.; Weiss, Benjamin P. NASA’s Psyche spacecraft launched on October 13, 2023, and soon afterward the mission operations team began spacecraft initial checkout activities. For the electric propulsion system, the feed system and thruster gimbals were first prepared and then the rest of the subsystem completed an initial operations test during thruster bakeout. Thrust for each thruster was measured across the full range of operating powers and was in good agreement with pre-flight expectations. A weeklong test of the spacecraft and mission operations plan during thrusting activities was successful, but a thruster burn-in phenomenon was observed during full power operation that was longer than expected based on previous flight history. Data accumulated during the initial checkout activities shows that this burn-in behavior is different for each thruster and suggests that it is a result of the thruster discharge transitioning between two different plasma modes that can be mitigated by reducing discharge power and by adjusting the thruster magnet current. At the conclusion of the checkout activities, the subsystem had accumulated 357 h of thrusting operations while consuming 18.5 kg of propellant and was fully ready to begin the cruise phase of the mission.

Derandomizing Logspace With a Small Shared Hard Drive

Mon, 22 Sep 2025 00:00:00 GMT

Derandomizing Logspace With a Small Shared Hard Drive Pyne, Edward We obtain new catalytic algorithms for space-bounded derandomization. In the catalytic computation model introduced by (Buhrman, Cleve, Koucký, Loff, and Speelman STOC 2013), we are given a small worktape, and a larger catalytic tape that has an arbitrary initial configuration. We may edit this tape, but it must be exactly restored to its initial configuration at the completion of the computation. We prove that B P S P A C E [ S ] ⊆ C S P A C E [ S , S 2 ] where B P S P A C E [ S ] corresponds to randomized space S computation, and C S P A C E [ S , C ] corresponds to catalytic algorithms that use O(S) bits of workspace and O(C) bits of catalytic space. Previously, only B P S P A C E [ S ] ⊆ C S P A C E [ S , 2 O ( S ) ] was known. In fact, we prove a general tradeoff, that for every α ∈ [ 1 , 1.5 ] , B P S P A C E [ S ] ⊆ C S P A C E [ S α , S 3 - α ] . We do not use the algebraic techniques of prior work on catalytic computation. Instead, we develop an algorithm that branches based on if the catalytic tape is conditionally random, and instantiate this primitive in a recursive framework. Our result gives an alternate proof of the best known time-space tradeoff for B P S P A C E [ S ] , due to (Cai, Chakaravarthy, and van Melkebeek, Theory Comput. Sys. 2006). As a final application, we extend our results to solve search problems in C S P A C E [ S , S 2 ] . As far as we are aware, this constitutes the first study of search problems in the catalytic computing model.

Dopamine modulation of aggression

Tue, 23 Sep 2025 00:00:00 GMT

Dopamine modulation of aggression Dai, Bing; Lin, Dayu Rationale Aggression is an innate social behavior prevalent across animal species. However, in modern human society, inter-personal aggression is considered disruptive and detrimental to both families and communities. Clinically, antipsychotics, which primarily target dopamine (DA) receptors, have been widely used to suppress hyper-aggression. However, the mechanisms underlying the effect of the antipsychotics remain incompletely understood. Objectives We reviewed key steps in brain DA synthesis and summarized genetic and pharmacological evidence supporting the role of the mesolimbic DA system in aggression. Next, we discussed recent circuit studies that elucidate the DA action in modulating aggression-related brain regions. These lines of evidence collectively suggest that DA acts on different brain regions to facilitate aggression and self-learning, and signals the valence of the fighting experience.

Singularities of Ricci flow and diffeomorphisms

Mon, 22 Sep 2025 00:00:00 GMT

Singularities of Ricci flow and diffeomorphisms Colding, Tobias H.; Minicozzi, William P. We solve a well-known open problem in Ricci flow: Strong rigidity of cylinders. Strong rigidity is an illustration of a shrinker principle that uniqueness radiates out from a compact set. It implies that if one tangent flow at a future singular point is a cylinder, then all tangent flows are. At the heart of this problem in Ricci flow is comparing and recognizing metrics. This can be rather complicated because of the group of diffeomorphisms. Two metrics, that could even be the same, could look completely different in different coordinates. This is the gauge problem. Often it can be avoided if one uses some additional structure of the particular situation. The gauge problem is subtle for non-compact spaces without additional structure. We solve this gauge problem by solving a nonlinear system of PDEs. The PDE produces a diffeomorphism that fixes an appropriate gauge in the spirit of the slice theorem for group actions. We then show optimal bounds for the displacement function of the diffeomorphism. Strong rigidity relies on gauge fixing and several other new ideas. One of these is “propagation of almost splitting”, another is quadratic rigidity in the right gauge, and a third is an optimal polynomial growth bound for PDEs that holds in great generality.

A Parametric, second-order cone representable model of fairness for decision-making problems

Thu, 10 Apr 2025 00:00:00 GMT

A Parametric, second-order cone representable model of fairness for decision-making problems Sundar, Kaarthik; Deka, Deepjyoti; Bent, Russell The article develops a parametric model of fairness called “ ε -fairness” that can be represented using a single second-order cone constraint and incorporated into existing decision-making problem formulations without impacting the complexity of solution techniques. We develop the model from the fundamental result of finite-dimensional norm equivalence in linear algebra and show that this model has a closed-form relationship to an existing metric for measuring fairness widely used in the literature. Finally, a simple case study on the optimal operation of a damaged power transmission network illustrates its effectiveness.

Semiclassical Measures for Complex Hyperbolic Quotients

Thu, 28 Aug 2025 00:00:00 GMT

Semiclassical Measures for Complex Hyperbolic Quotients Athreya, Jayadev; Dyatlov, Semyon; Miller, Nicholas We study semiclassical measures for Laplacian eigenfunctions on compact complex hyperbolic quotients. Geodesic flows on these quotients are a model case of hyperbolic dynamical systems with different expansion/contraction rates in different directions. We show that the support of any semiclassical measure is either equal to the entire cosphere bundle or contains the cosphere bundle of a compact immersed totally geodesic complex submanifold. The proof uses the one-dimensional fractal uncertainty principle of Bourgain–Dyatlov (Ann. Math. (2) 187(3):825–867, 2018) along the fast expanding/contracting directions, in a way similar to the work of Dyatlov–Jézéquel (Ann. Henri Poincaré, 2023) in the toy model of quantum cat maps, together with a description of the closures of fast unstable/stable trajectories relying on Ratner theory.

A divisor generating q-series and cumulants arising from random graphs

Thu, 20 Nov 2025 00:00:00 GMT

A divisor generating q-series and cumulants arising from random graphs Agarwal, Archit; Bhoria, Subhash C.; Eyyunni, Pramod; Maji, Bibekananda; Wakhare, Tanay Uchimura, in 1987, introduced a probability generating function for a random variable X and using properties of this function, he discovered an interesting q-series identity. He further showed that the m-th cumulant with respect to the random variable X is nothing but the generating function for the generalized divisor function σ m - 1 ( n ) . Simon, Crippa, and Collenberg, in 1993, explored the G n , p -model of a random acyclic digraph and defined a random variable γ n ∗ ( 1 ) . Quite interestingly, they found links between the limit of its mean and the generating function for the divisor function d(n). Later in 1997, Andrews, Crippa and Simon extended these results using q-series techniques. They calculated the limit of the mean and the variance of the random variable γ n ∗ ( 1 ) which correspond to the first and second cumulants. In this paper, we generalize the result of Andrews, Crippa and Simon by calculating the limit of the t-th cumulant in terms of the generalized divisor function. Furthermore, we also discover limit forms for identities of Uchimura and Dilcher. This provides a fourth side to the Uchimura–Ramanujan–divisor-type three-way partition identities expounded by the first four authors recently.

Arithmetic properties encoded in undermonoids

Fri, 19 Sep 2025 00:00:00 GMT

Arithmetic properties encoded in undermonoids Gotti, Felix; Li, Bangzheng Let M be a cancellative and commutative monoid. A submonoid N of M is called an undermonoid if the Grothendieck groups of M and N coincide. For a given property p , we are interested in providing an answer to the following main question: does it suffice to check that all undermonoids of M satisfy p to conclude that all submonoids of M satisfy p ? In this paper, we give a positive answer to this question for the property of being atomic, and then we prove that if M is hereditarily atomic (i.e., every submonoid of M is atomic), then M must satisfy the ACCP, proving a recent conjecture posed by Vulakh and the first author. We also give positive answers to our main question for the following well-studied factorization properties: the bounded factorization property, half-factoriality, and length-factoriality. Finally, we determine all the monoids whose submonoids/undermonoids are half-factorial/length-factorial.

The rocky road to modernity: an assessment of Pakistan’s 75 years

Mon, 12 Dec 2022 00:00:00 GMT

The rocky road to modernity: an assessment of Pakistan’s 75 years Hoodbhoy, Pervez To assess whether Pakistan is moving towards or away from modernity I examine here the evolution of three key aspects: the overall idea system of society, the political system, and national culture. A meaningful analysis must begin with pre-colonial India, examine how British rule made fundamental changes, and the emergence of Pakistan as a result of Muslim religious identity. Although the beginnings of Pakistani modernity were shaky, the earlier inclination was to equalise with the developed world at large. In the mid-1980s this changed profoundly with the advent of political Islam, explicit repudiation of overt forms of western modernity, and a sharply increased tendency to seek examplars in the Islamic past. That trend has since accelerated under the influence of social media. But most Pakistanis, I argue, still want to hedge their bets and seek the fruits of modernity within a framework that they perceive as not inimical to their faith in Islam.

Precipitate Size in GRCop-42 and GRCop-84 Cu-Cr-Nb Alloy Gas Atomized Powder and L-PBF Additive Manufactured Material

Thu, 26 Jan 2023 00:00:00 GMT

Precipitate Size in GRCop-42 and GRCop-84 Cu-Cr-Nb Alloy Gas Atomized Powder and L-PBF Additive Manufactured Material Seltzman, AH; Wukitch, SJ Laser powder bed fusion (L-PBF) of Glenn Research Copper 42 or 84 (GRCop-42 or GRCop-84) produces a Cr2Nb precipitation-hardened high-conductivity copper alloy with tensile strength superior to other competing copper alloys. Precipitate diameters within GRCop-42 gas-atomized powder increase with powder diameter due to slower cooling rates, however, unlike GRCop-84, no threshold diameter above which extensive precipitate agglomerations form was observed in GRCop-42. Large Cr2Nb crystals were observed in GRCop-42 powder particles, implying formation within the crucible melt. A consistent precipitate volume of ~7% over a range of powder particle diameters indicated a consistent atomization process. Occasional voids were observed in GRCop-42 powder. Precipitate size was refined in L-PBF GRCop-42 to a greater extent than in GRCop-84, improving Orowan strengthening, however, this benefit was lost after heat treatment due to greater coarsening of precipitates. Precipitates in GRCop-42 accumulated on grain boundaries during heat treatment to a greater extent than in GRCop-84.

US-Russian partnerships in science: working with differences

Wed, 16 Feb 2022 00:00:00 GMT

US-Russian partnerships in science: working with differences Dezhina, Irina; Wood, Elizabeth A In the early 1990s, Russian and US observers were pessimistic about Russian science and its global integration. Yet scientists from the two countries were actively collaborating in new ways nonetheless. In order to explore the nature of those collaborations, we conducted open-ended interviews with 13 US scientists and 13 in Russia who collaborated trans-nationally in 1995–2014. Our results suggest that recognizing and working with differences benefited these colleagues. Despite ongoing political tensions and differences in scientific cultures, respondents told us that understanding those differences – in funding, cultures of doing science, institutional structures, and treatment of graduate students – helped them avoid missteps. Respect for each other’s country’s scientific contributions, interpersonal diplomacy, and personal interconnections further strengthened their work together. Diaspora scientists in particular, played a positive role as mediators and cultural interpreters.

Agrammatic output in non-fluent, including Broca’s, aphasia as a rational behavior

Fri, 18 Nov 2022 00:00:00 GMT

Agrammatic output in non-fluent, including Broca’s, aphasia as a rational behavior Fedorenko, Evelina; Ryskin, Rachel; Gibson, Edward Background: Speech of individuals with non-fluent, including Broca's, aphasia is often characterized as "agrammatic" because their output mostly consists of nouns and, to a lesser extent, verbs and lacks function words, like articles and prepositions, and correct morphological endings. Among the earliest accounts of agrammatic output in the early 1900s was the "economy of effort" idea whereby agrammatic output is construed as a way of coping with increases in the cost of language production. This idea resurfaced in the 1980s, but in general, the field of language research has largely focused on accounts of agrammatism that postulated core deficits in syntactic knowledge. Aims: We here revisit the economy of effort hypothesis in light of increasing emphasis in cognitive science on rational and efficient behavior. Main contribution: The critical idea is as follows: there is a cost per unit of linguistic output, and this cost is greater for patients with non-fluent aphasia. For a rational agent, this increase leads to shorter messages. Critically, the informative parts of the message should be preserved and the redundant ones (like the function words and inflectional markers) should be omitted. Although economy of effort is unlikely to provide a unifying account of agrammatic output in all patients-the relevant population is too heterogeneous and the empirical landscape too complex for any single-factor explanation-we argue that the idea of agrammatic output as a rational behavior was dismissed prematurely and appears to provide a plausible explanation for a large subset of the reported cases of expressive aphasia. Conclusions: The rational account of expressive agrammatism should be evaluated more carefully and systematically. On the basic research side, pursuing this hypothesis may reveal how the human mind and brain optimize communicative efficiency in the presence of production difficulties. And on the applied side, this construal of expressive agrammatism emphasizes the strengths of some patients to flexibly adapt utterances in order to communicate in spite of grammatical difficulties; and focusing on these strengths may be more effective than trying to "fix" their grammar.

Burns on Strauss’s Liberating Liberal Education

Wed, 18 Jan 2023 00:00:00 GMT

Burns on Strauss’s Liberating Liberal Education Rabieh, Linda R. Leo Strauss on Democracy, Technology, and Liberal Education is an invaluable source of historical learning and philosophic guidance. Timothy W. Burns provides us with an in-depth and careful study of four important writings by Leo Strauss that examine the challenges faced by modern democracy and the ways in which liberal education can supply a modest remedy. According to Burns, Strauss understands the problems facing modern democracy to be rooted in the ascendancy of technology as the ultimate political aim, which prioritizes acquiring the means to pursue whatever ends we happen to desire rather than the good life itself (9). Subsequent developments in the service of this goal have led to our present situation, which Strauss characterizes as “hardly more than the interplay of mass taste with high grade but strictly speaking unprincipled efficiency” (13; see also 35, 69, 75–78). Burns sharpens his analysis of Strauss by comparing Strauss’s understanding of technology with that of Heidegger. In contrast to Heidegger’s argument for a “new thinking” to address modernity’s ills, Strauss looks to an older thinking from which he gleans an argument for liberal education, which he describes as the cultivation of “an aristocracy within democracy,” i.e., a class within society whose thinking is informed by both serious education in tradition and the study of the Great Books (15; see also 21, 84, 166). Although Burns’s book addresses many aspects of Strauss’s account of the way in which technology came to dominate politics and shape our modern world, I will focus on the thread throughout these essays that explains what Strauss means by liberal education and why it is needed today.

Meta-UNet: enhancing skin-lesion segmentation with multimodal feature integration and uncertainty estimation

Wed, 30 Jul 2025 00:00:00 GMT

Meta-UNet: enhancing skin-lesion segmentation with multimodal feature integration and uncertainty estimation Sikha, O. K.; Stone, Alaysia L. B.; González Ballester, Miguel A. Purpose Medical image segmentation plays a crucial role in diagnostic pipelines. This study investigates the integration of lesion-specific metadata with image data to enhance segmentation accuracy and reduce predictive uncertainty. Methods The standard U-Net architecture was modified to incorporate lesion-specific metadata (Meta-UNet). Various integration strategies, including addition, weighted addition, and embedding layers, were evaluated. Additionally, a Bayesian Meta-UNet with Monte Carlo Dropout (MCD) was developed to assess the impact of metadata integration on model uncertainty. Uncertainty was quantified using measures such as Confidence Maps, Entropy, Mutual Information, and Expected Pairwise Kullback–Leibler divergence (EPKL). An aggregation strategy was also introduced to provide a single comprehensive uncertainty score per image. Results Meta-UNet outperformed standard U-Net across PH2, ISIC 2018, and HAM10000 datasets. On PH2, it achieved 84.64% accuracy and 90.62% Intersection over Union (IoU), compared to 83.36% and 89.19%. On ISIC 2018, U-Net scored 71.02 ± 6.69 IoU and 79.89 ± 5.09 Dice. On HAM10000, Meta-UNet achieved 88.66 ± 6.09 IoU and 93.42 ± 5.19 Dice. Meta-UNet reduced uncertainty (e.g., 0.149 vs. 0.1745), highlighting the benefit of metadata integration in improving segmentation accuracy and model confidence. Conclusion Integrating lesion-specific metadata into the U-Net architecture significantly improves segmentation accuracy and reduces predictive uncertainty. The inclusion of metadata enhances model confidence and reliability, underscoring its potential to strengthen diagnostic segmentation pipelines.

Increasing the quantum tunneling probability through a learned ancilla-assisted protocol

Tue, 05 Aug 2025 00:00:00 GMT

Increasing the quantum tunneling probability through a learned ancilla-assisted protocol Testa, Renzo; Rodriguez Garcia, Alejandro; d’Onofrio, Alberto; Trombettoni, Andrea; Benatti, Fabio; Anselmi, Fabio Increasing the probability of quantum tunneling between two states, while keeping constant the resources of the underlying physical system, is a task of key importance in several physical contexts and platforms, including ultracold atoms confined by double-well potentials and superconducting qubits. We propose a novel ancillary assisted protocol showing that when a quantum system—such as a qubit—is coupled to an ancilla, one can learn the optimal ancillary component and its coupling, to increase the tunneling probability. As a case study, we consider a quantum system that, due to the presence of an energy detuning between two modes, cannot transfer by tunneling the particles from one mode to the other. However, it does it through a learned coupling with an ancillary system characterized by a detuning not smaller than the one of the primary system. We provide several illustrative examples for the paradigmatic case of a two-mode system and a two-mode ancilla in the presence of interacting particles. This reduces to a qubit coupled to an ancillary qubit in the case of one particle in the system and one in the ancilla. Our proposal provides an effective method to increase the tunneling probability in all those physical situations where no direct improvement of the system parameters, such as tunneling coefficient or energy detuning, is either possible or resource efficient. Finally, we also argue that the proposed strategy is not hampered by weak coupling to noisy environments.

Attitudes, aboutness, and indirect restriction

Mon, 04 Aug 2025 00:00:00 GMT

Attitudes, aboutness, and indirect restriction von Fintel, Kai; Pasternak, Robert On its surface, a sentence like If Laura becomes a zombie, she wants you to shoot her looks like a plain conditional with the attitude want in its consequent. However, the most salient reading of this sentence is not about the desires of a hypothetical zombie-Laura. Rather, it asserts that the actual, non-zombie Laura has a certain restricted attitude: her present desires, when considering only possible states of affairs in which she becomes a zombie, are such that you shoot her. This can be contrasted with the shifted reading about zombie-desires that arises with conditional morphosyntax, e.g., If Laura became a zombie, she would want you to shoot her. Furthermore, as Blumberg and Holguín (J Semant 36(3):377–406, 2019) note, restricted attitude readings can also arise in disjunctive environments, as in Either a lot of people are on the deck outside, or I regret that I didn’t bring more friends. We provide a novel analysis of restricted and shifted readings in conditional and disjunctive environments, with a few crucial features. First, both restricted and shifted attitude conditionals are in fact “regular” conditionals with attitudes in their consequents, which accords with their surface-level appearance and contrasts with Pasternak’s (The mereology of attitudes, Ph.D. thesis, Stony Brook University, Stony Brook, NY, 2018) Kratzerian approach, in which the if-clause restricts the attitude directly. Second, whether the attitude is or is not shifted—i.e., zombie versus actual desires—is dependent on the presence or absence of conditional morphosyntax. And third, the restriction of the attitude is effected by means of aboutness, a concept for which we provide two potential implementations. We conclude by discussing our analysis’s prospective repercussions for the theory of conditionals more generally.

Sulfated dietary fiber protects gut microbiota from antibiotics

Wed, 06 Aug 2025 00:00:00 GMT

Sulfated dietary fiber protects gut microbiota from antibiotics Wu, Fuqing; Yu, Xiaoqian A.; Angeles-Albores, David; Erdman, Susan E.; Alm, Eric J. Background Antibiotics, while essential for combating pathogens, also disrupt commensal bacteria, leading to gut microbiota imbalance and associated diseases. However, strategies to mitigate such collateral damage remain largely underexplored. Result In this study, we found that fucoidan, a marine polysaccharide derived from brown seaweed, provides broad-spectrum growth protection against multiple classes of antibiotics for human gut microbial isolates in vitro and for fecal communities ex vivo. This protective effect is dependent on the structural integrity, molecular weight, and sulfur content of the polysaccharide. Transcriptomic analysis showed that while fucoidan had minimal impact on baseline gene expression, it counteracted about 60% of the genes induced by kanamycin, suggesting a potential inhibition of kanamycin. Mass spectrometry results further showed that this inhibition may be due to the non-specific binding of fucoidan to kanamycin in solution. Finally, animal model experiments revealed that fucoidan facilitated the recovery of gut microbes following antibiotic treatment in vivo. Conclusion These findings suggest fucoidan could serve as a potential intervention to help protect gut microbiota during antibiotic therapy. Further studies are needed to evaluate its clinical potential and ensure it does not compromise antimicrobial efficacy. Video Abstract

Additivity, Haag duality, and non-invertible symmetries

Fri, 01 Aug 2025 00:00:00 GMT

Additivity, Haag duality, and non-invertible symmetries Shao, Shu-Heng; Sorce, Jonathan; Srivastava, Manu The algebraic approach to quantum field theory focuses on the properties of local algebras, whereas the study of (possibly non-invertible) global symmetries emphasizes global aspects of the theory and spacetime. We study connections between these two perspectives by examining how either of two core algebraic properties — “additivity” or “Haag duality” — is violated in a 1+1D CFT or lattice model restricted to the symmetric sector of a general global symmetry. For the Verlinde symmetry of a bosonic diagonal RCFT, we find that additivity is violated whenever the symmetry algebra contains an invertible element, while Haag duality is violated whenever it contains a non-invertible element. We find similar phenomena for the Kramers-Wannier and Rep(D8) non-invertible symmetries on spin chains.

Observation of the Λ b 0 → J / ψ Ξ - K + and Ξ b 0 → J / ψ Ξ - π + decays

Mon, 28 Jul 2025 00:00:00 GMT

Observation of the Λ b 0 → J / ψ Ξ - K + and Ξ b 0 → J / ψ Ξ - π + decays The first observation of the Ξ b 0 → J / ψ Ξ - π + decay and the most precise measurement of the branching fraction of the Λ b 0 → J / ψ Ξ - K + decay are reported, using proton-proton collision data from the LHCb experiment collected in 2016–2018 at a centre-of-mass energy of 13 \,Te V , corresponding to an integrated luminosity of 5.4 \,fb - 1 . Using the Λ b 0 → J / ψ Λ and Ξ b - → J / ψ Ξ - decays as normalisation channels, the ratios of branching fractions are measured to be B ( Λ b 0 → J / ψ Ξ - K + ) B ( Λ b 0 → J / ψ Λ ) = ( 1.17 ± 0.14 ± 0.08 ) × 10 - 2 , B ( Ξ b 0 → J / ψ Ξ - π + ) B ( Ξ b - → J / ψ Ξ - ) = ( 11.9 ± 1.4 ± 0.6 ) × 10 - 2 , where the first uncertainty is statistical and the second systematic.

Incorporating teacher effect when modeling student engagement in smart STEM classrooms: a cluster analysis

Wed, 10 Sep 2025 00:00:00 GMT

Incorporating teacher effect when modeling student engagement in smart STEM classrooms: a cluster analysis Shreeve, Kelly; Perry, Anthony; Cassidy, Michael; Jessen Eller, Kathryn; Price, Beth; Jackson, Brandy; Celi, Leo; Lourentzou, Ismini; Hendrik, Luk Student engagement during learning serves as a critical predictor of academic success and plays a pivotal role in nurturing interest and readiness for future careers. As digital platforms become increasingly important to learning, it is essential that we understand how the interactions that students have with them reflects their engagement with learning. Previous research has often modeled engagement in a fully online context, where students pursue lessons independently and outside the influence of the classroom, paced and structured by digital systems. However, in STEM (Science, Technology, Engineering, and Math) subjects—and many others—learning more frequently happens in a physical classroom setting, under the guidance of a teacher, and involves interactions with other students and tangible objects. Here digital materials are used to scaffold and support learning but are not typically the focus of where learning happens. To study how student interactions with digital materials in these settings might allow us to measure, evaluate and help teachers enhance engagement, we have developed and deployed a smart digital learning platform that guides instruction and captures real-time multimodal student learning events in the physical STEM classroom. Previously we have shown that a subset of student interactions measured with this platform can be used to model student learning and generate human-like insights into engagement. Here we report on the significant influence that teachers have on student interactions with our smart platform in the STEM classroom, and the impact that this has on evaluating their engagement with learning. In an analysis of 108 high school students that used the platform to complete a 19-lesson data science curriculum in 5 different classrooms, we found significant differences between teachers both in the measured time students spent on the lesson and the percentage of the lesson they completed. In this setting, taking teacher influence into account improves the outcomes of our machine learning clustering models that group students based on their level of engagement. These findings inform how we develop smart classroom technology and machine learning applications that are globally informed but locally relevant, and support teachers to enhance student engagement and learning outcomes in dynamic and highly variable STEM classroom learning environments.

On determining αs(mZ) from dijets in e+e− thrust

Fri, 25 Jul 2025 00:00:00 GMT

On determining αs(mZ) from dijets in e+e− thrust Benitez, Miguel A.; Hoang, André H.; Mateu, Vicent; Stewart, Iain W.; Vita, Gherardo We update a previous N3LL′+ O α s 3 determination of the strong coupling from a global fit to thrust data by including newly available perturbative ingredients, upgrading the renormalization scales to include a fully canonical scaling region, and implementing the log resummation in a way which ensures the integrated cross section is unaffected by the leading 1/Q hadronization power corrections. Detailed discussions are provided concerning the stability of the results under variations of the fit range and the importance of summing up higher-order logarithmic terms for convergence and stability. We show that high-precision results can be achieved even when carrying out a more conservative fit by restricting the dataset to a region which is more clearly dominated by dijet events. This leads to αs(mZ) = 0.1136 ± 0.0012 with χ2/dof = 0.86, fully compatible with earlier results using a larger fit range. We also demonstrate that a number of additional effects associated to power corrections have a small impact on this fit result, including modifications to the renormalon substraction scheme for dijet power corrections and the inclusion of three-jet power correction models. The fit is also shown to provide very good agreement with data outside the fit range.

Measurement of the ψ(2S) to J/ψ cross-section ratio as a function of centrality in PbPb collisions at √sNN = 5.02 TeV

Wed, 23 Jul 2025 00:00:00 GMT

Measurement of the ψ(2S) to J/ψ cross-section ratio as a function of centrality in PbPb collisions at √sNN = 5.02 TeV Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; LHCb collaboration The ratio of prompt production cross-sections of ψ(2S) and J/ψ mesons in their dimuon final state is measured as a function of centrality, using data collected by the LHCb detector in PbPb collisions at √ sNN = 5.02 TeV, for the first time in the forward rapidity region. The measured ratio shows no dependence on the collision centrality, and is compared to the latest theory predictions and to the recent measurements in literature.

Legal causation*

Fri, 14 Oct 2022 00:00:00 GMT

Legal causation* Byrne, Thomas I propose a new formalist account of legal (/proximate) causation – one that holds legal causation to be a matter of amoral, descriptive fact. The account starts with a metaphysical relation, akin to but distinct from common-sense causation, and it argues that legal causation aligns exactly with that relation; it is unified and principled.

Space Architecture in Microgravity: TESSERAE Project for Large Scale Space Structures

Mon, 21 Nov 2022 00:00:00 GMT

Space Architecture in Microgravity: TESSERAE Project for Large Scale Space Structures Ekblaw, Ariel NASA and international partners are planning a crewed returnto the lunar surface in this decade, with the explicit long-termgoal of establishing sustainable lunar habitat infrastructure.International space agencies and several space entrepreneurshave shared plans for human missions to Mars in the 2030s.A menagerie of “new space” start-up companies is poised tosupport extensive activity for in-space habitation. Space explo-ration is entering an age of burgeoning commercial movement,fueled not only by the unique science experiments performedin microgravity but also by space tourism and a need for inhab-itable next-generation space architecture.Designers such as architects, engineers, and space structurepractitioners should aim to democratize access to space andchallenge the prevailing paradigm of space as an exclusive andinaccessible domain. In that case, they must build space architec-ture that can scale to welcome, safeguard, and inspire human-kind. Our space structures research program applies biomimeticprinciples to design modular, reconfigurable, and self-assemblingspace architecture. Currently, The team includes electrical andmechanical engineers, designers, a university-trained architect,and a spaceflight mission integration specialist.

Infrastructure, Revenue, and Services: Non-State Governance in Iraq’s Disputed Territories

Wed, 05 Oct 2022 00:00:00 GMT

Infrastructure, Revenue, and Services: Non-State Governance in Iraq’s Disputed Territories Cancian, Matthew; Greenwald, Diana B. While states and non-state armed groups often engage in militarised conflict over contested territory, at other times they co-govern in a tenuous equilibrium. Using a survey of over 1,600 Kurdish soldiers (Peshmerga) and elite interviews, we investigate local variation in shared governance in one such context – the disputed territories of northern Iraq. Despite the area being under Kurdish military control, the Iraqi government continued to provide services in districts where it had pre-existing infrastructural capacity. However, in revenue-producing districts, Kurdish actors appropriated infrastructural power to provide services themselves. This illustrates that non-state governance strategies, and their outputs, can vary locally.

Which Information Matters? Measuring Landlord Assessment of Tenant Screening Reports

Tue, 30 Aug 2022 00:00:00 GMT

Which Information Matters? Measuring Landlord Assessment of Tenant Screening Reports So, Wonyoung This research studies how tenant screening services’ presentation ofinformation influences landlord decisions. Tenant screening services util-ize criminal records, eviction records, and credit score databases to pro-duce reports that landlords use to inform their decisions about who torent to. However, little is known about how landlords assess the infor-mation presented by tenant screening reports. Through a behavioralexperiment with landlords using simulated tenant screening reports,this study shows that landlords use blanket screening policies, that theyconflate the existence of tenant records with outcomes (e.g., eviction fil-ings with executed evictions), and that they display, on average, tenden-cies toward automation bias that are influenced by the risk assessmentsand scores presented by tenant screening reports. I argue that maintain-ing blanket screening policies and automation bias, combined with thedownstream effects of creating and using racially biased eviction andcriminal records, means that people of color will inevitably experiencedisproportionate exclusion from rental housing due to perceived “risk”on the part of landlords.

Learning to make noise: toward a process model of artistic practice within experimental music scenes

Fri, 15 Jul 2022 00:00:00 GMT

Learning to make noise: toward a process model of artistic practice within experimental music scenes Woods, Peter J Emerging at the intersection of industrial, punk, electronic music, and avant-garde jazz, noise music represents a niche subgenre reliant on loud, discordant, and arrhythmic sounds to make music. Yet despite its place within the (broadly defined) experimental music tradition, research into experimental music education has largely overlooked the genre. In response, I explore noise music through the lens of situated learning theory by addressing the following research question: how do noise musicians develop their artistic practice? To do so, I present findings from a comparative case study centered on two intertwined experimental music concert and workshop series focused on noise music. I begin by analyzing interview data from seventeen featured artists to construct a process model of artistic practice shared between musicians. I then employ bidirectional artifact analysis to trace the development of one novice participant in the series through this model. In turn, these findings not only illuminate how experimental musicians learn within informal settings but provide a potential model of learning for informal education communities more broadly. This study also holds implications for situated learning theory by asserting the influence of non-anthropocentric actors within communities of practice.

Experiencer troubles: A reappraisal of the predicate-based asymmetry in child passives

Mon, 17 Oct 2022 00:00:00 GMT

Experiencer troubles: A reappraisal of the predicate-based asymmetry in child passives Aravind, Athulya; Koring, Loes Children’s understanding of passives of certain mental state predicates appears to lag behind passives of so-called actional predicates, an asymmetry that has posed a major empirical challenge for theories of passive acquisition. This paper argues against the dominant view in the literature that treats the predicate-based asymmetry as theoretically irrelevant. We instead propose a novel account that locates the problem in the syntax of experiencer constructions. Synthesizing theoretical and developmental evidence, we build a case for an early misanalysis of transitive subject-experiencer constructions as unaccusatives – structures that, by design, cannot passivize.

Challenges and Opportunities of Machine Learning on Neutron and X-ray Scattering

Wed, 12 Oct 2022 00:00:00 GMT

Challenges and Opportunities of Machine Learning on Neutron and X-ray Scattering Drucker, Nathan C; Liu, Tongtong; Chen, Zhantao; Okabe, Ryotaro; Chotrattanapituk, Abhijatmedhi; Nguyen, Thanh; Wang, Yao; Li, Mingda Machine learning has been highly successful in boosting the re-search for neutron and X-ray scattering in the past few years [1, 2]. Fordiffraction, machine learning has shown great promise in phase map-ping [3, 4] and crystallographic information determination [5, 6]. Insmall-angle scattering, machine learning shows the power in reachingsuper-resolution [7, 8], reconstructing structures for macromolecules[9], and building structure-property relations [10]. As for absorptionspectroscopy, machine learning has enabled the rapid inverse searchfor optimized structures [11, 12] with improved spectral interpretability[13, 14]. Overall, as a data-driven approach, the success of the machine-learning-based scattering analysis depends on a few criteria, including:• Quantity of available experimental data, and feasibility to extractcertain data labels;• Quality of experimental data that can separate the intrinsic effect(e.g., materials properties) from extrinsic influence (e.g., instru-mental or data artifacts);• Feasibility to generate high volume of computational data;• Accuracy of computational data that can simulate the experimen-tal data.

Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation

Thu, 29 Sep 2022 00:00:00 GMT

Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation Camerlenghi, Federico; Favaro, Stefano; Masoero, Lorenzo; Broderick, Tamara There is a growing interest in the estimation of the number of unseen features, mostly driven by biological applications. A recent work brought out a peculiar property of the popular completely random measures (CRMs) as prior models in Bayesian nonparametric (BNP) inference for the unseen-features problem: for fixed prior's parameters, they all lead to a Poisson posterior distribution for the number of unseen features, which depends on the sampling information only through the sample size. CRMs are thus not a flexible prior model for the unseen-features problem and, while the Poisson posterior distribution may be appealing for analytical tractability and ease of interpretability, its independence from the sampling information makes the BNP approach a questionable oversimplification, with posterior inferences being completely determined by the estimation of unknown prior's parameters. In this article, we introduce the stable-Beta scaled process (SB-SP) prior, and we show that it allows to enrich the posterior distribution of the number of unseen features arising under CRM priors, while maintaining its analytical tractability and interpretability. That is, the SB-SP prior leads to a negative Binomial posterior distribution, which depends on the sampling information through the sample size and the number of distinct features, with corresponding estimates being simple, linear in the sampling information and computationally efficient. We apply our BNP approach to synthetic data and to real cancer genomic data, showing that: (i) it outperforms the most popular parametric and nonparametric competitors in terms of estimation accuracy; (ii) it provides improved coverage for the estimation with respect to a BNP approach under CRM priors. Supplementary materials for this article are available online.

Precision DIS thrust predictions for HERA and EIC

Thu, 24 Jul 2025 00:00:00 GMT

Precision DIS thrust predictions for HERA and EIC Ee, June-Haak; Kang, Daekyoung; Lee, Christopher; Stewart, Iain W. We present predictions for the DIS 1-jettiness event shape τ 1 b , or DIS thrust, using the framework of Soft Collinear Effective Theory (SCET) for factorization, resummation of large logarithms, and rigorous treatment of nonperturbative power corrections, matched to fixed-order QCD away from the resummation region. Our predictions reach next-to-next-to-next-to-leading-logarithmic (N3LL) accuracy in resummed perturbation theory, matched to O ( α s 2 ) fixed-order QCD calculations obtained using the program NLOJet++. We include a rigorous treatment of hadronization corrections, which are universal across different event shapes and kinematic variables x and Q at leading power, and supplement them with a systematic scheme to remove O (ΛQCD) renormalon ambiguities in their definition. The framework of SCET allows us to connect smoothly the nonperturbative, resummation, and fixed-order regions, whose relative importance varies with x and Q, and to rigorously estimate theoretical uncertainties, across a broad range of x and Q covering existing experimental results from HERA as well as expected new measurements from the upcoming Electron- Ion-Collider (EIC). Our predictions will serve as an important benchmark for the EIC program, enabling the precise determination of the QCD strong coupling αs and the universal nonperturbative first moment parameter Ω1.

Semi-classical dilaton gravity and the very blunt defect expansion

Tue, 22 Jul 2025 00:00:00 GMT

Semi-classical dilaton gravity and the very blunt defect expansion Kruthoff, Jorrit; Levine, Adam We explore dilaton gravity with general dilaton potentials in the semi-classical limit viewed both as a gas of blunt defects and also as a semi-classical theory in its own right. We compare the exact defect gas picture with that obtained by naively canonically quantizing the theory in geodesic gauge. We find a subtlety in the canonical approach due to a non-perturbative ambiguity in geodesic gauge. Unlike in JT gravity, this ambiguity arises already at the disk level. This leads to a distinct mechanism from that in JT gravity by which the semi-classical approximation breaks down at low temperatures. Along the way, we propose that new, previously un-studied saddles contribute to the density of states of dilaton gravity. This in particular leads to a re-interpretation of the disk-level density of states in JT gravity in terms of two saddles with fixed energy boundary conditions: the disk, which caps off on the outer horizon, and another, sub-leading complex saddle which caps off on the inner horizon. When the theory is studied using a defect expansion, we show how the smooth classical geometries of dilaton gravity arise from a dense gas of very blunt defects in the GN → 0 limit. The classical saddle points arise from a balance between the attractive force on the defects toward negative dilaton and a statistical pressure from the entropy of the configuration. We end with speculations on the nature of the space-like singularity present inside black holes described by certain dilaton potentials.

Measurement of the branching fraction ratio RK at large dilepton invariant mass

Thu, 17 Jul 2025 00:00:00 GMT

Measurement of the branching fraction ratio RK at large dilepton invariant mass Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; The LHCb collaboration A test of lepton universality between muons and electrons is performed using B+ → K+ℓ+ℓ− decays (where ℓ = e, μ), in the dilepton invariant-mass-squared region above 14.3 GeV2/c4. The data used for the measurement consists of beauty meson decays produced in proton-proton collisions, corresponding to an integrated luminosity of 9 fb−1, collected by the LHCb experiment between 2011 and 2018. The ratio of branching fractions for B+ → K+μ+μ− and B+ → K+e+e− decays is measured to be R K = 1.0 8 − 0.09 + 0.11 stat − 0.04 + 0.04 syst , which is consistent with the Standard Model prediction of unity. This constitutes the most precise test of lepton flavour universality using B+ → K+ℓ+ℓ− decays with dilepton invariant-mass-squared above the ψ(2S) mass, whilst being the first of its kind at a hadron collider.

Iterating Sine, Equivalence Classes of Variable Changes, and Groups with Few Conjugacy Classes

Wed, 23 Jul 2025 00:00:00 GMT

Iterating Sine, Equivalence Classes of Variable Changes, and Groups with Few Conjugacy Classes Etingof, Pavel This is an expository paper about iterations of a smooth real function f on [0, ) such that f(0) = 0, f E (0) = 1, and f(x) < x for x > 0, i.e., the sequence defined by xn+1 = f(xn). This sequence has interesting asymptotics, whose study leads to the question of classifying conjugacy classes in the group of formal changes of variable y = f(x), i.e., formal series f(x) = x + a2x2 + a3x2 + ⋯ with real coefficients (under composition). The same classification applies over a finite field p for suitably truncated series f, defining a family of p-groups that have the smallest number of conjugacy classes for a given order, i.e., are the “most noncommutative” finite groups currently known. The paper should be accessible to undergraduates and at least partially to advanced high school students.

Quantum information meets high-energy physics: input to the update of the European strategy for particle physics

Tue, 09 Sep 2025 00:00:00 GMT

Quantum information meets high-energy physics: input to the update of the European strategy for particle physics Afik, Yoav; Fabbri, Federica; Low, Matthew; Marzola, Luca; Aguilar-Saavedra, Juan A.; Altakach, Mohammad M.; Asbah, Nedaa A.; Bai, Yang; Banks, Hannah; Barr, Alan J.; Bernal, Alexander; Browder, Thomas E.; Caban, Paweł; Casas, J. A.; Cheng, Kun; Déliot, Frédéric; Demina, Regina; Di Domenico, Antonio; Eckstein, Michał; Fabbrichesi, Marco Some of the most astonishing and prominent properties of Quantum Mechanics, such as entanglement and Bell nonlocality, have only been studied extensively in dedicated low-energy laboratory setups. The feasibility of these studies in the high-energy regime explored by particle colliders was only recently shown and has gathered the attention of the scientific community. For the range of particles and fundamental interactions involved, particle colliders provide a novel environment where quantum information theory can be probed, with energies exceeding by about 12 orders of magnitude those employed in dedicated laboratory setups. Furthermore, collider detectors have inherent advantages in performing certain quantum information measurements and allow for the reconstruction of the state of the system under consideration via quantum state tomography. Here, we elaborate on the potential, challenges, and goals of this innovative and rapidly evolving line of research and discuss its expected impact on both quantum information theory and high-energy physics.

On approximability of Satisfiable k -CSPs: I

Tue, 22 Jul 2025 00:00:00 GMT

On approximability of Satisfiable k -CSPs: I Bhangale, Amey; Khot, Subhash; Minzer, Dor We consider the P -CSP problem for 3-ary predicates P on satisfiable instances. We show that under certain conditions on P and a ( 1 , s ) integrality gap instance of the P -CSP problem, it can be translated into a dictatorship vs. quasirandomness test with perfect completeness and soundness s + ϵ , for every constant ϵ > 0 . Compared to Ragahvendra (in: Proceedings of the fortieth annual ACM symposium on theory of computing (STOC), pp 245–254, 2008), we do not lose perfect completeness. This is particularly interesting as this test implies new hardness results on satisfiable constraint satisfaction problems, assuming the Rich 2-to-1 Games Conjecture by Braverman et al. (in: Lee JR (ed) Volume 185 of Leibniz international proceedings in informatics (LIPIcs), 27:1–27:20. Schloss Dagstuhl–Leibniz-Zentrum für Informatik, Dagstuhl, 2021b. https://drops.dagstuhl.de/opus/volltexte/2021/13566 ).Our result can be seen as the first step of a potentially long-term challenging program of characterizing optimal inapproximability of every satisfiable k -ary CSP. At the heart of the reduction is our main analytical lemma for a class of 3-ary predicates, which is a generalization of a lemma by Mossel (Geom Funct Anal 19(6):1713–1756, 2010). The lemma and a further generalization of it that we conjecture may be of independent interest.

Measurement of light-by-light scattering and the Breit-Wheeler process, and search for axion-like particles in ultraperipheral PbPb collisions at √sNN = 5.02 TeV

Fri, 01 Aug 2025 00:00:00 GMT

Measurement of light-by-light scattering and the Breit-Wheeler process, and search for axion-like particles in ultraperipheral PbPb collisions at √sNN = 5.02 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R.; Schwarz, D.; The CMS collaboration Measurements of light-by-light scattering (LbL, γγ → γγ) and the Breit-Wheeler process (BW, γγ → e+e−) are reported in ultraperipheral PbPb collisions at a centre-of-mass energy per nucleon pair of 5.02 TeV. The data sample, corresponding to an integrated luminosity of 1.7 nb−1, was collected by the CMS experiment at the CERN LHC in 2018. Events with an exclusively produced γγ or e+e− pair with invariant masses mγγ,ee > 5 GeV, along with other fiducial criteria, are selected. The measured BW fiducial production cross section, σfid(γγ → e+e−) = 263.5 ± 1.8(stat) ± 17.8(syst) μb, as well as the differential distributions for various kinematic observables, are in agreement with leading-order quantum electrodynamics predictions complemented with final-state photon radiation. The measured differential BW cross sections allow discrimination between different theoretical descriptions of the photon flux of the lead ion. In the LbL final state, 26 exclusive diphoton candidate events are observed compared with 12.0 ± 2.9 expected for the background. Combined with previous results, the observed significance of the LbL signal with respect to the background-only hypothesis is above five standard deviations. The measured fiducial LbL scattering cross section, σfid(γγ → γγ) = 107 ± 24(stat) ± 13(syst) nb, is in agreement with next- to-leading-order predictions. Limits on the production of axion-like particles coupled to photons are set over the mass range 5–100 GeV, including the most stringent limits to date in the range of 5–10 GeV.

The PLATO mission

Mon, 21 Apr 2025 00:00:00 GMT

The PLATO mission Rauer, Heike; Aerts, Conny; Cabrera, Juan; Deleuil, Magali; Erikson, Anders; Gizon, Laurent; Goupil, Mariejo; Heras, Ana; Walloschek, Thomas; Lorenzo-Alvarez, Jose; Marliani, Filippo; Martin-Garcia, César; Mas-Hesse, J. M.; O’Rourke, Laurence; Osborn, Hugh; Pagano, Isabella; Piotto, Giampaolo PLATO (PLAnetary Transits and Oscillations of stars) is ESA’s M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2R Earth ) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5%, 10%, 10% for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO‘s target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile towards the end of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

DisruptionBench and Complimentary New Models: Two Advancements in Machine Learning Driven Disruption Prediction

Sat, 24 May 2025 00:00:00 GMT

DisruptionBench and Complimentary New Models: Two Advancements in Machine Learning Driven Disruption Prediction Spangher, Lucas; Bonotto, Matteo; Arnold, William; Chayapathy, Dhruva; Gallingani, Tommaso; Spangher, Alexander; Cannarile, Francesco; Bigoni, Daniele; de Marchi, Eliana; Rea, Cristina Plasma disruptions remain a major obstacle to sustained commercial operation of tokamak-based fusion devices. Although machine learning (ML) methods have shown promise for predicting disruptions, their performance and generalizability suffer from a lack of common benchmarks and comprehensive multi-device evaluations. To address this, we present DisruptionBench, a new benchmarking platform designed to standardize how ML-driven disruption prediction systems are trained and evaluated on multi-machine data. DisruptionBench spans three devices - Alcator C-Mod, DIII-D, and EAST - and includes tasks of varying difficulty: zero-shot, few-shot, and many-shot training regimes to assess each model’s ability to transfer learned representations to new or data-limited machines. We evaluate four state-of-the-art ML architectures. Two are re-implementations of notable prior work: a random forest (Cristina Rea in PPCF 60:084008, 2018) and the Hybrid Deep Learner (HDL) (Zhu in NC 61: 026607, 2020). We also propose two new approaches tailored for disruption prediction: a transformer-based model inspired by GPT-2, capable of learning long-range temporal dependencies through self-attention, and a Continuous Convolutional Neural Network (CCNN) that leverages continuous kernels to capture subtle variations in plasma signals. Across the nine benchmarking tasks, the CCNN demonstrates consistently strong performance and achieves the highest overall Area Under the ROC Curve (AUC) in intra-machine tests (up to 0.97 on C-Mod). Nevertheless, the GPT-2-based approach and HDL can outperform CCNN in specific transfer scenarios, particularly when the test machine is underrepresented in training data. We further analyze the significance of memory length in capturing precursor phenomena, providing evidence that longer context windows can boost predictive accuracy.

From Crucible Steel to the Battlefield: Investigating a Unique Early Medieval Arrowhead from Anatolia

Fri, 06 Jun 2025 00:00:00 GMT

From Crucible Steel to the Battlefield: Investigating a Unique Early Medieval Arrowhead from Anatolia Güder, Ümit; Yavaş, Alptekin; Demirel Gökalp, Zeliha; Taşan, Cemal C.; Raabe, Dierk An arrowhead that was recovered during the excavations of the lower city church of Byzantine Stronghold Amorium in central Anatolia has been subjected to archaeometric analysis. Coins discovered in the same context date the arrowhead to the Middle Byzantine period (ninth–tenth century CE). It is a three-bladed arrowhead with a needle-type tang. Metallography (OM, SEM), SEM–EDS and EBSD techniques were used to examine samples taken from the head and the tang sections of the arrowhead. The arrowhead was determined to be made of manganese-alloyed crucible steel (0.4–1% Mn), shaped through warm forging cycles and selectively quenched and tempered to enhance its mechanical properties. The hardened head, likely designed for armor penetration, along with the potential watered surface pattern (firind), suggests that the arrowhead functioned both as a weapon and a symbol of prestige. Historical sources and archaeometallurgical evidence link the arrowhead to mounted Turkic archers in the Abbasid army during the 838 CE Sack of Amorium. This study of the arrowhead revealed it to be the earliest crucible steel find and the only example of such an object manufactured from crucible steel discovered in medieval Anatolian excavations.

Bayesian Methods for Magnetic and Mechanical Optimization of Superconducting Magnets for Fusion

Fri, 14 Mar 2025 00:00:00 GMT

Bayesian Methods for Magnetic and Mechanical Optimization of Superconducting Magnets for Fusion Packman, Sam; Riva, Nicolò; Rodriguez-Fernandez, Pablo Stellarators as compact fusion power sources have incredible potential to help combat climate change. However, the task of making that a reality faces many challenges. This work uses Bayesian optimization, (BO) which is a method that is well suited to black-box optimizations, to address the complicated optimization problem inherent by stellarator design. In particular it focuses on the mechanical optimization necessary to withstand the Lorentz forces generated by the magnetic coils. This work leverages surrogate models that are constructed to integrate as much information as possible from the available data points, significantly reducing the number of required model evaluations. It showcases the efficacy of Bayesian optimization as a versatile tool for enhancing both magneto-static and mechanical properties within stellarator winding packs. Employing a suite of Bayesian optimization algorithms, we iteratively refine 2D and 3D models of solenoid and stellarator configurations, and demonstrate a 15% increase in optimization speed using multi-fidelity Bayesian optimization. For fusion technology to progresses from experimental stages to commercial viability, precise and efficient design methodologies will be essential. By emphasizing its modularity and transferability, our approach lays the foundation for streamlining optimization processes, facilitating the integration of fusion power into a sustainable energy infrastructure.

Pseudo-Anosov representatives of stable Hamiltonian structures

Mon, 08 Sep 2025 00:00:00 GMT

Pseudo-Anosov representatives of stable Hamiltonian structures Zung, Jonathan A pseudo-Anosov homeomorphism of a surface is a canonical representative of its mapping class. Conditional on the foundations of symplectic field theory, we explain that a transitive pseudo-Anosov flow is similarly a canonical representative of its stable Hamiltonian class. It follows that there are finitely many pseudo-Anosov flows admitting positive Birkhoff sections on any given rational homology 3-sphere. This result has a purely topological consequence: any 3-manifold can be obtained in at most finitely many ways as p/q surgery on a fibered hyperbolic knot in S 3 for a slope p/q satisfying q ≥ 6 , p ≠ 0 , ± 1 , ± 2 mod q . The proof of the main theorem generalizes an argument of Barthelmé–Bowden–Mann.

Hindered segmental dynamics in associative protein hydrogels studied by neutron spin-echo spectroscopy

Wed, 26 Jul 2023 00:00:00 GMT

Hindered segmental dynamics in associative protein hydrogels studied by neutron spin-echo spectroscopy Rao, Ameya; Carrick, Brian R; Yao, Helen; Olsen, Bradley D Transient binding between associating macromolecules can cause qualitative changes to chain dynamics, including modes of conformational relaxation and diffusion, through tethering effects imparted by long-range connectivity. In this work, the role of binding on short-time segmental dynamics in associative polymer gels is investigated by neutron spin-echo (NSE) measurements on a class of model artificial coiled-coil proteins with a systematically varied architecture, probing timescales of 0.1–130 ns, and length scales close to the molecular radius of gyration. The results illustrate effects of transient cross-linking on chain dynamics on different timescales, manifested in changes in segmental relaxation behavior with variations in strand length, chain concentration, and sticker distribution (endblock- vs midblock-functionalized). In all gels, a short-time cooperative diffusion mode is seen over all wave vectors, analogous to a semidilute solution, with no transitions seen at any known structural length scale. However, the diffusion coefficients are found to decrease with increasing junction density across all gels, with the strand length and number of stickers per chain in each gel appearing to play a relatively minor role. The slowing of cooperative diffusion with junction density contrasts with classical predictions of a greater restoring force for fluctuation dissipation due to the increased elasticity, suggesting additional effects of the coiled-coil junctions such as an enhancement in local viscosity that slows dynamics. Notably, the relaxation rates for all gels can be rescaled by the interjunction spacing inferred from small-angle neutron scattering, where they collapse onto a master curve suggestive of self-similar dynamics even in networks with different strand lengths and chain architectures. On long timescales (but shorter than the junction exchange time), a slowing of network relaxation is observed, resulting in a nondecaying plateau in the spin-echo amplitude attributed to a freezing of chain dynamics due to tethering. A characteristic length scale corresponding to the extent of dynamic fluctuations is estimated for each gel, which appears to be smaller than the interjunction spacing but similar to the correlation blob size of the overlapping strands. The results indicate an important role of transient binding on molecular-scale dynamics in associative polymer gels, even on timescales shorter than the junction exchange time, in addition to its effects on long-range self-diffusion previously observed.

Techno-economic assessment of co-production of edible bioplastic and food supplements from Spirulina

Thu, 22 Jun 2023 00:00:00 GMT

Techno-economic assessment of co-production of edible bioplastic and food supplements from Spirulina Chalermthai, Bushra; Charoensuppanimit, Pongtorn; Nootong, Kasidit; Olsen, Bradley D; Assabumrungrat, Suttichai Large amount of plastic wastes harming the environment have raised concerns worldwide on finding alternatives to non-biodegradable plastics. Microalgae has been found as a potential source for bioplastic production, besides its more common application in the pharmaceutical and nutraceutical industry. In this study, the objective was to techno-economically evaluate the large-scale co-production of Spirulina powder as food supplements and edible bioplastic for food packaging. The scale of production was large enough to satisfy 1% of local (Thailand) plastic demand (i.e., approx. 1200 MT y−1), and 1% of the global Spirulina demand (approx. 1000 MT y−1) as food supplements. Results showed that the co-production of the Spirulina powder and bioplastic revealed an attractive venture with a payback time (PBT) as low as 2.6 y and ROI as high as 38.5%. This was because the revenues generated were as high as US$ 55.6 million y−1, despite high capital (US$ 55.7 million) and operating (US$ 34.9 million y−1) costs. Sensitivity analysis showed differences in the profitability based on variations of major parameters in the study, where the split ratio of biomass used for food supplement versus bioplastic production and the bioplastic’s selling price were found to be the most sensitive.

Counterfactual Worlds

Tue, 03 Jun 2025 00:00:00 GMT

Counterfactual Worlds Brast-McKie, Benjamin This paper extends Kit Fine’s (2012a, 2012b, 2017a, 2017b, 2017c) truthmaker framework to provide a novel task semantics for tensed counterfactual conditionals. Instead of taking possible worlds to be primitive elements in a model, possible worlds will be defined in terms of states, parthood, tasks, and times where the task relation encodes the possible transitions between states. Rather than invoking primitive relations for similarity or imposition, possible worlds will be compared at a time independent of that time’s past and future where the comparison will be carried out in modal and mereological terms. After reviewing motivations for this approach, I will provide the hyperintensional semantics for counterfactuals that is implemented in the model-checker software along with a unified logic for counterfactual, modal, and tense operators. I will then extend the language to include further tense operators in order to analyze forwards, backwards, and backtracking counterfactuals.

Tight mixed-integer optimization formulations for prescriptive trees

Thu, 29 May 2025 00:00:00 GMT

Tight mixed-integer optimization formulations for prescriptive trees Biggs, Max; Perakis, Georgia We focus on modeling the relationship between an input feature vector and the predicted outcome of a trained decision tree using mixed-integer optimization. This can be used in many practical applications where a decision tree or a tree ensemble is incorporated into an optimization problem to model the predicted outcomes of a decision. We propose novel tight mixed-integer optimization formulations for this problem. Existing formulations can be shown to have linear relaxations that have fractional extreme points, even for the simple case of modeling a single decision tree or a very large number of constraints, which leads to slow solve times in practice. A formulation we propose, based on a projected union of polyhedra approach, is ideal (i.e., the extreme points of the linear relaxation are integer when required) for a single decision tree. Although the formulation is generally not ideal for tree ensembles, it generally has fewer extreme points, leading to a faster time to solve. We also study formulations with a binary representation of the feature vector and present multiple approaches to tighten existing formulations. We show that fractional extreme points are removed when multiple splits are on the same feature. At an extreme, we prove that this results in an ideal formulation for a tree ensemble modeling a one-dimensional feature vector. Building on this result, we also show that these additional constraints result in significantly tighter linear relaxations when the feature vector is low dimensional.

Adaptive optimization for prediction with missing data

Mon, 24 Mar 2025 00:00:00 GMT

Adaptive optimization for prediction with missing data Bertsimas, Dimitris; Delarue, Arthur; Pauphilet, Jean When training predictive models on data with missing entries, the most widely used and versatile approach is a pipeline technique where we first impute missing entries and then compute predictions. In this paper, we view prediction with missing data as a two-stage adaptive optimization problem and propose a new class of models, adaptive linear regression models, where the regression coefficients adapt to the set of observed features. We show that some adaptive linear regression models are equivalent to learning an imputation rule and a downstream linear regression model simultaneously instead of sequentially. We leverage this joint-impute-then-regress interpretation to generalize our framework to non-linear models. In settings where data is strongly not missing at random, our methods achieve a 2–10% improvement in out-of-sample accuracy.

Designing Biodiversity Systems via Digital Kinships: Insights from Community Data Processes and Creative Practice

Mon, 16 Jun 2025 00:00:00 GMT

Designing Biodiversity Systems via Digital Kinships: Insights from Community Data Processes and Creative Practice Westerlaken, Michelle This study details how digital biodiversity data is used and gains meaning in local restoration projects, how these experiences contrast with large-scale innovation patterns, and what new design recommendations emerge from these insights. Digital innovations in biodiversity technologies are increasingly complex, fast-paced, and driven by technological capacities where data generation rather than biodiversity restoration risks becoming the primary goal. Focusing on a biodiversity restoration project with a living lab community in the Netherlands, this participatory research critically examines how plans for emerging technologies, such as biodiversity simulations and digital twins, contrast with local user relations to biodiversity data. Building on qualitative insights from six-months of fieldwork, a digital and physical data portal was designed to simulate ongoing technoscientific innovation and make their complex effects experientially available to users. Findings are brought directly in conversation with emerging technical features through four distinct themes with the aim to share user-insights and produce design recommendations for: environmental storytelling, prediction and future making, interactive dynamics, and simulation aesthetics. These themes articulate the community's preferences towards digital environments that support their nuanced, complex relationships with local biodiversity, suggesting a shift from top-down technocentric approaches to more community-driven and restoration-focused models. Based on this study, design recommendations are articulated for each of these four themes contributing detailed empirical and practice-oriented insights that propose how new biodiversity technologies can resonate more effectively with local biodiversity restoration efforts.

Asilomar Goes Underground: The Long Legacy of Recombinant DNA Hazard Debates for the Greater Boston Area Biotechnology Industry

Fri, 07 Mar 2025 00:00:00 GMT

Asilomar Goes Underground: The Long Legacy of Recombinant DNA Hazard Debates for the Greater Boston Area Biotechnology Industry Scheffler, Robin W. In 1975, a meeting on the potential hazards of recently invented recombinant DNA techniques was held at the Asilomar Conference Center in California. This meeting gave rise to a global debate over the safety and regulation of recombinant DNA (rDNA). In this paper, I use the historical development of recombinant DNA regulation in the Greater Boston Area—now home to the densest cluster of the biotechnology industry in the world—to provide a different interpretation of the legacies of Asilomar. While most accounts of Asilomar have considered its brief and dramatic impact on molecular biology on a national scale, an equally meaningful and overlooked impact is to be found in the development of regulations around recombinant DNA at the local level. Rather than hindering research, these events enabled the operations of the modern commercial biotechnology industry, which was founded on the promise of recombinant DNA. This approach highlights a different legacy of Asilomar, one which did not end with expert consensus that recombinant DNA was safe. Instead, attending to the material, infrastructural aspects of working with recombinant DNA in commercial settings reveals a wide range of communities involved in determining the social impacts of Asilomar—communities asking a broader set of questions about recombinant DNA than those originally posed in 1975.

A unified semantics for distributive and non-distributive universal quantifiers across languages

Wed, 09 Jul 2025 00:00:00 GMT

A unified semantics for distributive and non-distributive universal quantifiers across languages Haslinger, Nina; Hien, Alain N.; Rosina, Emil E.; Schmitt, Viola; Wurm, Valerie Universal quantifiers differ in whether they are restricted to distributive interpretations, like English every, or permit non-distributive interpretations, like English all. This interpretational difference is traditionally captured by positing two unrelated lexical entries for distributive and non-distributive quantification. But this lexical approach does not explain why distributivity correlates with number: cross-linguistically, distributive universal quantifiers typically take singular complements, while non-distributive quantifiers consistently take plural complements. We derive this correlation by proposing a single lexical meaning for the universal quantifier, which derives a non-distributive interpretation if the restrictor predicate is closed under sum, but a distributive interpretation if it is quantized. Support comes from languages in which the same lexical item expresses distributive or non-distributive quantification depending on the number of the complement. For languages like English that have different expressions for non-distributive and distributive quantification, we propose that the distributive forms contain an additional morphosyntactic element that is semantically restricted to combine with a predicate of atomic individuals. This is motivated by the fact that in several languages, the distributive form is structurally more complex than the non-distributive form and sometimes even contains it transparently. We further show that in such languages, there are empirical advantages to taking the choice between distributive and non-distributive quantifier forms to be driven by semantic properties of the restrictor predicate, rather than morphosyntactic number.

Passivization and composite A/Ā-movement in the Mandarin BEI-construction

Wed, 11 Jun 2025 00:00:00 GMT

Passivization and composite A/Ā-movement in the Mandarin BEI-construction Chen, Fulang The bei-construction in Mandarin is a well-studied construction known for exhibiting both passive-like properties and tough-movement-like properties (see e.g., Feng 1995, 2012; Ting 1995a, 1998; Huang 1999; Tang 2001; Huang et al. 2009; Bruening and Tran 2015; a.o.). In this paper, I argue for a novel analysis of the bei-construction in Mandarin as a passive construction where the passive head/bei hosts a composite probe [ϕ+Ā], which triggers composite A/Ā-movement, in the sense of Van Urk (2015). The subject in the bei-construction is derived via (successive-cyclic) composite A/Ā-movement, followed by a terminating step of A-movement, similar to Longenbaugh’s (2017) analysis of English tough-movement. Under the proposed analysis, the mixed A/Ā-properties associated with the bei-construction are direct consequences of composite A/Ā-movement (following Van Urk 2015; Longenbaugh 2017). The proposed analysis of the bei-construction accounts for two restrictions on long-distance dependencies in the bei-construction – a requirement that no overt, case-less NPs should intervene between the subject of bei and the gap in agent-less bei-constructions, and a subject/object contrast with respect to the possibility of crossing a finite clause boundary to become the subject of bei.

From concept to manufacturing: evaluating vision-language models for engineering design

Tue, 01 Jul 2025 00:00:00 GMT

From concept to manufacturing: evaluating vision-language models for engineering design Picard, Cyril; Edwards, Kristen M.; Doris, Anna C.; Man, Brandon; Giannone, Giorgio; Alam, Md F.; Ahmed, Faez Engineering design is undergoing a transformative shift with the advent of AI, marking a new era in how we approach product, system, and service planning. Large language models have demonstrated impressive capabilities in enabling this shift. Yet, with text as their only input modality, they cannot leverage the large body of visual artifacts that engineers have used for centuries and are accustomed to. This gap is addressed with the release of multimodal vision-language models (VLMs), such as GPT-4V, enabling AI to impact many more types of tasks. Our work presents a comprehensive evaluation of VLMs across a spectrum of engineering design tasks, categorized into four main areas: Conceptual Design, System-Level and Detailed Design, Manufacturing and Inspection, and Engineering Education Tasks. Specifically in this paper, we assess the capabilities of two VLMs, GPT-4V and LLaVA 1.6 34B, in design tasks such as sketch similarity analysis, CAD generation, topology optimization, manufacturability assessment, and engineering textbook problems. Through this structured evaluation, we not only explore VLMs’ proficiency in handling complex design challenges but also identify their limitations in complex engineering design applications. Our research establishes a foundation for future assessments of vision language models. It also contributes a set of benchmark testing datasets, with more than 1000 queries, for ongoing advancements and applications in this field.

Review of AI-assisted design of low-carbon cost-effective concrete toward carbon neutrality

Sat, 03 May 2025 00:00:00 GMT

Review of AI-assisted design of low-carbon cost-effective concrete toward carbon neutrality Mahjoubi, Soroush; Barhemat, Rojyar; Meng, Weina; Bao, Yi Decarbonizing concrete production is a critical step toward achieving carbon neutrality by 2050. This paper highlights the advancements in artificial intelligence-assisted design of low-carbon cost-effective concrete, focusing on integrating machine learning-based property prediction with multi-objective optimization. Data collection and processing techniques, such as automatic data extraction, artificial data generation, and anomaly detection, are first discussed to address the importance of dataset quality. Strategies that capture physicochemical information of ingredients, including by-product supplementary cementitious materials and recycled aggregates, are then examined to enhance model generalizability. Various machine learning models—from individual regression approaches to heterogeneous ensemble methods—are compared for their predictive accuracy and robustness. Methods for hyperparameter tuning, model evaluation, and interpretation to ensure reliable and interpretable predictions are reviewed. Design optimization approaches are then highlighted, ranging from grid/random searches to more sophisticated gradient-based and metaheuristic algorithms, aimed at minimizing carbon footprint, embodied energy, and cost. Future research avenues encompass (1) application-specific design frameworks that integrate critical objectives—mechanical performance, durability, fresh-state behavior, and time-dependent properties such as creep and shrinkage—tailored to specific structural and environmental requirements; (2) holistic design optimization that simultaneously refines mixture design and structural parameters; and (3) probabilistic approaches to systematically manage uncertainties in materials, structural performance, and loading conditions systematically.

Making the eyes of the state: algorithmic alienation and mundane creativity in Peruvian street-level bureaucrats

Sat, 15 Feb 2025 00:00:00 GMT

Making the eyes of the state: algorithmic alienation and mundane creativity in Peruvian street-level bureaucrats Cerna-Aragon, Diego; García, Luis The production of state legibility has been a prolific subject of study. However, most works have not paid much attention to the quotidian labor of the street-level bureaucrats that implement legibility projects at a local level. The aim of this article is to explore the implementation of a social registry system at a local level to understand how frontline workers make the population legible. Instead of taking legibility as an object of evaluation or critique, we pay close attention to the inner workings of bureaucracies at the instances in which the sociomaterial conditions of the population are translated into data. Drawing from qualitative research in Peruvian municipalities, we describe the operations of an algorithmic system that classifies the population for the distribution of welfare. We observed how under-resourced bureaucrats were constrained by regulations and technologies of the system. Paradoxically, to make the system work for their local realities, the bureaucrats had to bend the rules and find workarounds. From this perspective, the making of legibility looks less like a top-down exercise of bureaucratic compliance or a story of domination over the population. Instead, we find actors attempting to maintain a delicate balance between inadequate legal rules, scarce resources, and sociopolitical demands.

Waveform modelling for the Laser Interferometer Space Antenna

Thu, 30 Oct 2025 00:00:00 GMT

Waveform modelling for the Laser Interferometer Space Antenna Afshordi, Niayesh; Akçay, Sarp; Seoane, Pau A.; Antonelli, Andrea; Aurrekoetxea, Josu C.; Barack, Leor; Barausse, Enrico; Benkel, Robert; Bernard, Laura; Bernuzzi, Sebastiano; Berti, Emanuele; Bonetti, Matteo; Bonga, Béatrice LISA, the Laser Interferometer Space Antenna, will usher in a new era in gravitational-wave astronomy. As the first anticipated space-based gravitational-wave detector, it will expand our view to the millihertz gravitational-wave sky, where a spectacular variety of interesting new sources abound: from millions of ultra-compact binaries in our Galaxy, to mergers of massive black holes at cosmological distances; from the early inspirals of stellar-mass black holes that will ultimately venture into the ground-based detectors’ view to the death spiral of compact objects into massive black holes, and many sources in between. Central to realising LISA’s discovery potential are waveform models, the theoretical and phenomenological predictions of the pattern of gravitational waves that these sources emit. This White Paper is presented on behalf of the Waveform Working Group for the LISA Consortium. It provides a review of the current state of waveform models for LISA sources, and describes the significant challenges that must yet be overcome.

Systematic discovery of subcellular RNA patterns in the gut epithelium

Wed, 29 Oct 2025 00:00:00 GMT

Systematic discovery of subcellular RNA patterns in the gut epithelium Lee, Minkyoung; Acar, Ilhan E.; Eletto, Davide; Adivarahan, Srivathsan; Mhamedi, Farah; Handler, Kristina; Lee, Jihyun; Vinzoni, Elena G.; Aguilar, Gustavo Background Subcellular RNA localization is crucial for the spatio-temporal control of protein synthesis and underlies key processes during development, homeostasis, and disease. In epithelial cells, RNA can localize asymmetrically along the apico-basal axis. Yet, the localization of most transcripts as well as the diversity of patterns that they adopt remains unexplored. Results Here, we use APEX-seq for proximity labeling and MERFISH for spatial transcriptomics to map subcellular transcript localization in intestinal organoids and tissue from adult mice. Many transcripts present localization bias, often localizing in granular structures. We uncover intrinsic and environmental factors that influence the formation of these patterns. Additionally, we identify translation-dependent and -independent localization patterns and pinpoint the role of 3′ untranslated regions and RNA-binding proteins. Conclusions This subcellular RNA atlas presents a detailed resource for understanding intestinal physiology.

Identifying delayed human response to external risks: an econometric analysis of mobility change during a pandemic

Wed, 29 Oct 2025 00:00:00 GMT

Identifying delayed human response to external risks: an econometric analysis of mobility change during a pandemic Zhang, Gaofei; Osi, Ann; Ghaffarzadegan, Navid; Rahmandad, Hazhir; Xu, Ran Background Human behavioral responses to changes in risks are often delayed. Methods for estimating these delayed responses either rely on rigid assumptions about the delay distribution (e.g., Erlang distribution), producing a poor fit, or yield period-specific estimates (e.g., estimates from the Autoregressive Distributed Lag (ARDL) model) that are difficult to integrate into simulation models. We propose a hybrid ARDL–Erlang approach that yields an interpretable summary of behavioral responses suitable for incorporation into simulation models. Method We apply the ARDL–Erlang approach to estimate the effect of COVID-19 deaths on mobility across US counties from October 2020 to July 2021. A standard panel autoregressive distributed lag (ARDL) model first estimates the effect of past deaths and past mobility on current mobility. The ARDL model is then transformed into an Infinite Distributed Lag (IDL) model consisting of only past deaths. The coefficients of the past deaths are aggregated into an overall effect and fit to an Erlang distribution, summarized by average delay length and shape parameter. Results Our results show that on the national level, a one-standard-deviation permanent increase in weekly deaths per 100,000 population (log-transformed) is associated with a 0.46-standard-deviation decrease in human mobility in the long run, where the delay distribution follows a first-order Erlang distribution, and the average delay length is about 3.2 weeks. However, there is much heterogeneity across states, with first- to third-order Erlang delays and 2 to 18 weeks of average delay providing a theoretically cogent summary of how mobility followed changes in deaths during the first year and a half of the pandemic. Conclusion This study provides a novel approach to estimating delayed human responses to health risks using a hybrid ARDL-Erlang model. Our findings highlight significant variability in the impact and timing of responses across states, underscoring the need for tailored public health policies. This study can also serve as guidelines and an example for identifying delayed human behavior in other settings.

Integrating single-cell RNA-seq datasets with substantial batch effects

Thu, 30 Oct 2025 00:00:00 GMT

Integrating single-cell RNA-seq datasets with substantial batch effects Hrovatin, Karin; Moinfar, Amir Ali; Zappia, Luke; Parikh, Shrey; Lapuerta, Alejandro T.; Lengerich, Ben; Kellis, Manolis; Theis, Fabian J. Integration of single-cell RNA-sequencing (scRNA-seq) datasets is standard in scRNA-seq analysis. Nevertheless, current computational methods struggle to harmonize datasets across systems such as species, organoids and primary tissue, or different scRNA-seq protocols, including single-cell and single-nuclei. Conditional variational autoencoders (cVAE) are a popular integration method, however, existing strategies for stronger batch correction have limitations. Increasing the Kullback–Leibler divergence regularization does not improve integration and adversarial learning removes biological signals. Here, we propose sysVI, a cVAE-based method employing VampPrior and cycle-consistency constraints. We show that sysVI integrates across systems and improves biological signals for downstream interpretation of cell states and conditions.

High-throughput experimentation for discovery of biodegradable polyesters

Tue, 30 May 2023 00:00:00 GMT

High-throughput experimentation for discovery of biodegradable polyesters Fransen, Katharina A; Av-Ron, Sarah HM; Buchanan, Tess R; Walsh, Dylan J; Rota, Dechen T; Van Note, Lana; Olsen, Bradley D The consistent rise of plastic pollution has stimulated interest in the development of biodegradable plastics. However, the study of polymer biodegradation has historically been limited to a small number of polymers due to costly and slow standard methods for measuring degradation, slowing new material innovation. High-throughput polymer synthesis and a high-throughput polymer biodegradation method are developed and applied to generate a biodegradation dataset for 642 chemically distinct polyesters and polycarbonates. The biodegradation assay was based on the clear-zone technique, using automation to optically observe the degradation of suspended polymer particles under the action of a single Pseudomonas lemoignei bacterial colony. Biodegradability was found to depend strongly on aliphatic repeat unit length, with chains less than 15 carbons and short side chains improving biodegradability. Aromatic backbone groups were generally detrimental to biodegradability; however, ortho- and para-substituted benzene rings in the backbone were more likely to be degradable than metasubstituted rings. Additionally, backbone ether groups improved biodegradability. While other heteroatoms did not show a clear improvement in biodegradability, they did demonstrate increases in biodegradation rates. Machine learning (ML) models were leveraged to predict biodegradability on this large dataset with accuracies over 82% using only chemical structure descriptors.

Antigen-adjuvant interactions, stability, and immunogenicity profiles of a SARS-CoV-2 receptor-binding domain (RBD) antigen formulated with aluminum salt and CpG adjuvants

Mon, 06 Jun 2022 00:00:00 GMT

Antigen-adjuvant interactions, stability, and immunogenicity profiles of a SARS-CoV-2 receptor-binding domain (RBD) antigen formulated with aluminum salt and CpG adjuvants Bajoria, Sakshi; Kaur, Kawaljit; Kumru, Ozan S; Van Slyke, Greta; Doering, Jennifer; Novak, Hayley; Rodriguez Aponte, Sergio A; Dalvie, Neil C; Naranjo, Christopher A; Johnston, Ryan S; Silverman, Judith Maxwell; Kleanthous, Harry; Love, J Christopher; Mantis, Nicholas J; Joshi, Sangeeta B; Volkin, David B Low-cost, refrigerator-stable COVID-19 vaccines will facilitate global access and improve vaccine coverage in low- and middle-income countries. To this end, subunit-based approaches targeting the receptorbinding domain (RBD) of SARS-CoV-2 Spike protein remain attractive. Antibodies against RBD neutralize SARS-CoV-2 by blocking viral attachment to the host cell receptor, ACE2. Here, a yeast-produced recombinant RBD antigen (RBD-L452K-F490W or RBD-J) was formulated with various combinations of aluminum-salt (Alhydrogel®, AH; AdjuPhos®, AP) and CpG 1018 adjuvants. We assessed the effect of antigenadjuvant interactions on the stability and mouse immunogenicity of various RBD-J preparations. While RBD-J was 50% adsorbed to AH and <15% to AP, addition of CpG resulted in complete AH binding, yet no improvement in AP adsorption. ACE2 competition ELISA analyses of formulated RBD-J stored at varying temperatures (4, 25, 37°C) revealed that RBD-J was destabilized by AH, an effect exacerbated by CpG. DSC studies demonstrated that aluminum-salt and CpG adjuvants decrease the conformational stability of RBD-J and suggest a direct CpG-RBD-J interaction. Although AH+CpG-adjuvanted RBD-J was the least stable in vitro, the formulation was most potent at eliciting SARS-CoV-2 pseudovirus neutralizing antibodies in mice. In contrast, RBD-J formulated with AP+CpG showed minimal antigen-adjuvant interactions, a better stability profile, but suboptimal immune responses. Interestingly, the loss of in vivo potency associated with heat-stressed RBD-J formulated with AH+CpG after one dose was abrogated by a booster. Our findings highlight the importance of elucidating the key interrelationships between antigen-adjuvant interactions, storage stability, and in vivo performance to enable successful formulation development of stable and efficacious subunit vaccines.

Synthetic Collagen Hydrogels through Symmetric Self‐Assembly of Small Peptides

Thu, 23 Nov 2023 00:00:00 GMT

Synthetic Collagen Hydrogels through Symmetric Self‐Assembly of Small Peptides Tanrikulu, I Caglar; Dang, Lianna; Nelavelli, Lekha; Ellison, Aubrey J; Olsen, Bradley D; Jin, Song; Raines, Ronald T Animal‐sourced hydrogels, such as collagen, are widely used as extracellular‐matrix (ECM) mimics in tissue engineering but are plagued with problems of reproducibility, immunogenicity, and contamination. Synthetic, chemically defined hydrogels can avoid such issues. Despite the abundance of collagen in the ECM, synthetic collagen hydrogels are extremely rare due to design challenges brought on by the triple‐helical structure of collagen. Sticky‐ended symmetric self‐assembly (SESSA) overcomes these challenges by maximizing interactions between the strands of the triple helix, allowing the assembly of collagen‐mimetic peptides (CMPs) into robust synthetic collagen nanofibers. This optimization, however, also minimizes interfiber contacts. In this work, symmetric association states for the SESSA of short CMPs to probe their increased propensity for interfiber association are modelled. It is found that 33‐residue CMPs not only self‐assemble through sticky ends, but also form hydrogels. These self‐assemblies behave with remarkable consistency across multiple scales and present a clear link between their triple‐helical architecture and the properties of their hydrogels. The results show that SESSA is an effective and robust design methodology that enables the rational design of synthetic collagen hydrogels.

The BostonWalks study: a longitudinal travel survey using smartphone tracking

Sat, 28 Jun 2025 00:00:00 GMT

The BostonWalks study: a longitudinal travel survey using smartphone tracking Meister, Adrian; Bashan, Nail F.; Basu, Rounaq; Shen, Xianglu; Wang, Ryan Q.; Sevtsuk, Andres This paper introduces the BostonWalks (BWS) study, detailing its methodology, the resulting dataset, and an initial analysis. The BWS study is a smartphone-based GNSS-tracking study in the Boston metropolitan area, designed to generate an up-to-date dataset on travel behavior, with a particular focus on non-auto travel behavior and its representativeness across all population segments. The dataset encompasses approximately 155,000 trips from 990 participants, making it one of the most extensive datasets of its kind in North America. It includes both raw trajectory data and comprehensive socio-demographic information about participants. The paper outlines the survey methodology, including the technical infrastructure, recruitment strategy, and data processing techniques. A comparison of the socio-demographic and travel behavior characteristics of BWS participants with those from the National Household Travel Survey is provided. Lastly, the paper highlights the richness of the data through correlation and cluster analysis.

Diverging global incidence trends of early-onset cancers: comparisons with incidence trends of later-onset cancers and mortality trends of early-onset cancers

Fri, 14 Nov 2025 00:00:00 GMT

Diverging global incidence trends of early-onset cancers: comparisons with incidence trends of later-onset cancers and mortality trends of early-onset cancers Terashima, Miyu; Nakayama, Kota; Shirai, Sora; Ugai, Satoko; Lee, Hwa-Young; Matsui, Haruna; Mizuno, Hiroki; Tanaka, Shiori; Song, Minkyo; Sasamoto, Naoko; Kawachi, Ichiro; Giovannucci, Edward L.; Ugai, Tomotaka Background The global increase in the incidence of early-onset cancers (defined as cancers diagnosed at 20–49 years old) is a serious public health problem. We investigated 1) whether the incidence trend of early-onset cancers differs from that of later-onset cancers and 2) whether both the incidence and mortality of early-onset cancers have increased concurrently. Methods We utilized age-standardized incidence and mortality rates for early-onset and later-onset cancers diagnosed between 2000 and 2017 from the Cancer Incidence in Five Continents and World Health Organization (WHO) mortality databases. The national obesity prevalence among adults aged 20–49 years was obtained from the National Clinical Database. Using joinpoint regression models, we calculated average annual percentage changes (AAPCs) for cancer incidence and mortality by cancer types and countries. We additionally conducted human development index (HDI)-stratified analyses and assessed the correlation between the obesity prevalence in younger populations and early-onset cancer incidence by country. To investigate the more recent trend of early-onset cancer mortality, we extended our mortality analysis after 2017 for cancer types and countries with statistically significant positive AAPCs in both incidence and mortality of early-onset cancers between 2000 and 2017. Results Our analysis showed that 10 early-onset cancer types (thyroid cancer, breast cancer, melanoma, uterine cancer, colorectal cancer, kidney cancer, cervical cancer, pancreatic cancer, multiple myeloma, Hodgkin lymphoma) in females and 7 early-onset cancer types (thyroid cancer, kidney cancer, testis cancer, prostate cancer, colorectal cancer, melanoma, leukemia) in males had statistically significant positive AAPCs in at least 10 countries. Among these, the following early-onset cancer types had significantly higher AAPCs than later-onset cancer types in females: colorectal cancer (6 countries; AAPC range: 1.8–3.8%), cervical cancer (6 countries; AAPC range: 1.2–3.3%), pancreatic cancer (5 countries; AAPC range: 2.3–13.0%), and multiple myeloma (5 countries; AAPC range: 3.1–9.8%); in males: prostate cancer (12 countries; AAPC range: 3.9–18.4%), colorectal cancer (8 countries; AAPC range: 1.8–3.2%), and kidney cancer (6 countries; AAPC range: 2.0–6.0%). We observed statistically significant positive AAPCs in both the incidence and mortality of the following early-onset cancer types: uterine cancer (5 countries) and colorectal cancer (3 countries in females and 5 countries in males). The steeper increases in early-onset cancers compared with later-onset cancers were mainly observed in the very high-HDI country group, including early-onset colorectal cancer (AAPC = 2.4%, 95% CI 2.1–2.6 in females; AAPC = 2.0%, 95% CI 1.7–2.4 in males) to later-onset colorectal cancer (AAPC = −0.1%, 95% CI −0.2 to 0 in females; AAPC = −0.2%, 95% CI −0.3 to 0 in males). We observed strong positive correlations between the increasing obesity prevalence and the rising incidence of early-onset obesity-related cancers in several countries, including Australia (7 cancer types), United Kingdom (7 cancer types), Canada (7 cancer types), Republic of Korea (7 cancer types), and USA (6 cancer types) in females and United Kingdom (7 cancer types), Canada (6 cancer types), Australia (5 cancer types), Sweden (5 cancer types), and Republic of Korea (4 cancer types) in males. Although we did not observe an apparent spike after 2017 in many countries, we observed continued increases in the mortality of certain cancer types, such as uterine cancer (Japan, Republic of Korea, United Kingdom, USA, and Ecuador) in females and colorectal cancer (Argentina, Canada, United Kingdom, and USA) in males. Conclusions The increase in many early-onset cancer types was significantly higher than that of later-onset cancers, and the incidence and mortality of certain early-onset cancer types (such as colorectal cancer) increased simultaneously. Our study highlights global differences in cancer incidence and mortality trends of early-onset and later-onset cancers.

Generalizable MRI normative modelling to detect age-inappropriate neurodegeneration

Wed, 12 Nov 2025 00:00:00 GMT

Generalizable MRI normative modelling to detect age-inappropriate neurodegeneration Parker, Thomas D.; Bethlehem, Richard A. I.; Seidlitz, Jakob; White, Simon R.; David, Michael C. B.; Kolanko, Magdalena A.; Bernstock, Joshua D.; Dorfschmidt, Lena; Bourke, Niall; Gailly de Taurines, Anastasia; Hain, Jessica A.; Del Giovane, Martina; Graham, Neil S. N. Background Determining whether MRI brain scans demonstrate atrophy that is beyond “normal for age” is challenging. Automated measurements of structural metrics in individual brain regions have shown promise as biomarkers of neurodegeneration, yet widely available reference standards that aid interpretation at the individual level are lacking. Normative modelling, enabling standardized “brain charts”, represents a significant step in addressing this challenge by generating individualized age- and sex- adjusted centile scores derived from large, aggregated datasets for MRI-derived quantitative metrics. Methods Using normative data from 56,173 participants across the life course, we have developed regional cortical thickness and amygdala/hippocampal volume brain charts (adjusted for total intracranial volume) that can be applied at the individual level. At the group level, we investigate whether regional centile scores relate to cognitive performance (mini-mental state examination) and discriminate individuals with neuropathological evidence of Alzheimer’s disease (n = 351) from propensity-matched controls from the National Alzheimer's Coordinating Center (NACC) dataset. In addition, we explored the relationships between disease stage, cognition, regional tau deposition and regional centile scores in amyloid-β-PET-positive individuals with Alzheimer’s disease dementia (n = 39) and mild cognitive impairment (n = 71) from the Alzheimer’s Disease Neuroimaging Initiative-3 (ADNI-3). We then extended this approach to phenotypes of frontotemporal lobar degeneration using the Neuroimaging in Frontotemporal Dementia dataset (n = 113). Results We demonstrate BrainChart’s application to illustrative individual cases. At the group level, we show that in Alzheimer’s disease, regional centile scores from brain charting predicted cognitive performance, temporal lobe tau PET tracer uptake and discriminated disease groups from propensity matched cognitively normal controls in independent cohorts. Distinct patterns of age-inappropriate cortical atrophy were also evident in different clinical phenotypes of frontotemporal lobar degeneration from the Neuroimaging in Frontotemporal Dementia dataset. Conclusions Regional centile scores derived from an extensive normative dataset represent a generalizable method for objectively identifying atrophy in neurodegenerative diseases and can be applied to determine neurodegenerative atrophy at the individual level.

Inclusive B-meson flavour-tagging algorithm at LHCb

Mon, 10 Nov 2025 00:00:00 GMT

Inclusive B-meson flavour-tagging algorithm at LHCb Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. A new algorithm is developed to identify the flavour of neutral B mesons at production in pp collisions by utilising all tracks from the hadronisation process. The algorithm is calibrated separately for B0 and B s 0 mesons using B0 → J/ψK+π− and B s 0 → D s − π + decays from pp collision data collected by the LHCb experiment at a centre-of-mass energy of 13 TeV. This new algorithm improves the tagging power by 35% for B0 mesons and 20% for B s 0 mesons when compared to the combined performance of the existing LHCb flavour-tagging algorithms.

Analytical benchmark problems and methodological framework for the assessment and comparison of multifidelity optimization methods

Mon, 10 Nov 2025 00:00:00 GMT

Analytical benchmark problems and methodological framework for the assessment and comparison of multifidelity optimization methods Mainini, Laura; Serani, Andrea; Pehlivan-Solak, Hayriye; Di Fiore, Francesco; Rumpfkeil, Markus P.; Minisci, Edmondo; Quagliarella, Domenico; Yildiz, Sihmehmet; Ficini, Simone; Pellegrini, Riccardo; Thelen, Andrew; Bryson, Dean; Nikbay, Melike; Diez, Matteo; Beran, Philip S. As engineering systems increase in complexity and performance demands intensify, Multidisciplinary Design Optimization (MDO) methodologies are becoming essential for integrating models from multiple disciplines to optimize complex multi-physics systems. Within this context, major challenges remain in selecting appropriate disciplinary fidelity levels, and how to couple them effectively. Multifidelity methods offer a promising path forward by strategically combining information sources of varying fidelity - whether computational or experimental - to enable efficient and scalable design exploration and optimization. Despite the development of numerous multifidelity methods, their comparative performance remains difficult to assess due to the absence of standardized benchmark frameworks capable of evaluating performance across diverse optimization tasks. To address this gap, this paper introduces a comprehensive benchmarking framework that includes: (i) a suite of analytical benchmark optimization problems designed to stress-test and validate multifidelity methods; (ii) a set of assessment metrics for quantifying and comparing performance over measurable objectives; and (iii) the classification, evaluation, and comparison of several families of multifidelity optimization methods and frameworks using the proposed benchmarks to identify their respective strengths and weaknesses in real-world scenarios. The proposed benchmark problems are analytically defined functions carefully selected to capture mathematical challenges commonly encountered in real-world applications, including high dimensionality, multimodality, discontinuities, and noise. Their closed-form nature ensures computational efficiency, high reproducibility, and a clear separation of algorithmic behavior from numerical artifacts. The accompanying performance metrics support the systematic evaluation of multifidelity methods, measuring both optimization effectiveness and global approximation accuracy. By providing a rigorous, reproducible, and accessible benchmarking framework, this work aims to enable the broader community to understand, compare, and advance multifidelity optimization methods for complex problems in science and engineering.

Embodiment, Relationships, and Sexuality: An Ethical Analysis of Extended Reality Technologies

Fri, 14 Nov 2025 00:00:00 GMT

Embodiment, Relationships, and Sexuality: An Ethical Analysis of Extended Reality Technologies Ramirez, Erick J.; Clark, Laura; Campbell, Sydney; Dreiman, Julian; Clay, Dorian; Gupta, Raghav; Jennett, Shelby Abstract Communication technologies change the way we relate to each other and ourselves. In this essay we analyze the effects that extended reality (XR) technologies are likely to have on conceptions of the self, romantic relationships, and other associated concepts like sexual orientation. While these technologies are in their infancy, key psychological and philosophical concepts are already being explored. We begin by defining extended reality and the family of technologies that make it possible. We pay special attention to the way these immersive technologies ground the experiences of presence which can become virtually real. These experiences provide a useful framework for understanding the phenomena of XR embodiment. XR embodiment, the experience of one’s self as embodied in XR, opens up the possibility of blended physical and digital narrative selves which form the basis of new forms of relationships. In a future where XR is incorporated into the basic social and political structures of society, XR embodiment and virtually real experiences challenge normative concepts like sex and sexual orientation. Contemporary conceptions of the self, sex, consent, and love emerged in purely physical contexts to help us navigate the limitations of physical embodiment. XR embodiment requires a new ethical framework to make room for these possibilities. We end the paper by assessing ethical risks XR embodiment can introduce for XR developers, and researchers.

IsoDAR@Yemilab: Preliminary design report—volume II (beam transport, neutrino source, and shielding)

Mon, 10 Nov 2025 00:00:00 GMT

IsoDAR@Yemilab: Preliminary design report—volume II (beam transport, neutrino source, and shielding) Spitz, Joshua; Alonso, Jose R.; Ameel, Jon; Barlow, Roger; Bartoszek, Larry; Bungau, Adriana; Shaevitz, Michael H.; Voirin, Erik A.; Winklehner, Daniel; Conrad, Janet M.; Engebretson, Samuel J.; Moon, Jarrett; Winkler, Eleanor; Adelmann, Andreas; Axani, Spencer N.; Barletta, William A.; Calabretta, Luciano; Calvo, Pedro; Chan, Andrew; Karagiorgi, Georgia This Preliminary Design Report (PDR) describes the IsoDAR electron-antineutrino source in two volumes which are mostly site-independent and describe the cyclotron driver providing a 60 MeV, 10 mA proton beam (Volume I); and the Medium Energy Beam Transport (MEBT) line and target (this Volume). The IsoDAR driver and target will produce about 1.15 · 10 23 electron-antineutrinos over 5 calendar years. Paired with a kton-scale liquid scintillator detector, this will enable a broad particle physics program including searches for new symmetries, new interactions and new particles. Here in Volume II, we describe the Medium Energy Beam Transport line, the antineutrino source beam-target and surrounding sleeve, shielding, and plans for monitoring and installation.

On Nontrivial Winning and Losing Parameters of Schmidt Games

Fri, 14 Nov 2025 00:00:00 GMT

On Nontrivial Winning and Losing Parameters of Schmidt Games Neckrasov, Vasiliy; Zhan, Eric In this paper we study the classical Schmidt game on two families of sets: one related to frequencies of digits in base-2 expansions, and one connected to the set of the badly approximable numbers. Namely, we describe some nontrivial winning and losing parameters ( α , β ) for these sets.

International bureaucrats under transparency: The case of the WTO TRIPS Council

Tue, 11 Nov 2025 00:00:00 GMT

International bureaucrats under transparency: The case of the WTO TRIPS Council Park, Sojun; Kim, Minju How does transparency affect the behavior of international bureaucrats tasked with facilitating negotiations? Existing theories offer opposing expectations—greater transparency might induce international bureaucrats to engage more with contentious issues that matter to the public or lead them to avoid those issues whenever possible. We assess these competing perspectives by analyzing the World Trade Organization (WTO)’s 2002 document de-restriction reform that enhanced transparency to the public. Specifically, we examine how prompt public disclosure of documents shapes the way the WTO Secretariat writes reports about the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS). Using network statistics to estimate the state preference distributions on key topics, we find that, after the reform, the WTO Secretariat is more likely to issue reports on polarized topics in negotiations, using accountability-enhancing words. Our analysis at the country-year level shows that the reform led to greater national newspaper coverage of the WTO TRIPS, which in turn raised public awareness. The results suggest that transparency could empower international bureaucrats to tackle divisive issues in times of member-state gridlock.

Prediction of Large Events in Directed Sandpiles

Sat, 15 Nov 2025 00:00:00 GMT

Prediction of Large Events in Directed Sandpiles Shah, Dhruv The degree of predictability of large avalanche events in the directed sandpile model is studied. This degree is defined in terms of how successfully a strategy can predict such events, as compared to a random guess. A waiting time based prediction strategy which exploits the local anticorrelation of large events is discussed. With this strategy we show analytically and numerically that large events are predictable, and that this predictability persists in the thermodynamic limit. We introduce another strategy which predicts large avalanches in the future based on the present excess density in the sandpile. We obtain the exact conditional probabilities for large events given an excess density, and use this to determine the exact form of the ROC predictability curves. We show that for this strategy, the model is predictable only for finite lattice sizes, and unpredictable in the thermodynamic limit. This behaviour is to be contrasted with previously established numerical studies carried out for Manna sandpiles.

What are the most informative data points for predicting extreme events?

Mon, 22 Sep 2025 00:00:00 GMT

What are the most informative data points for predicting extreme events? Champenois, Bianca; Sapsis, Themistoklis P. The growing availability of large datasets that describe complex dynamical systems, such as climate models and turbulence simulations, has made machine learning an increasingly popular tool for modeling and analysis, but the inherent low representation of extreme events poses a major challenge for model accuracy in the tails of the distribution. This raises a fundamental question: Given a large dataset, which data points should we use to train machine learning models that effectively learn extremes? To address this question, we study a likelihood-weighted active data selection framework that identifies the most informative data points for model training. The framework improves predictions of extreme values of a target observable, scales to high-dimensional systems, and is model-agnostic. Unlike traditional active learning, which assumes the ability to query new data, our method is designed for problems where the dataset is fixed but vast, focusing on selection rather than acquisition. Points are scored using a likelihood-weighted uncertainty sampling criterion that prioritizes samples expected to reduce model uncertainty and improve predictions in the tails of the distribution for systems with non-Gaussian statistics. When applied to a machine learning climate model with input dimensionality on the order of tens of thousands, we find that the likelihood-weighted active data selection algorithm most accurately captures the statistics of extreme events using only a fraction of the original dataset. We also introduce analysis techniques to further interpret the optimally selected points. Looking ahead, the approach can serve as a compression algorithm that preserves information associated with extreme events in vast datasets.

Coclique level structure for stochastic chemical reaction networks

Mon, 10 Nov 2025 00:00:00 GMT

Coclique level structure for stochastic chemical reaction networks Bruno, Simone; Fu, Yi; Campos, Felipe A.; Del Vecchio, Domitilla; Williams, Ruth J. Continuous time Markov chains are commonly used as models for the stochastic behavior of chemical reaction networks. More precisely, these Stochastic Chemical Reaction Networks (SCRNs) are frequently used to gain a mechanistic understanding of how chemical reaction rate parameters impact the stochastic behavior of these systems. One property of interest is mean first passage times (MFPTs) between states. However, deriving explicit formulas for MFPTs can be highly complex. In order to address this problem, we first introduce the concept of $$coclique\, level\, structure$$ and develop theorems to determine whether certain SCRNs have this feature by studying associated graphs. Additionally, we develop an algorithm to identify, under specific assumptions, all possible coclique level structures associated with a given SCRN. Finally, we demonstrate how the presence of such a structure in a SCRN allows us to derive closed form formulas for both upper and lower bounds for the MFPTs. Our methods can be applied to SCRNs taking values in a generic finite state space and can also be applied to models with non-mass-action kinetics. We illustrate our results with examples from the biological areas of epigenetics, neurobiology and ecology.

The Psyche Light Elements Investigation

Tue, 11 Nov 2025 00:00:00 GMT

The Psyche Light Elements Investigation Prettyman, Thomas H.; Mittlefehldt, David W.; Asphaug, Erik I.; Binzel, Richard P.; Courville, Samuel W.; Elkins-Tanton, Linda T.; Lawrence, David J.; Marchi, Simone; Merayo, José M. G.; McCoy, Timothy J.; Weiss, Benjamin P. Light elements, such as C, S, Si, O, C, and H, are thought to be present in Earth’s liquid-Fe outer core. These elements lower melting temperatures, thereby allowing the core to remain in liquid state at high pressure and influencing magnetic and geodynamic processes. However, the identity and abundance of the light elements in the cores of terrestrial planets and how they were delivered to these cores is not well known. The NASA Psyche mission will travel to and explore (16) Psyche, which may be the metal-rich core of a differentiated planetesimal exposed by collisional stripping. If so, the Psyche mission could provide a direct assessment of the light element content of an asteroidal core, allowing comparisons to the inferred composition of planetary cores and the parent bodies of the magmatic iron group meteorites. In particular, Earth’s high-pressure core formed gradually (over ∼100 Myr), in a multistage process, under increasingly oxidizing conditions, whereas the cores of planetesimals formed quickly (within 10 Myr) at low pressure, likely in chemical equilibrium with their mantles. The trace element systematics and mineral composition of magmatic iron meteorites indicate the presence of C, P, and S in planetesimal cores prior to solidification. Such elements would have played a role in core dynamics, including dynamo generation. Their low solubility combined with the immiscibility of their mineral precipitates would have resulted in their separation from Fe upon crystallization and their eruption onto the surface of a stripped core (via ferrovolcanism). The Psyche spacecraft will detect their elemental, mineral, and magnetic signatures with the payload instruments, which include a Gamma Ray and Neutron Spectrometer, a Multispectral Imager, and a Magnetometer. Additional constraints on interior composition and processes influenced by light elements will be provided by Psyche’s gravity and geomorphology investigations. We provide a brief introduction to the topic of light elements along with prospects for (16) Psyche. While we emphasize core formation processes, we also consider other possibilities for the origin and evolution of this metal-rich body.

A double exponential chirp waveform for noisy rheology

Tue, 23 Sep 2025 00:00:00 GMT

A double exponential chirp waveform for noisy rheology Waeterloos, Jarno L.; McKinley, Gareth H.; Clasen, Christian In the search for faster rheometrical measurements techniques for fast time-evolving systems, optimally windowed chirps (OWCh) have recently been proposed for the determination of the complex modulus. However, such chirps are prone to artefacts at high frequencies due to fact that the input power is distributed over a range of frequencies leading to reduced signal-to-noise ratios in noisy conditions. The Tukey window which modulates the amplitude of the excitation disturbance and which is required to avoid spectral leakage directly reduces the signal-to-noise ratio at the edges of the signal leading to a divergence of the measured moduli at high frequencies. A new double exponential chirp (DEC) signal is proposed to overcome these limitations. Its capabilities are demonstrated with orthogonal superposition rheometry as an example of a demanding high-noise environment. The S-shaped time-frequency history of the new chirp signal redistributes the input power over the frequency spectrum. Numerical simulations using the Maxwell and Giesekus models, along with orthogonal superposition measurements on wormlike micellar fluids, demonstrate the effectiveness of the DEC waveform. Parameter optimization with the Giesekus model identifies the ideal input configurations for achieving a maximum signal-to-noise ratio during rheological measurements.

Generative BigSMILES: an extension for polymer informatics, computer simulations & ML/AI

Fri, 17 Nov 2023 00:00:00 GMT

Generative BigSMILES: an extension for polymer informatics, computer simulations & ML/AI Schneider, Ludwig; Walsh, Dylan; Olsen, Bradley; de Pablo, Juan The BigSMILES notation, a concise tool for polymer ensemble representation, is augmented here by introducing an enhanced version called generative BigSMILES. G-BigSMILES is designed for generative workflows, and is complemented by tailored software tools for ease of use. This extension integrates additional data, including reactivity ratios (or connection probabilities among repeat units), molecular weight distributions, and ensemble size. An algorithm, interpretable as a generative graph is devised that utilizes these data, enabling molecule generation from defined polymer ensembles. Consequently, the G-BigSMILES notation allows for efficient specification of complex molecular ensembles via a streamlined line notation, thereby providing a foundational tool for automated polymeric materials design. In addition, the graph interpretation of the G-BigSMILES notation sets the stage for robust machine learning methods capable of encapsulating intricate polymeric ensembles. The combination of G-BigSMILES with advanced machine learning techniques will facilitate straightforward property determination and in silico polymeric material synthesis automation. This integration has the potential to significantly accelerate materials design processes and advance the field of polymer science.

Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover’s Distance

Wed, 14 Feb 2024 00:00:00 GMT

Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover’s Distance Shi, Jiale; Walsh, Dylan; Zou, Weizhong; Rebello, Nathan J; Deagen, Michael E; Fransen, Katharina A; Gao, Xian; Olsen, Bradley D; Audus, Debra J Synthetic polymers, in contrast to small molecules and deterministic biomacromolecules, are typically ensembles composed of polymer chains with varying numbers, lengths, sequences, chemistry, and topologies. While numerous approaches exist for measuring pairwise similarity among small molecules and sequence-defined biomacromolecules, accurately determining the pairwise similarity between two polymer ensembles remains challenging. This work proposes the earth mover's distance (EMD) metric to calculate the pairwise similarity score between two polymer ensembles. EMD offers a greater resolution of chemical differences between polymer ensembles than the averaging method and provides a quantitative numeric value representing the pairwise similarity between polymer ensembles in alignment with chemical intuition. The EMD approach for assessing polymer similarity enhances the development of accurate chemical search algorithms within polymer databases and can improve machine learning techniques for polymer design, optimization, and property prediction.

Engineered selective biotoxin‐binding hydrogels for toxin sequestration

Fri, 22 Mar 2024 00:00:00 GMT

Engineered selective biotoxin‐binding hydrogels for toxin sequestration Morris, Melody A; Yang, Yun Jung; Mai, Danielle J; Olsen, Bradley D The development of synthetic selective membranes that separate materials of similar sizes, charges, and/or polarities remains a difficult challenge, and looking towards biology provides inspiration for new designs. In this work, a series of cholera toxin binding peptides (CTBPs) are identified, spanning a range of binding inhibitions, and integrated into chemically cross‐linked cholera toxin binding gels (CTBGs) via thiol‐Michael polycondensation reactions. All gels demonstrate rheological profiles consistent with elastic solids. The CTBGs are probed via small‐angle neutron scattering and exhibit a correlation length, ξ, smaller than most proteins (1.3–2.5 nm). Thus, an effective entropic mesh is formed to block non‐targeted proteins. However, the CTBGs have a dynamic mesh size, Ξ, that is larger than cholera toxin (CT) to allow the transport of target proteins. The CTBGs with the highest binding inhibitions both show high selectivity and permeation of CT, rejecting all other tested proteins. In total, two new highly selective CTBGs are synthesized and validated for use in cholera toxin remediation. Together, this platform demonstrates the wide applicability of selectively‐diffusive materials for difficult separations.

Accelerated small angle neutron scattering algorithms for polymeric materials

Fri, 10 Oct 2025 00:00:00 GMT

Accelerated small angle neutron scattering algorithms for polymeric materials Dai, Kexin; Olsen, Bradley D Small-angle neutron scattering (SANS) is an extremely powerful technique for characterizing a wide variety of soft, biological, magnetic, and quantum materials, but it is often throughput-limited. This work proposes an algorithm to accelerate small angle neutron scattering (SANS) experiments by estimating the minimum number of counts to perform parameter estimation and model differentiation tasks to a specified level of certainty. Three classes of model polymer materials were examined and analyzed, and time slices of SANS data were used to model a reduced number of counts. The scattering data with reduced numbers of counts were fitted to SANS model functions to perform parameter estimation and model differentiation tasks. For parameter estimation, estimators accurate to within 5–10% of the full count estimator can be produced with only 1–50% of the full counts depending upon the sample and parameter of interest. In order to project parameter uncertainties at lower number of counts prior to the completion of experiments, it is crucial to have a robust error quantification method that reflects the true uncertainty associated with each parameter. Uncertainties from Monte Carlo (MC) bootstrapping are shown to in general overestimate the error from fitting many experimental replicates. For most parameter estimation techniques, the weighted least squares estimator is unbiased; however, certain models yield biased estimators. To differentiate between models, both the Akaike information criterion (AIC) and Bayesian information criterion (BIC) can be used, and with either criterion, reduced numbers of counts can still identify the best model for our samples from a group of related candidate models for each material. The proposed algorithm can help SANS users optimize valuable beamtime and accelerate the use of SANS for structural characterization of libraries of materials while obtaining reasonable parameter estimation and model differentiation when scattering models are available.

Comparative study of conventional and process intensification by reactive distillation designs for glycerol carbonate production from glycerol and diethyl carbonate

Sun, 12 Jan 2025 00:00:00 GMT

Comparative study of conventional and process intensification by reactive distillation designs for glycerol carbonate production from glycerol and diethyl carbonate Chalermthai, Bushra; Sriharuethai, Chayanin; Olsen, Bradley D; Ngaosuwan, Kanokwan; Soottitantawat, Apinan; Assabumrungrat, Suttichai; Charoensuppanimit, Pongtorn Glycerol carbonate (GC) can be produced from glycerol (GL), a low-value byproduct in the biodiesel industry. In this work, continuous processes of GC production via transesterification from crude GL and diethyl carbonate (DEC) were developed using Aspen Plus. Two cases were considered, and their process performances were compared. In Case I, a conventional design consisted of a continuously stirred tank reactor for the reaction section and a distillation column for the purification section. In Case II, a process intensification design consisted of a reactive distillation column that could accommodate both reaction and purification within a single column. In both cases, the process optimizations were carried out by connecting the process models in Aspen Plus to MATLAB, using the Genetic Algorithm as the optimizer. The results showed that Case II was superior to Case I in terms of energy utilization, CO2 emissions, and economics with the specific energy consumption of 1.92 kWh/kg of diethyl carbonate, % internal rate of return of 274, payback period of 1.44 years, and CO2 emissions of 0.26 kg CO2/kg DEC. Lastly, the proposed process in Case II was compared with the GC production using dimethyl carbonate (DMC). It was found that using DEC was superior to DMC due to easier separation and glycidol avoidance.

Designing for degradation: the importance of considering biotic and abiotic polymer degradation

Thu, 10 Apr 2025 00:00:00 GMT

Designing for degradation: the importance of considering biotic and abiotic polymer degradation Tantawi, Omar; Joo, Wontae; Martin, Elijah E; Av-Ron, Sarah HM; Bannister, K'yal R; Prather, Kristala LJ; Olsen, Bradley D; Plata, Desiree L Considering the increasing global plastic demand, there is a critical need to gain insight into environmental processes that govern plastic degradation in order to inform novel design of sustainable polymers. Current biological degradation testing standards focus on formation of CO2 (i.e., mineralization) alone as a diagnostic, ultimately limiting identification of structure–degradation relationships in a timely fashion. This work developed a sequential abiotic (i.e., photodegradation and hydrolysis) and biotic degradation test and applied it to a suite of 18 polymers, including ten lab produced, novel polyhydroxyalkanoate polyesters, and eight commercially available, bio-based (i.e., polylactic acid and poly-3-hydroxybutyrate) and fossil-derived (i.e., polystyrene, polypropylene, low density polyethylene, poly(ethylene terephthalate) and tire rubber) polymers. Biomineralization alone following standard methods (i.e., ASTM 6691-17, ISO 23977-1 2020) underestimated polymer degradation up to two-fold over 28 days. Simulated sunlight enhanced the overall polymer degradation by mobilizing dissolved organic carbon (DOC). After photoirradiation, up to 100% of released dissolved organic carbon was bioavailable for marine microbes over 14 days. Photodegradation and hydrolysis could be explained by structural drivers in the commodity polymers, and the lab-synthesized polymers illustrated a limit to total degradation beyond which no enhancements in degradation were achieved. Taken together, this workflow allows for relatively fast experimental determination of environmentally relevant stimuli to help support eventual elucidation of structure–property relationships for enhanced a priori design of degradable polymers.

Seroprevalence of COVID-19 neutralizing antibodies among multi-ethnic staff of an Asian primary healthcare institution: insights from point-of-care testing and implications for booster vaccination decisions

Thu, 30 Oct 2025 00:00:00 GMT

Seroprevalence of COVID-19 neutralizing antibodies among multi-ethnic staff of an Asian primary healthcare institution: insights from point-of-care testing and implications for booster vaccination decisions Oka, Prawira; Jia, Huan; Kongsuphol, Patthara; Ng, Say Y.; Saravanan, Vivekanandan; Ng, Chirk J.; Moosa, Aminath S.; Xiong, Mengfei; Gun, Shih Y.; Tsang, Li P. M.; Lim, Jingyi; Vijaykumar, Kayshini; Ho, Cassandra X. Y.; Chua, Patrina W. L.; Ling, Sharon Y. H. Background COVID-19 vaccines have been crucial for establishing immunity; however, emerging data suggest vaccine efficacy is reduced within six months. Healthcare staff face an elevated COVID-19 risk and should make an informed decision to receive timely boosters to maintain their immunity. This study aims to determine the COVID-19 neutralizing antibody (nAb) seroprevalence among primary care staff and the impact of serological testing on their vaccination decision. Methods This cross-sectional study involved multidisciplinary primary healthcare professionals working in 10 public primary care clinics from December 2022 to July 2023. A questionnaire captured sociodemographic data, COVID-19 related history and attitudes toward serological testing. Their COVID-19 nAb levels were measured via point-of-care CoVIm™ Rapid SARS-CoV-2 nAb Test and laboratory cPass™ SARS-CoV-2 nAb Detection Kit. Results The study included 474 subjects, mostly female (88.8%), with a mean age of 40.6 years (SD = 12.3). All received at least two COVID-19 vaccinations, and 80.6% reported at least one infection. COVID-19 nAb seroprevalence was high (99.2%). Post-vaccination, 79.7% contracted COVID-19, with the median time to infection being 163 days. Most staff (93.9%) desired to know their COVID-19 immunity status through a finger pick test (77.0%) instead of venepuncture. Over two-thirds (68.1%) indicated the results would influence their booster vaccination decision. Conclusion The study revealed a high seroprevalence of COVID-19 nAb among the fully vaccinated participating staff. The necessity for timely boosters is underscored by 79.7% contracting COVID-19 post-vaccination. Most subjects were willing to undergo point-of-care testing, with results potentially influencing their decisions for booster vaccination.

Problem structuring in urban science education: Why, what, and how

Thu, 09 Oct 2025 00:00:00 GMT

Problem structuring in urban science education: Why, what, and how Lai, Yuan; Lavi, Rea Urban science is an emerging and transdisciplinary field that attracts deep interest in planning degree programs from educational institutions worldwide. Urban science education emphasizes the science of cities and urban information technology by integrating design, engineering, system science, spatial science, behavioral and social science, decision science, and other disciplines. The increasing complexity of urban systems creates significant pedagogical challenges for urban science education, particularly in problem structuring, which is the process of structuring, or defining, (a) the scope of the problem, (b) the potential ways for addressing the problem, and (c) suitable criteria for judging solutions to the problem. In this article, we describe the theoretical foundations of problem structuring in relation to urban science education and explain why it is difficult to teach. In response to this pedagogical challenge, we propose DIMES (Describe, Inquire, Model, Extract, and State), a novel domain-agnostic method combining design thinking and systems thinking developed for problem structuring in any level of higher education. We describe how the DIMES method can be integrated into urban science curricula with relation to critical considerations for teaching urban science problem structuring, the fast-evolving smart city development, and the disruptive impact of generative artificial intelligence on urban science education. Finally, we provide our thoughts on potential future studies with DIMES in urban science learning settings.

The power of fragmented elites: the role of inadvertent robust action

Wed, 09 Apr 2025 00:00:00 GMT

The power of fragmented elites: the role of inadvertent robust action Mizruchi, Mark S.; Chu, Johan S. G. It is broadly accepted among political scientists, political sociologists, and social movement theorists that a unified group will have a higher probability of success than a group that experiences internal divisions or fragmentation. Similarly, it has been assumed that in a society with a relatively unified elite, the elite will experience disproportionately higher benefits relative to the larger population. We take issue with this claim. In the mid-twentieth century, large American corporations exhibited a relatively high level of unity but the relative economic benefits accruing to the elite were at historic lows. In more recent years, American big business has become increasingly fragmented, yet the economic benefits that these elites have received have reached historic highs, and the average American’s standard of living has stagnated. Drawing on Padgett and Ansell, we introduce the concept of inadvertent robust action to explain how a relatively fragmented, disorganized elite can reap benefits that exceed those that its more unified counterparts experienced in an earlier era. We conclude with a discussion of the conditions under which our formulation can be expected to hold.

Basic Elements of Strong Gravitational Lensing

Fri, 30 May 2025 00:00:00 GMT

Basic Elements of Strong Gravitational Lensing Schechter, Paul L.; Schnittman, Jeremy D. Even when used to describe the same phenomenon, equations, graphics and words each give different perspectives and lead to complementary insights. The basic elements of strong gravitational lensing are introduced here favoring words and graphics over equations whenever possible. Fermat’s principle is the fundamental driver of strong lensing. Three “D’s” encapsulate the essential effects of lensing: Delay, Deflection and Distortion. Gravity and geometry both contribute to the delay of photons from a lensed source. Their interplay determines how the images of a source are deflected and how they are stretched or compressed. Caustics and critical curves are explained. Images of doubly, triply, quadruply and quintuply lensed sources are displayed. A table of symbols, their definitions and distinctions provides a summary of the basic elements of strong lensing.

Search for dark matter production in association with a single top quark in proton-proton collisions at √s = 13 TeV

Wed, 17 Sep 2025 00:00:00 GMT

Search for dark matter production in association with a single top quark in proton-proton collisions at √s = 13 TeV Chekhovsky, V.; Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; The CMS collaboration A search for the production of a single top quark in association with invisible particles is performed using proton-proton collision data collected with the CMS detector at the LHC at $$\sqrt{s}=13$$ TeV, corresponding to an integrated luminosity of 138 fb−1. In this search, a flavor-changing neutral current produces a single top quark or antiquark and an invisible state nonresonantly. The invisible state consists of a hypothetical spin-1 particle acting as a new mediator and decaying to two spin-1/2 dark matter candidates. The analysis searches for events in which the top quark or antiquark decays hadronically. No significant excess of events compatible with that signature is observed. Exclusion limits at 95% confidence level are placed on the masses of the spin-1 mediator and the dark matter candidates, and are compared to constraints from the dark matter relic density measurements. In a vector (axial-vector) coupling scenario, masses of the spin-1 mediator are excluded up to 1.85 (1.85) TeV with an expectation of 2.0 (2.0) TeV, whereas masses of the dark matter candidates are excluded up to 0.75 (0.55) TeV with an expectation of 0.85 (0.65) TeV.

Measurement of the Ω c 0 and Ξ c 0 baryon lifetimes using hadronic b-baryon decays

Thu, 18 Sep 2025 00:00:00 GMT

Measurement of the Ω c 0 and Ξ c 0 baryon lifetimes using hadronic b-baryon decays Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. The lifetimes of the Ω c 0 and Ξ c 0 baryons are measured using a pp collision dataset collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb−1. The charm baryons are produced in the fully reconstructed decay chains Ω b − → Ω c 0 → p K − K − π + π − and Ξ b − → Ξ c 0 → p K − K − π + π − . The measurement uses topologically and kinematically similar B− → D0(→ K−K+π−π+)π− decays for normalisation. The measured lifetimes are τ Ω c 0 = 276.3 ± 19.4 stat ± 1.8 syst ± 0.7 τ D 0 fs , τ Ξ c 0 = 149.2 ± 2.5 stat ± 0.9 syst ± 0.4 τ D 0 fs , where the first uncertainty is statistical, the second systematic and the third due to the uncertainty of the D0 lifetime. These results are consistent with previous measurements performed by the LHCb experiment.

Wormholes, branes and finite matrices in sine dilaton gravity

Tue, 16 Sep 2025 00:00:00 GMT

Wormholes, branes and finite matrices in sine dilaton gravity Blommaert, Andreas; Levine, Adam; Mertens, Thomas G.; Papalini, Jacopo; Parmentier, Klaas We compute the double trumpet in sine dilaton gravity via WdW quantization. The wormhole size is discretized. The wormhole amplitude matches the spectral correlation of a finite-cut matrix integral, where matrices have large but finite dimensions. This strongly suggests an identification of the sine dilaton gravity theory with the q-deformed JT gravity matrix integral. At the very least, it captures all universal content of that matrix model. The disk decomposes into the physical (gauge invariant) solutions of the WdW equation, which are trumpets with discrete sizes. This decomposition modifies the usual no-boundary wavefunction to a normalizable one in sine dilaton gravity. We furthermore present an exact quantization of sine dilaton gravity with open and closed end of the world branes. These EOW branes correspond with FZZT branes for the two Liouville theories that make up sine dilaton gravity. The WdW equation implies redundancies in this space of branes, leaving a one parameter family of gauge invariant branes. One gauge choice corresponds with branes discussed by Okuyama in the context of DSSYK. Legendre transforming the EOW brane amplitude reproduces the trumpet. One could read our work as fleshing out the Hilbert space of closed universes in sine dilaton gravity.

Precision e+e− hemisphere masses in the dijet region with power corrections

Wed, 10 Sep 2025 00:00:00 GMT

Precision e+e− hemisphere masses in the dijet region with power corrections Hoang, André H.; Mateu, Vicent; Schwartz, Matthew D.; Stewart, Iain W. We derive high-precision results for the e+e− heavy jet mass (HJM) dσ/dρ and dihemisphere mass (DHM) d2σ/(ds1ds2) distributions, for s1 ~ s2, in the dijet region. New results include: i) the N3LL resummation for HJM of large logarithms lnn(ρ) at small ρ including the exact two-loop non-global hemisphere soft function, the 4-loop cusp anomalous dimension and the 3-loop hard and jet functions, ii) N3LL results for DHM with resummation of logarithms ln(s1,2/Q2) when there is no large separation between s1 and s2, iii) profile functions for HJM to give results simultaneously valid in the peak and tail regions, iv) a complete two-dimensional basis of non-perturbative functions which can be used for double differential observables, that are needed for both HJM and DHM in the peak region, and v) an implementation of renormalon subtractions for large-angle soft radiation to O α s 3 together with a resummation of the additional large ln(Qρ/ΛQCD) logarithms. Here Q is the e+e− center-of-mass energy. Our resummation results are combined with known fixed-order O α s 3 results and we discuss the convergence and remaining perturbative uncertainty in the cross section. We also prove that, at order 1/Q, the first moment of the HJM distribution involves an additional non-perturbative parameter compared to the power correction that shifts the tail of the spectrum (where 1 ≫ ρ ≫ ΛQCD/Q). This differs from thrust where a single non-perturbative parameter at order 1/Q describes both the first moment and the tail, and it disfavors models of power corrections employing a single non-perturbative parameter, such as the low-scale effective coupling model. In this paper we focus only on the dijet region, not the far-tail distribution for ρ ≳ 0.2 beyond which the trijet factorization and resummation become important.

Modular chaos, operator algebras, and the Berry phase

Wed, 10 Sep 2025 00:00:00 GMT

Modular chaos, operator algebras, and the Berry phase de Boer, Jan; Najian, Bahman; van der Heijden, Jeremy; Zukowski, Claire Modular Berry transport associates a geometric phase to a zero mode ambiguity in a family of modular operators. In holographic settings, this phase was shown to encode nontrivial information about the emergent spacetime geometry. We reformulate modular Berry transport for arbitrary von Neumann algebras, including giving a precise definition of the zero mode projection in terms of a conditional expectation. For a certain class of state perturbations, we demonstrate that the modular Berry phase gives rise to an emergent symplectic form in the large N limit, extending related results in the context of subregion/subalgebra duality. We also show that the vanishing of the Berry curvature for modular scrambling modes signals the emergence of a local Poincaré algebra, which plays a key role in the quantum ergodic hierarchy. These results provide an intriguing relation between geometric phases, modular chaos and the local structure of spacetime.

The Builtsphere: A Broken Geological Paradigm

Fri, 07 Oct 2022 00:00:00 GMT

The Builtsphere: A Broken Geological Paradigm Parreño Alonso, Cristina This essay discusses the role that architecture plays as a new geological paradigm. Similar to the way geologist Peter K. Haff conceived the technosphere as “the proliferation of technology across the globe,” this essay defines the builtsphere as the proliferation of everything built across the planet and proposes both—the technosphere and the builtsphere—as subsystems of the anthroposphere. This essay illustrates this way of thinking architecture with a pedagogical experiment developed as a design studio that takes issue with the various ways in which the builtsphere has caused the breakdown of the Earth cycles.

The Brinkmanship Game: Bargaining Under the Mutual Risk of Escalation*

Mon, 14 Feb 2022 00:00:00 GMT

The Brinkmanship Game: Bargaining Under the Mutual Risk of Escalation* Haun, Phil; O’Hara, Michael This article describes a simple two-player game which illustrates basicconcepts of brinkmanship, to include calculations of probability andexpected outcomes, and risk-taking profiles. The game befits a single50-minute class period with introduction, gameplay, and discussion.The game can supplement the study of conflict from classic Cold Warcase studies of crisis bargaining, to arms control, or negotiating inter-national protocols for global climate change such as the ParisAgreement. The Brinkmanship Game was developed for the seventhweek of a 10-week graduate course called Game Theory andDecisionmaking: Exploring Strategic Situations. The course features aflipped classroom with class time devoted to experimentation, game-play, and discussion of readings and games; lectures are online. TheBrinkmanship Game would be appropriate for students in anyadvanced undergraduate or graduate level course in international rela-tions, security studies, negotiation, or game theory. The BrinkmanshipGame provides an active learning opportunity that can be valuable forencouraging students to come to their own understanding of con-cepts of mutual risk-taking. The authors have found the game to beeffective in the classroom and hope it may prove valuable to thosesearching for ways to motivate students and to help them learn.

From the square to the shopping mall: new social media, state surveillance, and the evolving geographies of urban protest

Wed, 22 Jun 2022 00:00:00 GMT

From the square to the shopping mall: new social media, state surveillance, and the evolving geographies of urban protest Stokols, Andrew Despite the rise of social media as a major factor in protests sincethe early 2010s, scholars have documented the continuedimportance of urban space and “place-based networks” for socialmovements. However, the 2019–2020 Hong Kong Anti-ELABprotests saw a shift from occupying symbolic public space to amore variegated use of urban spaces in the city. Combiningnetwork analysis of Telegram channels and georeferencing ofprotest events, this study shows how new digital media platformssuch as Telegram enabled a diverse array of protest activities, aswell as a shift from formal centrally located civic spaces to awider range of everyday spaces including malls, oﬃces, andindustrial buildings. This study also asks why this occurred,situating the shifting geography of protests as a response toseveral factors: new social media technologies, strengthening ofstate surveillance of physical and digital space, and collectivelearning from the perceived failures of past movements. Theimplications of these shifts for the future of urban socialmovements and the “public sphere” are discussed.

Interdependence of driver and pedestrian behavior in naturalistic roadway negotiations

Fri, 26 Aug 2022 00:00:00 GMT

Interdependence of driver and pedestrian behavior in naturalistic roadway negotiations Noonan, T Zach; Gershon, Pnina; Domeyer, Josh; Mehler, Bruce; Reimer, Bryan OBJECTIVE: This paper characterizes the actions of pedestrian-driver dyads by examining their interdependence across intersection types (e.g., zebra crossings, stop signs). Additionally, the analysis of interdependence captures other external factors, such as other vehicles or pedestrians, that may influence the interaction. METHODS: A 228 epoch vehicle-pedestrian interaction dataset was extracted from a large naturalistic driving data collection effort, which included vehicle, pedestrian, and contextual information (e.g., intersection type, jaywalking, vehicle maneuver, and lead vehicle presence). An expanded Actor-Partner Interdependence Model (APIM) was used to analyze driver-pedestrian dyads using driver and pedestrian standard deviations of velocity as the independent variables and wait times as dependent variables. APIM structural equation models were augmented to include driver effects (i.e., lead vehicle and maneuver type) and pedestrian effects (i.e., lead pedestrian, crossing group size, crossing direction). RESULTS: The level of protection afforded by an intersection had an effect on the extent of driver-pedestrian dyadic behavior. Interactions in undesignated crossings (i.e., jaywalking) were associated with interdependent behavior whereas interactions in designated crossings (i.e., crosswalks and parking lots) showed a partner effect on the driver's wait time but no significant corresponding partner effect on the pedestrian. Finally, protected intersection interactions (i.e., traffic lights and stop signs) demonstrated no significant partner effects. CONCLUSIONS: The difference in behavior patterns associated with the intersection type and level of protection shows that context can mediate the level of negotiation required between drivers and pedestrians. These findings inform how context and driver-pedestrian interactions should be incorporated in future modeling efforts which may, ultimately, support design of automated systems that are able to interact more safely, efficiently, and socially.

When do systematic strategies decay?

Mon, 08 Aug 2022 00:00:00 GMT

When do systematic strategies decay? Falck, Antoine; Rej, Adam; Thesmar, David Published anomalies evaluated outside the data sample deliver about 50% of in-sample performance.

When AI Is Wrong: Addressing Liability Challenges in Women’s Healthcare

Mon, 20 Jun 2022 00:00:00 GMT

When AI Is Wrong: Addressing Liability Challenges in Women’s Healthcare Marotta, Angelica Healthcare professionals can leverage Artificial intelligence (AI) to provide better care for theirpatients. However, it is also necessary to consider that AI algorithms operate according to historicaldiagnostic data, which often include evidence gathered from men. The biases of prior practices andthe perpetuation of exclusionary processes toward women can lead to inaccurate medical deci-sions. The ramifications of such errors show that the incorrect use of AI raises several criticalquestions regarding who should be responsible for potential incidents. This study aims to providean analysis of the role of AI in affecting women’s healthcare and an overview of the liabilityimplications caused by AI mistakes. Finally, this work presents a framework for algorithmic auditingto ensure that AI data are collected and stored according to secure, legal, and fair practices.

Toughening and Imparting Deconstructability to 3D‐Printed Glassy Thermosets with “Transferinker” Additives

Wed, 11 Sep 2024 00:00:00 GMT

Toughening and Imparting Deconstructability to 3D‐Printed Glassy Thermosets with “Transferinker” Additives Qin, K Peter; Herzog‐Arbeitman, Abraham; Zou, Weizhong; Chakraborty, Saswata; Kristufek, Samantha L; Husted, Keith EL; Joly, Guy D; Craig, Stephen L; Olsen, Bradley D; Johnson, Jeremiah A Thermoset toughness and deconstructability are often opposing features; simultaneously improving both without sacrificing other mechanical properties (e.g., stiffness and tensile strength) is difficult, but, if achieved, could enhance the usage lifetime and end‐of‐life options for these materials. Here, a strategy that addresses this challenge in the context of photopolymer resins commonly used for 3D printing of glassy, acrylic thermosets is introduced. It is shown that incorporating bis‐acrylate “transferinkers,” which are cross‐linkers capable of undergoing degenerative chain transfer and new strand growth, as additives (5–25 mol%) into homemade or commercially available photopolymer resins leads to photopolymer thermosets with substantially improved tensile toughness and triggered chemical deconstructability with minimal impacts on Young's moduli, tensile strengths, and glass transition temperatures. These properties result from a transferinker‐driven topological transition in network structure from the densely cross‐linked long, heterogeneous primary strands of traditional photopolymer networks to more uniform, star‐like networks with few dangling ends; the latter structure more effectively bear stress yet is also more easily depercolated via solvolysis. Thus, transferinkers represent a simple and effective strategy for improving the mechanical properties of photopolymer thermosets and providing a mechanism for their triggered deconstructability.

DustNet++: Deep Learning-Based Visual Regression for Dust Density Estimation

Mon, 24 Feb 2025 00:00:00 GMT

DustNet++: Deep Learning-Based Visual Regression for Dust Density Estimation Michel, Andreas; Weinmann, Martin; Kuester, Jannick; AlNasser, Faisal; Gomez, Tomas; Falvey, Mark; Schmitz, Rainer; Middelmann, Wolfgang; Hinz, Stefan Detecting airborne dust in standard RGB images presents significant challenges. Nevertheless, the monitoring of airborne dust holds substantial potential benefits for climate protection, environmentally sustainable construction, scientific research, and various other fields. To develop an efficient and robust algorithm for airborne dust monitoring, several hurdles have to be addressed. Airborne dust can be opaque or translucent, exhibit considerable variation in density, and possess indistinct boundaries. Moreover, distinguishing dust from other atmospheric phenomena, such as fog or clouds, can be particularly challenging. To meet the demand for a high-performing and reliable method for monitoring airborne dust, we introduce DustNet++, a neural network designed for dust density estimation. DustNet++ leverages feature maps from multiple resolution scales and semantic levels through window and grid attention mechanisms to maintain a sparse, globally effective receptive field with linear complexity. To validate our approach, we benchmark the performance of DustNet++ against existing methods from the domains of crowd counting and monocular depth estimation using the Meteodata airborne dust dataset and the URDE binary dust segmentation dataset. Our findings demonstrate that DustNet++ surpasses comparative methodologies in terms of regression and localization capabilities.

The first half-century of empirical capital markets research in accounting in pictures

Sat, 07 Jun 2025 00:00:00 GMT

The first half-century of empirical capital markets research in accounting in pictures Kothari, S. P.; Schonberger, Bryce; Wasley, Charles; Xiao, Jason J. Seminal papers by Ball and Brown (1968) and Beaver (1968) spawned a vast literature on the role of accounting numbers in capital markets. This literature, often referred to as capital markets research in accounting (CMRA), is now more than a half-century old. In light of numerous changes to the economic and financial reporting environments over this time, we estimate CMRA’s major relations using a comprehensive sample period. We illustrate each relation using plots, allowing us to efficiently present CMRA’s first half-century consistent with the adage “a picture is worth a thousand words.” The aims of our study are to document the extent of time-series variation in CMRA’s major relations and to provide evidence on market-level determinants of that variation. In doing so, our study provides a natural starting point for future research designed to develop and test additional causal explanations for time-series variation in the properties of CMRA’s major relations.

SeCOM-B: an integrated model for understanding human behaviour change in wicked socio-ecological problems

Fri, 19 Sep 2025 00:00:00 GMT

SeCOM-B: an integrated model for understanding human behaviour change in wicked socio-ecological problems Nguyen-Trung, Kien; Saeri, Alexander K.; Zhao, Kun; Boulet, Mark; Kaufman, Stefan The COM-B model, widely adopted in behaviour change research, systematically explores and categorises the behavioural barriers and facilitators to inform intervention design. The model highlights that where the right mix of barriers and facilitators, in the broad categories of capability, motivation, and opportunity exist, a given behaviour is more likely to be enacted. However, for wicked problems, applying the COM-B model becomes challenging due to complexity, uncertainty, manageability challenges, and the interpretative opacity of the systems that influence behaviour. This paper introduces a combined framework (SeCOM-B) that integrates the Socio-ecological model (SEM) and the COM-B model, highlighting its potential application in co-designing behaviour change interventions to address wicked problems, which often involve non-scientific stakeholders and interdisciplinary team members. Drawing on three case studies of practical behaviour change projects taking place in Australia (2) and Vietnam (1) between March 2022 and July 2023, the paper further illustrates the application of the SeCOM-B model in analysing the drivers and barriers of behaviours, and exploring the implications for intervention design.

Horizontal transfer of matrix metalloproteinase genes links early animal and microbial evolution

Wed, 05 Nov 2025 00:00:00 GMT

Horizontal transfer of matrix metalloproteinase genes links early animal and microbial evolution Parsons, Chris; Fournier, Gregory P. Background The early evolution of animals is characterized by the emergence of complex tissues, organs, and integument, made possible in part by the diversification of groups of structural proteins. The abundance of this new kind of organic material in the environment would have provided novel nutrient opportunities for microbes, as part of the beginnings of animal-microbial coevolution. Indeed, a diverse ensemble of extant microbial groups appear to possess the enzymatic ability to cleave collagen, the most abundant animal-specific protein, through the use of matrix metalloproteinases (MMPs). In animals, MMPs serve to reshape the extracellular matrix in the course of development, but their prevalence in the microbial world has been largely overlooked. Results MMPs have extensive diversity in Bacteria, Eumetazoa, and Streptophyta. We show that in marine metagenomes, MMP abundance is highly correlated with chitinase abundance, implying that even microbial MMPs are associated with animal-derived substrates. Reconstructing the phylogeny of MMP proteins reveals a history of rapid diversification, as well as multiple interkingdom and interdomain horizontal gene transfers. Included among these is a transfer to the ancestral lineage of the archaeal family Methanosarcinaceae, constraining this group to postdate the evolution of collagen, and therefore animal diversification. Conclusions MMPs have an unusual genetic history, marked by multiple instances of gene transfer between bacteria and multicellular eukaryotes, a smoking gun for some of the earliest coevolution between prokaryotes and metazoans. By calculating an end-Permian divergence of Methanosarcina, we demonstrate that the phylogenies of substrate-specific enzymes can provide valuable older-bound age calibrations for improving molecular clock age estimates across the Tree of Life.

New physics versus quenching factors in Coherent Neutrino Scattering

Wed, 05 Nov 2025 00:00:00 GMT

New physics versus quenching factors in Coherent Neutrino Scattering Li, Yulun; Herrera, Gonzalo; Huber, Patrick Recent results on the Coherent Elastic Neutrino-Nucleus Scattering (CEνNS) on germanium present significant discrepancies among experiments. We perform a combined analysis of the Dresden-II, CONUS+ and COHERENT data, quantifying the impact of quenching factor uncertainties on their CEνNS cross section measurement. No choice of quenching factor can bring these three data sets into mutual agreement, whereas the combination of COHERENT with either Dresden-II or CONUS+ agrees well albeit for very different quenching factors. We further study the quenching factor dependence on the sensitivity of these experiments to a large neutrino magnetic moment, finding that the constraints can vary by up to an order of magnitude. Our work highlights the importance of reducing this uncertainty on quenching factors in order to probe new physics from neutrinos at the low-energy frontier.

Skydiving to bootstrap islands

Tue, 04 Nov 2025 00:00:00 GMT

Skydiving to bootstrap islands Liu, Aike; Simmons-Duffin, David; Su, Ning; van Rees, Balt C. We study families of semidefinite programs (SDPs) that depend nonlinearly on a small number of “external” parameters. Such families appear universally in numerical bootstrap computations. The traditional method for finding an optimal point in parameter space works by first solving an SDP with fixed external parameters, then moving to a new point in parameter space and repeating the process. Instead, we unify solving the SDP and moving in parameter space in a single algorithm that we call “skydiving”. We test skydiving on some representative problems in the conformal bootstrap, finding significant speedups compared to traditional methods.

Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at √s = 13 TeV

Wed, 29 Oct 2025 00:00:00 GMT

Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at √s = 13 TeV Chekhovsky, V.; Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; The CMS collaboration Several new physics models including versions of supersymmetry (SUSY) characterized by R-parity violation (RPV) or with additional hidden sectors predict the production of events with top quarks, low missing transverse momentum, and many additional quarks or gluons. The results of a search for top squarks decaying to two top quarks and six additional light-flavor quarks or gluons are reported. The search employs a novel machine learning method for background estimation from control samples in data using decorrelated discriminators. The search is performed using events with 0, 1, or 2 electrons or muons in conjunction with at least six jets. No requirement is placed on the magnitude of the missing transverse momentum. The result is based on a sample of proton-proton collisions at $$\sqrt{s}=13$$ TeV corresponding to 138 fb−1 of integrated luminosity collected with the CMS detector at the LHC in 2016–2018. With no statistically significant excess of events observed beyond the expected contributions from the standard model, the data are used to determine upper limits on the top squark pair production cross section in the frameworks of RPV and stealth SUSY. Models with top squark masses less than 700 (930) GeV are excluded at 95% confidence level for RPV (stealth) SUSY scenarios.

Study of same-sign W boson scattering and anomalous couplings in events with one tau lepton from pp collisions at √s = 13 TeV

Mon, 27 Oct 2025 00:00:00 GMT

Study of same-sign W boson scattering and anomalous couplings in events with one tau lepton from pp collisions at √s = 13 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R.; Schwarz, D.; Sonawane, M.; The CMS collaboration A first study is presented of the cross section for the scattering of same-sign W boson pairs via the detection of a τ lepton. The data from proton-proton collisions at the center-of-mass energy of 13 TeV were collected by the CMS detector at the LHC, and correspond to an integrated luminosity of 138 fb−1. Events were selected that contain two jets with large pseudorapidity and large invariant mass, one τ lepton, one light lepton (e or μ), and significant missing transverse momentum. The measured cross section for electroweak same-sign WW scattering is $${1.44}_{-0.56}^{+0.63}$$ times the standard model prediction. In addition, a search is presented for the indirect effects of processes beyond the standard model via the effective field theory framework, in terms of dimension-6 and dimension-8 operators.

Search for dark matter produced in association with a Higgs boson decaying to a τ lepton pair in proton-proton collisions at √s = 13 TeV

Tue, 21 Oct 2025 00:00:00 GMT

Search for dark matter produced in association with a Higgs boson decaying to a τ lepton pair in proton-proton collisions at √s = 13 TeV Chekhovsky, V.; Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; The CMS Collaboration A search for dark matter particles produced in association with a Higgs boson decaying into a pair of τ leptons is performed using data collected in proton-proton collisions at a center-of-mass energy of 13 TeV with the CMS detector. The analysis is based on a data set corresponding to an integrated luminosity of 101 fb−1 collected in 2017–2018. No significant excess over the expected standard model background is observed. This result is interpreted within the frameworks of the 2HDM+a and baryonic Z′ benchmark simplified models. The 2HDM+a model is a type-II two-Higgs-doublet model featuring a heavy pseudoscalar with an additional light pseudoscalar. Upper limits at 95% confidence level are set on the product of the production cross section and the branching fraction for each of these two simplified models. Heavy pseudoscalar boson masses between 400 and 700 GeV are excluded for a light pseudoscalar mass of 100 GeV. For the baryonic Z′ model, a statistical combination is made with an earlier search based on a data set of 36 fb−1 collected in 2016. In this model, Z′ boson masses up to 1050 GeV are excluded for a dark matter particle mass of 1 GeV.

Massively parallel enrichment of low-frequency alleles enables duplex sequencing at low depth

Thu, 17 Mar 2022 00:00:00 GMT

Massively parallel enrichment of low-frequency alleles enables duplex sequencing at low depth Gydush, Gregory; Nguyen, Erica; Bae, Jin H; Blewett, Timothy; Rhoades, Justin; Reed, Sarah C; Shea, Douglas; Xiong, Kan; Liu, Ruolin; Yu, Fangyan; Leong, Ka Wai; Choudhury, Atish D; Stover, Daniel G; Tolaney, Sara M; Krop, Ian E; Christopher Love, J; Parsons, Heather A; Mike Makrigiorgos, G; Golub, Todd R; Adalsteinsson, Viktor A Assaying for large numbers of low-frequency mutations requires sequencing at extremely high depth and accuracy. Increasing sequencing depth aids the detection of low-frequency mutations yet limits the number of loci that can be simultaneously probed. Here we report a method for the accurate tracking of thousands of distinct mutations that requires substantially fewer reads per locus than conventional hybrid-capture duplex sequencing. The method, which we named MAESTRO (for minor-allele-enriched sequencing through recognition oligonucleotides), combines massively parallel mutation enrichment with duplex sequencing to track up to 10,000 low-frequency mutations, with up to 100-fold fewer reads per locus. We show that MAESTRO can be used to test for chimaerism by tracking donor-exclusive single-nucleotide polymorphisms in sheared genomic DNA from human cell lines, to validate whole-exome sequencing and whole-genome sequencing for the detection of mutations in breast-tumour samples from 16 patients, and to monitor the patients for minimal residual disease via the analysis of cell-free DNA from liquid biopsies. MAESTRO improves the breadth, depth, accuracy and efficiency of mutation testing by sequencing.

Peanut oral immunotherapy differentially suppresses clonally distinct subsets of T helper cells

Tue, 23 Nov 2021 00:00:00 GMT

Peanut oral immunotherapy differentially suppresses clonally distinct subsets of T helper cells Monian, Brinda; Tu, Ang A; Ruiter, Bert; Morgan, Duncan M; Petrossian, Patrick M; Smith, Neal P; Gierahn, Todd M; Ginder, Julia H; Shreffler, Wayne G; Love, J Christopher Food allergy affects an estimated 8% of children in the United States. Oral immunotherapy (OIT) is a recently approved treatment, with outcomes ranging from sustained tolerance to food allergens to no apparent benefit. The immunological underpinnings that influence clinical outcomes of OIT remain largely unresolved. Using single-cell RNA-Seq and paired T cell receptor α/β (TCRα/β) sequencing, we assessed the transcriptomes of CD154+ and CD137+ peanut-reactive T helper (Th) cells from 12 patients with peanut allergy longitudinally throughout OIT. We observed expanded populations of cells expressing Th1, Th2, and Th17 signatures that further separated into 6 clonally distinct subsets. Four of these subsets demonstrated a convergence of TCR sequences, suggesting antigen-driven T cell fates. Over the course of OIT, we observed suppression of Th2 and Th1 gene signatures in effector clonotypes but not T follicular helper-like (Tfh-like) clonotypes. Positive outcomes were associated with stronger suppression of Th2 signatures in Th2A-like cells, while treatment failure was associated with the expression of baseline inflammatory gene signatures that were present in Th1 and Th17 cell populations and unmodulated by OIT. These results demonstrate that differential clinical responses to OIT are associated with both preexisting characteristics of peanut-reactive CD4+ T cells and suppression of a subset of Th2 cells.

Mitochondrial variant enrichment from high-throughput single-cell RNA sequencing resolves clonal populations

Thu, 24 Feb 2022 00:00:00 GMT

Mitochondrial variant enrichment from high-throughput single-cell RNA sequencing resolves clonal populations Miller, Tyler E; Lareau, Caleb A; Verga, Julia A; DePasquale, Erica AK; Liu, Vincent; Ssozi, Daniel; Sandor, Katalin; Yin, Yajie; Ludwig, Leif S; El Farran, Chadi A; Morgan, Duncan M; Satpathy, Ansuman T; Griffin, Gabriel K; Lane, Andrew A; Love, J Christopher; Bernstein, Bradley E; Sankaran, Vijay G; van Galen, Peter The combination of single-cell transcriptomics with mitochondrial DNA variant detection can be used to establish lineage relationships in primary human cells, but current methods are not scalable to interrogate complex tissues. Here, we combine common 3′ single-cell RNA-sequencing protocols with mitochondrial transcriptome enrichment to increase coverage by more than 50-fold, enabling high-confidence mutation detection. The method successfully identifies skewed immune-cell expansions in primary human clonal hematopoiesis.

SARS-CoV-2 receptor binding domain displayed on HBsAg virus–like particles elicits protective immunity in macaques

Wed, 16 Mar 2022 00:00:00 GMT

SARS-CoV-2 receptor binding domain displayed on HBsAg virus–like particles elicits protective immunity in macaques Authorized vaccines against SARS-CoV-2 remain less available in low- and middle-income countries due to insufficient supply, high costs, and storage requirements. Global immunity could still benefit from new vaccines using widely available, safe adjuvants, such as alum and protein subunits, suited to low-cost production in existing manufacturing facilities. Here, a clinical-stage vaccine candidate comprising a SARS-CoV-2 receptor binding domain–hepatitis B surface antigen virus–like particle elicited protective immunity in cynomolgus macaques. Titers of neutralizing antibodies (>104) induced by this candidate were above the range of protection for other licensed vaccines in nonhuman primates. Including CpG 1018 did not significantly improve the immunological responses. Vaccinated animals challenged with SARS-CoV-2 showed reduced median viral loads in bronchoalveolar lavage (~3.4 log10) and nasal mucosa (~2.9 log10) versus sham controls. These data support the potential benefit of this design for a low-cost modular vaccine platform for SARS-CoV-2 and other variants of concern or betacoronaviruses.

Searching for exotic scalars at fusion reactors

Mon, 27 Oct 2025 00:00:00 GMT

Searching for exotic scalars at fusion reactors Baruch, Chaja; Fitzpatrick, Patrick J.; Menzo, Tony; Soreq, Yotam; Trifinopoulos, Sokratis; Zupan, Jure Part of the energy created in deuterium-tritium fusion reactors is carried away from plasma by a high-intensity neutron flux, which is then absorbed by the reactor’s inner walls. The neutron flux can be used to sustain the reaction by the following mechanism: the walls are coated with lithium-rich breeding blankets, in which a fraction of neutrons interacts with lithium, creating tritium, which can be, in turn, used a fuel for the main reaction. The interactions of neutrons with the materials within the breeding blanket can also result in the production of dark sector particles, feebly interacting light scalars or pseudoscalars, via nuclear transitions. We estimate the potential size of such dark sector flux outside the reactor and consider possible detection methods at current and future thermonuclear fusion reactors. In our analysis, we take into account all other current bounds, recasting also the SNO axion bound for a CP even scalar. We find that year-long searches at current and future reactors can set leading constraints on dark scalar- and dark pseudoscalar-nucleon couplings.

Measurements of charmed meson and antimeson production asymmetries at √s = 13.6 TeV

Tue, 07 Oct 2025 00:00:00 GMT

Measurements of charmed meson and antimeson production asymmetries at √s = 13.6 TeV Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; The LHCb collaboration This article presents doubly differential measurements of the asymmetries in production rates between mesons containing a charm quark and those containing an anti-charm quark in proton-proton collisions at a centre-of-mass energy of s = 13.6 TeV using data recorded by the LHCb experiment. The asymmetries of D0, D+ and D s + mesons are measured for two-dimensional intervals in transverse momentum and pseudorapidity, within the range 2.5 < pT < 25.0 GeV/c and 2.0 < η < 4.5. No significant production asymmetries are observed. Comparisons to the Pythia 8 and Herwig 7 event generators are also presented, and their agreement with the data is evaluated. These measurements constitute the first measurements of production asymmetries at this centre-of-mass energy of colliding beams, and the first measurements with the LHCb Run 3 detector.

Urban Planning for Health Equity Must Employ an Intersectionality Framework

Tue, 12 Jul 2022 00:00:00 GMT

Urban Planning for Health Equity Must Employ an Intersectionality Framework Williams, Patrice C; Binet, Andrew; Alhasan, Dana M; Riley, Nyree M; Jackson, Chandra L Urban planning for health equity should be guided by an intersectional approach. Intersectionality is an essential framework for understanding the multiple overlapping factors, such as social and economic inequalities, that produce health disparities. We offer four strategies that planning researchers and practitioners can use to develop and integrate an intersectional approach into planning for health equity: challenging implicit and explicit assumptions, building cross-sectoral coalitions united by a shared vision for social and environmental justice, applying transdisciplinary and co-designing approaches throughout the planning process, and using existing tools to evaluate the impact of programs and policies on advancing health equity.

Characterizing driver speeding behavior when using partial-automation in real-world driving

Tue, 12 Jul 2022 00:00:00 GMT

Characterizing driver speeding behavior when using partial-automation in real-world driving Haus, Samantha H; Gershon, Pnina; Mehler, Bruce; Reimer, Bryan Objective: Speeding is a prevalent and complex risky behavior that can be affected by many fac-tors. Understanding how drivers speed is important for developing countermeasures, especially asnew automation features emerge. The current study seeks to identify and describe types of real-world speeding behaviors with and without the use of partial-automation. Methods: This study used a combination of supervised and unsupervised data analysis techniquesto assess relevant factors in real-world speeding epochs, extracted from the MIT Advanced VehicleTechnology Naturalistic Driving Study, and classified them into distinct speeding behaviors.Speeding epochs were defined as traveling at least 5 mph over the speed limit for a minimumduration of 3 s. Vehicle speed-exceedance profiles were characterized over time using DynamicTime Warping and included in multivariate models that evaluated the associations between differ-ent features of the speeding epochs, such as speeding duration and magnitude. Finally, the identi-fied features were used to cluster speeding behaviors using the Gower dissimilarity measure. Results: The analysis yielded four types of behaviors in both partially-automated and manual driv-ing: (i) Incidental speeding (low duration, low magnitude), (ii) Moderate speeding (low duration,moderate magnitude), (iii) Elevated speeding (moderate duration, high magnitude), and (iv)Extended speeding (long duration, high magnitude). When comparing the behaviors with andwithout partial-automation use, both Incidental and Moderate speeding were found to have sig-nificantly longer durations with partial-automation than manual driving. Elevated speeding wasfound to be more prevalent and associated with higher magnitudes during manual than with par-tially-automated driving. Finally, although Extended speeding was more prevalent during automa-tion use, it was associated with a lower mean and maximum speed magnitude compared toExtended speeding during manual driving. Conclusions: This work highlights the variability in speeding behavior between and within par-tially-automated and manual driving. The design of systems that mitigate risky speeding behav-iors should consider targeting divergent behaviors observed between manual and automateddriving as a mechanism to mitigate the prevalence of the different behaviors associated witheach state.

Validation and Uncertainty Quantification of Transient Reflood Models Using COBRA-TF and Machine Learning Techniques Based on the NRC/PSU RBHT Benchmark

Thu, 28 Jul 2022 00:00:00 GMT

Validation and Uncertainty Quantification of Transient Reflood Models Using COBRA-TF and Machine Learning Techniques Based on the NRC/PSU RBHT Benchmark Jin, Yue; Bajorek, Stephen M; Cheung, Fan-Bill The accurate prediction of the fluid flow mass and the heat transfer process as well as the system response during reflood transients has long been a critical and challenging issue for reactor system safety analyses. Accurate characterization of the flow and energy transport can also significantly facilitate the various system/component design and optimization tasks. In the current study based on the U.S. Nuclear Regulatory Commission/Pennsylvania State University Rod Bundle Heat Transfer (RBHT) reflood experimental data, a comprehensive uncertainty analysis framework is developed using DAKOTA. The developed framework is used to perform an in-depth reflood model validation and verification for the subchannel analysis code COBRA-TF. In the meantime, the artificial intelligence (AI)–based machine learning (ML) model for rod cladding temperature prediction during reflood is also developed and evaluated using the current framework. Key input parametric effects for reflood thermal-hydraulic prediction include the system pressure, inlet liquid temperature/enthalpy, inlet mass flow rate, and average bundle power input. The figure of merit under consideration is the peak cladding temperature variations. It is found in the current study that, while further model improvement is needed, COBRA-TF can predict the correct parametric trends when compared with the RBHT data. On the other hand, it is challenging for the pure AI-based ML models to correctly reflect the parametric trends. Suggestions for future ML model development are provided in the end.

Remote language revitalisation efforts during COVID-19

Mon, 13 Jun 2022 00:00:00 GMT

Remote language revitalisation efforts during COVID-19 Wiley-Camacho, Grahm; Hillaire, Garron; Buttimer, Christopher J; Colwell, Richard As schools shift to online instruction during the COVID-19 pandemic, it is important to support disenfranchised populations and keep issues of equity at the centre of our response. In this study, the authors focus on supporting one of the few urban-based Indigenous language schools in the United States because language revitalisation is critical for Native American communities. The authors explore the extent to which video conferencing and flipped classrooms support the development of a community of speakers. The study focuses on a single classroom of 16 students in first through third grade. The authors use a digital decolonisation framework focused on empowering local communities in conjunction with design-based research methodology to explore contextualised remote instruction solutions. They report on benefits for the development of a community of speakers from remote instruction that come with costs in reduced efficacy of language learning. Finally, they distil those results into preliminary design principles.

Cohomogeneity Two Ricci Solitons with Sub-Euclidean Volume

Mon, 27 Oct 2025 00:00:00 GMT

Cohomogeneity Two Ricci Solitons with Sub-Euclidean Volume Firester, Benjy; Tsiamis, Raphael We introduce new families of four-dimensional Ricci solitons of cohomogeneity two with volume collapsing ends. In a local presentation of the metric conformal to a product, we reduce the soliton equation to a degenerate Monge-Ampère equation for the conformal factor coupled with ODEs. We obtain explicit complete expanding solitons as well as abstract existence results for shrinking and steady solitons with boundary. These families of Ricci solitons specialize to classical examples of Einstein and soliton metrics. We also classify local solutions of this Monge-Ampère equation to prove rigidity for these solitons.

How Many Sexes? How Many Genders?

Wed, 10 Sep 2025 00:00:00 GMT

How Many Sexes? How Many Genders? Byrne, Alex The British philosopher and public intellectual C. E. M. Joad was a regular panelist on the BBC radio show The Brains Trust during and after the Second World War. He often began an answer to listeners’ questions with his catchphrase “It all depends what you mean by…,” which caught on throughout the country (Ayto & Crofton, 2011). If any question deserves Joad’s catchphrase, it is “How many genders?”

Is There Super-Normal Profit in Real Estate Development?*

Mon, 11 Jul 2022 00:00:00 GMT

Is There Super-Normal Profit in Real Estate Development?* Geltner, David; Kumar, Anil; Van de Minne, Alex M This paper explores the question of whether real estate development (RED) projects systematically present positive net present value (NPV) and therefore, provide super-normal profit. Such projects are the products of a business operation that governs the exercise of the real call option on development that is represented by developable land. We present a framework for considering super-normal profit in the RED industry, and then in light of that framework we examine RED projects produced by publicly-traded equity real estate investment trusts (REITs). We find strong evidence of positive correlation between REITs’ Tobin-Q ratios, indicative of positive NPV, and the ratio of development assets to total assets in the firm, controlling for other factors. The nature of the firm’s Tobin’s-Q metric is such that the implied added firm value is net of land cost and net of overhead and search costs associated with the RED business operation. While our findings do not prove a direction of causality between REITs’ RED activity and positive NPV, the robust positive correlation controlling for other factors raises interesting implications which are discussed in the paper.

Countervailing Effects of Extreme Maximum and Minimum Temperature Days on Conflict in Mainland Southeast Asia

Mon, 03 Nov 2025 00:00:00 GMT

Countervailing Effects of Extreme Maximum and Minimum Temperature Days on Conflict in Mainland Southeast Asia Gasser, André Tashi; Lanz, Bruno We exploit 0.5◦ × 0.5◦ raster data to document how exceedances of the local 90th percentile thresholds for daily maximum and minimum temperatures affect conflict in mainland Southeast Asia. We show that conflict incidence increases with extreme high maximum temperature days and decreases with extreme high minimum temperature days. This implies that failing to control for extreme minimums understates the effects of extreme maximums. Moreover, as the frequency of extreme maximums and minimums is expected to increase together with average temperatures, the countervailing effects at both tails of the temperature distribution offset one another in mean-temperature regressions, helping to explain earlier inconclusive findings for the region. We also show that the effects of extreme maximums and minimums differ by conflict type, actors involved and affected populations. Thus, even in the absence of an aggregate mean-temperature effect, a rising frequency of extreme temperature days may generate complex distributional conflict incidence.

An Optimization-Based Construction Procedure for Function Space-Based Summation-by-Parts Operators on Arbitrary Grids

Thu, 06 Nov 2025 00:00:00 GMT

An Optimization-Based Construction Procedure for Function Space-Based Summation-by-Parts Operators on Arbitrary Grids Glaubitz, Jan; Nordström, Jan; Öffner, Philipp We introduce a novel construction procedure for one-dimensional function space summation-by-parts (FSBP) operators. Existing construction procedures for FSBP operators of the form D = P - 1 Q proceed as follows: Given a boundary operator B, the norm matrix P is first determined and then in a second step the complementary matrix Q is calculated to finally get the FSBP operator D. In contrast, the approach proposed here determines the norm and complementary matrices, P and Q, simultaneously by solving an optimization problem. The proposed construction procedure applies to classical summation-by-parts (SBP) operators based on polynomial approximation and the broader class of FSBP operators. According to our experiments, the presented approach yields a numerically stable construction procedure and FSBP operators with higher accuracy for diagonal norm difference operators at the boundaries than the traditional approach. Through numerical simulations, we highlight the advantages of our proposed technique.

Cochlea to categories: The spatiotemporal dynamics of semantic auditory representations

Tue, 21 Jun 2022 00:00:00 GMT

Cochlea to categories: The spatiotemporal dynamics of semantic auditory representations Lowe, Matthew X; Mohsenzadeh, Yalda; Lahner, Benjamin; Charest, Ian; Oliva, Aude; Teng, Santani How does the auditory system categorize natural sounds? Here we apply multimodal neuroimaging to illustrate the progression from acoustic to semantically dominated representations. Combining magnetoencephalographic (MEG) and functional magnetic resonance imaging (fMRI) scans of observers listening to naturalistic sounds, we found superior temporal responses beginning ∼55 ms post-stimulus onset, spreading to extratemporal cortices by ∼100 ms. Early regions were distinguished less by onset/peak latency than by functional properties and overall temporal response profiles. Early acoustically-dominated representations trended systematically toward category dominance over time (after ∼200 ms) and space (beyond primary cortex). Semantic category representation was spatially specific: Vocalizations were preferentially distinguished in frontotemporal voice-selective regions and the fusiform; scenes and objects were distinguished in parahippocampal and medial place areas. Our results are consistent with real-world events coded via an extended auditory processing hierarchy, in which acoustic representations rapidly enter multiple streams specialized by category, including areas typically considered visual cortex.

Rapid and automated alloy design with graph neural network-powered large language model-driven multi-agent AI

Thu, 06 Nov 2025 00:00:00 GMT

Rapid and automated alloy design with graph neural network-powered large language model-driven multi-agent AI Ghafarollahi, Alireza; Buehler, Markus J. A multi-agent artificial intelligence (AI) model is developed to automate the discovery of new metallic alloys, integrating multimodal data and external knowledge, including insights from physics via atomistic simulations. The system consists of (a) large language models (LLMs) for tasks such as reasoning and planning, (b) AI agents with distinct roles collaborating dynamically, and (c) a newly developed graph neural network (GNN) model for rapid retrieval of physical properties. We chose the ternary NbMoTa body-centered-cubic alloy as our model system and developed the GNN to predict two fundamental materials properties: the Peierls barrier and the solute/screw dislocation interaction energy. Our GNN model efficiently predicts these properties, reducing reliance on costly brute-force calculations and alleviating the computational demands on the multi-agent system. By combining the predictive capabilities of GNNs with the collaborative intelligence of LLM-driven reasoning agents, the system autonomously explores vast alloy design spaces, identifies trends in atomic-scale properties, and predicts macroscale mechanical strength, as demonstrated by several computational experiments. This synergistic approach accelerates the discovery of advanced alloys and holds promise for broader applications in other complex systems, marking a step forward in automated materials discovery and design. Impact statement Traditional deep learning models, such as graph neural networks and convolutional neural networks, operate within the confines of their training data sets, making single-step inferences for regression or classification. Our work introduces a multi-agent strategy that transcends these limitations by integrating deep learning with reasoning and decision-making capabilities. This intelligent system actively interprets results, determines subsequent actions, and iteratively refines predictions, accelerating the materials design process. We demonstrate its effectiveness in exploring the vast compositional space of a ternary alloy, where the model dynamically solicits data, analyzes trends, generates visualizations, and derives insights into materials behavior. By enabling accurate predictions of key alloy characteristics, our approach advances the discovery of novel metallic systems and underscores the critical role of solid-solution alloying. More broadly, it represents a major step toward integrating artificial intelligence with scientific reasoning, moving closer to artificial general intelligence in engineering. This paradigm shift has profound implications for materials science, enabling more efficient, autonomous, and intelligent exploration of complex materials spaces. Graphical Abstract

Latent Space Alignment Using Adversarially Guided Self-Play

Fri, 26 Aug 2022 00:00:00 GMT

Latent Space Alignment Using Adversarially Guided Self-Play Tucker, Mycal; Zhou, Yilun; Shah, Julie A We envision a world in which robots serve as capable partners in heterogeneous teams composed of other robots or humans. A crucial step towards such a world is enabling robots to learn to use the same representations as their partners; with a shared representation scheme, information may be passed among teammates. We define the problem of learning a fixed partner’s representation scheme as that of latent space alignment and propose metrics for evaluating the quality of alignment. While techniques from prior art in other fields may be applied to the latent space alignment problem, they often require interaction with partners during training time or large amounts of training data. We developed a technique, Adversarially Guided Self-Play (ASP), that trains agents to solve the latent space alignment problem with little training data and no access to their pre-trained partners. Simulation results confirmed that, despite using less training data, agents trained by ASP aligned better with other agents than agents trained by other techniques. Subsequent human-participant studies involving hundreds of Amazon Mechanical Turk workers showed how laypeople understood our machines enough to perform well on team tasks and anticipate their machine partner’s successes or failures.

Sensing Lights: The Challenges of Transforming Street Lights into an Urban Intelligence Platform

Mon, 22 Aug 2022 00:00:00 GMT

Sensing Lights: The Challenges of Transforming Street Lights into an Urban Intelligence Platform Alvarez, Ricardo; Duarte, Fabio; Frenchman, Dennis; Ratti, Carlo The technological transformation behind intelligent infrastructure systems requires institutional and stakeholder realignment in their development. In this article, we evaluate the challenges for the production of smart infrastructure through an in-depth analysis of the development of smart street lighting strategies. We conduct surveys and semi-structured interviews with key stakeholders and industry leaders in public illumination, as well with public officials from cities in three continents to understand the related challenges they face, the strategies being developed to meet those challenges, and reflect on the lessons provided for the design, creation, and operation of public smart infrastructure systems. We find that there are key barriers. First, differences in vision that reflect a lack of fit between operators of the current infrastructure and the new possibilities afforded by digital technologies. Second, lack of policies that would help facilitate the adoption of these new technologies particularly in regards to privacy and data operationalization. Third, difficulties in public engagement. These barriers to innovation hinder the capacity of cities to maximize the possibilities as well as the social value of intelligent street lights as a future-proof platform for urban knowledge and urban applications.

Intratumorally anchored cytokine therapy

Thu, 02 Jun 2022 00:00:00 GMT

Intratumorally anchored cytokine therapy Wittrup, K Dane; Kaufman, Howard L; Schmidt, Michael M; Irvine, Darrell J INTRODUCTION: On-target, off-tumor toxicity severely limits systemic dosing of cytokines and agonist antibodies for cancer. Intratumoral administration is increasingly being explored to mitigate this problem. Full exploitation of this mode of administration must include a mechanism for sustained retention of the drug; otherwise, rapid diffusion out of the tumor eliminates any advantage. AREAS COVERED: We focus here on strategies for anchoring immune agonists in accessible formats. Such anchoring may utilize extracellular matrix components, cell surface receptor targets, or exogenously administered particulate materials. Promising alternative strategies not reviewed here include slow release from the interior of a material depot, expression following local transfection, and conditional proteolytic activation of masked molecules. EXPERT OPINION: An effective mechanism for tissue retention is a critical component of intratumorally anchored cytokine therapy, as leakage leads to decreased tumor drug exposure and increased systemic toxicity. Matching variable drug release kinetics with receptor-mediated cellular uptake is an intrinsic requirement for the alternative strategies mentioned above. Bioavailability of an anchored form of the administered drug is key to obviating this balancing act.

The Generative Dialogue Framework and the Pursuit of Better Listening by Journalists: A Design-Centered Approach for More Constructive Conversations with Audiences

Wed, 18 May 2022 00:00:00 GMT

The Generative Dialogue Framework and the Pursuit of Better Listening by Journalists: A Design-Centered Approach for More Constructive Conversations with Audiences Dimitrakopoulou, Dimitra; Lewis, Seth C This article introduces the Generative Dialogue Framework (GDF) and explores its potential as a pedagogical intervention, one that could help reimagine the future of engaged journalism by bringing design-thinking practices, creativity, and deep-listening modalities into play. The framework is developed through design thinking and builds around principles from the field of design. It uses virtual meeting technologies to organize small-group conversations, allows for creative and playful activities to help people share stories and feelings, and aims to create an ambient atmosphere of mutual understanding and co-creative problem-solving. With this article, we aspire to initiate a conversation around the value of “pollinating” journalism studies with concepts and principles from design thinking and facilitation so that journalists could become empowered to connect with their audiences with greater empathy and compassion and thereby surface diverse and rich lived experiences using more active and reflective listening skills. To test the framework’s potential for enhancing engaged journalism curricula, we collaborated with 17 journalism students at a U.S. university in a series of activities, from initial training on the platform to hosting a conversation using the GDF to ultimately producing a news story based on the insights acquired through this design-centered approach.

Programmable Continuous Electrowetting of Liquid Metal for Reconfigurable Electronics

Mon, 15 Sep 2025 00:00:00 GMT

Programmable Continuous Electrowetting of Liquid Metal for Reconfigurable Electronics Babatain, Wedyan; Park, Christine; Harraz, Deiaa M; Kilic Afsar, Ozgun; Honnet, Cedric; Lov, Sarah; Labrune, Jean‐Baptiste; Dickey, Michael D; Ishii, Hiroshi Dynamic manipulation of the shape and position of liquid metal (LM), a conductive and deformable conductor, presents new opportunities for reconfigurable electronics, fluidic logic, and soft-actuation systems. This study combines continuous electrowetting (CEW) with electrochemical modulation of the interface of LM in electrolyte to achieve tunable and directional LM manipulation in 2D spaces. A key finding is that under a fixed external electric field, the LM moves in a direction that depends on its electrochemical potential. The LM potential is controlled using a substrate featuring patterns of laser-induced graphene (LIG) since it is non-wetting to LM and electrically conductive. This strategy enables a range of functionalities, including “valves” for on-demand LM control, LM droplet sorting, feedback sensing, and fluidic logic gates. The strategy can also control the motion of LM droplets across 2D spaces. Finally, it is utilized within a reconfigurable circuit platform where the LM functions as a dynamic interconnect for sequential activation, parallel switching, and self-healing circuits. By coupling the electrically-driven motion of LM and the versatility of LIG patterning, this work establishes a versatile framework for reconfigurable electronics, programmable fluidic systems, and adaptive systems.

Optimization of CEST MRI Reporter Protein Design Using Cation‐Pi Networks

Wed, 10 Sep 2025 00:00:00 GMT

Optimization of CEST MRI Reporter Protein Design Using Cation‐Pi Networks Korenchan, David E.; French, Ethan J.; Runco, Emerenziana; Dhakan, Chetan B.; Yan, Jinwu; Nakashima, Hiroshi; McMahon, Michael T.; Gilad, Assaf A.; Farrar, Christian T. Nucleic acid-based therapeutics, such as oncolytic virotherapy or gene therapy, would benefit greatly from a reporter gene that induces endogenous production of a protein biomarker to noninvasively track the delivery, persistence, and spread with imaging. Several chemical exchange saturation transfer (CEST) reporter proteins detectable by magnetic resonance imaging (MRI) have been demonstrated to have high sensitivity. However, to date none can provide strong CEST contrast at a distinct resonance from that of endogenous proteins, limiting their specificity. We investigated proteins and peptides containing tyrosine (Tyr), tryptophan (Trp), and lysine (Lys) residues that demonstrate CEST contrast shifted far downfield (4–10 ppm) from water. Although Tyr, Trp, and Lys exchangeable protons are typically not detectable under physiological conditions, those in our tested molecules are, having exchange rates of 400–2500 s−1. The large chemical shift dispersion and rapid exchange rates are attributed to unique hydrogen bonding and cation-π network interactions. These discoveries set the stage for designing a stable reporter protein with high detection specificity and sensitivity that can facilitate the in vivo monitoring of viral and gene therapies using MRI.

3D‐Printed Mixed Ionic‐Electronic Conductive Polymer Composites for Long‐Term Bioelectronic Sensing

Sun, 07 Sep 2025 00:00:00 GMT

3D‐Printed Mixed Ionic‐Electronic Conductive Polymer Composites for Long‐Term Bioelectronic Sensing Bagatella, Simone; Roh, Heejung; Cavallaro, Marco; Suriano, Raffaella; Levi, Marinella; Gumyusenge, Aristide Reliable, long-term monitoring of health data is becoming increasingly essential in modern healthcare. While computational and machine learning capabilities continue to advance, the lack of lightweight, conformable, and customizable hardware remains a key limitation. In the context of heart health, traditional electrocardiogram (ECG) electrodes are rigid and often uncomfortable for continuous wear. Existing soft electrodes tend to be either cost-prohibitive or unreliable over extended use. In this work, all-polymer, 3D-printed, highly stable, and conformable ECG patches are developed for long-term signal acquisition. Through material optimization, composite materials with electrical conductivity up to 1.7 S cm−1 are developed, maintaining over 85% of their conductivity after 60 days of exposure to open air. These materials also exhibit remarkable stretchability (strain at break up to 253%) and high mechanical strength (tensile strength of 25 MPa). The formulated inks are fully compatible with 3D material extrusion techniques, significantly reducing manufacturing costs. The printed electrodes are flexible, stretchable, and capable of recording high-quality ECG signals, performing comparably to state-of-the-art metal electrodes, even after more than a month of use-and-store in open air.

A causal inference framework to compare the effectiveness of life-sustaining ICU therapies—using the example of cancer patients with sepsis

Mon, 08 Sep 2025 00:00:00 GMT

A causal inference framework to compare the effectiveness of life-sustaining ICU therapies—using the example of cancer patients with sepsis Matos, João; Struja, Tristan; Woite, Naira Link; Restrepo, David; Waschka, Andre Kurepa; Celi, Leo A; Sauer, Christopher M The rise in cancer patients could lead to an increase in intensive care units (ICUs) admissions. We explored differences in treatment practices and outcomes of invasive therapies between patients with sepsis with and without cancer. Adults from 2008 to 2019 admitted to the ICU for sepsis were extracted from the databases MIMIC-IV and eICU-CRD. Using Extreme Gradient Boosting, we estimated the odds for invasive mechanical ventilation (IMV) or vasopressors. Targeted maximum likelihood estimation (TMLE) models estimated treatment effects of IMV and vasopressors on in-hospital mortality and 28 hospital-free days. 58,988 adult septic patients were included, of which 6145 had cancer. In-hospital mortality was higher for cancer patients (30.3% vs. 16.1%). Patients with cancer had lower odds of receiving IMV (aOR [95%CI], 0.94 [0.90–0.97]); pronounced for hematologic patients (aOR 0.89 [0.84–0.93]). Odds for vasopressors were also lower for hematologic patients (aOR 0.89 [0.84–0.94]). TMLE models found IMV to be overall associated with higher in-hospital mortality for solid and hematological patients (ATE 3% [1%–5%], 6% [3%–9%], respectively), while vasopressors were associated with higher in-hospital mortality for patients with solid and metastatic cancer (ATE 6% [4%–8%], 3% [1%–6%], respectively). We utilized US-wide ICU data to estimate a relationship between mortality and the use of common therapies. With the exception of hematologic patients being less likely to receive IMV, we did not find differential treatment patterns. We did not demonstrate an average survival benefit for therapies, underscoring the need for a more granular analysis to identify subgroups who benefit from these interventions.

Accelerated Navigator for Rapid ∆B0 Field Mapping for Real-Time Shimming and Motion Correction of Human Brain MRI

Thu, 04 Sep 2025 00:00:00 GMT

Accelerated Navigator for Rapid ∆B0 Field Mapping for Real-Time Shimming and Motion Correction of Human Brain MRI Jayadev, Nutandev Bikkamane; Stockmann, Jason; Frost, Robert; Arango, Nicolas; Chang, Yulin; van der Kouwe, André; Andronesi, Ovidiu C. ∆B0 shim optimization performed at the beginning of an MR scan is unable to correct for ∆B0 field inhomogeneities caused by patient motion or hardware instability during scans. Navigator-based methods have been demonstrated previously to be effective for motion and shim correction. The purpose of this work was to accelerate volumetric navigators to allow fast acquisition of the parent navigated sequence with short real-time feedback time and high spatial resolution of the ∆B0 field mapping. A GRAPPA-accelerated 3D dual-echo EPI vNav was implemented on a 3 T Prisma MRI scanner. Testing was performed on an anthropomorphic head phantom and 11 human participants. vNav-derived ∆B0 field maps with various spatial resolutions were compared to Cartesian-encoded gold-standard 3D gradient-echo ∆B0 field mapping. ∆B0 shimming was evaluated for the scanner's spherical harmonics shims and a custom-made AC/DC RF-receive/∆B0-shim array. The performance of dual-echo and single-echo accelerated navigators was compared for tracking and updating ∆B0 field maps during motion. Real-time motion and shim corrections for 2D MRI and 3D MRSI sequences were assessed in vivo with controlled head movement. Up to 8-fold acceleration of volumetric navigators (vNavs) significantly reduced geometric distortions and signal dropouts near air-tissue interfaces and metal implants. Acceleration allowed a flexible tradeoff between spatial resolution (2.5–7.5 mm) and acquisition time (242–1302 ms). Notably, accelerated high-resolution (5 mm) vNav was faster (378 ms) than unaccelerated low-resolution (7.5 mm) vNav (700 ms) and showed better agreement with 3D-GRE ∆B0 field mapping with 5.5 Hz RMSE, 1 Hz bias, and [−10%, +10%] confidence interval. Accelerated vNavs improved 3D MRSI and 2D MRI in real-time motion and shim correction applications. Advanced shimming with spherical harmonic and shim array showed superior ΔB0 correction, especially with joint shim optimization. GRAPPA-accelerated vNavs provide fast, robust, and high-quality ∆B0 field mapping and shimming over the whole-brain. The accelerated vNavs enable rapid correction of ∆B0 field inhomogeneities and faster acquisition of the navigated parent sequence. This methodology can be used for real-time motion and shim correction to enhance data quality in various MRI applications.

Wirelessly Powered Ingestible Capsule for Optical Stimulation of the Gastrointestinal Tract in Rodents

Wed, 20 Aug 2025 00:00:00 GMT

Wirelessly Powered Ingestible Capsule for Optical Stimulation of the Gastrointestinal Tract in Rodents Elsherif, Mohamed; El‐Din, Rawan Badr; Makhambetova, Zhansaya; Naser, Heba; Boitet, Maylis; Singh, Rahul; Oh, Keonghwan; Sukesan, Revathi; Ha, Sohmyung; Ramadi, Khalil B. Optogenetics enables cell-specific activation and inhibition of neurons. The gut contains intricate networks of enteric and central neurons, but in vivo investigation is difficult due to its motile and harsh environment. This work reports an ingestible electronic capsule for non-invasive optical gut stimulation (ICOPS) in rodents. ICOPS is wirelessly powered via a transmitter coil, delivered by oral gavage, and excreted safely without obstruction within 20 h. The device integrates a micro-light-emitting diode (µLED) operating at 470 nm—a standard wavelength for channelrhodopsin-2 activation—together with a 460-turn ferrite-core coil and a shunt capacitor. Optimized circuits enable efficient power transfer at low frequencies (45–140 kHz), addressing weak coupling and misalignment. ICOPS operates effectively up to 14 cm longitudinally, 9 cm laterally, and at 75° rotation relative to the magnetic field. Specific absorption rate (SAR) analysis confirms exposure within safe occupational limits at 6 A and 45/63 kHz. In vivo validation using an in vivo imaging system (IVIS) and micro-computed tomography (µCT) confirms functionality and safety. ICOPS is the first rodent-scale ingestible capsule fabricated entirely in-house using 3D printing, without the need for cleanroom facilities, providing a compact, scalable platform for non-invasive optogenetic modulation of enteric circuits.

RBD-VLP Vaccines Adjuvanted with Alum or SWE Protect K18-hACE2 Mice against SARS-CoV-2 VOC Challenge

Mon, 15 Aug 2022 00:00:00 GMT

RBD-VLP Vaccines Adjuvanted with Alum or SWE Protect K18-hACE2 Mice against SARS-CoV-2 VOC Challenge Wong, Ting Y; Russ, Brynnan P; Lee, Katherine S; Miller, Olivia A; Kang, Jason; Cooper, Melissa; Winters, Michael T; Rodriguez-Aponte, Sergio A; Dalvie, Neil C; Johnston, Ryan S; Rader, Nathaniel A; Wong, Zeriel Y; Cyphert, Holly A; Martinez, Ivan; Shaligram, Umesh; Batwal, Saurabh; Lothe, Rakesh; Chandrasekaran, Rahul; Nagar, Gaurav; Rajurkar, Meghraj; Rao, Harish; Bevere, Justin R; Barbier, Mariette; Love, J Christopher; Damron, F Heath The ongoing COVID-19 pandemic has contributed largely to the global vaccine disparity. Development of protein subunit vaccines can help alleviate shortages of COVID-19 vaccines delivered to low-income countries. Here, we evaluated the efficacy of a three-dose virus-like particle (VLP) vaccine composed of hepatitis B surface antigen (HBsAg) decorated with the receptor binding domain (RBD) from the Wuhan or Beta SARS-CoV-2 strain adjuvanted with either aluminum hydroxide (alum) or squalene in water emulsion (SWE). RBD HBsAg vaccines were compared to the standard two doses of Pfizer mRNA vaccine. Alum-adjuvanted vaccines were composed of either HBsAg conjugated with Beta RBD alone (b RBD HBsAg1Al) or a combination of both Beta RBD HBsAg and Wuhan RBD HBsAg (b/Wu RBD HBsAg1Al). RBD vaccines adjuvanted with SWE were formulated with Beta RBD HBsAg (b RBD HBsAg1SWE) or without HBsAg (b RBD1SWE). Both alum-adjuvanted RBD HBsAg vaccines generated functional RBD IgG against multiple SARS-CoV-2 variants of concern (VOC), decreased viral RNA burden, and lowered inflammation in the lung against Alpha or Beta challenge in K18-hACE2 mice. However, only b/Wu RBD HBsAg1Al was able to afford 100% survival to mice challenged with Alpha or Beta VOC. Furthermore, mice immunized with b RBD HBsAg1SWE induced cross-reactive neutralizing antibodies against major VOC of SARS-CoV-2, lowered viral RNA burden in the lung and brain, and protected mice from Alpha or Beta challenge similarly to mice immunized with Pfizer mRNA. However, RBD1SWE immunization failed to protect mice from VOC challenge. Our findings demonstrate that RBD HBsAg VLP vaccines provided similar protection profiles to the approved Pfizer mRNA vaccines used worldwide and may offer protection against SARS-CoV-2 VOC.

On Monoid Algebras Having Every Nonempty Subset of N ≥ 2 as a Length Set

Sat, 12 Apr 2025 00:00:00 GMT

On Monoid Algebras Having Every Nonempty Subset of N ≥ 2 as a Length Set Geroldinger, Alfred; Gotti, Felix We construct monoid algebras that satisfy the ascending chain condition on principal ideals and have the property that every nonempty subset of N ≥ 2 occurs as a length set.

The Psyche Multispectral Imager Investigation: Characterizing the Geology, Topography, and Multispectral Properties of a Metal-Rich World

Wed, 21 May 2025 00:00:00 GMT

The Psyche Multispectral Imager Investigation: Characterizing the Geology, Topography, and Multispectral Properties of a Metal-Rich World Bell, J. F.; Ravine, M. A.; Caplinger, M. A.; Schaffner, J. A.; Brylow, S. M.; Clark, M. J.; Peckham, D. A.; Otjens, P. T.; Price, G. J.; Rowell, T.; Ravine, J. W.; Laramee, J. D.; Juergens, R. C.; Morgan, W.; Parker, A. G. The Psyche Multispectral Imager (“the Imager”) is a payload system designed to directly achieve or to indirectly enable the key scientific goals and optical navigation requirements of NASA’s Psyche mission, which will conduct the first up-close orbital investigation of the metal-rich Main Belt asteroid (16) Psyche. The Imager consists of a pair of block redundant cameras and electronics that are mounted inside the thermally controlled spacecraft body, with a view out the spacecraft −X panel that will be nadir-pointed during nominal asteroid orbital mapping operations. The two identical Camera Heads are connected to a separate Digital Electronics Assembly (DEA) box that interfaces to the spacecraft avionics and that provides power, commanding, data processing, and onboard image storage. The Imager system shares significant heritage with imaging instruments flown on the Mars Climate Orbiter, the Mars Science Laboratory and Mars 2020 rovers, and Juno. Each camera consists of a 1600 × 1200 photosensitive pixel charge-coupled device (CCD) detector and its associated electronics, a 9-position filter wheel assembly, a compact catadioptric f /2.9 telescope with a fixed focal length of 148 mm, and a sunshade to minimize stray and scattered light. The Imager CCD, filters, and optics enable broadband polychromatic (∼540 ± 250 nm) imaging plus narrowband imaging in 7 colors centered from 439 to 1015 nm. An additional neutral density filter enables protection of the CCD from direct solar illumination. Each camera has a field of view of 4.6° × 3.4° and an instantaneous field of view of 50 μrad/pixel that enables imaging of the asteroid at scales ranging from ∼35 m/pix from 700 km altitude to ∼4 m/pix at 75 km altitude. The primary camera (“Imager A”) is pointed along the spacecraft −X axis, and the backup camera (“Imager B”) is toed-out by 3.7° to potentially enable greater surface area coverage per unit time if both Imagers are operated simultaneously during some mission phases. Stereoscopic mapping is performed by observing the same surface regions with either camera over a range of off-nadir pointing angles.

Mechanobiochemical finite element model to analyze impact-loading-induced cell damage, subsequent proteoglycan loss, and anti-oxidative treatment effects in articular cartilage

Sat, 10 May 2025 00:00:00 GMT

Mechanobiochemical finite element model to analyze impact-loading-induced cell damage, subsequent proteoglycan loss, and anti-oxidative treatment effects in articular cartilage Kosonen, Joonas P.; Eskelinen, Atte S. A.; Orozco, Gustavo A.; Coleman, Mitchell C.; Goetz, Jessica E.; Anderson, Donald D.; Grodzinsky, Alan J.; Tanska, Petri; Korhonen, Rami K. Joint trauma often leads to articular cartilage degeneration and post-traumatic osteoarthritis (PTOA). Pivotal determinants include trauma-induced excessive tissue strains that damage cartilage cells. As a downstream effect, these damaged cells can trigger cartilage degeneration via oxidative stress, cell death, and proteolytic tissue degeneration. N-acetylcysteine (NAC) has emerged as an antioxidant capable of inhibiting oxidative stress, cell death, and cartilage degeneration post-impact. However, the temporal effects of NAC are not fully understood and remain difficult to assess solely by physical experiments. Thus, we developed a computational finite element analysis framework to simulate a drop-tower impact of cartilage in Abaqus, and subsequent oxidative stress-related cell damage, and NAC treatment upon cartilage proteoglycan content in Comsol Multiphysics, based on prior ex vivo experiments. Model results provide evidence that immediate NAC treatment can reduce proteoglycan loss by mitigating oxidative stress, cell death (improved proteoglycan biosynthesis), and enzymatic proteoglycan depletion. Our simulations also indicate that delayed NAC treatment may not inhibit cartilage proteoglycan loss despite reduced cell death after impact. These results enhance understanding of the temporal effects of impact-related cell damage and treatment that are critical for the development of effective treatments for PTOA. In the future, our modeling framework could increase understanding of time-dependent mechanisms of oxidative stress and downstream effects in injured cartilage and aid in developing better treatments to mitigate PTOA progression.

The three-point energy correlator in the coplanar limit

Mon, 04 Aug 2025 00:00:00 GMT

The three-point energy correlator in the coplanar limit Gao, Anjie; Yang, Tong-Zhi; Zhang, Xiaoyuan Energy correlators are a type of observables that measure how energy is distributed across multiple detectors as a function of the angles between pairs of detectors. In this paper, we study the three-point energy correlator (EEEC) at lepton colliders in the three-particle near-to-plane (coplanar) limit. The leading-power contribution in this limit is governed by the three-jet (trijet) configuration. We introduce a new approach by projecting the EEEC onto the volume of the parallelepiped formed by the unit vectors aligned with three detected final-state particles. Analogous to the back-to-back limit of the two-point energy correlator probing the dijet configuration, the small-volume limit of the EEEC probes the trijet configuration. We derive a transverse momentum dependent (TMD) based factorization theorem that captures the soft and collinear logarithms in the coplanar limit, which enables us to achieve the next-to-next-to-next-to-leading logarithm (N3LL) resummation. To our knowledge, this is the first N3LL result for a trijet event shape. Additionally, we demonstrate that a similar factorization theorem can be applied to the fully differential EEEC in the three-particle coplanar limit, which provides a clean environment for studying different coplanar trijet shapes.

Reduction of Plane Quartics and Cayley Octads

Mon, 02 Jun 2025 00:00:00 GMT

Reduction of Plane Quartics and Cayley Octads van Bommel, Raymond; Docking, Jordan; Dokchitser, Vladimir; Lercier, Reynald; Lorenzo García, Elisa We give a conjectural characterisation of the stable reduction of plane quartics over local fields in terms of their Cayley octads. This results in p-adic criteria that efficiently give the stable reduction type amongst the 42 possible types, and whether the reduction is hyperelliptic or not. These criteria are in the vein of the machinery of “cluster pictures” for hyperelliptic curves. We also construct explicit families of quartic curves that realise all possible stable types, against which we test these criteria. We give numerical examples that illustrate how to use these criteria in practice.

How Exceptional Is the Ear?

Mon, 12 May 2025 00:00:00 GMT

How Exceptional Is the Ear? Bergevin, Christopher; Freeman, Dennis M.; Coffin, Allison Studies of hearing often conclude that the ear is “remarkable” or that its performance is “exceptional.” Some common examples include the following: ▹ the ears of mammals are encased in the hardest bone in the body; ▹ the ear contains the most vascularized tissue in body; ▹ the ear has the highest resting potential in the body; ▹ ears have a unique “fingerprint”; ▹ the ear can detect signals below the thermal noise floor; and ▹ the ear is highly nonlinear (or highly linear, depending upon who you ask). Some claims hold up to further scrutiny, while others do not. Additionally, several claims hold for animals in one taxon, while others are shared across taxa. Most frequently, our sense of wonder results from the differences between ears as products of natural selection (over eons) and artificial systems as products of engineering design. Our goal in analyzing claims of remarkable or exceptional performance is to deepen our appreciation of these differences.

Somato‐Cognitive Action Network in Focal Dystonia

Thu, 28 Aug 2025 00:00:00 GMT

Somato‐Cognitive Action Network in Focal Dystonia Wang, Yuchao; Huynh, Baothy; Ren, Jianxun; Chen, Mo; Zhang, Wei; Hu, Dan; Li, Shasha; Liu, Hesheng; Kimberley, Teresa J. Background The central pathology causing idiopathic focal dystonia remains unclear. The recently identified somato-cognitive action network (SCAN) has been implicated. Objective We tested whether the effector-agnostic SCAN may constitute a central pathology shared across dystonia subtypes, whereas the effector-specific regions in the primary sensorimotor cortex may show distinct functional changes specific to the dystonic body part. Methods We collected functional magnetic resonance imaging (MRI) from patients with focal dystonia (laryngeal dystonia [LD], N = 24; focal hand dystonia [FHD], N = 18) and healthy control participants (N = 21). Regions of interest were selected a priori within the basal ganglia-thalamo-cortical and cerebello-thalamo-cortical sensorimotor pathways. We investigated dystonia-dependent resting-state connectivity changes: between SCAN and related cortical regions, between cortical and noncortical regions, and among noncortical regions. Cortical network boundaries were individualized based on resting-state data. Separately, individualized hand and mouth/larynx regions were also generated from task-based MRI (finger-tapping and phonation, respectively) for comparison. Results Both focal dystonia subtypes showed significant functional changes (P = 0.048 for LD, P = 0.017 for FHD) compared to controls, driven by SCAN's higher functional connectivity to task-based mouth/larynx region and concomitantly lower connectivity to the cingulo-opercular network. No significant subcortical or cerebellar changes were observed when LD and FHD were modeled as independent groups. However, exploratory analysis combining LD and FHD suggested a dystonia-dependent asynchronization between SCAN and sensorimotor cerebellum (P = 0.010) that may indicate a pathological rather than compensatory process. Conclusions We demonstrate that SCAN is uniquely associated with focal dystonia dysfunction beyond the dystonic effector regions, offering insights into pathophysiology and treatments. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming

Wed, 02 Jul 2025 00:00:00 GMT

A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming Lu, Haihao; Yang, Jinwen Convex quadratic programming (QP) is an important class of optimization problem with wide applications in practice. The classic QP solvers are based on either simplex or barrier method, both of which suffer from the scalability issue because their computational bottleneck is solving linear equations. In this paper, we design and analyze a first-order method for QP, called restarted accelerated primal-dual hybrid gradient (rAPDHG), whose computational bottleneck is matrix-vector multiplication. We show that rAPDHG has a linear convergence rate to an optimal solution when solving QP, and the obtained linear rate is optimal among a wide class of primal-dual methods. Furthermore, we connect the linear rate with a sharpness constant of the KKT system of QP, which is a standard quantity to measure the hardness of a continuous optimization problem. Numerical experiments demonstrate that both restarts and acceleration can significantly improve the performance of the algorithm. Lastly, we present PDQP.jl, an open-source solver based on rAPDHG that can be run on both GPU and CPU. With a numerical comparison with SCS and OSQP on standard QP benchmark sets and large-scale synthetic QP instances, we demonstrate the effectiveness of rAPDHG for solving QP.

Effect of Iron Oxidation State on Solvent Extraction Scandium Extraction Process from Bauxite Residue and Life Cycle Assessment

Mon, 15 Sep 2025 00:00:00 GMT

Effect of Iron Oxidation State on Solvent Extraction Scandium Extraction Process from Bauxite Residue and Life Cycle Assessment Braz, Vitor M. P.; Vaccari, Mentore; Espinosa, Denise C. R.; Tenório, Jorge A. S.; Botelho Junior, Amilton B. The extraction of Sc from bauxite residue (also known as red mud) is a promising but challenging secondary source due to the high Fe content, reducing efficiency. This study investigated the impact of Fe on Sc recovery by solvent extraction and evaluated the environmental impact of the process. A hydrometallurgical route was chosen for Sc extraction involving leaching with H2SO4 followed by solvent extraction with Cyanex 923 and Alamine 336. Synergistic combination of these extractants was tested to increase selectivity. Results showed that Cyanex 923 extracted nearly 100% of the Sc, but the co-extraction of Fe (25–80%) remained a significant challenge. A combination of Cyanex 923 and Alamine 336 improved Sc selectivity by minimizing Fe extraction at pH 0.5–1.0 (< 20%). LCA indicated that leaching had the greatest environmental impact due to high energy consumption, while solvent extraction also contributed considerably because of kerosene use for dilution. The highest environmental impact is on ozone depletion in all steps of the process (leaching and solvent extraction). Synergistic use of Cyanex 923 and Alamine 336 is an efficient strategy for Sc extraction with low Fe co-extraction. Further optimizations are needed for the industrial scale, particularly concerning environmental impacts.

Membrane Application in Hydrometallurgical Processing

Tue, 18 Feb 2025 00:00:00 GMT

Membrane Application in Hydrometallurgical Processing Botelho Junior, Amilton B.; Peng, Hong; Kim, Jihye Critical minerals are crucial for energy transition and for the success of commercialization of hydro power, wind turbines, and photovoltaic panels. The increasing demand puts pressure on the search for new sources, including new mining sites, tailings, and urban solid wastes. Membrane-based separation is well-stated for water desalination and wastewater treatment. Recently, the search for new processes to recover critical minerals in aqueous processing has shed light on its potential application. Electrodialysis has demonstrated a mature electrochemical separation technique, while supported liquid membranes have great potential for future developments. Membrane cost represents the main drawback, and for this reason new materials are under development including synthesis for a specific critical mineral, such as Li and rare earth elements.

Review of The Rhetoricity of Philosophy: Audience in Perelman and Ricoeur After the Badiou-Cassin Debate

Sat, 06 Sep 2025 00:00:00 GMT

Review of The Rhetoricity of Philosophy: Audience in Perelman and Ricoeur After the Badiou-Cassin Debate Schiappa, Edward In this well-written and superbly researched book, Blake D. Scott uses the “debate” between Alain Badiou and Barbara Cassin as a point of departure to revisit the longstanding tension between philosophy and rhetoric. Through substantial exegeses of the work of Chaïm Perelman and Lucie Olbrechts‑Tyteca, as well as selected writings by Paul Ricœur, Scott rejects the conventional view that philosophy and rhetoric are separate disciplines. He argues instead for their asymmetrical interdependence: rhetoric is constitutive of philosophical practice. Central to his thesis is the concept of rhetoricity—the rhetorical dimension inherent in all discourse by virtue of the human “rhetorical capacity,” our ability to reflect on audiences and the potential for persuasion.

Household Portfolios and Retirement Saving over the Life Cycle

Tue, 12 Aug 2025 00:00:00 GMT

Household Portfolios and Retirement Saving over the Life Cycle PARKER, JONATHAN A; SCHOAR, ANTOINETTE; COLE, ALLISON; SIMESTER, DUNCAN Using account-level data on millions of U.S. middle-class investors over 2006 to 2018, we characterize the share of investable wealth that they hold in the stock market over their working lives. Relative to the 1990s, this share has both risen by 10% and become age-dependent. The Pension Protection Act (PPA)—which allowed target date funds (TDFs) to be default options in retirement plans—played an important role: younger (older) workers starting at a firm after TDFs became the default option post-PPA invested more (less) in stocks, in line with the TDF glidepath. In contrast, contribution rates changed little following the PPA.

How Many Americans Work Remotely? A Survey of Surveys and Their Measurement Issues

Tue, 28 Oct 2025 00:00:00 GMT

How Many Americans Work Remotely? A Survey of Surveys and Their Measurement Issues Brynjolfsson, Erik; Horton, John; Makridis, Christos; Mas, Alex; Ozimek, Adam; Rock, Daniel; TuYe, Hong‐Yi Remote work surged during the COVID-19 pandemic, but estimates vary widely. To address this, we field the Remote Life Survey (RLS), a nationally representative survey. In October 2020, we find that 31.6% of continuously employed workers always worked from home (WFH), and 21.9% did so sometimes or rarely, totaling 53.5%. We compare our results with government surveys and assess four factors contributing to measurement differences: (a) web versus mail-based respondents, (b) inclusion of self-employed workers, (c) occupation mix, and (d) exclusion of pre-pandemic remote workers. We find that (d) explains most of the discrepancy between the Current Population Survey (CPS) and other measures. Policymakers and researchers relying on CPS data should note that it may underestimate remote work prevalence by up to 25 percentage points. Our preferred estimates suggest that about half of the U.S. workforce worked remotely at least one day per week as of December 2020.

The Impact of Internal Variability on Benchmarking Deep Learning Climate Emulators

Tue, 26 Aug 2025 00:00:00 GMT

The Impact of Internal Variability on Benchmarking Deep Learning Climate Emulators Lütjens, Björn; Ferrari, Raffaele; Watson‐Parris, Duncan; Selin, Noelle E Full-complexity Earth system models (ESMs) are computationally very expensive, limiting their use in exploring the climate outcomes of multiple emission pathways. More efficient emulators that approximate ESMs can directly map emissions onto climate outcomes, and benchmarks are being used to evaluate their accuracy on standardized tasks and data sets. We investigate a popular benchmark in data-driven climate emulation, ClimateBench, on which deep learning-based emulators are currently achieving the best performance. We compare these deep learning emulators with a linear regression-based emulator, akin to pattern scaling, and show that it outperforms the incumbent 100M-parameter deep learning foundation model, ClimaX, on 3 out of 4 regionally resolved climate variables, notably surface temperature and precipitation. While emulating surface temperature is expected to be predominantly linear, this result is surprising for emulating precipitation. Precipitation is a much more noisy variable, and we show that deep learning emulators can overfit to internal variability noise at low frequencies, degrading their performance in comparison to a linear emulator. We address the issue of overfitting by increasing the number of climate simulations per emission pathway (from 3 to 50) and updating the benchmark targets with the respective ensemble averages from the MPI-ESM1.2-LR model. Using the new targets, we show that linear pattern scaling continues to be more accurate on temperature, but can be outperformed by a deep learning-based technique for emulating precipitation. We publish our code and data at https://github.com/blutjens/climate-emulator.

Don’t Just Send in the Chiefs

Tue, 19 Apr 2022 00:00:00 GMT

Don’t Just Send in the Chiefs Wright, Randall S. A few years ago, my wife and I visited the aircraft carrierMidway on a vacation to San Diego. The Midway is one ofthe largest aircraft carriers ever built. It was to be deployedin World War II, but the war ended before the Midway couldbe commissioned. It was the largest ship in the US Navy until1955 and the first aircraft carrier too big to pass through thePanama Canal. The ship was in service for 47 years, includingthe Vietnam War and Operation Desert Storm. It’s now afloating museum (Wikimedia Foundation 2022).

Updated measurement of CP violation and polarisation in B s 0 → J / ψ K ¯ ∗ 892 0 decays

Tue, 21 Oct 2025 00:00:00 GMT

Updated measurement of CP violation and polarisation in B s 0 → J / ψ K ¯ ∗ 892 0 decays Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; The LHCb Collaboration A time-integrated angular analysis of the decay B s 0 → J / ψ K ¯ ∗ 892 0 , with J/ψ → μ+μ− and K ¯ ∗ 892 0 → K − π + , is presented. The analysis employs a sample of proton-proton collision data collected by the LHCb experiment during 2015–2018 at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb−1. A simultaneous maximum-likelihood fit is performed to the angular distributions in bins of the K−π+ mass. This fit yields measurements of the CP-averaged polarisation fractions and CP asymmetries for the P-wave component of the K−π+ system. The longitudinal and parallel polarisation fractions are determined to be f0 = 0.534 ± 0.012 ± 0.009 and f|| = 0.211 ± 0.014 ± 0.005, respectively, where the first uncertainty is statistical and the second is systematic. The CP asymmetries are measured with 3–7% precision and are found to be consistent with zero. These measurements, along with an updated determination of the branching fraction relative to the B0 → J/ψK*0 decay, are combined with previous LHCb results, providing the most precise values for these observables to date.

Measurements of inclusive and differential Higgs boson production cross sections at √s = 13.6 TeV in the H → γγ decay channel

Mon, 08 Sep 2025 00:00:00 GMT

Measurements of inclusive and differential Higgs boson production cross sections at √s = 13.6 TeV in the H → γγ decay channel Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Damanakis, K.; Dragicevic, M.; Giordano, C.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; The CMS Collaboration Inclusive and differential cross sections for Higgs boson production in protonproton collisions at a centre-of-mass energy of 13.6 TeV are measured using data collected with the CMS detector at the LHC in 2022, corresponding to an integrated luminosity of 34.7 fb−1 . Events with the diphoton final state are selected, and the measured inclusive fiducial cross section is σfid = 74±11 (stat)+5 −4 (syst) fb, in agreement with the standard model prediction of 67.8 ± 3.8 fb. Differential cross sections are measured as functions of several observables: the Higgs boson transverse momentum and rapidity, the number of associated jets, and the transverse momentum of the leading jet in the event. Within the uncertainties, the differential cross sections agree with the standard model predictions.

On the structure of multiple stable equilibria in competitive ecological systems

Mon, 06 Oct 2025 00:00:00 GMT

On the structure of multiple stable equilibria in competitive ecological systems Taylor, Washington; O’Dwyer, James For some ecological systems with a large pool of possible species, there can be multiple stable equilibria with different species composition. Natural or anthropogenic disruption can induce a shift between different such equilibria. While some work has been done on ecological systems with multiple equilibria, there is no general theory governing the distribution of equilibria or characterizing the basins of attraction of different equilibria. This article addresses these questions in a simple class of Lotka-Volterra models. We focus on competitive systems of species on a niche axis with multiple equilibria. We find that basins of attraction are generally larger for equilibria with greater biomass; in many cases, the basin of attraction size scales roughly exponentially with the net biomass of equilibria. This is illustrated in two ecologically relevant limits. In a continuous limit with species spaced arbitrarily closely on the niche axis, equilibria with different numbers of species provide a new perspective on the notion of limiting similarity. In another limit, akin to a statistical mechanical model, the niche axis becomes infinite while the range of interactions remains fixed; in this limit, we prove the exponential relation between basin size and biomass using the Markov chain central limit theorem.

Measurement of branching fractions and CP asymmetries in Λ b 0 Ξ b 0 → p K S 0 h − decays

Tue, 21 Oct 2025 00:00:00 GMT

Measurement of branching fractions and CP asymmetries in Λ b 0 Ξ b 0 → p K S 0 h − decays Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; The LHCb Collaboration A study of Λ b 0 and Ξ b 0 baryon decays to the final states p K S 0 π − and p K S 0 K − is performed using pp collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb−1. The decays Λ b 0 → p K S 0 K − and Ξ b 0 → p K S 0 K − are observed for the first time, with significances reaching eight standard deviations. The branching fractions and integrated CP asymmetries are measured for the Λ b 0 → p K S 0 π − , Λ b 0 → p K S 0 K − , and Ξ b 0 → p K S 0 K − decays. For the decay Λ b 0 → p K S 0 π − , the CP asymmetries are measured in different regions of the Dalitz plot. No evidence of CP violation is observed.

(Not so) universal literacy screening: a survey of educators reveals variability in implementation

Wed, 29 Oct 2025 00:00:00 GMT

(Not so) universal literacy screening: a survey of educators reveals variability in implementation Ozernov-Palchik, Ola; Elizee, Zoe; Catania, Fabio; Hacikamiloglu, Meral; Shattuck-Hufnagel, Stefanie; Petscher, Yaacov; Ghosh, Satrajit; Gabrieli, John D. E. Currently, most states in the United States have enacted legislation mandating universal screening for literacy risk in kindergarten through 3rd grade. However, the degree to which these policies translate into consistent, high-quality screening practices remains unclear. In this survey study, we collected responses from a diverse sample of K–3 educators (N = 251) across 39 states, representing varied school types, professional roles, and experience levels, to examine the real-world implementation of universal screening. Guided by the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework, we analyzed quantitative and qualitative data to identify real-world factors that could impede the fidelity and effectiveness of screening implementation. We found substantial variability across multiple dimensions of literacy screening implementation. Educators described considerable variation in screener selection, administration practices, testing environments, training quality, scoring accuracy, and the use of results to guide intervention. Notably, many indicated insufficient training and professional development, expressing uncertainty about administering and interpreting screeners, particularly for English language learners. Nearly half also reported the absence of systematic procedures for developing intervention plans, suggesting that many students identified as at risk do not receive appropriate follow-up support. These implementation challenges occurred despite widespread recognition among educators of screening’s importance for early literacy intervention. Educators from lower-socioeconomic status schools reported significantly greater time burdens in conducting screenings and more technology-related challenges compared to their higher-SES counterparts. Without systematic improvements to implementation support and training, current screening initiatives may fail to achieve their intended goal of early identification and intervention for struggling readers.

Development of a Compton imager setup

Tue, 04 Nov 2025 00:00:00 GMT

Development of a Compton imager setup Arya, Anuraag; Bilkhu, Harmanjeet S.; Vishwakarma, Sandeep; Belatikar, Hrishikesh; Bhalerao, Varun; Ghodgaonkar, Abhijeet; Koyande, Jayprakash G.; Marathe, Aditi; Mithun, N. P. S.; Narang, Sanjoli; Nimbalkar, Sudhanshu; Page, Pranav; Palit, Sourav; Patel, Arpit; Shetye, Amit; Tallur, Siddharth Hard X-ray photons with energies in the range of hundreds of keV typically undergo Compton scattering when they are incident on a detector. In this process, an incident photon deposits a fraction of its energy at the point of incidence and continues onwards with a change in direction that depends on the amount of energy deposited. By using a pair of detectors to detect the point of incidence and the direction of the scattered photon, we can calculate the scattering direction and angle. The position of a source in the sky can be reconstructed using many Compton photon pairs from a source. We demonstrate this principle in the laboratory by using a pair of Cadmium Zinc Telluride (CZT) detectors sensitive in the energy range of 20–200 keV, similar to those used in AstroSat/CZT Imager (CZTI). The laboratory setup consists of two detectors placed perpendicular to each other in a lead-lined box. The detectors are read out by a custom-programmed Xilinx PYNQ-Z2 FPGA board, and data are then transferred to a personal computer (PC). There are two key updates from CZTI: the detectors are read concurrently rather than serially, and the time resolution has been improved from 20 to 7.5 μ s. We irradiated the detectors with a collimated 133 Ba source and identified Compton scattering events for the 356 keV line. We run a Compton reconstruction algorithm to correctly infer the location of the source in the detector frame, with a location-dependent angular response measure of 16 ∘ –30 ∘ . This comprises a successful technology demonstration for a Compton imaging camera in the hard X-ray regime. We present the details of our setup, the data acquisition process, and software algorithms, and showcase our results. We also quantify the limitations of this setup and discuss ways of improving the performance in future experiments.

The Situation Awareness Framework for Explainable AI (SAFE-AI) and Human Factors Considerations for XAI Systems

Wed, 22 Jun 2022 00:00:00 GMT

The Situation Awareness Framework for Explainable AI (SAFE-AI) and Human Factors Considerations for XAI Systems Sanneman, Lindsay; Shah, Julie A Recent advances in artificial intelligence (AI) have drawn attention to the need for AI systems to beunderstandable to human users. The explainable AI (XAI) literature aims to enhance human under-standing and human-AI team performance by providing users with necessary information about AI sys-tem behavior. Simultaneously, the human factors literature has long addressed importantconsiderations that contribute to human performance, including how to determine human informa-tional needs, human workload, and human trust in autonomous systems. Drawing from the human fac-tors literature, we propose the Situation Awareness Framework for Explainable AI (SAFE-AI), a three-level framework for the development and evaluation of explanations about AI system behavior. Ourproposed levels of XAI are based on the informational needs of human users, which can be deter-mined using the levels of situation awareness (SA) framework from the human factors literature. Basedon our levels of XAI framework, we also suggest a method for assessing the effectiveness of XAI sys-tems. We further detail human workload considerations for determining the content and frequency ofexplanations as well as metrics that can be used to assess human workload. Finally, we discuss theimportance of appropriately calibrating user trust in AI systems through explanations along with othertrust-related considerations for XAI, and we detail metrics that can be used to evaluate user trust inthese systems.

Remove hydrogen and store it too: an acid-in-clay based electro-chemical solution

Thu, 14 Nov 2024 00:00:00 GMT

Remove hydrogen and store it too: an acid-in-clay based electro-chemical solution Kim, Kyung-Shik; Park, Jin-Sung; Yoon, Young-Chul; Kim, Jinwoo; Li, Ju; Yildiz, Bilge; Tasan, Cemal Cem Extracting hydrogen from metallic components can open up a new pathway for preventing hydrogen embrittlement. To this end, we propose an electrochemically driven, all-solid method for hydrogen control, capable of both extracting and storing hydrogen simultaneously. In this approach, we employ acid-in-clay as a proton conducting electrolyte at room temperature. Through this electrochemical treatment, hydrogen is efficiently extracted from pre-charged steels, thereby restoring their tensile properties and preventing embrittlement. Moreover, it has been confirmed that the extracted hydrogen can be efficiently collected at the counter electrode, demonstrating the significant advantages of the process.

Contrasting interchain order and mixed ionic–electronic conduction in conjugated polymers: an isoindigo case study

Tue, 22 Oct 2024 00:00:00 GMT

Contrasting interchain order and mixed ionic–electronic conduction in conjugated polymers: an isoindigo case study Meacham, Rebecca F; Roh, Heejung; Cunin, Camille E; Lee, Eric R; Li, Wenhao; Zhao, Yan; Samal, Sanket; Gumyusenge, Aristide In mixed ionic–electronic conductive polymers, electronic conduction is optimal in tightly packed flat chains, while ionic conduction benefits from free volume accommodating large ions. To this end, polymers with high crystallinity are often excluded from structure–property studies of high-performing mixed conductors due to their unbalanced transport, which favors electronic charges over ionic ones. Herein, we investigated how mixed conduction can be achieved in ordered conjugated polymers by systematically combining interchain order with side chain engineering. We synthesized a series of isoindigo (IID)-based copolymers with varying amounts of aliphatic and hydrophilic side chains and examined the impact of interchain order on mixed conduction. Through crystallographic, spectro-electrochemical, and molecular dynamics studies, we demonstrated that systematically introducing hydrophilic side chains reduces the bulk order and long-range aggregation by increasing chain flexibility while preserving the interchain stacking distances within crystalline domains. Testing these IID polymers in transistor devices revealed that ion insertion and device transconductance strongly depend on the amount of hydrophilic side chains. We demonstrated that glycol side chains can enhance mixed conduction while maintaining interchain order. Our findings suggest that the IID system is promising for designing polymers that can accommodate ionic species without compromising the chain ordering required for electronic conduction.

Molecular engineering of a cryptic epitope in Spike RBD improves manufacturability and neutralizing breadth against SARS-CoV-2 variants

Fri, 27 Jan 2023 00:00:00 GMT

Molecular engineering of a cryptic epitope in Spike RBD improves manufacturability and neutralizing breadth against SARS-CoV-2 variants Rodriguez-Aponte, Sergio A; Dalvie, Neil C; Wong, Ting Y; Johnston, Ryan S; Naranjo, Christopher A; Bajoria, Sakshi; Kumru, Ozan S; Kaur, Kawaljit; Russ, Brynnan P; Lee, Katherine S; Cyphert, Holly A; Barbier, Mariette; Rao, Harish D; Rajurkar, Meghraj P; Lothe, Rakesh R; Shaligram, Umesh S; Batwal, Saurabh; Chandrasekaran, Rahul; Nagar, Gaurav; Kleanthous, Harry; Biswas, Sumi; Bevere, Justin R; Joshi, Sangeeta B; Volkin, David B; Damron, F Heath; Love, J Christopher There is a continued need for sarbecovirus vaccines that can be manufactured and distributed in low- and middle-income countries (LMICs). Subunit protein vaccines are manufactured at large scales at low costs, have less stringent temperature requirements for distribution in LMICs, and several candidates have shown protection against SARS-CoV-2. We previously reported an engineered variant of the SARS-CoV-2 Spike protein receptor binding domain antigen (RBD-L452K-F490W; RBD-J) with enhanced manufacturability and immunogenicity compared to the ancestral RBD. Here, we report a second-generation engineered RBD antigen (RBD-J6) with two additional mutations to a hydrophobic cryptic epitope in the RBD core, S383D and L518D, that further improved expression titers and biophysical stability. RBD-J6 retained binding affinity to human convalescent sera and to all tested neutralizing antibodies except antibodies that target the class IV epitope on the RBD core. K18-hACE2 transgenic mice immunized with three doses of a Beta variant of RBD-J6 displayed on a virus-like particle (VLP) generated neutralizing antibodies (nAb) to nine SARS-CoV-2 variants of concern at similar levels as two doses of Comirnaty. The vaccinated mice were also protected from challenge with Alpha or Beta SARS-CoV-2. This engineered antigen could be useful for modular RBD-based subunit vaccines to enhance manufacturability and global access, or for further development of variant-specific or broadly acting booster vaccines.

Immunotherapy-induced neutralizing antibodies disrupt allergen binding and sustain allergen tolerance in peanut allergy

Tue, 17 Jan 2023 00:00:00 GMT

Immunotherapy-induced neutralizing antibodies disrupt allergen binding and sustain allergen tolerance in peanut allergy LaHood, Nicole A; Min, Jungki; Keswani, Tarun; Richardson, Crystal M; Amoako, Kwasi; Zhou, Jingjia; Marini-Rapoport, Orlee; Bernard, Hervé; Hazebrouck, Stéphane; Shreffler, Wayne G; Love, J Christopher; Pomes, Anna; Pedersen, Lars C; Mueller, Geoffrey A; Patil, Sarita U In IgE-mediated food allergies, exposure to the allergen activates systemic allergic responses. Oral immunotherapy (OIT) treats food allergies through incremental increases in oral allergen exposure. However, OIT only induces sustained clinical tolerance and decreased basophil sensitivity in a subset of individuals despite increases in circulating allergen-specific IgG in all treated individuals. Therefore, we examined the allergen-specific antibodies from 2 OIT cohorts of patients with sustained and transient responses. Here, we compared antibodies from individuals with sustained or transient responses and discovered specific tolerance-associated conformational epitopes of the immunodominant allergen Ara h 2 recognized by neutralizing antibodies. First, we identified what we believe to be previously unknown conformational, intrahelical epitopes using x-ray crystallography with recombinant antibodies. We then identified epitopes only recognized in sustained tolerance. Finally, antibodies recognizing tolerance-associated epitopes effectively neutralized allergen to suppress IgE-mediated effector cell activation. Our results demonstrate the molecular basis of antibody-mediated protection in IgE-mediated food allergy, by defining how these antibodies disrupt IgE-allergen interactions to prevent allergic reactions. Our approach to studying the structural and functional basis for neutralizing antibodies demonstrates the clinical relevance of specific antibody clones in antibody-mediated tolerance. We anticipate that our findings will form the foundation for treatments of peanut allergy using neutralizing antibodies and hypoallergens.

Tissue-specific abundance of interferon-gamma drives regulatory T cells to restrain DC1-mediated priming of cytotoxic T cells against lung cancer

Tue, 14 Feb 2023 00:00:00 GMT

Tissue-specific abundance of interferon-gamma drives regulatory T cells to restrain DC1-mediated priming of cytotoxic T cells against lung cancer Zagorulya, Maria; Yim, Leon; Morgan, Duncan M; Edwards, Austin; Torres-Mejia, Elen; Momin, Noor; McCreery, Chloe V; Zamora, Izabella L; Horton, Brendan L; Fox, James G; Wittrup, K Dane; Love, J Christopher; Spranger, Stefani Local environmental factors influence CD8+ T cell priming in lymph nodes (LNs). Here, we sought to understand how factors unique to the tumor-draining mediastinal LN (mLN) impact CD8+ T cell responses toward lung cancer. Type 1 conventional dendritic cells (DC1s) showed a mLN-specific failure to induce robust cytotoxic T cells responses. Using regulatory T (Treg) cell depletion strategies, we found that Treg cells suppressed DC1s in a spatially coordinated manner within tissue-specific microniches within the mLN. Treg cell suppression required MHC II-dependent contact between DC1s and Treg cells. Elevated levels of IFN-γ drove differentiation Treg cells into Th1-like effector Treg cells in the mLN. In patients with cancer, Treg cell Th1 polarization, but not CD8+/Treg cell ratios, correlated with poor responses to checkpoint blockade immunotherapy. Thus, IFN-γ in the mLN skews Treg cells to be Th1-like effector Treg cells, driving their close interaction with DC1s and subsequent suppression of cytotoxic T cell responses.

Minimal purification method enables developability assessment of recombinant proteins

Fri, 17 Mar 2023 00:00:00 GMT

Minimal purification method enables developability assessment of recombinant proteins Rodriguez‐Aponte, Sergio A; Naranjo, Christopher A; Johnston, Ryan S; Dalvie, Neil C; Crowell, Laura E; Bajoria, Sakshi; Kumru, Ozan S; Joshi, Sangeeta B; Volkin, David B; Love, J Christopher Analytical characterization of proteins is a critical task for developing therapeutics and subunit vaccine candidates. Assessing candidates with a battery of biophysical assays can inform the selection of one that exhibits properties consistent with a given target product profile (TPP). Such assessments, however, require several milligrams of purified protein, and ideal assessments of the physicochemical attributes of the proteins should not include unnatural modifications like peptide tags for purification. Here, we describe a fast two‐stage minimal purification process for recombinant proteins secreted by the yeast host Komagataella phaffii from a 20 mL culture supernatant. This method comprises a buffer exchange and filtration with a Q‐membrane filter and we demonstrate sufficient removal of key supernatant impurities including host‐cell proteins (HCPs) and DNA with yields of 1–2 mg and >60% purity. This degree of purity enables characterizing the resulting proteins using affinity binding, mass spectrometry, and differential scanning calorimetry. We first evaluated this method to purify an engineered SARS‐CoV‐2 subunit protein antigen and compared the purified protein to a conventional two‐step chromatographic process. We then applied this method to compare several SARS‐CoV‐2 RBD sequences. Finally, we show this simple process can be applied to a range of other proteins, including a single‐domain antibody, a rotavirus protein subunit, and a human growth hormone. This simple and fast developability methodology obviates the need for genetic tagging or full chromatographic development when assessing and comparing early‐stage protein therapeutics and vaccine candidates produced in K. phaffii.

Interstellar Mapping And Acceleration Probe: The NASA IMAP Mission

Thu, 30 Oct 2025 00:00:00 GMT

Interstellar Mapping And Acceleration Probe: The NASA IMAP Mission McComas, D. J.; Christian, E. R.; Schwadron, N. A.; Gkioulidou, M.; Allegrini, F.; Baker, D. N.; Bzowski, M.; Clark, G.; Cohen, C. M. S.; Cohen, I. NASA’s Interstellar Mapping and Acceleration Probe (IMAP) mission provides extensive and well-coordinated new observations of the inner and outer heliosphere and scientific closure on two of the most important topics in Heliophysics: 1) the acceleration of charged particles and 2) the interaction of the solar wind with the local interstellar medium. These topics are intimately coupled because particles accelerated in the inner heliosphere propagate outward through the solar wind and mediate its interaction with the very local interstellar medium (VLISM). The IMAP mission is designed to address these topics, provide extensive new real-time measurements critical to Space Weather observations and predictions, and much more. IMAP’s ten instruments are mounted on a simple, spinning spacecraft that orbits about the first Sun-Earth Lagrange point, L1, and repoints its Sun-facing solar arrays and spin axis toward the Sun each day. The instruments provide complete and synergistic observations that examine particle energization processes at 1 au while simultaneously probing the global heliospheric interaction with the VLISM. The 1 au in-situ observations include solar wind electrons and ions from solar wind through suprathermal energies, pickup and energetic ions, as well as the interplanetary magnetic field. IMAP provides Energetic Neutral Atom (ENA) global imaging of the outer heliosphere via ENAs from tens of eV up through hundreds of keV, as well as observations of interstellar neutral atoms traversing the heliosphere. IMAP also directly measures interstellar dust that enters the heliosphere and the solar-wind-modulated ultraviolet glow. This paper provides the mission overview for the full IMAP mission, acts as a roadmap to the other papers in this IMAP collection and provides the citable reference for the overall IMAP mission going forward.

The Passive Regolith Sampler: From Concept to Delivery to the Lunar Surface

Thu, 30 Oct 2025 00:00:00 GMT

The Passive Regolith Sampler: From Concept to Delivery to the Lunar Surface Stober, Keith J.; Dorrington, Scott; Rupasinghe, Dinuri; Mao, Claire; Romero, Elizabeth; Moswane, Rethabile; Zhang, Jackson; Mahfouth AlShehhi, Abdulla; Els, Sebastian G.; Wood, Danielle This paper outlines the development and testing of two light-weight, low-cost, passive sensors developed by the MIT Space Enabled Research Group that were delivered to the moon in 2023 onboard the Rashid-1 rover as part of the Emirates Lunar Mission. The Passive Regolith Sampler (PRS) is a simple device mounted to the wheels of the rover, containing an aluminum tray with a cover plate of perforated holes of varying size and spacing. The device uses the motion of the rover wheel to press the device into the lunar surface, capturing small samples of lunar regolith in the holes. The Passive Wax Thermometer (PWT) is a collection of 10 wax samples, contained in individual capsules covered with sapphire windows. Each wax sample is an alkane with a different melting temperature determined by its chemical formula. Each wax sample undergoes temperature-dependent changes in opacity, providing a method for inferring temperature via image analysis. In preparation for lunar surface operations, the Space Enabled team performed a series of laboratory experiments and analytical analyses aiming to replicate conditions expected to be encountered during the mission. These experiments and analyses explored the physical mechanisms of the rover/regolith interaction, the lighting and thermal conditions at the landing site, and the quality of images captured from the rover mast camera. This paper outlines the results of these experiments and analyses, and their influence on the design and operations planning for the two payloads. Due to landing anomalies, the 2023 mission did not complete lunar surface operations; further work is planned to explore future operational opportunities.

Von Neumann-Morgenstern stability and internal closedness in matching theory

Thu, 30 Oct 2025 00:00:00 GMT

Von Neumann-Morgenstern stability and internal closedness in matching theory Faenza, Yuri; Stein, Cliff; Wan, Jia Gale and Shapley’s stability criterion enjoys a rich mathematical structure, which propelled its application in various settings. Although immensely popular, the approach by Gale and Shapley cannot encompass all the different features that arise in applications, motivating the search for alternative solution concepts. We investigate alternatives that rely on the concept of internal stability, a notion introduced for abstract games by von Neumann and Morgenstern and motivated by the need of finding a set of mutually compatible solutions. The set of stable matchings is internally stable. However, the class of internally stable sets is much richer, for an internally stable set of matchings may also include unstable matchings and/or exclude stable ones. In this paper, we focus on two families of internally stable sets of matchings: von Neumann-Morgenstern stable and internally closed. We study algorithmic questions around those concepts in both the marriage and the roommate models. One of our results implies that, in the marriage model, internally closed sets are an alternative to stable matchings that is as tractable as stable matchings themselves, a fairly rare occurrence in the area. Both our positive and negative results rely on new structural insights and extensions of classical algebraic structures associated with sets of matchings, which we believe to be of independent interest.

Order-forcing in Neural Codes

Tue, 28 Oct 2025 00:00:00 GMT

Order-forcing in Neural Codes Jeffs, R. A.; Lienkaemper, Caitlin; Youngs, Nora Convex neural codes are subsets of the Boolean lattice that record the intersection patterns of convex sets in Euclidean space. Much work in recent years has focused on finding combinatorial criteria on codes that can be used to classify whether or not a code is convex. In this paper we introduce order-forcing, a combinatorial tool which recognizes when certain regions in a realization of a code must appear along a line segment between other regions. We use order-forcing to construct novel examples of non-convex codes, and to expand existing families of examples. We also construct a family of codes which shows that a dimension bound of Cruz, Giusti, Itskov, and Kronholm (referred to as monotonicity of open convexity) is tight in all dimensions.

Co-evolution of alpha-helical transmembrane protein residues: large-scale variant profiling and complete mutational landscape of 2277 known PDB entries representing 504 unique human protein sequences

Wed, 24 Sep 2025 00:00:00 GMT

Co-evolution of alpha-helical transmembrane protein residues: large-scale variant profiling and complete mutational landscape of 2277 known PDB entries representing 504 unique human protein sequences Karagöl, Taner; Karagöl, Alper; Zhang, Shuguang Membrane proteins play fundamental roles in cellular function, yet the evolutionary dynamics of their amino acid composition remain poorly understood. Our current study investigates the substitutional landscape and evolutionary patterns of hydrophilic and hydrophobic residues in membrane α-helical proteins, addressing a significant gap in our knowledge of protein evolution. We analyzed 2277 high-resolution protein structures from the RCSB Protein Data Bank corresponding to 458 unique PDB structures, 504 UniProt transmembrane entries and their AlphaMissense predicted mutational libraries including more than 5.8 million amino acid substitutions, focusing on known transmembrane α-helical proteins in Homo sapiens. Our analysis showed that the pathological outcome of the substitutions is diverse, as nonpolar to polar changes showed higher pathological scores in general. Notably, F <=> Y substitutions showed significantly lower pathological scores. Our further analysis revealed a significant asymmetry in the evolutionary frequencies of polar and nonpolar amino acids. We identified key residue pairs driving this asymmetry, with F <=> Y, A <=> T, V <=> T and A <=> S co-evolution diverging from the expected negative correlations (Spearman’s rho > 0.20, p < 0.001). The V <=> T substitution via an alanine intermediate and the G <=> N substitution via a serine intermediate lower their statistical barrier, which would otherwise require two sequential base changes. We propose two evolutionary game theory (EGT) based models to explain their diversification, with partial correlation analysis on residue frequencies in homolog sequences. These mathematical insights suggest a previously unrecognized evolutionary pressure, potentially linked to functional diversification, which could be targeted to combat drug resistance. Our results offer insights into membrane protein evolution and may inform improved methods for protein structure prediction and design.

Perforation of the host cell plasma membrane during Toxoplasma invasion requires rhoptry exocytosis

Fri, 19 Sep 2025 00:00:00 GMT

Perforation of the host cell plasma membrane during Toxoplasma invasion requires rhoptry exocytosis Male, Frances; Kegawa, Yuto; Blank, Paul S.; Jiménez-Munguía, Irene; Sidik, Saima M.; Valleau, Dylan; Lourido, Sebastian; Lebrun, Maryse; Zimmerberg, Joshua; Ward, Gary E. Toxoplasma gondii is an obligate intracellular parasite. Proteins released during host cell invasion from apical secretory organelles known as rhoptries are delivered into the host cell cytosol to perform functions critical for parasite survival and virulence. How these effector proteins move across the host cell plasma membrane is unknown but may involve a previously noted temporary loss of host cell plasma membrane barrier integrity. Here, we use high-speed, multi-wavelength fluorescence imaging to spatially monitor the barrier integrity of the host cell plasma membrane, in real time, during invasion. The data reveal that early in invasion the parasite creates a transient perforation in the host cell membrane. The perforation occurs at the point on the host membrane in contact with the parasite’s apical end. Parasites depleted of any of five proteins known to be required for rhoptry exocytosis are unable to perforate the host cell membrane. These data suggest a model in which perforating agents stored within rhoptries are released onto the host cell at the initiation of invasion to create a conduit for the delivery of rhoptry effector proteins.

Unknottedness of free boundary minimal surfaces and self-shrinkers

Mon, 08 Sep 2025 00:00:00 GMT

Unknottedness of free boundary minimal surfaces and self-shrinkers Chu, Sabine; Franz, Giada We study unknottedness for free boundary minimal surfaces in a three-dimensional Riemannian manifold with nonnegative Ricci curvature and strictly convex boundary, and for self-shrinkers in the three-dimensional Euclidean space. For doing so, we introduce the concepts of boundary graph for free boundary minimal surfaces and of graph at infinity for self-shrinkers. We prove that these surfaces are unknotted in the sense that any two such surfaces with isomorphic boundary graph or graph at infinity are smoothly isotopic.

The wavefront set: bounds for the Langlands parameter

Tue, 09 Sep 2025 00:00:00 GMT

The wavefront set: bounds for the Langlands parameter Ciubotaru, Dan; Kim, Ju-Lee For an irreducible smooth representation of a connected reductive p-adic group, two important associated invariants are the wavefront set and the (partly conjectural) Langlands parameter. While a wavefront set consists of p-adic nilpotent orbits, one constituent of the Langlands parameter is a complex nilpotent orbit in the dual Lie algebra. For unipotent representations in the sense of Lusztig, the corresponding nilpotent orbits on the two sides are related via the Lusztig–Spaltenstein duality (Ciubotaru et al. in Am J Math arXiv:2112.14354v4 , J Reine Angew Math (Crelles J) 823:191–253, 2025). In this paper, we formulate a general upper-bound conjecture and several variants relating the nilpotent orbits that appear in the wavefront set and in the Langlands parameter. We also verify these expectations in some cases, including the depth-zero supercuspidal representations of classical groups and all the irreducible representations of G2.

An open-source and low-cost dual-extruder 3D printer for macroscale biotic materials

Wed, 22 Oct 2025 00:00:00 GMT

An open-source and low-cost dual-extruder 3D printer for macroscale biotic materials de Alva, Jesse P.; Buehler, Markus This work presents the design and fabrication of a novel, dual-extruder biotic 3D printer, tailored for precise deposition of natural biomaterials such as pectin, chitosan, and cellulose. Moving beyond the limitations of traditional thermoplastic extrusion which relies on non-renewable plastics and produces significant waste, this printer utilizes a syringe-based mechanical extruder to deposit viscous biotic material hydrogels. The integration of a dual-extruder system enables the creation of multi-material prints, offering new possibilities for sustainable and biotic manufacturing. Designed with accessibility and versatility in mind, the system features user-friendly operation suitable for non-experts with open-source hardware and software. By providing a robust, customizable, and open-source platform, this work aims to empower researchers, educators, and innovators to advance biomaterials research and expand the reach of sustainable additive manufacturing. The printer fosters a collaborative community and lays the groundwork for further exploration of biological designs and materials.

Observation of the doubly-charmed-baryon decay Ξ cc + + → Ξ c 0 π + π +

Thu, 16 Oct 2025 00:00:00 GMT

Observation of the doubly-charmed-baryon decay Ξ cc + + → Ξ c 0 π + π + Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; The LHCb Collaboration A search for the doubly-charmed-baryon decay Ξ cc + + → Ξ c 0 π + π + is performed using proton-proton collision data collected by the LHCb experiment at a centre-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 5.4 fb−1. A significant structure consistent with the Ξ cc + + baryon is observed in the Ξ c 0 π + π + invariant-mass spectrum. Using the Ξ cc + + → Λ c + K − π + π + decay as the normalisation channel, the branching fraction ratio, B Ξ cc + + → Ξ c 0 π + π + B Ξ cc + + → Λ c + K − π + π + , is measured to be 1.37 ± 0.18 (stat) ± 0.09 (syst) ± 0.35 (ext). This measurement provides critical input for testing QCD factorisation methods in the weak decays of doubly-heavy baryons, particularly in quantifying nonperturbative effects such as final-state interactions and resonance contributions to the hadronisation process.

Experimental evidence for nodal superconducting gap in moiré graphene

Thu, 06 Nov 2025 00:00:00 GMT

Experimental evidence for nodal superconducting gap in moiré graphene Park, Jeong Min; Sun, Shuwen; Watanabe, Kenji; Taniguchi, Takashi; Jarillo-Herrero, Pablo Understanding the nature of superconductivity in magic-angle graphene remains challenging. A key difficulty lies in discerning the different energy scales in this strongly interacting system, particularly the superconducting gap. Here, we report simultaneous tunneling spectroscopy and transport measurements of magic-angle twisted trilayer graphene. This approach allows us to identify two coexisting V-shaped tunneling gaps with different energy scales: a distinct low-energy superconducting gap that vanishes at the superconducting critical temperature and magnetic field, and a higher-energy pseudogap. The superconducting tunneling spectra display a linear gap-filling behavior with temperature and magnetic field and exhibit the Volovik effect, consistent with a nodal order parameter. Our work suggests an unconventional nature of the superconducting gap and establishes an experimental framework for multidimensional investigation of tunable quantum materials.

Mitigating matrix effects in oil and gas wastewater analysis: LC-MS/MS method for ethanolamines

Thu, 26 Dec 2024 00:00:00 GMT

Mitigating matrix effects in oil and gas wastewater analysis: LC-MS/MS method for ethanolamines de Vera, Glen Andrew D; Caldiero, Loredana; Conte, Giovanni; Plata, Desirée L The high salinity and organic content in oil and gas wastewaters can cause ion suppression during liquid chromatography mass spectrometry (LC/MS) analysis, diminishing the sensitivity and accuracy of measurements in available methods. This suppression is severe for low molecular weight organic compounds such as ethanolamines (e.g., monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA), N-methyldiethanolamine (MDEA), and N,N-ethyldiethanolamine (EDEA)). Here, we deployed solid phase extraction (SPE), mixed-mode LC, triple quadrupole MS with positive electrospray ionization (ESI), and a suite of stable isotope standards (i.e., one per target compound) to correct for ion suppression by salts and organic matter, SPE losses, and instrument variability. The method was evaluated in produced water samples from Italy (NaCl salinity from 8110–18 100 mg L−1; diesel range organic compounds ranging from 5.1–7.9 mg L−1). After correcting for matrix effects, ethanolamines in produced water samples were quantified. The first batch of samples (March 2019) had 37–646 μg L−1 total ethanolamines. The second batch of samples (September 2019) had greater ethanolamine content of 77–3976 μg L−1 which was attributed to a reduced water cut during oil production, enhancing the proportionate abundance of these compounds in the aqueous phase. In all samples, DEA and MEA were the dominant ethanolamine species. Possible sources (e.g., corrosion inhibitor and biotransformation) and natural attenuation potential during storage (e.g., at different temperatures, acidification, and addition of sodium azide) were investigated. The developed analytical method enables further investigation of the fate of low molecular weight organic additives in oil and gas development and provides an enhanced ability to evaluate risks associated with chemical release to the environment.

Sensitivity analysis of aromatic chemistry to gas-phase kinetics in a dark molecular cloud model

Mon, 21 Oct 2024 00:00:00 GMT

Sensitivity analysis of aromatic chemistry to gas-phase kinetics in a dark molecular cloud model Byrne, Alex N; Xue, Ci; Van Voorhis, Troy; McGuire, Brett A The increasingly large number of complex organic molecules detected in the interstellar medium necessitates robust kinetic models that can be relied upon for investigating the involved chemical processes. Such models require rate coefficients for each of the thousands of reactions; the values of these are often estimated or extrapolated, leading to large uncertainties that are rarely quantified. We have performed a global Monte Carlo and a more local one-at-a-time sensitivity analysis on the gas-phase rate coefficients in a 3-phase dark cloud model. Time-dependent sensitivities have been calculated using four metrics to determine key reactions for the overall network as well as for the cyanonaphthalene molecule in particular, an important interstellar species that is severely under-produced by current models. All four metrics find that reactions involving small, reactive species that initiate hydrocarbon growth have large effects on the overall network. Cyanonaphthalene is most sensitive to a number of these reactions as well as ring-formation of the phenyl cation (C6H5+) and aromatic growth from benzene to naphthalene. Future efforts should prioritize constraining rate coefficients of key reactions and expanding the network surrounding these processes. These results highlight the strength of sensitivity analysis techniques to identify critical processes in complex chemical networks, such as those often used in astrochemical modeling.

Automated electrochemical oxygen sensing using a 3D-printed microfluidic lab-on-a-chip system

Sat, 28 Dec 2024 00:00:00 GMT

Automated electrochemical oxygen sensing using a 3D-printed microfluidic lab-on-a-chip system Kaufman, Daniel; Winkler, Steffen; Heuer, Christopher; Shibli, Ahed; Snezhko, Alexander; Livshits, Gideon I; Bahnemann, Janina; Ben-Yoav, Hadar Dissolved oxygen is crucial for metabolism, growth, and other complex physiological and pathological processes; however, standard physiological models (such as organ-on-chip systems) often use ambient oxygen levels, which do not reflect the lower levels that are typically found in vivo. Additionally, the local generation of reactive oxygen species (ROS; a key factor in physiological systems) is often overlooked in biology-mimicking models. Here, we present a microfluidic system that integrates electrochemical dissolved oxygen sensors with lab-on-a-chip technology to monitor the physiological oxygen concentrations and generate hydrogen peroxide (H2O2; a specific ROS). This microfluidic lab-on-a-chip system was fabricated using high-resolution 3D printing technology in a one-step process. It incorporates a micromixer, an on-chip bubble-trap, an electrochemical cell with fabricated gold or platinum black-coated working electrodes as well as an Ag/AgCl reference electrode, and a commercial optical oxygen sensor for validation. This device enables an automated variation of the oxygen levels as well as sensitive electrochemical oxygen monitoring (limit of detection = 11.9 ± 0.3 μM), with a statistically significant correlation with the optical sensor. The proposed system can serve as a tool to characterize and evaluate custom-made electrodes. Indeed, we envision that in the future it will be used to regulate dissolved oxygen levels and oxygen species in real time in organ-on-chip systems.

A critical review on Li-ion transport, chemistry and structure of ceramic–polymer composite electrolytes for solid state batteries

Mon, 18 Nov 2024 00:00:00 GMT

A critical review on Li-ion transport, chemistry and structure of ceramic–polymer composite electrolytes for solid state batteries Sand, Sara Catherine; Rupp, Jennifer LM; Yildiz, Bilge In the transition to safer, more energy-dense solid state batteries, polymer–ceramic composite electrolytes may offer a potential route to achieve simultaneously high Li-ion conductivity and enhanced mechanical stability. Despite numerous studies on the polymer–ceramic composite electrolytes, disagreements persist on whether the polymer or the ceramic is positively impacted in their constituent ionic conductivity for such composite electrolytes, and even whether the interface is a blocking layer or a highly conductive lithium ion path. This lack of understanding limits the design of effective composite solid electrolytes. By thorough and critical analysis of the data collected in the field over the last three decades, we present arguments for lithium conduction through the bulk of the polymer, ceramic, or their interface. From this analysis, we can conclude that the unexpectedly high conductivity reported for some ceramic–polymer composites cannot be accounted for by the ceramic phase alone. There is evidence to support the theory that the Li-ion conductivity in the polymer phase increases along this interface in contact with the ceramic. The potential mechanisms for this include increased free volume, decreased crystallinity, and modulated Lewis acid–base effects in the polymer, with the former two to be the more likely mechanisms. Future work in this field requires understanding these factors more quantitatively, and tuning of the ceramic surface chemistry and morphology in order to obtain targeted structural modifications in the polymer phase.

Na vs. Li metal anodes for batteries: unraveling thermodynamic and electronic origins of voids and developing descriptors for artificial surface coatings

Tue, 24 Sep 2024 00:00:00 GMT

Na vs. Li metal anodes for batteries: unraveling thermodynamic and electronic origins of voids and developing descriptors for artificial surface coatings Venturi, Victor; Freitas, Rodrigo; Abate, Iwnetim Iwnetu Techno-economic, humanitarian, and safety concerns limit the possible uses of conventional lithium-ion and lithium-metal batteries. Sodium-based batteries constitute a promising alternative to address these issues; however, due to the similarities between the two alkali metals, they present similar failure modes as their lithium counterparts. In this work, we focus on one of such failure mechanisms: the thermodynamically-driven accumulation of vacancies on the surface of the metallic anode, which leads to the formation of voids and pits, detrimental to battery performance and cycle life. We investigate the differences in behavior between anode/coating interfaces of both lithium and sodium. Adhesion energy, a descriptor previously argued to be a reliable design principle for lithium metal anodes, is found to not exhibit the same predictive power for sodium metal architectures: in cases where vacancy congregation is not thermodynamically favorable for isolated sodium slabs, we find strong interfacial interactions to have adverse effects on void formation. By studying select coating materials, we also reveal that these material interactions at alkali/coating interfaces are highly nuanced, and that the field of surface science and engineering is ripe with opportunities for further discovery and tuning of surface properties via coating selection.

Interface‐Induced Stability of Nontrivial Topological Spin Textures: Unveiling Room‐Temperature Hopfions and Skyrmions

Mon, 18 Aug 2025 00:00:00 GMT

Interface‐Induced Stability of Nontrivial Topological Spin Textures: Unveiling Room‐Temperature Hopfions and Skyrmions Katmis, Ferhat; Lauter, Valeria; Yagan, Rawana; Brandt, Iuri S; Cheghabouri, Arash M; Zhou, Hua; Freeland, John W; de Araujo, Clodoaldo IL; Jamer, Michelle E; Heiman, Don; Onbasli, Mehmet C; Moodera, Jagadeesh S Topological spin configurations, such as soliton-like spin texture and Dirac electron assemblies, have recently emerged in fundamental science and technology. Achieving stable topological spin textures at room temperature is crucial for their use as long-range information carriers. However, their creation and manipulation are hindered by multi-step field training and competing interactions. Thus, a spontaneous ground state for multidimensional topological spin textures is desirable, with skyrmions forming swirling, hedgehog-like spin structures in two dimensions and hopfions as their twisted 3D counterparts. Here, the first observation of robust and reproducible topological spin textures of hopfions and skyrmions observed at room temperature and in zero magnetic field is reported, which are stabilized by geometric confinement and protected by interfacial magnetism in a ferromagnet/topological insulator/ferromagnet trilayer heterostructure. These skyrmion-hopfion configurations are directly observed at room temperature with Lorenz transmission electron microscopy. Using micromagnetic modeling, the experimental observations of hopfion-skyrmion assemblies are reproduced. This model reveals a complete picture of how spontaneously organized skyrmion lattices encircled by hopfion rings are controlled by surface electrons, uniaxial anisotropy, and Dzyaloshinskii-Moriya interaction. This study provides evidence that topological chiral spin textures can facilitate the development of magnetic topological carriers, paving the way for ultralow-power and high-density information processing.

Genetic Surfaceome E. coli Reprogramming Enables Selective Water Oxidation

Fri, 15 Aug 2025 00:00:00 GMT

Genetic Surfaceome E. coli Reprogramming Enables Selective Water Oxidation Sedenho, Graziela C; Pacheco, Jéssica C; Gut, Melanie; Lima, Filipe CDA; Dey, Sunanda; Crespilho, Frank N; Furst, Ariel L Programming catalytic behavior at the microbial genome level is a frontier in synthetic biology with direct impact on bioelectrocatalysis. A key challenge is the coordinated control of gene expression, localization, folding, and cofactor maturation required to achieve proper bioelectrocatalytic activity. Here, a synthetic operon in Escherichia coli is engineered to reprogram its surfaceome for selective water oxidation. Using orthogonal IPTG-inducible control and codon-optimized expression, a fungal bilirubin oxidase (BOD) displayed at the cell surface is produced by ice nucleation protein anchoring (BOD-E. coli). Post-overexpression copper catalytic site reconstitution provides an active holoenzyme. The developed engineered living material performs water oxidation at near-zero overpotential (27 mV at pH 9.1), with complete suppression of the oxygen reduction reaction. These results show how regenerable microbial platforms can be designed for selective catalysis and artificial photosynthesis.

Surprises From the Basal Ganglia: Stop and Go Have New Meaning

Thu, 14 Aug 2025 00:00:00 GMT

Surprises From the Basal Ganglia: Stop and Go Have New Meaning Graybiel, Ann M This perspective highlights new worksuggesting the need for revision of the canonical direct–indirect model of the basal ganglia’s inﬂuence on move-ment, with fresh evidence that there is a formerlyunappreciated pair of direct and indirect pathways thatparallel the standard model’s canonical direct and indi-rect pathways, and promising evidence pointing towardimproved clinical treatments for Parkinson’s disease. Asa working hypothesis, it is suggested that the non-canonical direct and indirect pathways, which arise instriosomes, might act as homeostatic circuits that canreign in or amplify the activity of the canonical pathwaysin the face of their imbalance, including that occurring inhyperkinetic or hypokinetic disorders.

Simulating the Potential for Invasive Grass Expansion to Alter Wildfire Behavior in Southern California With WRF‐Fire

Wed, 13 Aug 2025 00:00:00 GMT

Simulating the Potential for Invasive Grass Expansion to Alter Wildfire Behavior in Southern California With WRF‐Fire Wang, Bowen; Madakumbura, Gavin D; Juliano, Timothy W; Williams, A Park Invasion by non‐native annual grasses poses a serious threat to native vegetation in California,facilitated through interaction with wildfires. Our work is the first attempt to use the coupled fire‐atmospheremodel, WRF‐Fire, to investigate how shifts from native, shrub‐dominated vegetation to invasive grasses couldhave affected a known wildfire event in southern California. We simulate the Mountain Fire, which burned>11,000 ha in July 2013, under idealized fuel conditions representing varying extents of grass invasion.Expanding grass to double its observed coverage causes fire to spread faster due to the lower fuel load in grassesand increased wind speed. Beyond this, further grass expansion reduces the simulated spread rate because lowerheat release partially offsets the positive effects. Our simulations suggest that grass expansion may generallypromote larger faster‐spreading wildfires in southern California, motivating continued efforts to contain andreduce the spread of invasive annual grasses in this region.

Vaccine-boosted CAR T crosstalk with host immunity to reject tumors with antigen heterogeneity

Thu, 20 Jul 2023 00:00:00 GMT

Vaccine-boosted CAR T crosstalk with host immunity to reject tumors with antigen heterogeneity Ma, Leyuan; Hostetler, Alexander; Morgan, Duncan M; Maiorino, Laura; Sulkaj, Ina; Whittaker, Charles A; Neeser, Alexandra; Pires, Ivan Susin; Yousefpour, Parisa; Gregory, Justin; Qureshi, Kashif; Dye, Jonathan; Abraham, Wuhbet; Suh, Heikyung; Li, Na; Love, J Christopher; Irvine, Darrell J Chimeric antigen receptor (CAR) T cell therapy effectively treats human cancer, but the loss of the antigen recognized by the CAR poses a major obstacle. We found that in vivo vaccine boosting of CAR T cells triggers the engagement of the endogenous immune system to circumvent antigen-negative tumor escape. Vaccine-boosted CAR T promoted dendritic cell (DC) recruitment to tumors, increased tumor antigen uptake by DCs, and elicited the priming of endogenous anti-tumor T cells. This process was accompanied by shifts in CAR T metabolism toward oxidative phosphorylation (OXPHOS) and was critically dependent on CAR-T-derived IFN-γ. Antigen spreading (AS) induced by vaccine-boosted CAR T enabled a proportion of complete responses even when the initial tumor was 50% CAR antigen negative, and heterogeneous tumor control was further enhanced by the genetic amplification of CAR T IFN-γ expression. Thus, CAR-T-cell-derived IFN-γ plays a critical role in promoting AS, and vaccine boosting provides a clinically translatable strategy to drive such responses against solid tumors.

Early cellular and molecular signatures correlate with severity of West Nile virus infection

Fri, 15 Dec 2023 00:00:00 GMT

Early cellular and molecular signatures correlate with severity of West Nile virus infection Lee, Ho-Joon; Zhao, Yujiao; Fleming, Ira; Mehta, Sameet; Wang, Xiaomei; Wyk, Brent Vander; Ronca, Shannon E; Kang, Heather; Chou, Chih-Hung; Fatou, Benoit; Smolen, Kinga K; Levy, Ofer; Clish, Clary B; Xavier, Ramnik J; Steen, Hanno; Hafler, David A; Love, J Christopher; Shalek, Alex K; Guan, Leying; Murray, Kristy O; Kleinstein, Steven H; Montgomery, Ruth R Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16⁺ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.

Full-length single-cell BCR sequencing paired with RNA sequencing reveals convergent responses to pneumococcal vaccination

Sat, 28 Sep 2024 00:00:00 GMT

Full-length single-cell BCR sequencing paired with RNA sequencing reveals convergent responses to pneumococcal vaccination Morgan, Duncan M; Zhang, Yiming J; Kim, Jin-Hwan; Murillo, MaryAnn; Singh, Suddham; Loschko, Jakob; Surendran, Naveen; Sekulovic, Ognjen; Feng, Ellie; Shi, Shuting; Irvine, Darrell J; Patil, Sarita U; Kanevsky, Isis; Chorro, Laurent; Christopher Love, J Single-cell RNA sequencing (scRNA-seq) can resolve transcriptional features from individual cells, but scRNA-seq techniques capable of resolving the variable regions of B cell receptors (BCRs) remain limited, especially from widely-used 3′-barcoded libraries. Here, we report a method that can recover paired, full-length variable region sequences of BCRs from 3′-barcoded scRNA-seq libraries. We first verify this method (B3E-seq) can produce accurate, full-length BCR sequences. We then apply this method to profile B cell responses elicited against the capsular polysaccharide of Streptococcus pneumoniae serotype 3 (ST3) by glycoconjugate vaccines in five infant rhesus macaques. We identify BCR features associated with specificity for the ST3 antigen which are present in multiple vaccinated monkeys, indicating a convergent response to vaccination. These results demonstrate the utility of our method to resolve key features of the B cell repertoire and profile antigen-specific responses elicited by vaccination.

Rapidity and multiplicity dependence of charged-particle flow in pPb collisions at s NN = 8.16 TeV

Wed, 15 Oct 2025 00:00:00 GMT

Rapidity and multiplicity dependence of charged-particle flow in pPb collisions at s NN = 8.16 TeV Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; LHCB Collaboration The elliptic and triangular flow of charged particles are measured using two-particle angular correlations in pPb collisions in the pseudorapidity range 2.0 < |η| < 4.8. The data sample was collected by the LHCb experiment in 2016 at a centre-of-mass energy per nucleon pair of s NN = 8.16 TeV, containing in total approximately 1.5 billion collision events. Non-flow contributions are obtained in low-multiplicity collisions and subtracted to extract the flow harmonics. The results are presented as a function of event multiplicity and hadron transverse momentum. Comparisons with a full (3+1)D dynamic model indicate that it overestimates the measured elliptic flow. A comparison between the forward and backward regions reveals no significant differences in flow parameters, suggesting that final-state effects may dominate over initial-state effects in the origin of flow in small systems.

Truth and perspective

Thu, 23 Oct 2025 00:00:00 GMT

Truth and perspective Ricciardi, Giuseppe; Reuter, Kevin Several studies in experimental philosophy and semantics have shown that a substantial number of English speakers consider a statement true even if it does not align with the facts, as long as it is justified from the speaker's perspective. These findings challenge the prevailing view among philosophers that truth in the empirical domain is uniformly based on a statement's correspondence to reality. In this study, we explore how perspective-taking influences truth assessments by showing that this influence depends on how the critical question assessing the statement’s truth is phrased. Our results show that when the question targets only the proposition, e.g., “Is it true that [the uttered proposition]?”), participants typically apply a correspondence view of truth—consistent with philosophical convention. But when the question also highlights the speaker (e.g., “Is [the speaker]’s answer true?”), many participants shift toward judging the statement from the speaker’s perspective. We discuss four possible explanations for this behavior and examine the implications of the findings for other philosophical discussions concerning truth and lying, the theory of reference, and norms of assertion.

Curtain Model for CAT(0) Spaces and Isometries

Wed, 30 Jul 2025 00:00:00 GMT

Curtain Model for CAT(0) Spaces and Isometries Chen, Yutong This paper studies the dynamics of isometries in the curtain model, which is used to capture the hyperbolicity in a fixed CAT(0) space. We establish several fundamental properties and fully classify the behavior of semisimple isometries of a CAT(0) space in the associated curtain model. In the nonsemisimple case, we restrict the behavior of parabolic actions with positive translation length in the curtain model in most cases of interest, allowing the use of ping-pong-like techniques on the curtain model to provide insights into the study of CAT(0) groups.

An Algorithm for Estimating the Crossing Number of Dense Graphs, and Continuous Analogs of the Crossing and Rectilinear Crossing Numbers

Tue, 21 Oct 2025 00:00:00 GMT

An Algorithm for Estimating the Crossing Number of Dense Graphs, and Continuous Analogs of the Crossing and Rectilinear Crossing Numbers Solé-Pi, Oriol We present a deterministic n 2 + o ( 1 ) -time algorithm that approximates the crossing number of any graph G of order n up to an additive error of o ( n 4 ) . We also provide a randomized polynomial-time algorithm that constructs a drawing of G with cr ( G ) + o ( n 4 ) crossings. These results yield a 1 + o ( 1 ) approximation algorithm for the crossing number of dense graphs. Our work complements a paper of Fox, Pach and Súk [20], who obtained similar results for the rectilinear crossing number. The results in [20] and in this paper imply that the (normalized) crossing and rectilinear crossing numbers are estimable parameters. Motivated by this, we introduce two graphon parameters, the crossing density and the rectilinear crossing density, and we prove that, in a precise sense, these are the correct continuous analogs of the crossing and rectilinear crossing numbers of graphs.

Improved measurement of η/η′ mixing in B s 0 → J / ψ η ′ decays

Tue, 14 Oct 2025 00:00:00 GMT

Improved measurement of η/η′ mixing in B s 0 → J / ψ η ′ decays Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J.; Aleksiejunas, R. Branching fraction ratios between the decays B s 0 → J / ψ η ′ are measured using proton-proton collision data collected by the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb−1. The measured ratios of these branching fractions are B B 0 → J / ψη ′ B B 0 → J / ψη = 0.48 ± 0.06 ± 0.02 ± 0.01 , B B s 0 → J / ψη ′ B B s 0 → J / ψη = 0.80 ± 0.02 ± 0.02 ± 0.01 , where the uncertainties are statistical, systematic and related to the precision of the η(′) branching fractions, respectively. They are used to constrain the η/η′ mixing angle, ϕP, and to probe the presence of a possible glueball component in the η′ meson, described by the gluonic mixing angle ϕG. The obtained results are ϕ P = 41.6 − 1.2 + 1.0 ∘ , ϕ G = 28.1 − 4.0 + 3.9 ∘ , where the uncertainties are statistically dominated. While the value of ϕP is compatible with existing experimental determinations and theoretical calculations, the angle ϕG differs from zero by more than four standard deviations, which points to a substantial glueball component in the η′ meson and/or unexpectedly large contributions from gluon-mediated processes in these decays. The absolute branching fractions are also measured relative to that of the well-established B s 0 → J / ψϕ decay, which serves as the normalisation channel. These results supersede the previous LHCb measurements and are the most precise to date.

Zero carbon challenges in supply chain management to achieve sustainability

Tue, 19 Aug 2025 00:00:00 GMT

Zero carbon challenges in supply chain management to achieve sustainability Derse, O.; Yontar, E. Reducing carbon emissions due to increasing climate concerns has become important at every stage of the supply chain line, as it is in every sector. Many activities take place in the supply chain processes and it takes serious work for these activities to be in line with the net zero carbon strategy. This paper addresses the challenges that are preventing the supply chain from achieving its net zero carbon target. Challenges addressed; It is categorized as environmental challenges, financial and economic challenges, organizational challenges, social and consumer challenges, technical and technological challenges, and administrative challenges. Depending on the 6 main categories determined, 24 sub-challenges are determined and the network structure, relations and rankings of the determined challenges are determined by the Analytical Network Process (ANP) method, one of the Multi-Criteria Decision Making methods. The risks of the challenges identified by the ANP-based Failure Mode and Effect Analysis (FMEA) are also listed. According to the ANP and ANP based FMEA methods, it is seen that the riskiest results and the most important challenges are Financial and Economic challenges and Technical and Technological challenges, respectively. According to the ANP, the most important challenges are respectively “Lack of technical competence and field experts”, “Lack of resources”, and “High initial investment cost”. According to the ANP based FMEA, the most important challenges are “Lack of resources”, “Lack of technical competence and field experts” and “Uncertain long-term economic return/payback periods and investment risks”, respectively. In the study, it is thought that the relationships and rankings determined will be a roadmap to reach net zero carbon targets in supply chains.

Robust longitudinal and lateral control for mixed-vehicular platoons with string stability guarantees

Wed, 16 Jul 2025 00:00:00 GMT

Robust longitudinal and lateral control for mixed-vehicular platoons with string stability guarantees Chen, Qien; Wang, Shimin; Gao, Bolin; Zhan, Zhi; Zhong, Renxin Integrating longitudinal and lateral controls for vehicular platoons mixed with Connected and Autonomous Vehicles (CAVs) and Level-2 Automated Vehicles (L2AVs) to guarantee string stability against model uncertainty and external disturbances is essential yet challenging. This paper tackles this challenge by introducing a novel integrated longitudinal and lateral control (ILLC) strategy that guarantees input-to-state string stability (ISSS) for heterogeneous vehicular platoons. The proposed ILLC strategy significantly enhances the robustness of vehicular platoons by maintaining the desired headway and ensuring the ISSS against disturbances. By incorporating a disturbance observer, we directly address the disturbance estimation error within the string stability analysis. We validate the effectiveness of our method through simulations of various traffic scenarios. Compared to conventional cooperative adaptive cruise control (CACC) techniques, the proposed method achieves faster convergence to the desired states and exhibits bounded state fluctuations. Furthermore, our method can effectively attenuate external disturbances and dissipate stop-and-go waves.

Finite Rank Perturbation of Non-Hermitian Random Matrices: Heavy Tail and Sparse Regimes

Mon, 29 Sep 2025 00:00:00 GMT

Finite Rank Perturbation of Non-Hermitian Random Matrices: Heavy Tail and Sparse Regimes Han, Yi Abstract In this work we investigate spectral properties of squared random matrices with independent entries that have only two finite moments. We revisit the problem of perturbing a large, i.i.d. random matrix by a finite rank error. We prove that under a merely second moment condition, for a large class of perturbation matrix with bounded rank and bounded operator norm, the outlier eigenvalues of perturbed matrix still converge to that of the perturbation, which was previously known when matrix entries have finite fourth moment. We then show that the same perturbation holds for very sparse random matrices with i.i.d. entries, all the way up to a constant number of nonzero entries per row and column.

Arene extrusion as an approach to reductive elimination at boron: implication of carbene-ligated haloborylene as a transient reactive intermediate

Thu, 03 Oct 2024 00:00:00 GMT

Arene extrusion as an approach to reductive elimination at boron: implication of carbene-ligated haloborylene as a transient reactive intermediate Zhang, Chonghe; Gilliard, Robert J; Cummins, Christopher C Herein, we report boron-centered arene extrusion reactions to afford putative cyclic(alkyl)(amino) carbene (CAAC)-ligated chloroborylene and bromoborylene intermediates. The borylene precursors, chloro-boranorbornadiene (ClB(C6Me6), 2Cl) and bromo-boranorbornadiene (BrB(C6Me6), 2Br) were synthesized through the reaction of the corresponding 1-halo-2,3,4,5-tetramethylborole dimer (XBC4Me4)2 (X = Cl, 1Cl; X = Br, 1Br) with 2-butyne. Treatment of 2Cl with CAACs resulted in the release of di-coordinate chloro-borylene (CAAC)BCl from hexamethylbenzene (C6Me6) at room temperature. In contrast, the reaction of 2Br with CAAC led to the formation of a boronium species [(CAAC)BC6Me6]+Br− (7) at room temperature. Heating 7 in toluene promoted the release of di-coordinate bromo-borylene (CAAC)BBr as a transient species. Surprisingly, heating 7 in dichloromethane resulted in the C–H activation of hexamethylbenzene. The conversion of a CAAC-stabilized bromo-borepin to a borylene, a boron-centered retro Büchner reaction, was also investigated.

Clustering in typical unit-distance avoiding sets

Mon, 22 Sep 2025 00:00:00 GMT

Clustering in typical unit-distance avoiding sets Cohen, A.; Mani, N. In the 1960s Moser asked how dense a subset of R d can be if no pairs of points in the subset are exactly distance 1 apart. There has been a long line of work showing upper bounds on this density. One curious feature of dense unit distance avoiding sets is that they appear to be ''clumpy,'' i.e. forbidding unit distances comes hand in hand with having more than the expected number distance ≈ 2 pairs. In this work we rigorously establish this phenomenon in R 2 . We show that dense unit distance avoiding sets have over-represented distance ≈ 2 pairs, and that this clustering extends to typical unit distance avoiding sets. To do so, we build off of the linear programming approach used previously to prove upper bounds on the density of unit distance avoiding sets.

Structure of Lower Tails in Sparse Random Graphs

Mon, 11 Aug 2025 00:00:00 GMT

Structure of Lower Tails in Sparse Random Graphs Chin, Byron We study the typical structure of a sparse Erdős–Rényi random graph conditioned on the lower tail subgraph count event. We show that in certain regimes, a typical graph sampled from the conditional distribution resembles the entropy minimizer of the mean field approximation in the sense of both subgraph counts and cut norm. The main ingredients are an adaptation of an entropy increment scheme of Kozma and Samotij, and a new stability for the solution of the associated entropy variational problem. The proof can be interpreted as a structural application of the new probabilistic hypergraph container lemma for sparser than average sets, and suggests a more general framework for establishing such typical behavior statements.

t-channel dark matter models – a whitepaper

Fri, 12 Sep 2025 00:00:00 GMT

t-channel dark matter models – a whitepaper Arina, Chiara; Fuks, Benjamin; Panizzi, Luca; Baker, Michael J.; Cornell, Alan S.; Heisig, Jan; Maier, Benedikt; Pedro, Rute; Trischuk, Dominique; Agin, Diyar; Arbey, Alexandre; Arcadi, Giorgio; Bagnaschi, Emanuele; Bai, Kehang; Bhatia, Disha; Becker, Mathias; Belyaev, Alexander; Benoit, Ferdinand; Blanke, Monika; Burzynski, Jackson This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of t-channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring t-channel dark matter models at colliders and in cosmology.

Organic aerosol formation from 222 nm germicidal light: ozone-initiated vs. non-ozone pathways

Thu, 17 Oct 2024 00:00:00 GMT

Organic aerosol formation from 222 nm germicidal light: ozone-initiated vs. non-ozone pathways Goss, Matthew B; Kroll, Jesse H Germicidal ultraviolet lamps outputting 222 nm light (GUV222) have the potential to reduce the airborne spread of disease through effective inactivation of pathogens, while remaining safe for direct human exposure. However, recent studies have identified these lamps as a source of ozone and other secondary pollutants such as secondary organic aerosol (SOA), and the health effects of these pollutants must be balanced against the benefits of pathogen inactivation. While ozone reactions are likely to account for much of this secondary indoor air pollution, 222 nm light may initiate additional non-ozone chemical processes, including the formation of other oxidants and direct photolytic reactions, which are not as well understood. This work examines the impacts of GUV222 on SOA formation and composition by comparing limonene oxidation under GUV222 and O3-only control conditions in a laboratory chamber. Differences between these experiments enable us to distinguish patterns in aerosol formation driven by ozone chemistry from those driven by other photolytic processes. These experiments also examine the influence of the addition of NO2 and nitrous acid (HONO), and investigate SOA formation in sampled outdoor air. SOA composition and yield vary only slightly with respect to GUV222vs. ozone-only conditions; NO2 and HONO photolysis do not appreciably affect the observed chemistry. In contrast, we observe consistent new particle formation under high-fluence 222 nm light (45 μW cm−2) that differs substantially from ozone-only experiments. This observed new particle formation represents an additional reason to keep GUV222 fluence rates to the lowest effective levels.

Leveraging Electrons for Electrochemical CO2 Capture Using a Hemi-Labile Iron Complex

Mon, 04 Aug 2025 00:00:00 GMT

Leveraging Electrons for Electrochemical CO2 Capture Using a Hemi-Labile Iron Complex Seo, Hyowon; Chen, Ying; Walter, Eric; Abdinejad, Maryam; Hatton, T Alan Climate change, driven by anthropogenic carbon emissions, demands urgent action to prevent a 2050 tipping point. With CO2 levels at 427 ppm (50% above pre-industrial levels), deploying energy-efficient carbon capture technologies is crucial. Electrochemical carbon capture processes that have been touted to have the potential to meet these needs rely on the applied cell voltage, and electron utilization (CO2 molecules separated per electron), which has generally been asserted to have a theoretical limit of one. Here, we introduce an electron-leveraging strategy to enhance electron utilization beyond this limit to 1.43 by employing Fe-EDDHA, a redox-active coordination complex having a ligand with multiple hemi-labile coordination sites. The reversibility and robustness of the system were enabled by the efficient prevention of CO2 reduction upon the introduction of nicotinamide as a guardian of the iron(2+) center. The proof-of-concept cyclic system exhibits a minimum operational energy of 22.6 kJe mol−1 and an average of 63.7 kJe mol−1 over 29 cycles, using a simulated flue gas (15% CO2). Our electron-leveraging strategy holds promise for advancing energy-efficient electrochemical carbon capture technologies, and offers an alternative to prevalent redox potential shifting methods proposed to mitigate undesired electron transfer reactions in redox-active materials across diverse operational conditions.

A Programmable Nanovaccine Platform Based on M13 Bacteriophage for Personalized Cancer Vaccine and Therapy

Wed, 27 Aug 2025 00:00:00 GMT

A Programmable Nanovaccine Platform Based on M13 Bacteriophage for Personalized Cancer Vaccine and Therapy Huang, Shengnan; He, Yanpu; Madow, Allison; Peng, Huaiyao; Griffin, Mirielle; Qi, Jifa; Huang, Mantao; Amoroso, Heather; Abrashoff, Riley; Heldman, Nimrod; Belcher, Angela M Nanovaccines co-assemble antigens and adjuvants to elicit robust immuneresponses but often require complex synthesis and post-modiﬁcationprocedures. Here, a programmable nanovaccine platform based on the M13bacteriophage is developed for the scalable production of vaccines andsingle-step modular engineering of adjuvanticity, length, and antigen density.By reprogramming the sequence and size of the noncoding phage genome,the Toll-like receptor 9 activation and the length of the phage are preciselycontrolled. With a novel molecular engineering approach, the antigen densityis tuned from 13.6% to 70.3%. A systematic modulation reveals an optimaladjuvanticity at a constant antigen density for maximum anti-tumor CD8+ Tcell response, and vice versa, using the model antigen SIINFEKL. The M13phage-based nanovaccine induces durable memory immunity lasting over ayear. In addition, a 24-fold increase in neoantigen-speciﬁc CD8+ T cellfrequency is achieved when increasing both the adjuvanticity and antigendensity. Furthermore, when combined with anti-PD-1 therapy, the M13phage-based personalized vaccine eradicates established MC-38 tumors in75% of treated animals and they develop 100% resistance against tumorinvasion when challenged 5 months after treatment. These ﬁndings establishM13 phage as a powerful and versatile nanovaccine platform withtransformative potential for personalized cancer immunotherapy.

Efficient Approximate Unitary Designs from Random Pauli Rotations

Thu, 30 Oct 2025 00:00:00 GMT

Efficient Approximate Unitary Designs from Random Pauli Rotations Haah, Jeongwan; Liu, Yunchao; Tan, Xinyu We construct random walks on simple Lie groups that quickly converge to the Haar measure for all moments up to order t. Specifically, a step of the walk on the unitary or orthogonal group of dimension 2 n is a random Pauli rotation e i θ P / 2 . The spectral gap of this random walk is shown to be Ω ( 1 / t ) , which coincides with the best previously known bound for a random walk on the permutation group on { 0 , 1 } n . This implies that the walk gives an ε -approximate unitary t-design in depth O ( n t 2 + t log 1 ε ) d where d = O ( log n ) is the circuit depth to implement e i θ P / 2 . Our simple proof uses quadratic Casimir operators of Lie algebras.

How FDI reshapes host markets’ trade profile and politics

Fri, 12 Sep 2025 00:00:00 GMT

How FDI reshapes host markets’ trade profile and politics Kim, In Song; Liao, Steven; Miyano, Sayumi A fast-growing literature indicates that ﬁrms’ engagement in foreign directinvestment (FDI) and trade is key to understanding deepening global valuechains and their political implications. However, existing studies have mainlyfocused on the ramiﬁcations for FDI home countries while often overlookingthe ﬁrm-product level interactions between FDI and trade, where their inter-dependencies manifest. This study examines how ﬁrms’ FDI reshapes hostcountries’ trade proﬁles at this level, empowering new political coalitions fortrade liberalization. Analyzing greenﬁeld FDI projects globally since 2003, weﬁnd that hosts experienced an average increase of over 45 export products inthe following year. To overcome the challenges of connecting ﬁrms to prod-ucts, we link FDI data with Vietnamese customs records. We ﬁnd that Viet-namese export (import) volumes of FDI-related products increased by 90%(30%) within 4 years of initial investments. Importantly, these products alsobeneﬁted from more substantial tariff cuts in bilateral Free Trade Agreements.

Integrating metabolic scaling and coexistence theories

Tue, 05 Aug 2025 00:00:00 GMT

Integrating metabolic scaling and coexistence theories Saavedra, Serguei; Arroyo, José Ignacio; Deng, Jie; Marquet, Pablo A; Kempes, Christopher P Metabolic scaling theory has been pivotal in formalizing the expected energyexpenditures across populations as a function of body size. Coexistence theoryhas provided a mathematization of the environmental conditions compatiblewith multispecies coexistence. Yet, it has been challenging to explain howobserved community-wide patterns, such as the inverse relationship betweenpopulation abundance density and body size, can be unified under boththeories. Here, we provide the foundation for a tractable, scalable, and extend-able framework to study the coexistence of resource-mediated competingpopulations as a function of their body size. For a given thermal domain andresponse, this integration reveals that the metabolically predicted 1/4 powerdependence of carrying capacity of biomass density on body size can be under-stood as the average distribution of carrying capacities across feasible environ-mental conditions, especially for large communities. In line with empiricalobservations, our integration predicts that such average distribution leads tocommunities in which population biomass densities at equilibrium are inde-pendent from body size, and consequently, population abundance densitiesare inversely related to body size. This integration opens new opportunities toincrease our understanding of how metabolic scaling relationships at thepopulation level can shape processes at the community level under changingenvironments.

Covariant phase space and L∞ algebras

Fri, 05 Sep 2025 00:00:00 GMT

Covariant phase space and L∞ algebras Bernardes, Vinícius; Erler, Theodore; Fırat, Atakan H. We propose a symplectic structure for the phase space of a generic Lagrangian field theory expressed in the framework of L∞ algebras. The symplectic structure does not require explicit knowledge of the derivative content of the Lagrangian, and therefore is applicable to nonlocal models, such as string field theory, where traditional constructions are difficult to apply. We test our proposal in a number of examples ranging from general relativity to p-adic string theory.

Deciphering the origins of the elements through galactic archeology

Fri, 12 Sep 2025 00:00:00 GMT

Deciphering the origins of the elements through galactic archeology Farouqi, Khalil; Frebel, Anna; Thielemann, Friedrich-Karl Low-metallicity stars preserve the signatures of the first stellar nucleosynthesis events in the Galaxy, as their surface abundances reflect the composition of the interstellar medium from the time when they were born. Aside from primordial Big Bang nucleosynthesis, massive stars, due to their short lifetimes, dominate the wind and explosive ejecta into the interstellar medium of the early Galaxy. Most of them will end as core-collapse supernova (CCSN) explosions, and typical ejected abundance distributions, e.g. in terms of the α -element-to-Fe ratios, reflect these contributions. Essentially all CCSNe contribute 56Fe (decaying from radioactive 56Ni). Therefore, low-metallicity stars can be used to test whether the abundances of any other elements are correlated with those of Fe, i.e. whether these elements have been co-produced in the progenitor sources or if they require either a different or additional astrophysical origin(s). The present analysis focuses on stars with [Fe/H]<-2, as they probe the earliest formation phase of the Galaxy when only one or very few nucleosynthesis events had contributed their ejecta to the gas from which the lowest metallicity stars form. This was also the era before low and intermediate mass stars (or type Ia supernovae) could contribute any additional heavy elements. Following earlier work on the origin of heavy r-process elements [1], we extend the present study to examine Pearson and Spearman correlations of Fe with Li, Be, C, N, O, Na, Mg, Si, S, K, Ca, Ti, Cr, Ni, Zn, Ge, Se, Sr, Y, Zr, Mo, Ba, La, Ce, Sm, Eu, Gd, Dy, Yb, Lu, Hf, Os, Ir, Pb, and Th, using high-resolution stellar abundance data from the SAGA [2] and JINA [3] databases. The main goal is to identify which of the observed elements (i) may have been co-produced with Fe in (possibly a variety of) CCSNe, and which elements require (ii) either a completely different, or (iii) at least an additional astrophysical origin.

Absolute Security with Multiple-Slit Diffraction in Terahertz Communication Links

Mon, 18 Aug 2025 00:00:00 GMT

Absolute Security with Multiple-Slit Diffraction in Terahertz Communication Links Shiri, Yaseman; Yeh, Chia-Yi; Fang, Zhaoji; Shrestha, Rabi; Guerboukha, Hichem; Médard, Muriel; Malowicki, John; Overrocker, David; Fanelli, Paul; Thawdar, Ngwe; Mittleman, Daniel M. Many widely used antennas in terahertz (THz) directional communications (including horn antennas) are not fully compatible with the recently proposed absolute security approach due to the absence of strong frequency-dependent minima in the intrinsic antenna pattern. To this end, we propose to use a multiple-slit aperture to modify these non-suitable radiation patterns in a non-intrusive manner. Based on the principle of diffraction, the multi-slit aperture creates frequency varying minima critical for absolute security. We show that improved security performance, quantified by the size of the secure region in space (termed blind region), can be achieved by employing a wider diffraction aperture with a wider slit opening. We further characterize how the non-uniform wavefront, which is typical in practical transmission and results in varying amplitude and phase at different slit openings, affects the size of the blind region. This diffraction-based scheme is experimentally demonstrated with a horn antenna operating near 200 GHz. We demonstrate that, while the intrinsic horn antenna yields no blind region for angles within 16° from the intended user, the modified antenna configuration produces strong minima sufficient to create blind regions at angles as small as 4° and an expanding blind region with increasing transmission bandwidth, thus validating the security gain with this approach.

A gravity-based mounting approach for large-scale cryogenic calorimeter arrays

Tue, 02 Sep 2025 00:00:00 GMT

A gravity-based mounting approach for large-scale cryogenic calorimeter arrays CUPID Collaboration Cryogenic calorimeters are among the leading technologies for searching for rare events. The CUPID experiment is exploiting this technology to deploy a tonne-scale detector to search for neutrinoless double-beta decay of 100 Mo. The CUPID collaboration proposed an innovative approach to assembling cryogenic calorimeters in a stacked configuration, held in position solely by gravity. This gravity-based assembly method is unprecedented in the field of cryogenic calorimeters and offers several advantages, including relaxed mechanical tolerances and simplified construction. To assess and optimize its performance, we constructed a medium-scale prototype hosting 28 Li 2 MoO 4 crystals and 30 Ge light detectors, both operated as cryogenic calorimeters at the Laboratori Nazionali del Gran Sasso (Italy). Despite an unexpected excess of noise in the light detectors, the results of this test proved (i) a thermal stability better than ±0.5 mK at 10 mK, (ii) a good energy resolution of Li 2 MoO 4 cryogenic calorimeters, (6.6 ± 2.2) keV FWHM at 2615 keV, and (iii) a Li 2 MoO 4 light yield measured by the closest light detector of 0.36 keV/MeV, sufficient to guarantee the particle identification requested by CUPID.

A Higher Spin-Statistics Theorem for Invertible Quantum Field Theories

Mon, 01 Sep 2025 00:00:00 GMT

A Higher Spin-Statistics Theorem for Invertible Quantum Field Theories Krulewski, Cameron; Stehouwer, Luuk; Müller, Lukas We prove that every unitary invertible quantum field theory satisfies a generalization of the famous spin statistics theorem. To formulate this extension, we define a higher spin action of the stable orthogonal group O on appropriate spacetime manifolds, which extends both the reflection involution and spin flip. On the algebraic side, we define a higher statistics action of O on the universal target for invertible field theories, I Z , which extends both complex conjugation and fermion parity ( - 1 ) F . We prove that every unitary invertible quantum field theory intertwines these actions.

Computational metrology for materials

Thu, 31 Jul 2025 00:00:00 GMT

Computational metrology for materials Warren, James; Read, Jake; Seppala, Jonathan; Strand, Erik; Gershenfeld, Neil Advanced materials hold great promise, but their adoption is impeded by the challenges of developing, characterizing, and modeling them, then of designing, processing, and producing something with them. Even if the results are open, the means to do each of these steps are typically proprietary and segregated. We show how principles of open-source software and hardware can be used to develop open instrumentation for materials science, so that a measurement can be accompanied by a complete computational description of how to reproduce it. And then we show how this approach can be extended to effectively measure predictive computational models rather than just model parameters. We refer to these interrelated concepts as “computational metrology.” These are illustrated with examples including a 3D printer that can do rheological characterization of unfamiliar and variable materials.

Assessing Science Robustness in Uncertain Environments: Application to a Uranus Flagship Mission

Mon, 14 Jul 2025 00:00:00 GMT

Assessing Science Robustness in Uncertain Environments: Application to a Uranus Flagship Mission Gentgen, Chloe; Landau, Damon; Weiss, Benjamin P.; Jasinski, Jamie M.; De Weck, Olivier Defining science objectives for missions to unexplored bodies can be difficult when the underlying processes and mechanisms are not well understood. This uncertainty presents a challenge when attempting to determine mission requirements to address these objectives. Additionally, uncertainties in the environment may present risks to the system and mission operations. To this end, uncertainty quantification is increasingly used to inform and validate mission design. However, a framework has yet to be developed to support trajectory tradespace exploration of missions targeting uncertain environments through science modeling. The proposed methodology develops a science systems engineering framework integrating a science representation with trajectory designs to compute quantitative science value metrics. The science model is established by identifying relevant physical models (such as governing equations and assumptions) and input variables from the literature, simulation data, as well as past mission results. Variables are defined with probability distributions, and Monte Carlo simulations are used to quantify the uncertainties. For a given trajectory, the analysis outputs predictive probability distributions of the science value metrics, highlighting the trajectory's science performance and its robustness to uncertainty in the physical processes. The framework is applicable to any mission targeting highly dynamic and uncertain processes. This paper demonstrates its application to a future Uranus Flagship mission, focusing on magnetosphere science objectives. Listed as the highest priority Flagship mission by the latest Decadal Survey, a mission to the Uranian system aims to answer science questions regarding Uranus's interior and atmosphere, its satellites and rings, and its magnetosphere. Analytic and numerical models have been developed to understand Uranus' magnetosphere; however, significant uncertainties remain, leading to challenges when defining magnetosphere science investigations. By applying the proposed methodology, this paper shows a significant variation in predicted science metrics of interest (e.g., number of magnetopause crossings) that can be expected from similar trajectories due to varying environment conditions (solar wind and interplanetary magnetic field) or different arrival times at Uranus. These results should inform the flow-down of measurement requirements to mission design requirements for magnetosphere science. 2025 IEEE Aerospace Conference, 1-8 March, Big Sky, MT, USA

A Magnetotelluric Study of Mantle Heterogeneities Beneath the Northeastern United States

Sat, 25 Oct 2025 00:00:00 GMT

A Magnetotelluric Study of Mantle Heterogeneities Beneath the Northeastern United States Kim, Jae Deok; Evans, Rob. L. Analysis of magnetotelluric (MT) data across the northern Appalachian region reveals significantmantle heterogeneity. By inverting a subset of long‐period EarthScope USArray MT data, we constructed athree‐dimensional electrical resistivity model that provides new insights into the seismic low‐velocity NorthernAppalachian Anomaly (NAA). Comparison with empirical conductivity models indicates that the low‐resistivity anomalies along the northern and western edges of the NAA cannot be explained by temperaturealone and likely require the presence of volatiles, such as CO2‐rich or hydrous melts, or other volatile‐bearingphases, to reduce mantle resistivity to the observed levels. In addition, our modeling suggests that certainalternative lithologies, particularly hydrous clinopyroxenites, may also contribute to the observed conductivity,implying that compositional heterogeneity plays a role alongside fluids or melt. These conductive features mayreflect partial melting or metasomatic enrichment of carbonated and hydrated mantle domains introduced duringpast subduction or plume interactions, potentially mobilized by edge‐driven convection at lithosphericboundaries. We also resolve a deep resistive feature in western New England, interpreted as a dry and depletedlithospheric block, though its nature remains uncertain due to limited seismic expression and the relatively lowsensitivity of MT to resistive structures. Our results suggest that the upper mantle beneath New England is bothcompositionally and thermally heterogeneous, shaped by a complex tectonic history involving subduction,metasomatism, lithospheric thinning, and ongoing asthenospheric processes.

“Reason” En Masse

Sun, 03 Aug 2025 00:00:00 GMT

“Reason” En Masse Watkins, Eliot We can use “reason,” with its normative sense, as both a count noun (“there is a reason for her to Φ”) and a mass noun (“there is plenty of reason for her to Φ”). How are the count and mass senses of “reason” related? Daniel Fogal argues that the mass sense is fundamental: Just as lights are merely those things that give light and anxieties are merely those things that give anxiety, reasons are merely those things that give reason. In this article, I develop an opposing analysis of the mass noun “reason” that puts reasons first. Just as the detail on the Mona Lisa is composed of particular details (brushstrokes and colors) and the crime in L.A. is composed of particular crimes (pickpocketings and speeding offenses), so the reason for you to go to the dentist is composed of your reasons to go. Reasons stand to reason as parts to a whole. Such a picture makes reasons fundamental once more, but it has a cost of entry. In order to accommodate the behavior of “reason” in comparative constructions, you need to abandon the idea that reasons are facts we can count up. On the contrary: They're not facts, and you can't count them.

Battle in the Clouds

Fri, 18 Jul 2025 00:00:00 GMT

Battle in the Clouds Moran‐Thomas, Amy This narrative experiment brings together scenes from my family histories in western Pennsylvania coal country, alongsideongoing visits to learn about rising health issues in the region today. Increasing numbers of residents express concerns aboutchronic problems such as young cancers, and many people worry about potential exposures coming from past and present energyinfrastructures. These growing health concerns, some of them my own, also brought me to revisit Rachel Carson’s medical writingsfrom her family home in western Pennsylvania. Looking out from her childhood bedroom with my mother and returning toCarson’s archival notes on “transmissible cancers” and her childhood essay, “A Battle in the Clouds,” these descriptions circlelong-accumulating debates about chronic diseases and their causes and effects over time. Returning to varieties of changing cloudstoday, this essay reflects on how chronic exposures—unevenly accumulating in bodies and landscapes and across generations—show “undone sciences” of many kinds in need of collective attention. It traces how families are grappling with the sense ofneeding to connect their own dots; the ways local communities are coming together to process displaced responsibilities; and theimplications for health, public trust, and care when so much is left in clouds.

Leaf Stripping on Uniform Attachment Trees

Mon, 04 Aug 2025 00:00:00 GMT

Leaf Stripping on Uniform Attachment Trees Addario‐Berry, Louigi; Brandenberger, Anna; Briend, Simon; Broutin, Nicolas; Lugosi, Gábor In this note, we analyze the performance of a simple root-finding algorithm in uniform attachment trees. The leaf-stripping algorithm recursively removes all leaves of the tree for a carefully chosen number of rounds. We show that, with probability 1 − 𝜀, the set of remaining vertices contains the root and has a size only depending on 𝜀 but noton the size of the tree.

Unnatural Wills: Inheritance Disputes and Inequality

Wed, 23 Jul 2025 00:00:00 GMT

Unnatural Wills: Inheritance Disputes and Inequality O'Brien, Shay Within the conceptual frame of relational economic sociology, inheritance disputes are a canonical form of relational mismatch.But the social patterning of relational mismatches, and their various ties to inequality, remain murky. In this paper, I examineall known inheritance disputes in Dallas from 1895–1945 within their social context to generate hypotheses about the rela-tionship between inequality and mismatches more broadly. Inheritance disputes were usually resolved by increasing the spreadof fortunes; in this sense, they moderated wealth inequality between individuals. But not everyone was equally able to maketheir preferred estate distribution a reality. Using a series of case studies, I argue that dispute resolutions tended to reifynormative family structures and naturalize sharp, moralized distinctions between fuzzy social categories. The legal resolutionsto this class of relational mismatches may marginally mitigate individual‐level wealth inequality and simultaneously producecategorical inequalities by race, class, gender, sexuality, and family structure. I conclude with a set of hypotheses and questionsfor future studies.

Decentralization, Blockchain, Artificial Intelligence (AI): Challenges and Opportunities

Tue, 22 Jul 2025 00:00:00 GMT

Decentralization, Blockchain, Artificial Intelligence (AI): Challenges and Opportunities Hui, Xiang; Tucker, Catherine New technologies like blockchain allow firms to decentralize core functions, forcing managers to reconsider the trade-off be-tween closed, proprietary control and open strategies that involve external contributors. While proponents often advocate forfull decentralization, we argue this view overlooks important economic trade-offs. We propose that the better strategy is selectivedecentralization: a disciplined approach to choosing where to centralize for efficiency and where to decentralize for innovation.We propose a three-level framework—Infrastructure, Decision-Making, and Operational Control—to guide this choice, helpingmanagers analyze the specific costs and benefits at each layer. We apply this framework to the strategic adoption of ArtificialIntelligence (AI), where the technology's powerful pull toward centralization provides a stark test case. Our analysis shows thatan “open source AI” strategy—decentralizing operations to foster innovation while keeping infrastructure centralized for effi-ciency—is more pragmatic than full decentralization. Selective decentralization therefore emerges as a key managerial capabilityfor capturing blockchain's benefits without sacrificing scale efficiencies.

Characterizing the response time of unpumped oxygen optodes for profiling applications

Sat, 26 Jul 2025 00:00:00 GMT

Characterizing the response time of unpumped oxygen optodes for profiling applications Park, Ellen; Nicholson, David; Dever, Mathieu; Atamanchuk, Dariia; Richards, Clark The response times of the Aanderaa 4330, Aanderaa 4330 WTW, RBRcoda T.ODO|slow, and PyroScience PICO-O2-SUB were evaluated in the laboratory over a range of profiling speeds at two temperatures. The PyroScience PICO-O2-SUB had the fastest response time (1–4 s), followed by the RBRcoda T.ODO|slow (~ 15–35 s), Aanderaa 4330 (~ 30–60 s), and Aanderaa 4330W (~ 50–100 s). This study provides recommendations on improving the quality of oxygen data from optodes in profiling applications by additionally assessing the impact of response time testing setups, thermal inertia effects, and foil types on sensor response times. This study provides a new response time function based on physical principles to predict response time for these four optode types.

Tapping ressentiment: pharmakeus and the sublime poisons of white supremacy

Mon, 14 Apr 2025 00:00:00 GMT

Tapping ressentiment: pharmakeus and the sublime poisons of white supremacy Ruffin, Jessica This auto-philosophical essay takes up Nietzsche’s concept of ressentiment; the archival record of Mark and Phillis; and Derrida’s engagement with pharmakon as a means of working through the question of what is to be done with the poisons of white supremacy, which persist in present worldly environments as well as our bodies and histories. Engaging aesthetics, Black thought, and phenomenology of race, the work aims for an embodied therapeutic movement that might open the way for ethical receptivity within the white supremacist world. Eschewing a universalizing tone while recognizing the ahistoricities of white supremacist cultural techniques, the essay enlists autobiography and practices of the self to give voice to the reservoirs of white supremacist poison permeating a worldly body.

SLAM Handbook: From Localization and Mapping to Spatial Intelligence

SLAM Handbook: From Localization and Mapping to Spatial Intelligence Carlone, Luca; Kim, Ayoung; Barfoot, Timothy; Cremers, Daniel; Dellaert, Frank Simultaneous Localization and Mapping —better known as SLAM— refers to the fundamental problem of building spatial models of an environment while simultaneously determining the position of a robot within that environment. The term itself was first coined in 1995 by Hugh Durrant-Whyte and John Leonard, marking the formalization of a problem that sits at the intersection of robotics, geometry, controls, and probabilistic inference. SLAM is as elegant as it is formidable. At its core, it addresses the challenge of reasoning over high-dimensional, uncertain, and dynamic systems. The process demands precise spatial inference and robust probabilistic modeling to build coherent maps of the world —maps that must be constructed in real time, often under conditions of noise and ambiguity. What makes SLAM particularly compelling is its universality. In computer vision, it is mirrored in the problem of Structure from Motion; in robotics, it underpins everything from indoor autonomous navigation to planetary exploration and selfdriving cars. Since its inception, SLAM has inspired tens of thousands of research papers, drawing deeply from disciplines as diverse as physics, statistics, computer vision, geometry, controls, and machine learning. Its evolution has catalyzed the development of increasingly capable autonomous systems, able to operate at scale in complex, open-world environments. This volume brings together contributions from some of the field’s foremost experts and rising stars. The chapters represent the state of the art in SLAM today, reflecting both the depth of theoretical innovations and the breadth of practical applications. From its early formulations based on Kalman filters and Bayesian estimation, SLAM has matured into a rich tapestry of mathematical frameworks —encompassing graph-based optimization, factor graphs, nonlinear least squares, and deep learning-based techniques. Beyond introducing the mathematical foundations of SLAM, this volume provides valuable guidance to the practitioner by discussing real-world use cases ranging from vision-based and LiDAR-based SLAM systems to legged locomotion. It also covers recent developments in Spatial AI, showing how advances in deep learning, differentiable rendering, and large vision and language models point the way toward representations that provide robots with a rich spatial and semantic understanding of their environment.

Towards a Science Exocortex

Thu, 15 Aug 2024 00:00:00 GMT

Towards a Science Exocortex Yager, Kevin G. Artificial intelligence (AI) methods are poised to revolutionize intellectual work, with generative AI enabling automation of text analysis, text generation, and simple decision making or reasoning. The impact to science is only just beginning, but the opportunity is significant since scientific research relies fundamentally on extended chains of cognitive work. Here, we review the state of the art in agentic AI systems, and discuss how these methods could be extended to have even greater impact on science. We propose the development of an exocortex, a synthetic extension of a person's cognition. A science exocortex could be designed as a swarm of AI agents, with each agent individually streamlining specific researcher tasks, and whose inter-communication leads to emergent behavior that greatly extend the researcher's cognition and volition.

Domestic groundwater wells in Appalachia show evidence of low-dose, complex mixtures of legacy pollutants

Thu, 20 Jun 2024 00:00:00 GMT

Domestic groundwater wells in Appalachia show evidence of low-dose, complex mixtures of legacy pollutants Bugher, Nicolette Anna; Xiong, Boya; Gentles, Runako I.; Glist, Lukas D.; Siegel, Helen G.; Johnson, Nicholaus P.; Clark, Cassandra J.; Deziel, Nicole; Saiers, James E.; Plata, Desiree Lack of water quality data for private drinking water sources prevents robust evaluation of exposure risk for communities co-located with historically contaminated sites and ongoing industrial activity. Areas of the Appalachian region of the United States (i.e., Pennsylvania, Ohio and West Virginia) contain extensive hydraulic fracturing activity, as well as other extractive and industrial technologies, in close proximity to communities reliant on private drinking water sources, creating concern over potential groundwater contamination. In this study, we characterized volatile organic compound (VOC) occurrence at 307 private groundwater well sites within Pennsylvania, Ohio, and West Virginia. The majority (97%) of water samples contained at least one VOC, while the average number of VOCs detected at a given site was 5 ± 3. The majority of individual VOC concentrations fell below applicable U.S. Environmental Protection Agency (EPA) Maximum Contamination Levels (MCLs), except for chloroform (MCL of 80 μg L−1; n = 1 at 98 μg L−1), 1,2-dibromoethane (MCL of 0.05 μg L−1; n = 3 ranging from 0.05 to 0.35 μg L−1), and 1,2-dibromo-3-chloropropane (MCL of 0.2 μg L−1; n = 7 ranging from 0.20 to 0.58 μg L−1). To evaluate well susceptibility to VOCs from industrial activity, distance to hydraulic fracturing site was used to assess correlations with contaminant occurrences. Proximity to closest hydraulic fracturing well-site revealed no statistically significant linear relationships with either individual VOC concentrations, or frequency of VOC detections. Evaluation of other known industrial contamination sites (e.g., US EPA Superfund sites) revealed elevated levels of three VOCs (chloroform, toluene, benzene) in groundwaters within 10 km of those Superfund sites in West Virginia and Ohio, illuminating possible point source influence. Lack of correlation between VOC concentrations and proximity to specific point sources indicates complex geochemical processes governing trace VOC contamination of private drinking water sources. While individual concentrations of VOCs fell well below recommended human health levels, the low dose exposure to multiple VOCs occurring in drinking supplies for Appalachian communities was noted, highlighting the importance of groundwater well monitoring.

The Opportunity for Utilizing End‐of‐Life Scrap to Meet Growing Copper Demand

Fri, 11 Jul 2025 00:00:00 GMT

The Opportunity for Utilizing End‐of‐Life Scrap to Meet Growing Copper Demand Diersen, Isabel; Bhuwalka, Karan; Olivetti, Elsa As electrification trends and clean energy deployment drive up copper demand, there will be pressure on copper supply chains.With annual copper demand expected to grow by 50% and reach 49 Mt by 2035, the world will continue to need additional sourcesof copper supply. While expanding mining projects could increase copper production, given the significant stock of material,secondary copper can play a vital role in meeting demand. We analyze the opportunity to meet growing copper demand via in-creased scrap collection and improved technical recycling efficiencies. We use an economic model of the global copper system—with China analyzed separately from the rest of the world—to quantify supply evolution by incorporating price feedback betweendemand and supply. The model quantifies the impact of the increased collection on the displacement of mining production anddemonstrates how increasing recycling can modulate supply risks and copper prices. Aligned with recent literature on futurecopper flows, we find that there is an opportunity to increase scrap supply in 2040 by 46% (6.3 Mt) compared with the baseline.

Topographic Stress as a Mechanical Weathering Mechanism on Titan

Tue, 29 Jul 2025 00:00:00 GMT

Topographic Stress as a Mechanical Weathering Mechanism on Titan Seltzer, Cassandra; Martel, Stephen J; Perron, J Taylor Titan is unique among icy moons for its active surface processes and extensive erosional features.The presence of coarse sediment suggests that mechanical weathering breaks down Titan's surface material, butthe exact processes of mechanical weathering are unknown. We tested the idea that topographic features perturbambient crustal stresses enough to generate or enhance fractures. We used a two‐dimensional boundary elementmodel to predict the likely stress state within hypothetical erosional landforms on Titan, including river valleysand isolated ridges, and to model the locations and types of resulting fractures. Our results suggest thattopographic stress perturbations are indeed sufficient to generate fractures and drive mechanical weathering,with little sensitivity to the density of the material making up Titan's crust and landforms and no dependence onits elastic moduli. For material density of 800 to1,200 kg/m3, opening‐mode failure is predicted to occur withinhypothetical Titan landforms with a width of hundreds of meters, relief of tens of meters or more, and horizontaltidal or tectonic stresses up to 1 MPa of compression, which encompasses typical predicted tidal stresses rangingbetween 10 kPa of compression and 10 kPa of tension. Under the same conditions, shear fracture is predicted tooccur if the cohesion of the material is less than 100 kPa or if pore fluid pressures reduce local effective normalstresses. We therefore suggest that Titan's crust may be highly fractured and permeable, and that the predictedfractures could help generate sediment and provide pathways for subsurface transport of fluids.

The existence of subspace designs

Thu, 17 Jul 2025 00:00:00 GMT

The existence of subspace designs Keevash, Peter; Sah, Ashwin; Sawhney, Mehtaab We prove the existence of subspace designs with anygiven parameters, provided that the dimension of theunderlying space is sufficiently large in terms of theother parameters of the design and satisfies the obvi-ous necessary divisibility conditions. This settles an openproblem from the 1970s. Moreover, we also obtain anapproximate formula for the number of such designs.

Verbal disputes, social totality, and trans politics

Tue, 22 Jul 2025 00:00:00 GMT

Verbal disputes, social totality, and trans politics Zhou, Katie A puzzling feature about the dispute over whether transwomen are women is its apparent verbality: gender-critical theorists assert a biological fact about transwomen, and trans-inclusionary theorists respond byasserting a social/psychological fact about trans women.But plausibly, both theorists’ assertions are compatible,and so there is no real disagreement. In this paper, Iargue that the two theorists are not talking past eachother. But I also argue that extant accounts of the dis-pute fail to adequately explain why the dispute is notmerely verbal. Indeed, clarifying the dispute requires usto ask what it is for something to be a gender concept,as opposed to a merely biological or social/psychologicalconcept. After developing a questions-based account ofconcepts and conceptual roles, I suggest that a neces-sary feature of gender concepts is that we use them toconstruct unified and portable narratives about how wewill stand in relation to one another as social individu-als, regardless of the particular social context we are in.This allows us to understand the trans woman disputeas a dispute about whether we should prioritize biolog-ical or social/psychological facts when interpreting ourrelations to one another.

Microscale Metal Additive Manufacturing by Solid‐State Impact Bonding of Shaped Thin Films

Mon, 14 Jul 2025 00:00:00 GMT

Microscale Metal Additive Manufacturing by Solid‐State Impact Bonding of Shaped Thin Films Reiser, Alain; Schuh, Christopher A The deposition of device-grade inorganic materials is one key challenge towardthe implementation of additive manufacturing (AM) in microfabrication, andto that end, a broad range of physico-chemical principles has been exploredfor 3D fabrication with micro- and nanoscale resolution. Yet, for metals,a process that achieves material quality rivalling that of established thin-ﬁlmdeposition methods, and at the same time, has the potential to combinehigh throughput production with a broad palette of processable materials, isstill lacking. Here, the kinetic, solid-state bonding of metal thin ﬁlms for theadditive assembly of high-purity, high-density metals with micrometer-scaleprecision is introduced. Indirect laser ablation accelerates micrometer-thickgold ﬁlms to hundreds of meters per second without their heating or ablation.Their subsequent impact on the substrate above a critical velocity forms apermanent, metallic bond in the solid state. Stacked layers are of high density(>99%). By deﬁning thin-ﬁlm layers with established lithographic methodsprior to launch, a variable feature size (2–50 µm), arbitrary shape of bondedlayers, and parallel transfer of up to 36 independent ﬁlm units in a single shot,is demonstrated. Thus, the solid-state kinetic bonding principle as a viableand potentially versatile route for micro-scale AM of metals is established.

Persistent Disruptions in Prefrontal Connectivity Despite Behavioral Rescue by Environmental Enrichment in a Mouse Model of Rett Syndrome

Thu, 17 Jul 2025 00:00:00 GMT

Persistent Disruptions in Prefrontal Connectivity Despite Behavioral Rescue by Environmental Enrichment in a Mouse Model of Rett Syndrome Ährlund‐Richter, Sofie; Harpe, Jonathan; Fernandes, Giselle; Lam, Ruby; Sur, Mriganka Rett syndrome, a neurodevelopmental disorder caused by loss-of-function mutations in the MECP2 gene, is characterized by severe motor, cognitive, and emotional impairments. Some of the deficits may result from changes in cortical connections, especially downstream projections of the prefrontal cortex (PFC), which may also be targets of restoration following rearing conditions such as environmental enrichment that alleviate specific symptoms. Here, using a heterozygous Mecp2+/− female mouse model closely analogous to human Rett syndrome, we investigated the impact of early environmental enrichment on behavioral deficits and PFC connectivity. Behavioral analyses revealed that enriched housing rescued fine motor deficits and reduced anxiety, with enrichment-housed Mecp2+/− mice performing comparably to wild-type (WT) controls in rotarod and open field assays. Anatomical mapping of top-down anterior cingulate cortex (ACA) projections demonstrated altered PFC connectivity in Mecp2+/− mice, with increased axonal density in the somatosensory cortex and decreased density in the motor cortex compared to WT controls. ACA axons revealed shifts in hemispheric distribution, particularly in the medial network regions, with Mecp2+/− mice exhibiting reduced ipsilateral dominance. These changes were unaffected by enriched housing, suggesting that structural abnormalities in PFC connectivity persist despite behavioral improvements. Enriched housing rescued brain-derived neurotrophic factor (BDNF) levels in the hippocampus but failed to restore BDNF levels in the PFC, consistent with the persistent deficits observed in prefrontal axonal projections. These findings highlight the focal nature of changes induced by reduction of MeCP2 and by exposure to environmental enrichment and suggest that environmental enrichment starting in adolescence can alleviate behavioral deficits in Mecp2+/− mice without reversing abnormalities in large-scale cortical connectivity.

Agentic deep graph reasoning yields self-organizing knowledge networks

Thu, 31 Jul 2025 00:00:00 GMT

Agentic deep graph reasoning yields self-organizing knowledge networks Buehler, Markus J. We present an agentic, autonomous graph expansion framework that iteratively structures and refines knowledge in situ. Unlike conventional knowledge graph construction methods relying on static extraction or single-pass learning, our approach couples a reasoning-native large language model with a continually updated graph representation. At each step, the system actively generates new concepts and relationships, merges them into a global graph, and formulates subsequent prompts based on its evolving structure. Through this feedback-driven loop, the model organizes information into a scale-free network characterized by hub formation, stable modularity, and bridging nodes that link disparate knowledge clusters. Over hundreds of iterations, new nodes and edges continue to appear without saturating, while centrality measures and shortest path distributions evolve to yield increasingly distributed connectivity. Applied to materials design problems, we present compositional reasoning experiments to foster knowledge synthesis, yielding cross-domain ideas that transcend rote summarization.

EvenQuads Game and Error-Correcting Codes

Fri, 22 Aug 2025 00:00:00 GMT

EvenQuads Game and Error-Correcting Codes Byrapuram, Nikhil; Choi, Hwiseo; Ge, Adam; Ge, Selena; Lee, Sylvia Z.; Liang, Evin; Mandal, Rajarshi; Oki, Aika; Wu, Daniel; Yang, Michael; Khovanova, Tanya EvenQuads is a new card game that is a generalization of the SET game, where each card is characterized by three attributes, each taking four possible values. Four cards form a quad when, for each attribute, the values are the same, all different, or half and half. For any ℓ cards selected from the deck of EvenQuads, it is possible to construct an error-correcting linear binary code of length ℓ and Hamming distance 4, where quads correspond to codewords of weight 4. Using error-correcting codes, we calculate the number of possible quads that can be formed with up to 8 cards. We also estimate the number of cards that do not contain quads for decks of different sizes. In addition, we discuss properties of error-correcting codes built on semimagic, magic, and strongly magic quad squares. This highlights a rich interplay between recreational mathematics games and coding theory and encourages others to explore similar combinatorial games for hidden connections!

Machine Learning Applications Enabling Fusion Energy: Recent Developments

Wed, 03 Sep 2025 00:00:00 GMT

Machine Learning Applications Enabling Fusion Energy: Recent Developments Rea, Cristina Over the last few years, machine learning helped to develop advanced capabilities for fusion energy over a broad range of domains. This includes advanced algorithms to extract information from fusion diagnostics, enhanced algorithms for plasma state estimation and control, accelerated simulation tools to improve predictive capabilities, and expanded modeling capabilities for fusion materials design. This topical collection covers recent developments in machine learning applied research further enabling the path to fusion energy; in particular it covers a wide breadth of fusion subfields – from inertial confinement fusion, to magnetically confined plasma, including high temperature superconducting magnet design and optimization. This editorial summarizes the collection while also providing a critical outlook on how machine learning can be used in the future to accelerate the development of fusion energy as a reliable energy source.

Synthesis‐Related Nanoscale Defects in Mo‐Based Janus Monolayers Revealed by Cross‐Correlated AFM and TERS Imaging

Fri, 08 Aug 2025 00:00:00 GMT

Synthesis‐Related Nanoscale Defects in Mo‐Based Janus Monolayers Revealed by Cross‐Correlated AFM and TERS Imaging Zhang, Tianyi; Krayev, Andrey; Yang, Tilo H; Mao, Nannan; Hoang, Lauren; Wang, Zhien; Liu, Hongwei; Peng, Yu‐Ren; Zhu, Yunyue; Zheng, Xudong; Isotta, Eleonora; Kira, Maria E; Righi, Ariete; Pimenta, Marcos A; Chueh, Yu‐Lun; Pop, Eric; Mannix, Andrew J; Kong, Jing 2D Janus transition metal dichalcogenides (TMDs) are promising candidatesfor various applications including non-linear optics, energy harvesting, andcatalysis. These materials are usually synthesized via chemical conversionof pristine TMDs. Nanometer-scale characterization of the obtained Janusmaterials’ morphology and local composition is crucial for both the synthesisoptimization and the future device applications. In this work, we present theresults of cross-correlated atomic force microscopy (AFM) and tip-enhancedRaman spectroscopy (TERS) study of Janus monolayers synthesizedby the hydrogen plasma-assisted chemical conversion of MoSe 2 andMoS2 . We demonstrate that the choice of both the growth substrate and thestarting TMD inﬂuences the residual strain, thereby shaping the nanoscalemorphology of the resulting Janus material. Furthermore, by employingTERS imaging, we show the presence of nanoscale islands (≈20 nm across)of MoSe 2 - Mo SSe (MoS2 -MoSeS ) vertical heterostructures originating from thebilayer nanoislands in the precursor monolayer crystals. The understanding ofthe origins of nanoscale defects in Janus TMDs revealed in this study can helpwith further optimization of the Janus conversion process towards uniformand wrinkle-/crack-free Janus materials. Moreover, this work shows thatcross-correlated AFM and TERS imaging is a powerful and accessible methodfor studying nanoscale composition and defects in Janus TMD monolayers.

The Kigali story, the Singapore model, and rights to the city

Tue, 05 Aug 2025 00:00:00 GMT

The Kigali story, the Singapore model, and rights to the city Fischer, Michael MJ Three recent ethnographies of Kigali's urban planning and development provide a welcome addition to a long tradition of such ethnographies, including Lisa Redfield Peattie's famous fieldwork in the planning of Ciudad Guayana (1968; 1987), Grace Goodell's ethnographic account of the disjunction between planning offices in Tehran and the urban settlements (sharaks) of the Khuzistan Development Project modelled on the Tennessee Vally Authority (1986), and Gökce Günel's ethnographic analysis of the disjunction between plans for, and implementation of, Mazdar City and Mazdar Institute in Abu Dhabi (2019).

Pressurized plankton observatory offers a new window into deep‐sea larval behavior

Wed, 23 Jul 2025 00:00:00 GMT

Pressurized plankton observatory offers a new window into deep‐sea larval behavior Zúñiga Mouret, Rodrigo; Hourdez, Stéphane; Curran, Molly; DiBenedetto, Michelle H.; Mills, Susan W.; Vetriani, Costantino; Arellano, Shawn M.; Weston, Johanna N. J.; Dykman, Lauren N.; Best, Ayinde C.; Pires, Anthony; Mullineaux, Lauren S. The High-Pressure Plankton Observatory (HiPPO) is designed to quantify motions of zooplankton for behavioral study, including swimming and metabolic responses to environmental perturbations. It builds on prior chamber designs while filling gaps in capability for resolving orientation of small (< 1 mm) plankton, tracking their movements over ecologically relevant spatial scales, and recording in flow-through conditions on a vessel at sea. The HiPPO chamber has a direct light path for silhouette imaging of zooplankton as they move vertically and horizontally across a 3.56 cm diameter viewing area. Seawater forced by a high-performance liquid chromatography pump is exchanged continuously through the chamber, but flushing of zooplankton is prevented by fine mesh at the ports. A high-resolution camera/computer setup enables sustained imaging of plankton motions for quantitative analysis. Application of HiPPO to an investigation of larval behavior of deep-sea hydrothermal vent species revealed swimming behaviors similar to those of shallow-water species, including upward and downward helices, meandering, and short hovers. In conditions with microbial biofilm (a potential settlement cue) on a 2024 expedition, vent larvae unexpectedly swam rapidly upward in tight helices at velocities (0.15 cm s−1) higher than those observed in prior experiments with no biofilm (0.03 cm s−1). Many factors varied between the 2024 and earlier trials, so the difference cannot be attributed with certainty to a cue response. This study describes key new features of HiPPO and demonstrates the system's ability to document novel zooplankton behavior.

Social-ecological system approaches for water resources management

Thu, 18 Jun 2020 00:00:00 GMT

Social-ecological system approaches for water resources management Gain, Animesh K.; Hossain, Sarwar; Benson, David; Di Baldassarre, Giuliano; Giupponi, Carlo; Huq, Nazmul In the era of the Anthropocene, understanding the dynamic interactions between humans andwater is crucial for supporting both human well-being and the sustainable management ofresources. The current water management challenges are inherently unpredictable and difficultto control. Social-ecological systems (SESs) approaches explicitly recognize the connections andfeedbacks between human and natural systems. For addressing the complex challenges of theAnthropocene, consideration of SES attributes such as causality (or interdependence), feedback,non-linearity, heterogeneity, and cross-scale dynamics is important. In addition, innovative quali-tative and quantitative methods such as Bayesian networks, agent-based modelling, systemdynamics, network analysis, multicriteria analysis, integrated assessment and role-play gameshave recently been used in SES research. The overall goal of this review is to gauge the extentto which SES attributes and methods are considered within the current interdisciplinary waterparadigm. The paper therefore develops the normative theoretical characteristics of SES in termsof its key attributes (i.e. causality, feedback, heterogeneity, nonlinearity, and cross-scale dynamics)incorporated in the water paradigm approaches. The paper then compares the methods appliedin the interdisciplinary water paradigm and examines how they can complement each other.Finally, the paper reflects back on the usefulness of SES attributes and methods for assessing theinterdisciplinary water paradigm and makes recommendations for future research.

Quantifying and improving the optical performance of the laser ablation aerosol particle time of flight mass spectrometer (LAAPToF) instrument

Fri, 21 Feb 2020 00:00:00 GMT

Quantifying and improving the optical performance of the laser ablation aerosol particle time of flight mass spectrometer (LAAPToF) instrument Zawadowicz, Maria A; Lance, Sara; Jayne, John T; Croteau, Philip; Worsnop, Douglas R; Mahrt, Fabian; Leisner, Thomas; Cziczo, Daniel J Single particle mass spectrometer (SPMS) instruments have been used for in-situ chemicalcharacterization of atmospheric aerosols, both in the field and laboratory, for over two deca-des. SPMSs typically combine precise optical particle sizing with laser desorption and ioniza-tion followed by time of flight mass spectrometry. Among the advantages of SPMSs overother aerosol chemistry measurement techniques are their single particle resolution andhigh sensitivity to trace chemical species. The AeroMegt Laser Ablation Aerosol ParticleTime of Flight Mass Spectrometer (LAAPToF) is a commercially available member of thisinstrument class, aiming for a compact size and simplicity for the end user. This articlequantifies the performance of LAAPToF with an emphasis on optical counting efficiency.Recommendations for improving detection compared to the base LAAPToF hardware aredescribed. Our results show that changes to the optical detection scheme can lead to overtwo orders of magnitude improvement in optical counting efficiency in the size range500–2000 nm vacuum aerodynamic diameter. We also present mass spectral performancefor characterizing atmospherically relevant particles in a comparison to a current SPMSdesign, the Particle Analysis by Laser Mass Spectrometry.

Expression of endogenous Anopheles gambiae microRNAs using an Anopheles gambiae densovirus (AgDNV) intronic expression system

Tue, 19 Aug 2025 00:00:00 GMT

Expression of endogenous Anopheles gambiae microRNAs using an Anopheles gambiae densovirus (AgDNV) intronic expression system Johnson, Rebecca M.; Metz, Hillery C.; Suzuki, Yasutsugu; McLean, Kyle J.; Rasgon, Jason L. Background Anopheles gambiae densovirus (AgDNV) is a highly species-specific parvovirus that reaches high titers in adult Anopheles gambiae mosquitoes with few transcriptomic effects and minimal significant fitness effects. Given these characteristics, AgDNV has been proposed as a viral vector for basic research and mosquito control. Previous work created an AgDNV co-expression system with a wild-type AgDNV helper plasmid and a transducing plasmid expressing enhanced green fluorescent protein (EGFP) that can be used to co-transfect cells to generate infectious recombinant transducing AgDNV virions. Generated virions infect the An. gambiae midgut, fat body, and ovaries, yet this viral vector system is limited in the size of transgenes that can be expressed due to capsid packaging limitations. Methods Considering these size constraints, we created an artificial intron within the EGFP gene of the transducing construct that can express small pieces of genetic material such as microRNAs (miRNAs), microRNA sponges, or other small sequences. Placement of this intron in EGFP created a fluorescent reporter such that incorrect splicing produces a frameshift mutation in EGFP and an early stop codon, whereas correct splicing results in normal EGFP expression and co-transcription of the intronic genetic cargo. A selection of miRNAs with predicted or demonstrated importance in mosquito immunity and reproduction with expression localized to the fat body or ovaries were chosen as intronic cargo. Construct expression and splicing was evaluated, and the impact of miRNA expression on putative miRNA targets was measured in vitro and in vivo. Results The created intron was correctly spliced in cells and mosquitoes; however, miRNA delivery resulted in inconsistent changes to miRNA and predicted target gene transcript levels—possibly due to organ-specific miRNA expression or inaccurate putative target predictions leading to miRNA–target gene sequence mismatch. Conclusions Although our results on target gene expression were inconsistent, with optimization this viral vector and developed intron have potential as an expression tool within An. gambiae mosquitoes or cell lines.

Advanced Modeling and Microstructural Insights into the Hot Deformation Behavior of Fe–11Al–5Mn–1Nb–1C Low-Density Steel

Sun, 18 May 2025 00:00:00 GMT

Advanced Modeling and Microstructural Insights into the Hot Deformation Behavior of Fe–11Al–5Mn–1Nb–1C Low-Density Steel Mahanta, Bashista K.; Rawat, Pankaj; Bhan, Sumit; Roy, Swagata The hot deformation behavior of Fe–11Al–5Mn–1Nb–1C low-density steel was investigated using a GLEEBLE 3800R thermomechanical simulator across a temperature range of 900–1200 ℃ and strain rates of 1–0.001 s−1. An Arrhenius-type constitutive model was developed to predict flow stress during deformation, alongside a bilayer evolutionary neural network (EvoNN) model based on an artificial neural network (ANN) approach. The EvoNN model demonstrated higher prediction accuracy than the constitutive model. Microstructural analysis revealed a ferritic matrix with kappa carbide as a secondary phase at 900 and 1000 ℃, while at 1100 and 1200 ℃, a dual-phase structure (ferrite + austenite) with fine kappa carbides at the phase interface was observed. NbC particles were consistently present in all hot compressed samples. Partial dynamic recrystallization (DRX) occurred at 900 and 1000 ℃, whereas more extensive DRX was observed at 1100 and 1200 ℃. Grain coarsening was evident at lower strain rates, increasing as the strain rate decreased. Fine NbC particles and kappa carbides pinned grain boundaries, potentially delaying DRX onset, while coarse NbC particles appeared to enhance particle-stimulated nucleation (PSN), introducing complexity to DRX dynamics and contributing to model discrepancies in the constitutive and EvoNN model.

Three-pion Bose-Einstein correlations measured in proton-proton collisions

Thu, 21 Aug 2025 00:00:00 GMT

Three-pion Bose-Einstein correlations measured in proton-proton collisions Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. A study on the Bose-Einstein correlations for triplets of same-sign pions is presented. The analysis is performed using proton-proton collisions at a centre-of-mass energy of s = 7 TeV, recorded by the LHCb experiment, corresponding to an integrated luminosity of 1.0 fb−1. For the first time, the results are interpreted in the core-halo model. The parameters of the model are determined in regions of charged-particle multiplicity. This measurement provides insight into the nature of hadronisation in terms of coherence, being consistent with the presence of coherent emission of pions.

Search for dark matter produced in association with one or two top quarks in proton-proton collisions at √s = 13 TeV

Tue, 12 Aug 2025 00:00:00 GMT

Search for dark matter produced in association with one or two top quarks in proton-proton collisions at √s = 13 TeV Chekhovsky, V.; Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I. A search is performed for dark matter (DM) produced in association with a single top quark or a pair of top quarks using the data collected with the CMS detector at the LHC from proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to 138 fb−1 of integrated luminosity. An excess of events with a large imbalance of transverse momentum is searched for across 0, 1 and 2 lepton final states. Novel multivariate techniques are used to take advantage of the differences in kinematic properties between the two DM production mechanisms. No significant deviations with respect to the standard model predictions are observed. The results are interpreted considering a simplified model in which the mediator is either a scalar or pseudoscalar particle and couples to top quarks and to DM fermions. Axion-like particles that are coupled to top quarks and DM fermions are also considered. Expected exclusion limits of 410 and 380 GeV for scalar and pseudoscalar mediator masses, respectively, are set at the 95% confidence level. A DM particle mass of 1 GeV is assumed, with mediator couplings to fermions and DM particles set to unity. A small signal-like excess is observed in data, with the largest local significance observed to be 1.9 standard deviations for the 150 GeV pseudoscalar mediator hypothesis. Because of this excess, mediator masses are only excluded below 310 (320) GeV for the scalar (pseudoscalar) mediator. The results are also translated into model-independent 95% confidence level upper limits on the visible cross section of DM production in association with top quarks, ranging from 1 pb to 0.02 pb.

A parametric approach to plot-based urban design: A climate-responsive algorithmic control for the generation of urban block

Fri, 17 Oct 2025 00:00:00 GMT

A parametric approach to plot-based urban design: A climate-responsive algorithmic control for the generation of urban block Çalışkan, Olgu; Akay, Mert In modern urbanism, (re)production of urban land predominantly relies on large parcels through intensive capital investments. Such a mainstream significantly shapes the overall urban form, subsequently influencing the quality of life through the perceived characteristics of the form and program of the planned districts. Consequently, critical urban design theory increasingly prioritizes the plot as the fundamental unit of future urban development. While ‘plot-based urbanism’ presents a responsive approach to this issue, there remains a notable gap in systematic methodologies that can be universally applied across different contexts. In this paper, the authors propose an algorithmic framework that would be employed as a design control tool based on the associative logic of plot-based urban formation. The model framework comprises three steps: (1) plot layout generation, (2) building configuration, and (3) incremental formation of the block fabric. The applied model demonstrates the compositional variation and coherence within the urban block while concurrently optimizing the climatic performance of the emerging fabric.

Assessing uncertainties in parton showers at double logarithmic accuracy for jet quenching studies

Wed, 20 Aug 2025 00:00:00 GMT

Assessing uncertainties in parton showers at double logarithmic accuracy for jet quenching studies Andres, Carlota; Apolinário, Liliana; Armesto, Néstor; Cordeiro, André; Dominguez, Fabio; Milhano, José G. We present a systematic study of how different choices of ordering and phase-space constraints in parton showers affect the space-time structure of vacuum parton cascades and their interface with jet quenching models. Using a simplified Monte Carlo shower implemented at double logarithmic accuracy, we analyse variations in emission patterns and resulting phase-space arising from three ordering variables: inverse formation time, invariant mass, and opening angle. These are coupled with two kinematic reconstruction schemes defined by different phase-space constraints. We show that, while global features are relatively stable, differences emerge in the temporal evolution of the cascade. To probe the impact of these differences, we introduce a simplified model for in-medium energy loss based on formation time and colour decoherence, enabling us to evaluate the sensitivity of quenching observables to the underlying space-time structure of the vacuum shower. We further quantify the role of time-ordering violations and propose strategies to preserve a consistent space-time interpretation. Lastly, we explore a range of alternative quenching models confirming the robustness of our conclusions. Our findings highlight the importance of maintaining a coherent space-time structure in parton shower algorithms when modelling jet propagation in an extended QCD medium, as this structure becomes a physically meaningful and testable component of the jet itself.

Caribbean Creep meets Chesapeake Creep: marine bioinvasions and community shifts along the Mid-Atlantic Coast, USA

Mon, 18 Aug 2025 00:00:00 GMT

Caribbean Creep meets Chesapeake Creep: marine bioinvasions and community shifts along the Mid-Atlantic Coast, USA Fowler, Amy E.; Blakeslee, April M. H.; Davinack, Andrew; Aguilar, Robert; Andersen, Miranda; Benadon, Clara; Choong, Henry H. C.; Green-Gavrielidis, Lindsay; Greenberg, Sarah R.; Hartshorn, El; Hobbs, Niels-Viggo; Labbe, Sara; Larson, Kristen The Mid-Atlantic waters of North America are warming faster than > 90% of other global oceans, leading to significant increases in bottom water temperatures and influencing shifts in marine community structure. Given this modern-day scenario of significant community shifts over space and time, baseline surveys of species diversity are increasingly valuable. Therefore, we performed the first-ever marine bioinvasions Rapid Assessment Survey (RAS) along the Mid-Atlantic waters of the United States in June 2023, focused on marina floating pontoons in Virginia, Maryland, Delaware, and New Jersey. We recorded 29 non-indigenous, 16 cryptogenic, and 10 species that have expanded their ranges in the mid-Atlantic. Seven of these 10 species have expanded northwards from southern locations in the Caribbean (“Caribbean Creep”) or the western Atlantic (“Chesapeake Creep”), and three have expanded southwards. Five non-indigenous species (NIS) were found at more than 60% of the 10 sampled sites: the bryozoans Bugula neritina, Schizoporella pungens, Tricellaria inopinata, macroalgae Codium fragile subsp. fragile, and the sea anemone Aiptasiogeton eruptaurantia. We did not document any new nonindigenous species not already recorded on the Western Atlantic coast. All 10 communities were distinctly different, and species dominance varied by latitude and by site. This first-ever RAS of the Mid-Atlantic waters of the United States provides critical insight into how marine communities have been and are changing as a result of colonization by NIS, including those that have expanded their ranges as a result of human-induced climate change.

Observation of the distribution of nuclear magnetization in a molecule

Thu, 23 Oct 2025 00:00:00 GMT

Observation of the distribution of nuclear magnetization in a molecule Wilkins, S. G.; Udrescu, S. M.; Athanasakis-Kaklamanakis, M.; Garcia Ruiz, R. F.; Belosevic, I.; Berger, R.; Bissell, M. L.; Breier, A. A.; Brinson, A. J.; Chrysalidis, K.; Cocolios, T. E.; de Groote, R. P.; Dorne, A.; Flanagan, K. T.; Franchoo, S.; Gaul, K.; Geldhof, S.; Giesen, T. F.; Hanstorp, D.; Heinke, R.; Isaev, T.; Koszorus, A.; Kujanpa, S.; Lalanne, L.; Neyens, G.; Nichols, M.; Perrett, H.A.; Reilly, J.R.; Skripnikov, L. V.; Rothe, S.; van den Borne, B.; Wang, W.; Wessolek, J.; Yang, X.F.; Zulch, C.Z. Rapid progress in the experimental control and interrogation of molecules, combined with developments in precise calculations of their structure, are enabling new opportunities in the investigation of nuclear and particle physics phenomena. Molecules containing heavy, octupole-deformed nuclei such as radium are of particular interest for such studies, offering an enhanced sensitivity to the properties of fundamental particles and interactions. Here, we report precision laser spectroscopy measurements and theoretical calculations of the structure of the radioactive radium monofluoride molecule, 225Ra19F. Our results allow fine details of the short-range electron-nucleus interaction to be revealed, indicating the high sensitivity of this molecule to the distribution of magnetization, currently a poorly constrained nuclear property, within the radium nucleus. These results provide a direct and stringent test of the description of the electronic wavefunction inside the nuclear volume, highlighting the suitability of these molecules to investigate subatomic phenomena.

Design and Performance of Metal Hydride Composite Neutron Shields for Compact, High-Power Fusion Reactors

Mon, 04 Aug 2025 00:00:00 GMT

Design and Performance of Metal Hydride Composite Neutron Shields for Compact, High-Power Fusion Reactors Fletcher, Jack W; Peterson, Ethan E; Trelewicz, Jason R; Snead, Lance L We present the process and results of neutronics-driven shielding design using metal and ceramic matrix metal hydride neutron shields within the context of compact, high-power tokamaks. In particular, hafnium hydrides were considered within a matrix of stainless steel or magnesium oxide and contrasted with established and novel fast neutron shielding materials. These shielding materials are found to substantially increase the lifetime of toroidal field magnets made of high-temperature superconductors by a factor of up to 14.5. Specifically, a stainless steel–20% HfH1.7 thermal shield and outer neutron shield, paired with an inner tungsten carbide (WC) shield and toroidal field magnet case and winding pack both doped with 40% HfH1.7 by volume, were found to achieve a 93.1% reduction in peak fast neutron flux to high-temperature superconductor tapes. Simultaneously, this configuration reduced the total mass (and cost) of the neutron shield, as well as the nuclear heating rate of the magnet coil, in comparison to monolithic shields of WC and boron carbide.

GeoConformal Prediction: A Model-Agnostic Framework for Measuring the Uncertainty of Spatial Prediction

Tue, 01 Jul 2025 00:00:00 GMT

GeoConformal Prediction: A Model-Agnostic Framework for Measuring the Uncertainty of Spatial Prediction Lou, Xiayin; Luo, Peng; Meng, Liqiu Spatial prediction is a fundamental task in geography, providing essential data support for various scenarios.Recent advancements, empowered by the development of geospatial artificial intelligence (GeoAI), haveprimarily focused on improving prediction accuracy while overlooking reliable measurements of predictionuncertainty. Such measures are crucial for enhancing model trustworthiness and supporting responsibledecision-making. To address this issue, we propose a model-agnostic uncertainty assessment method calledGeoConformal Prediction (GeoCP). First, a simulation study is conducted to validate the usefulness ofGeoCP. Then, we applied GeoCP to two classic spatial prediction cases, spatial regression and spatialinterpolation, to evaluate its reliability. For the case of spatial regression, we used XGBoost to predicthousing prices, followed by GeoCP to calculate uncertainty. Our results show that GeoCP achieved acoverage rate of 93.67 percent, whereas bootstrapping methods reached a maximum coverage of 81.00percent after 2,000 runs. We then applied GeoCP for the case of spatial interpolation models. By comparinga GeoAI-based geostatistical model with a traditional geostatistical model (Kriging), we found that theuncertainty obtained from GeoCP aligned closely with the variance in Kriging. Finally, using GeoCP, weanalyzed the sources of uncertainty in spatial prediction. We found that explicitly including local features inAI models can significantly reduce prediction uncertainty, especially in areas with strong local dependence.Our findings suggest that GeoCP holds substantial potential not only for geographic knowledge discovery butalso for guiding the design of future GeoAI models, paving the way for more reliable and interpretablespatial prediction frameworks. The method is implemented in an open-source Python package namedgeoconformal. Key Words: conformal prediction, GeoAI, Kriging, spatial regression, spatial uncertainty.

Belief revision revised

Sun, 27 Jul 2025 00:00:00 GMT

Belief revision revised Pearson, Joshua Edward I outline a novel counterexample to the principle ofbelief revision, Anticipation: if both learning 𝑒 andlearning not-𝑒 would render belief in 𝑝 unjustified, youcannot now be justified in believing 𝑝. If I am right,not only is the leading theory of belief revision false, soare various recently proposed weakenings. I develop anddefend a new theory that correctly predicts the failuresof Anticipation I argue for, predicated on the simpleidea that one is justified in ruling out possibility just incase that possibility is sufficiently improbable.

Incorporating Deep Learning Into System Dynamics: Amortized Bayesian Inference for Scalable Likelihood‐Free Parameter Estimation

Tue, 21 Jan 2025 00:00:00 GMT

Incorporating Deep Learning Into System Dynamics: Amortized Bayesian Inference for Scalable Likelihood‐Free Parameter Estimation Rahmandad, Hazhir; Akhavan, Ali; Jalali, Mohammad S Estimating parameters and their credible intervals for complex system dynamics models is challenging but critical to continu-ous model improvement and reliable communication with an increasing fraction of audiences. The purpose of this study is tointegrate Amortized Bayesian Inference (ABI) methods with system dynamics. Utilizing Neural Posterior Estimation (NPE), wetrain neural networks using synthetic data (pairs of ground truth parameters and outcome time series) to estimate parameters ofsystem dynamics models. We apply this method to two example models: a simple Random Walk model and a moderately complexSEIRb model. We show that the trained neural networks can output the posterior for parameters instantly given new unseentime series data. Our analysis highlights the potential of ABI to facilitate a principled, scalable, and likelihood-free inferenceworkflow that enhance the integration of models of complex systems with data. Accompanying code streamlines application todiverse system dynamics models.

Influences of Non‐Oberbeck–Boussinesq Effects on Tracer Transport in Icy Ocean Worlds

Mon, 14 Jul 2025 00:00:00 GMT

Influences of Non‐Oberbeck–Boussinesq Effects on Tracer Transport in Icy Ocean Worlds Wang, Shuang; Kang, Wanying The subsurface oceans on icy satellites are potentially habitable. To understand their habitability,we need to know how tracers with various lifetimes distribute. Convection is the main vehicle for tracertransport, and we expect convection on icy satellites to differ from regular rotating convection, because aspressure increases, water's thermal expansivity can vary by orders of magnitude or even reverse sign nearfreezing point. Any variation of fluid properties would break the Oberbeck–Boussinesq approximation, leadingto non‐Oberbeck–Boussinesq (NOB) effects, measured by a coefficient ϵ. In this work, we identify twocompeting impacts of NOB effects on tracer transport. The first promotes overall upward tracer transport at ϵ2‐order, while the second enhances transport near the bottom source but inhibits transport further up at ϵ3‐order. Inweakly nonlinear regime, the former effect dominates, causing more tracers reaching the ice shell. While instrongly nonlinear regime, the latter effect dominates, reducing tracer concentrations near the ice shell. Byvarying particle lifetimes, we find that NOB corrections are most pronounced when particle lifetime iscomparable to the timescale of upward tracer transport. Additionally, when NOB effects are strong enough tocreate a stratified layer in the upper part of the ocean, tracer transport into the stratified layer is set by energetics.These effects are expected to prolong the transport timescale of chemical tracers or biosignatures from theseafloor to the ice shell on icy satellites.

Single Word Change Is All You Need: Using LLMs to Create Synthetic Training Examples for Text Classifiers

Mon, 07 Jul 2025 00:00:00 GMT

Single Word Change Is All You Need: Using LLMs to Create Synthetic Training Examples for Text Classifiers Xu, Lei; Alnegheimish, Sarah; Berti‐Equille, Laure; Cuesta‐Infante, Alfredo; Veeramachaneni, Kalyan In text classification, creating an adversarial example means subtly perturbing a few words in a sentence without changing itsmeaning, causing it to be misclassified by a classifier. A concerning observation is that a significant portion of adversarial exam-ples generated by existing methods change only one word. This single-word perturbation vulnerability represents a significantweakness in classifiers, which malicious users can exploit to efficiently create a multitude of adversarial examples. This paperstudies this problem and makes the following key contributions: (1) We introduce a novel metric 𝜌 to quantitatively assess a clas-sifier's robustness against single-word perturbation. (2) We present the SP-Attack, designed to exploit the single-word perturbationvulnerability, achieving a higher attack success rate, better preserving sentence meaning, while reducing computation costscompared to state-of-the-art adversarial methods. (3) We propose SP-Defence, which aims to improve 𝜌 by applying data augmen-tation in learning. Experimental results on 4 datasets and 2 masked language models show that SP-Defence improves 𝜌 by 14.6%and 13.9% and decreases the attack success rate of SP-Attack by 30.4% and 21.2% on two classifiers respectively, and decreasesthe attack success rate of existing attack methods that involve multiple-word perturbation.

Evaluation and Spatial Optimization Model of Urban Medical Resource Distribution Considering Equity and Efficiency

Sat, 05 Jul 2025 00:00:00 GMT

Evaluation and Spatial Optimization Model of Urban Medical Resource Distribution Considering Equity and Efficiency Yao, Yao; Wang, Yujia; Liang, Lin; Yan, Xiaoqin; Dong, Anning; Guan, Qingfeng; Luo, Peng The rapidly increasing demand for medical resources in accelerating urbanization countries is facing the challenge of unequalresource distribution. Despite numerous studies on the siting of medical resources aimed at improving public accessibility andefficiency to these resources, there is comparatively less research focusing on the equity of access to medical resources. Thisstudy establishes a framework that optimizes the distribution of medical resources by considering both equity and efficiency. Weintroduce an optimization allocation model for both equity and efficiency based on the location set coverage problem (LSCP). Themodel combines region growing algorithm and genetic algorithm to optimize site selection for hospitals. Taking Wuhan as thestudy area, the results demonstrate that the optimized service coverage increases by 21.2%, and the number of people served hasreached 87.3%. The hospital bed utilization rate in downtown areas reaches 92.89%, while it exceeds 99% at suburban hospitals.The optimized site selection significantly enhances medical resource utilization efficiency, effectively addressing the resourcedistribution inequity between urban and rural areas. This study offers a novel approach to optimizing medical resource alloca-tion, effectively balancing equity and efficiency, and providing valuable theoretical underpinnings for enhancing medical servicesystems in emerging urban areas.

On the use of high‐density polyethylene bottles for long‐term storage of total alkalinity samples

Wed, 25 Jun 2025 00:00:00 GMT

On the use of high‐density polyethylene bottles for long‐term storage of total alkalinity samples Woosley, Ryan J; Neithardt, Daina; Bruno, Jessica A; Lahn, Lou Total alkalinity (TA) plays an important role in buffering seawater and determining how much anthropogeniccarbon dioxide the oceans can absorb and mitigate the rise in atmospheric concentrations. Total alkalinity varieswith location, depth, and time making it an important variable needed to quantify and monitor ocean acidiﬁcation,and potentially for ocean alkalinity enhancement interventions. Currently, best practices are to use expensivehigh-quality borosilicate glass bottles for collecting and storing these samples. However, unlike other carbon systemvariables, TA is not affected by gas exchange meaning plastic bottles may be suitable for TA sample storage. Plasticbottles are lighter, cheaper, and less prone to breakage making them easier to handle and ship. Here, we test the suit-ability of high-density polyethylene (HDPE) for collection and long-term storage of TA samples. In two sets of exper-iments, it was determined that HDPE is not suitable for long-term storage of TA samples as there were large changesin TA over time and precision of duplicate samples was very poor. We hypothesize that HDPE plastic is slightlyporous leading to leaching of alkalinity either into or out of the bottle over time impacting the value of the sample.Use of HDPE bottles for TA samples is not recommended for long term sample storage.

Adapting temporal preference to scarcity: A role for emotion?

Fri, 20 Jun 2025 00:00:00 GMT

Adapting temporal preference to scarcity: A role for emotion? Blain, Bastien; Globig, Laura K.; Sharot, Tali A critical optimization problem is how to distribute resource consumption over time. Humans tend to value immediate rewards over equivalent future rewards—a phenomenon called temporal discounting. Such imbalance can lead to poor health, education, and financial decisions. It is also a hurdle for implementing sustainability policies. A major research goal is to identify factors that influence temporal discounting, so that policymakers could develop interventions to correct for this imbalance. One such factor is available resources; scarcity may increase in temporal discounting. Another potential factor is emotion; negative emotions may lead to high temporal discounting. However, emotion and resources are not independent. For example, losing a large sum of money will lead to negative affect. Here, we take advantage of one of the largest global ‘income shocks’ in history, to tease apart the role of emotion and income on temporal discounting. We tested 1,145 individuals as the market was crashing in late March 2020 and unemployment rising and then retested 200 of those individuals as the market was recovering in June 2020. We found that income shock was strongly related to an increase in delay discounting using cross-sectional and longitudinal data. Importantly, this relationship was independent of the negative impact on affect. These findings suggest that, contrary to wide held assumptions, people directly adapt delay discounting to environmental constraints, without the need for input from the affective system. This independence may be adaptive, as affect is a noisy reflection of environmental constraints, which may lead to suboptimal choice.

Shattering in the Ising p-spin glass model

Thu, 11 Sep 2025 00:00:00 GMT

Shattering in the Ising p-spin glass model Gamarnik, David; Jagannath, Aukosh; Kızıldağ, Eren C. We study the Ising p-spin glass model for large p. We show that for any inverse temperature ln 2 < β < 2 ln 2 and any large p, the model exhibits shattering: w.h.p. as n → ∞ , there exists exponentially many well-separated clusters such that (a) each cluster has exponentially small Gibbs mass, and (b) the clusters collectively contain all but a vanishing fraction of Gibbs mass. Moreover, these clusters consist of configurations with energy near β . Range of temperatures for which shattering occurs is within the replica symmetric region. To the best of our knowledge, this is the first shattering result regarding the Ising p-spin glass models. Furthermore, we show that for any γ > 0 and any large enough p, the model exhibits an intricate geometrical property known as the multi Overlap Gap Property above the energy value γ 2 ln 2 . Our proofs are elementary, and in particular based on simple applications of the first and the second moment methods.

Combined mechanical ventilatory and mechanical circulatory support aids pulmonary vascular state in cardiogenic shock

Wed, 15 Oct 2025 00:00:00 GMT

Combined mechanical ventilatory and mechanical circulatory support aids pulmonary vascular state in cardiogenic shock Lamberti, Kimberly K.; Edelman, Elazer R.; Keller, Steven P. Background Percutaneous ventricular assist devices (pVADs) support patients in circulatory failure and increasingly concomitant respiratory failure. The presence of co-existent lung disease creates a management challenge due to cardiopulmonary interactions, especially when there is simultaneous mechanical ventilation and mechanical circulatory support. Enhanced understanding of the combined effects of these devices is necessary to better inform care for circulatory failure patients. Methods A porcine model of titratable acute cardiogenic shock was used to quantify the effect of pVAD support on cardiac loading states in five intubated animals with positive pressure ventilation and varied intrathoracic pressure. Cardiovascular hemodynamics were assessed across positive end-expiratory pressure (PEEP) ramps in animals in health, health with pVAD, and pVAD-supported cardiogenic shock induced via coronary microembolization. Results This study employed invasive physiological metrics and assessment of right and left ventricular press-volume loops to recreate classic Frank-Starling curves. Increased intrathoracic pressure altered transmural pressure in the ventricles and the pulmonary vasculature and resulted in decreased venous return and stroke volume while increasing end-diastolic pressure consistent with decreased ventricular compliance. In pVAD-supported cardiogenic shock, elevated PEEP enhanced left ventricular output and increased pulmonary vascular compliance in several animals, contrary to traditional decrements observed with elevated PEEP. The right ventricular functional response aligned with these varied responses in pulmonary vascular state. Conclusions These results demonstrate that combined used of cardiopulmonary support devices in cardiogenic shock can create variable responses compared to classic physiological understanding. In pVAD-supported cardiogenic shock, an increase in ventilatory PEEP increased unloading from the heart and improved right ventricular function, counter to traditional findings. This demonstrates that combined use of these technologies could be leveraged to optimize a patient’s volume status in complex shock and provides promise for management of patients with cardiopulmonary failure requiring simultaneous use of mechanical circulatory support and mechanical ventilation.

On Chip-Firing on Undirected Binary Trees

Mon, 18 Aug 2025 00:00:00 GMT

On Chip-Firing on Undirected Binary Trees Inagaki, Ryota; Khovanova, Tanya; Luo, Austin Chip-firing is a combinatorial game played on an undirected graph in which we place chips on vertices and disperse them. We study chip-firing on an infinite binary tree in which we add a self-loop to the root to ensure each vertex has degree 3. A vertex can fire if the number of chips placed on it is at least its degree. In our case, a vertex can fire if it has at least three chips, and it fires by dispersing one chip to each neighbor. Motivated by a 2023 paper by Musiker and Nguyen on this setting of chip-firing, we give an upper bound for the number of stable configurations when we place 2 ℓ - 1 labeled chips at the root. When starting with N chips at the root where N is a positive integer, we determine the number of times each vertex fires when N is not necessarily of the form 2 ℓ - 1 . We also calculate the total number of fires in this case.

Measurement of charged hadron multiplicity in Au+Au collisions at s NN = 200 GeV with the sPHENIX detector

Tue, 12 Aug 2025 00:00:00 GMT

Measurement of charged hadron multiplicity in Au+Au collisions at s NN = 200 GeV with the sPHENIX detector Abdulhamid, M. I.; Acharya, U.; Adams, E. R.; Adawi, G.; Aidala, C. A.; Akiba, Y.; Alfred, M.; Ali, S.; Alsayegh, A.; Altaf, S.; Amedi, H.; Anderson, D. M.; Andrieux, V. V.; Angerami, A.; Applegate, N.; Aso, H.; Aune, S. The pseudorapidity distribution of charged hadrons produced in Au+Au collisions at a center-of-mass energy of s NN = 200 GeV is measured using data collected by the sPHENIX detector. Charged hadron yields are extracted by counting cluster pairs in the inner and outer layers of the Intermediate Silicon Tracker, with corrections applied for detector acceptance, reconstruction efficiency, combinatorial pairs, and contributions from secondary decays. The measured distributions cover |η| < 1.1 across various centralities, and the average pseudorapidity density of charged hadrons at mid-rapidity is compared to predictions from Monte Carlo heavy-ion event generators. This result, featuring full azimuthal coverage at mid-rapidity, is consistent with previous experimental measurements at the Relativistic Heavy Ion Collider, thereby supporting the broader sPHENIX physics program.

Search for a heavy pseudoscalar Higgs boson decaying to a 125 GeV Higgs boson and a Z boson in final states with two tau and two light leptons in proton-proton collisions at √s = 13 TeV

Thu, 09 Oct 2025 00:00:00 GMT

Search for a heavy pseudoscalar Higgs boson decaying to a 125 GeV Higgs boson and a Z boson in final states with two tau and two light leptons in proton-proton collisions at √s = 13 TeV Chekhovsky, V.; Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I. A search for a heavy pseudoscalar Higgs boson, A, decaying to a 125 GeV Higgs boson h and a Z boson is presented. The h boson is identified via its decay to a pair of tau leptons, while the Z boson is identified via its decay to a pair of electrons or muons. The search targets the production of the A boson via the gluon-gluon fusion process, gg → A, and in association with bottom quarks, bb¯A. The analysis uses a data sample corresponding to an integrated luminosity of 138 fb−1 collected with the CMS detector at the CERN LHC in proton-proton collisions at a centre-of-mass energy of √ s = 13 TeV. Constraints are set on the product of the cross sections of the A production mechanisms and the A → Zh decay branching fraction. The observed (expected) upper limit at 95% confidence level ranges from 0.049 (0.060) pb to 1.02 (0.79) pb for the gg → A process and from 0.053 (0.059) pb to 0.79 (0.61) pb for the bb¯A process in the probed range of the A boson mass, mA, from 225 GeV to 1 TeV. The results of the search are used to constrain parameters within the M 125 h,EFT benchmark scenario of the minimal supersymmetric extension of the standard model. Values of tan β below 2.2 are excluded in this scenario at 95% confidence level for all mA values in the range from 225 to 350 GeV.

Measurements of inclusive and differential cross sections for top quark production in association with a Z boson in proton-proton collisions at s = 13 TeV

Wed, 26 Feb 2025 00:00:00 GMT

Measurements of inclusive and differential cross sections for top quark production in association with a Z boson in proton-proton collisions at s = 13 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R.; Schwarz, D. Measurements are presented of inclusive and differential cross sections for Z boson associated production of top quark pairs ( t t ¯ Z ) and single top quarks (tZq or tWZ). The data were recorded in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb−1. Events with three or more leptons, electrons or muons, are selected and a multiclass deep neural network is used to separate three event categories, the t t ¯ Z and tWZ processes, the tZq process, and the backgrounds. A profile likelihood approach is used to unfold the differential cross sections, to account for systematic uncertainties, and to determine the correlations between the two signal categories in one global fit. The inclusive cross sections for a dilepton invariant mass between 70 and 110 GeV are measured to be 1.14 ± 0.07 pb for the sum of t t ¯ Z and tWZ, and 0.81 ± 0.10 pb for tZq, in good agreement with theoretical predictions.

Priming agents transiently reduce the clearance of cell-free DNA to improve liquid biopsies

Fri, 19 Jan 2024 00:00:00 GMT

Priming agents transiently reduce the clearance of cell-free DNA to improve liquid biopsies Martin-Alonso, Carmen; Tabrizi, Shervin; Xiong, Kan; Blewett, Timothy; Sridhar, Sainetra; Crnjac, Andjela; Patel, Sahil; An, Zhenyi; Bekdemir, Ahmet; Shea, Douglas; Wang, Shih-Ting; Rodriguez-Aponte, Sergio; Naranjo, Christopher A; Rhoades, Justin; Kirkpatrick, Jesse D; Fleming, Heather E; Amini, Ava P; Golub, Todd R; Love, J Christopher; Bhatia, Sangeeta N; Adalsteinsson, Viktor A Liquid biopsies enable early detection and monitoring of diseases such as cancer, but their sensitivity remains limited by the scarcity of analytes such as cell-free DNA (cfDNA) in blood. Improvements to sensitivity have primarily relied on enhancing sequencing technology ex vivo. We sought to transiently augment the level of circulating tumor DNA (ctDNA) in a blood draw by attenuating its clearance in vivo. We report two intravenous priming agents given 1 to 2 hours before a blood draw to recover more ctDNA. Our priming agents consist of nanoparticles that act on the cells responsible for cfDNA clearance and DNA-binding antibodies that protect cfDNA. In tumor-bearing mice, they greatly increase the recovery of ctDNA and improve the sensitivity for detecting small tumors.

Vaccine targeting to mucosal lymphoid tissues promotes humoral immunity in the gastrointestinal tract

Wed, 29 May 2024 00:00:00 GMT

Vaccine targeting to mucosal lymphoid tissues promotes humoral immunity in the gastrointestinal tract Kocabiyik, Ozgun; Amlashi, Parastoo; Vo, A Lina; Suh, Heikyung; Rodriguez-Aponte, Sergio A; Dalvie, Neil C; Love, J Christopher; Andrabi, Raiees; Irvine, Darrell J Viruses, bacteria, and parasites frequently cause infections in the gastrointestinal tract, but traditional vaccination strategies typically elicit little or no mucosal antibody responses. Here, we report a strategy to effectively concentrate immunogens and adjuvants in gut-draining lymph nodes (LNs) to induce gut-associated mucosal immunity. We prepared nanoemulsions (NEs) based on biodegradable oils commonly used as vaccine adjuvants, which encapsulated a potent Toll-like receptor agonist and displayed antigen conjugated to their surface. Following intraperitoneal administration, these NEs accumulated in gut-draining mesenteric LNs, priming strong germinal center responses and promoting B cell class switching to immunoglobulin A (IgA). Optimized NEs elicited 10- to 1000-fold higher antigen-specific IgG and IgA titers in the serum and feces, respectively, compared to free antigen mixed with NE, and strong neutralizing antibody titers against severe acute respiratory syndrome coronavirus 2. Thus, robust gut humoral immunity can be elicited by exploiting the unique lymphatic collection pathways of the gut with a lymph-targeting vaccine formulation.

Expansion of tumor-reactive CD8+ T cell clonotypes occurs in the spleen in response to immune checkpoint blockade

Fri, 13 Sep 2024 00:00:00 GMT

Expansion of tumor-reactive CD8+ T cell clonotypes occurs in the spleen in response to immune checkpoint blockade Morgan, Duncan M; Horton, Brendan L; Bhandarkar, Vidit; Van, Richard; Dinter, Teresa; Zagorulya, Maria; Love, J Christopher; Spranger, Stefani Immune checkpoint blockade (ICB) enhances T cell responses against cancer, leading to long-term survival in a fraction of patients. CD8+ T cell differentiation in response to chronic antigen stimulation is highly complex and it remains unclear precisely which T cell differentiation states at which anatomic sites are critical for the response to ICB. We identified an intermediate-exhausted population in the white pulp of the spleen which underwent significant expansion in response to ICB and gave rise to the majority of tumor-infiltrating clonotypes. Increased systemic antigen perturbed differentiation of this population towards a most circulatory exhausted_KLR state, while a lack of cross-presented tumor-antigen blunted its differentiation in the spleen. An analogous population of exhausted_KLR CD8+ T cells in human blood samples exhibited diminished tumortrafficking ability. Collectively, our data demonstrate the critical role of antigen density within the spleen for the differentiation and expansion of T cell clonotypes in response to ICB.

Drell-Yan transverse-momentum spectra at N3LL′ and approximate N4LL with SCETlib

Tue, 25 Feb 2025 00:00:00 GMT

Drell-Yan transverse-momentum spectra at N3LL′ and approximate N4LL with SCETlib Billis, Georgios; Michel, Johannes K. L.; Tackmann, Frank J. We provide state-of-the-art precision QCD predictions for the fiducial W and Z boson transverse momentum spectra at the LHC at N3LL′ and approximate N4LL in resummed perturbation theory, matched to available O α s 3 fixed-order results. Our predictions consistently combine all information from across the spectrum in a unified way, ranging from the nonperturbative region of small transverse momenta to the fixed-order tail, with an emphasis on estimating the magnitude of residual perturbative uncertainties, and in particular of those related to the matching. Parametric uncertainties related to the strong coupling, the collinear PDFs, and the nonperturbative transverse momentum-dependent (TMD) dynamics are studied in detail. To assess the latter, we explicitly demonstrate how the full complexity of flavor and Bjorken x-dependent TMD dynamics can be captured by a single, effective nonperturbative function for the resonant production of any given vector boson at a given collider. We point out that the cumulative p T Z cross section at the level of precision enabled by our predictions provides strong constraining power for PDF determinations at full N3LO.

Search for a heavy resonance decaying into a Z and a Higgs boson in events with an energetic jet and two electrons, two muons, or missing transverse momentum in proton-proton collisions at √s = 13 TeV

Thu, 13 Feb 2025 00:00:00 GMT

Search for a heavy resonance decaying into a Z and a Higgs boson in events with an energetic jet and two electrons, two muons, or missing transverse momentum in proton-proton collisions at √s = 13 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R. A search is presented for a heavy resonance decaying into a Z boson and a Higgs (H) boson. The analysis is based on data from proton-proton collisions at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 138 fb−1, recorded with the CMS experiment in the years 2016–2018. Resonance masses between 1.4 and 5 TeV are considered, resulting in large transverse momenta of the Z and H bosons. Final states that result from Z boson decays to pairs of electrons, muons, or neutrinos are considered. The H boson is reconstructed as a single large-radius jet, recoiling against the Z boson. Machine-learning flavour-tagging techniques are employed to identify decays of a Lorentz-boosted H boson into pairs of charm or bottom quarks, or into four quarks via the intermediate H → WW* and ZZ* decays. The analysis targets H boson decays that were not generally included in previous searches using the H → b b ¯ channel. Compared with previous analyses, the sensitivity for high resonance masses is improved significantly in the channel where at most one b quark is tagged.

Measurement of the CKM angle γ in B± → DK*(892)± decays

Tue, 18 Feb 2025 00:00:00 GMT

Measurement of the CKM angle γ in B± → DK*(892)± decays Aaij, R.; Abdelmotteleb, A. S. W.; Abellan Beteta, C.; Abudinén, F.; Ackernley, T.; Adefisoye, A. A.; Adeva, B.; Adinolfi, M.; Adlarson, P.; Agapopoulou, C.; Aidala, C. A.; Ajaltouni, Z.; Akar, S.; Akiba, K.; Albicocco, P.; Albrecht, J. Measurements of CP observables and the CKM angle γ are performed in B± → DK*(892)± decays, where D represents a superposition of D0 and D ¯ 0 states, using the LHCb dataset collected during Run 1 (2011–2012) and Run 2 (2015–2018). A study of this channel is presented with the D meson reconstructed in two-body final states K±π∓, K+K− and π+π−; four-body final states K±π∓π±π∓ and π+π−π+π−; and three-body final states K S 0 π + π − and K S 0 K + K − . This analysis includes the first observation of the suppressed B± → [π±K∓]DK*± and B± → [π±K∓π±π∓]DK*± decays. The combined result gives γ = (63 ± 13)°.

Measurement of the t¯tH and tH production rates in the H → bb¯ decay channel using proton-proton collision data at √s = 13 TeV

Fri, 14 Feb 2025 00:00:00 GMT

Measurement of the t¯tH and tH production rates in the H → bb¯ decay channel using proton-proton collision data at √s = 13 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R.; Schwarz, D. An analysis of the production of a Higgs boson (H) in association with a top quark-antiquark pair ( t t ¯ H ) or a single top quark (tH) is presented. The Higgs boson decay into a bottom quark-antiquark pair (H → b b ¯ ) is targeted, and three different final states of the top quark decays are considered, defined by the number of leptons (electrons or muons) in the event. The analysis utilises proton-proton collision data collected at the CERN LHC with the CMS experiment at s = 13 TeV in 2016–2018, which correspond to an integrated luminosity of 138 fb−1. The observed t t ¯ H production rate relative to the standard model expectation is 0.33 ± 0.26 = 0.33 ± 0.17(stat) ± 0.21(syst). Additionally, the t t ¯ H production rate is determined in intervals of Higgs boson transverse momentum. An upper limit at 95% confidence level is set on the tH production rate of 14.6 times the standard model prediction, with an expectation of 19.3 − 6.0 + 9.2 . Finally, constraints are derived on the strength and structure of the coupling between the Higgs boson and the top quark from simultaneous extraction of the t t ¯ H and tH production rates, and the results are combined with those obtained in other Higgs boson decay channels.

Differential cross section measurements for the production of top quark pairs and of additional jets using dilepton events from pp collisions at √s = 13 TeV

Tue, 11 Feb 2025 00:00:00 GMT

Differential cross section measurements for the production of top quark pairs and of additional jets using dilepton events from pp collisions at √s = 13 TeV Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; Pitters, F. M.; Schieck, J.; Schöfbeck, R. Differential cross sections for top quark pair ( t t ¯ ) production are measured in proton-proton collisions at a center-of-mass energy of 13 TeV using a sample of events containing two oppositely charged leptons. The data were recorded with the CMS detector at the CERN Large Hadron Collider and correspond to an integrated luminosity of 138 fb−1. The differential cross sections are measured as functions of kinematic observables of the t t ¯ system, the top quark and antiquark and their decay products, as well as of the number of additional jets in the event. The results are presented as functions of up to three variables and are corrected to the parton and particle levels. When compared to standard model predictions based on quantum chromodynamics at different levels of accuracy, it is found that the calculations do not always describe the observed data. The deviations are found to be largest for the multi-differential cross sections.

Search for dark matter produced in association with a pair of bottom quarks in proton-proton collisions at s = 13 TeV

Tue, 11 Feb 2025 00:00:00 GMT

Search for dark matter produced in association with a pair of bottom quarks in proton-proton collisions at s = 13 TeV Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R.; Schwarz, D.; Sonawane, M. A search for dark matter (DM) particles produced in association with bottom quarks is presented. The analysis uses proton-proton collision data at a center-of-mass energy of s = 13 TeV, corresponding to an integrated luminosity of 138 fb−1. The search is performed in a final state with large missing transverse momentum and a pair of jets originating from bottom quarks. No significant excess of data is observed with respect to the standard model expectation. Results are interpreted in the context of a type-II two-Higgs-doublet model with an additional light pseudoscalar (2HDM+a). An upper limit is set on the mass of the lighter pseudoscalar, probing masses up to 260 GeV at 95% confidence level. Sensitivity to the parameter space with the ratio of the vacuum expectation values of the two Higgs doublets, tan β, greater than 15 is achieved, capitalizing on the enhancement of couplings between pseudoscalars and bottom quarks with high tan β.

Boundary terms in string field theory

Tue, 11 Feb 2025 00:00:00 GMT

Boundary terms in string field theory Fırat, Atakan H.; Mamade, Raji A. We supplement the string field theory action with boundary terms to make its variational principle well-posed. Central to our considerations is the violation of the stress-energy tensor conservation in non-compact CFTs due to the boundary terms. This manifests as the failure of the cyclicity of the BRST operator, which encodes the target space integration by parts identities at the level of the worldsheet. Using this failure, we argue that the free closed string field theory action admits a well-posed variational principle upon including an additional boundary contribution. We explicitly work out the resulting action up to the massless level and show that it is related to the expansion of the low-energy effective string action endowed with the Gibbons-Hawking-York term on a flat background. We also discuss the structure of the boundary terms in the interacting theory.

Search for resonant pair production of Higgs bosons in the bbb¯ b¯ final state using large-area jets in proton-proton collisions at √s = 13 TeV

Fri, 07 Feb 2025 00:00:00 GMT

Search for resonant pair production of Higgs bosons in the bbb¯ b¯ final state using large-area jets in proton-proton collisions at √s = 13 TeV Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; Pitters, F. M. A search is presented for the resonant production of a pair of standard model-like Higgs bosons using data from proton-proton collisions at a centre-of-mass energy of 13 TeV, collected by the CMS experiment at the CERN LHC in 2016–2018, corresponding to an integrated luminosity of 138 fb−1. The final state consists of two b quark-antiquark pairs. The search is conducted in the region of phase space where at least one of the pairs is highly Lorentz-boosted and is reconstructed as a single large-area jet. The other pair may be either similarly merged or resolved, the latter reconstructed using two b-tagged jets. The data are found to be consistent with standard model processes and are interpreted as 95% confidence level upper limits on the product of the cross sections and the branching fractions of the spin-0 radion and the spin-2 bulk graviton that arise in warped extradimensional models. The limits set are in the range 9.74–0.29 fb and 4.94–0.19 fb for a narrow radion and a graviton, respectively, with masses between 1 and 3 TeV. For a radion and for a bulk graviton with widths 10% of their masses, the limits are in the range 12.5–0.35 fb and 8.23–0.23 fb, respectively, for the same masses. These limits result in the exclusion of a narrow-width graviton with a mass below 1.2 TeV, and of narrow and 10%-width radions with masses below 2.6, and 2.9 TeV, respectively.

Future Circular Collider Feasibility Study Report

Mon, 13 Oct 2025 00:00:00 GMT

Future Circular Collider Feasibility Study Report Benedikt, M.; Zimmermann, F.; Auchmann, B.; Bartmann, W.; Burnet, J. P.; Carli, C.; Chancé, A.; Craievich, P.; Giovannozzi, M.; Grojean, C.; Gutleber, J.; Hanke, K.; Henriques, A.; Janot, P.; Lourenço, C.; Mangano, M.; Otto, T.; Poole, J.; Rajagopalan, S.; Raubenheimer, T. Volume 3 of the FCC Feasibility Report presents studies related to civil engineering, the development of a project implementation scenario, and environmental and sustainability aspects. The report details the iterative improvements made to the civil engineering concepts since 2018, taking into account subsurface conditions, accelerator and experiment requirements, and territorial considerations. It outlines a technically feasible and economically viable civil engineering configuration that serves as the baseline for detailed subsurface investigations, construction design, cost estimation, and project implementation planning. Additionally, the report highlights ongoing subsurface investigations in key areas to support the development of an improved 3D subsurface model of the region. The report describes the development of the project scenario based on the ‘avoid-reduce-compensate’ iterative optimisation approach. The reference scenario balances optimal physics performance with territorial compatibility, implementation risks, and costs. Environmental field investigations covering almost 600 hectares of terrain—including numerous urban, economic, social, and technical aspects—confirmed the project’s technical feasibility and contributed to the preparation of essential input documents for the formal project authorisation phase. The summary also highlights the initiation of public dialogue as part of the authorisation process. The results of a comprehensive socio-economic impact assessment, which included significant environmental effects, are presented. Even under the most conservative and stringent conditions, a positive benefit-cost ratio for the FCC-ee is obtained. Finally, the report provides a summary of the studies conducted to document the current state of the environment.

Locational and Spatial Development Patterns in U.S. Urban Micro Housing

Thu, 16 Oct 2025 00:00:00 GMT

Locational and Spatial Development Patterns in U.S. Urban Micro Housing Wang, Bing; Seiler, Michael J.; Liu, Kui; Du, Jinfeng While previous studies of micro-housing have primarily relied on qualitative methods or case-based analyses, this study deploys a more rigorous, data-driven approach. We construct a hand-collected dataset covering 11 major U.S. cities to enable a quantitative examination of this emerging housing form. Drawing on 40 variables from 32 projects, including locational data, physical characteristics, market performance, and amenity features, we identified five distinct micro-housing typologies: TechEd, Dependent, Stand-Alone, Luxury, and Affordable Sharing Economy. In the context of increasing remote work and the growing influence of the sharing economy, these distinct micro-housing types are becoming increasingly relevant as an urban development model. This paper represents a first step toward systematically understanding these building typologies and uncovers their locational patterns through empirical analysis.

Psyche Mission Description and Design Rationale

Tue, 14 Oct 2025 00:00:00 GMT

Psyche Mission Description and Design Rationale Polanskey, Carol A.; Elkins-Tanton, Linda T.; Bell, James F.; Alonge, Eleanor K.; Bairstow, Sarah H.; Binzel, Richard P.; Biswas, Abhijit; Bury, Luke; Cisneros, Ernest; Han, Dongsuk; Jun, Insoo; Klipstein, William M.; Lawrence, David J.; McCoy, Timothy J.; Mastrodemos, Nickolaos The Psyche spacecraft launched on October 13, 2023 to journey to the asteroid of the same name. Psyche is the largest M-class asteroid and possibly the remanent core of an early differentiated planetesimal that was disrupted by collisions. The Psyche mission will test that hypothesis as the 14th mission in NASA’s Discovery Program. An alternative hypothesis is that the asteroid is unmelted primordial material. We describe the proposal competition process leading to selection of the mission and its context with other small body missions. This paper will briefly introduce the three science instruments, gravity science investigation, and Deep Space Optical Communications technology demonstration, leading into a detailed explanation of the science mission architecture. The orbital science phase is divided into a series of circular mapping orbits at four distinct altitudes, each selected to address specific science objectives. The requirements and objectives for each orbit are accompanied by an assessment of the effectiveness of each phase. We discuss the structure of the Psyche team during the operations phase along with the roles and responsibilities of the science and flight operations teams. Key elements of mission operations that are unique to the Psyche mission are provided. The Science Data Center manages and archives the Psyche mission data. The contents of the archive data sets for each instrument are outlined as well as the interfaces between the Science Data Center, the instrument teams, and the Planetary Data System.

Quantum Perfect Matchings

Tue, 14 Oct 2025 00:00:00 GMT

Quantum Perfect Matchings Cui, David; Mančinska, Laura; Nezhadi, Seyed S.; Roberson, David E. We investigate quantum and nonsignaling generalizations of perfect matchings in graphs using nonlocal games. Specifically, we introduce nonlocal games that test for L-perfect matchings in bipartite graphs, perfect matchings in general graphs and hypergraphs, and fractional perfect matchings. Our definitions come from the fact that these games are classical property tests for the corresponding matching conditions. We use the existence of perfect quantum and nonsignaling strategies for these games to define quantum and nonsignaling versions of perfect matchings. Finally, we provide characterizations of when graphs exhibit these extended properties: For nonsignaling matchings, we give a complete combinatorial characterization. In particular, a graph has a nonsignaling perfect matching if and only if it admits a fractional perfect matching that has bounded value on triangles. In bipartite graphs, the nonsignaling L-perfect matching property is achieved exactly when the left component of the graph can be split into two disjoint subgraphs: one with a classical L-perfect matching and another with left-degree 2. In the quantum setting, we show that complete graphs K n with odd n ≥ 7 have quantum perfect matchings. We prove that a graph has a quantum perfect matching if and only if the quantum independence number of its line graph is maximal, extending a classical relationship between perfect matchings and line graph independence numbers. For bipartite graphs, we establish that the L-perfect matching game does not exhibit quantum pseudotelepathy, but we characterize the quantum advantage for complete bipartite graphs K n , 2 . Additionally, we prove that deciding quantum perfect matchings in hypergraphs is undecidable and leaves open the question of its complexity in graphs.

Trophic transfer of lipid-derived energy through Adélie and gentoo penguins near Palmer Station along the west Antarctic Peninsula

Tue, 14 Oct 2025 00:00:00 GMT

Trophic transfer of lipid-derived energy through Adélie and gentoo penguins near Palmer Station along the west Antarctic Peninsula Bent, Shavonna M.; Cimino, Megan A.; Connors, Elizabeth J.; Thomas, Maya I.; Miller, Carolyn A.; Fredricks, Helen F.; Van Mooy, Benjamin A. S. Although Adélie and gentoo penguins are experiencing similar climatic conditions along the west Antarctic Peninsula (WAP), Adélie populations have decreased in the northern WAP, while gentoo populations have increased. We examined the lipid component of regurgitated prey (chick diets) from each penguin species to elucidate broader population trends. Nearly 90% of chick diet samples were composed of only krill, which we confirmed contained abundant phosphatidyl choline. Chick diets rich in fish had similar total caloric content to krill-only diets; however, these “fishy” chick diets had significantly more energy derived from triacylglycerides, an important energy-rich storage molecule, and were only found in gentoo penguins. We found that whole-krill eaten by adult penguins had 1.25–3.75 times more energy than chick diets, highlighting the role of digestion in the transfer of energy to chicks. Our results highlight dynamics between climate, predator–prey relationships, and trophic transfer of energy in the Antarctic food web.

IsoDAR@Yemilab: Preliminary design report—volume I (cyclotron driver)

Wed, 15 Oct 2025 00:00:00 GMT

IsoDAR@Yemilab: Preliminary design report—volume I (cyclotron driver) Winklehner, Daniel; Abs, Michel; Alonso, Jose R.; Conrad, Janet M.; Engebretson, Samuel J.; Forton, Eric; Herrod, Alexander T.; Joassin, Denis; Moon, Jarrett; de Neuter, Sébastien; Van der Kraaij, Erik; Wéry, Gil; Winkler, Eleanor; Adelmann, Andreas; Axani, Spencer N.; Barletta, William A.; Barlow, Roger; Bartoszek, Larry; Bungau, Adriana; Calabretta, Luciano This Preliminary Design Report (PDR) describes the IsoDAR electron-antineutrino source in two volumes which are mostly site-independent and describe the cyclotron driver providing a 10 mA/60 MeV proton beam (this Volume); and the medium energy beam transport line (MEBT) and target (Volume II). The IsoDAR driver and target will produce about 1.15 × 10 23 electron-antineutrinos over 5 years while operating with the anticipated 10 mA/60 MeV beam at an estimated 80% duty factor. Paired with a kton-scale liquid scintillator detector, it will enable a broad particle physics program including searches for new symmetries, new interactions and new particles. Here in Volume I, we describe the driver, which includes the ion source, low energy beam transport, and cyclotron. The latter features Radio-Frequency Quadrupole (RFQ) direct axial injection and represents the first accelerator purpose-built to make use of so-called vortex motion.

Physics-Based Inverse Problem Approach for Estimating Operating Conditions in Forced Convection Systems with Uncertainty Quantification

Wed, 03 Sep 2025 00:00:00 GMT

Physics-Based Inverse Problem Approach for Estimating Operating Conditions in Forced Convection Systems with Uncertainty Quantification Kim, Haeseong; Cetiner, Sacit M; Bucci, Matteo Accurately determining the operating conditions of thermal systems with limited measurements is a critical challenge in convection-dominated problems of interest for nuclear engineering applications. Because of the complexity of these phenomena, existing research has often relied on data-driven reconstruction of physical quantities. In this work, instead of using a data-driven approach, which usually lacks interpretability, we focus on a physics-based inverse problem to estimate unknown causes from available observations. We address the problem of estimating operating conditions (such as heat source intensity and flow rate) in a steady-state turbulent forced convection system from a limited number of temperature measurements. Based on a forward model with quantified uncertainty, we employed Newton’s method to estimate unknown parameters and incorporated uncertainty quantification. The uncertainty analysis addresses the impact of measurement uncertainty and errors in closure relationships. The identified uncertainties provide insights into their mitigation and inform experimental design. The structured approach to inverse analysis enables accurate estimation with minimal sensor data, as shown in this specific example. The analysis will contribute to the development of advanced sparse sensing techniques, with potential implications for broader industrial and environmental applications.

Design-Based Uncertainty for Quasi-Experiments

Wed, 27 Aug 2025 00:00:00 GMT

Design-Based Uncertainty for Quasi-Experiments Rambachan, Ashesh; Roth, Jonathan Design-based frameworks of uncertainty are frequently used in settings where the treatment is (conditionally) randomly assigned. This article develops a design-based framework suitable for analyzing quasi-experimental settings in the social sciences, in which the treatment assignment can be viewed as the realization of some stochastic process but there is concern about unobserved selection into treatment. In our framework, treatments are stochastic, but units may differ in their probabilities of receiving treatment, thereby allowing for rich forms of selection. We provide conditions under which the estimands of popular quasi-experimental estimators correspond to interpretable finite-population causal parameters. We characterize the biases and distortions to inference that arise when these conditions are violated. These results can be used to conduct sensitivity analyses when there are concerns about selection into treatment. Taken together, our results establish a rigorous foundation for quasi-experimental analyses that more closely aligns with the way empirical researchers discuss the variation in the data. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Golden Dome and Arms Control: Impediment or Opportunity?

Tue, 15 Jul 2025 00:00:00 GMT

Golden Dome and Arms Control: Impediment or Opportunity? Vaddi, Pranay R.; Warden, John K. The Trump administration identified arms control talks with Russia and China as an early priority. At the same time, the US President directed the Defense Department to develop a comprehensive air and missile defense system for the United States, and potentially for forward-deployed forces and allies as well. The interrelationship between strategic offensive and defensive arms will complicate, but not necessarily derail, the administration’s strategic arms control agenda.

Syndicated Lending Relationships, Information Asymmetry, and Market Making in the Secondary Loan Market

Wed, 16 Jul 2025 00:00:00 GMT

Syndicated Lending Relationships, Information Asymmetry, and Market Making in the Secondary Loan Market PHILLIPS, MATTHEW A This paper investigates why commercial lenders make markets for the loansthat they sell on the secondary market. Using loan-level data, I ﬁnd thatorigination lenders with extensive borrower relationships and more repu-tational capital at stake are more likely to serve as market makers. Greaterparticipation of origination lenders as market makers is associated with lowertrading costs for their borrowers’ loans. This association remains even in con-ditions where origination lenders could exploit their information advantagefor market making proﬁts. Lenders beneﬁt from being market makers bymaintaining strong subsequent lending relationships with their borrowers.Collectively, this evidence is consistent with origination lenders’ participationin the secondary market being motivated by reducing trading frictions ratherthan market making proﬁts.

Evolution of the South Pacific's Iron Cycle Over the Cenozoic

Thu, 03 Jul 2025 00:00:00 GMT

Evolution of the South Pacific's Iron Cycle Over the Cenozoic Tegler, Logan A.; Horner, Tristan J.; Nielsen, Sune G.; Heard, Andy W.; Squires, Katherine R.; Severmann, Silke; Peucker‐Ehrenbrink, Bernhard; Blusztajn, Jerzy; Dunlea, Ann G. Iron (Fe) availability impacts marine primary productivity, potentially influencing the efficiency of the biological carbon pump. Stable Fe isotope analysis has emerged as a tool to understand how Fe is sourced and cycled in the water column; however its application to sediment records is complicated by overlapping isotope signatures of different sources and uncertainties in establishing chronologies. To overcome these challenges, we integrate Fe and osmium isotope measurements with multi-element geochemical analysis and statistical modeling. We apply this approach to reconstruct the history of Fe delivery to the South Pacific from three pelagic clay sequences spanning 93 million years. Our analysis reveals five principal Fe sources—dust, distal background, two distinct hydrothermal inputs, and a magnesium-rich volcanic ash. Initially, hydrothermal inputs dominated Fe deposition, but as the sites migrated away from their respective mid-ocean ridges, other sources became prominent. Notably, from 66 to 40 million years ago (Ma), distal background Fe was the primary source before a shift to increasing dust dominance around 30 Ma. This transition implies that Fe in South Pacific seawater has been dust-dominated since ≈30 Ma, despite extremely low dust deposition rates today. We speculate that the shift to episodic and low Fe fluxes in the South Pacific and Southern Ocean over the Cenozoic helped shape an ecological niche that favored phytoplankton that adapted to these conditions, such as diatoms. Our analysis highlights how Fe delivery to the ocean is driven by large-scale tectonic and climatic shifts, while also influencing climate through its integral role in marine phytoplankton and Earth's biogeochemical cycles.

Starship as an Enabling Option for a Uranus Flagship Mission

Mon, 14 Jul 2025 00:00:00 GMT

Starship as an Enabling Option for a Uranus Flagship Mission Gochenaur, Daniel; Gentgen, Chloe; de Weck, Olivier In 2022, the National Academy of Sciences Planetary Science Decadal Survey recommended exploration of Uranus as its highest priority Flagship mission for the 2030s. The Decadal recommendation relied on the Uranus Orbiter and Probe (UOP) concept as its baseline for the mission. UOP assumed a launch in 2031 on a Falcon Heavy Expendable rocket and an intermediate Jupiter flyby, allowing it to arrive at Uranus before 2050. At present, it is likely that the original UOP launch will be postponed, which will cause a Jupiter gravity assist to become unavailable and could delay the arrival at Uranus. However, a later launch date allows us to consider launch vehicles currently under development such as SpaceX's Starship, a two-stage heavy-lift launch vehicle that is intended to be refuelable on-orbit. Although Starship's performance capabilities have yet to be demonstrated, current development timelines suggest they will be known before selecting a launch vehicle for a Uranus mission. This study investigates the possibility of leveraging the anticipated capabilities of Starship to support a Flagship mission to Uranus. The results show that with on-orbit refueling, Starship will be capable of performing direct transfer to Uranus without the need for intermediate planetary flybys. Direct transfer with Starship orbit insertion allows nearly five metric tonnes of mass to be deployed to Uranus orbit using nine refueling launches in ten years, compared to more than thirteen years for UOP. If the spacecraft is used to perform the orbit insertion maneuver, five tonnes of mass can be deployed in less than nine years with seven refueling trips. Larger payload masses and shorter times of flight can be achieved by using Starship to perform aerocapture. As a mid- to high-lift to drag ratio vehicle, Starship can succesfully perform aerocapture while maintaining deceleration and heating values that are not more severe than those observed by aerocapture studies for other vehicles. With seven refueling launches and a seven-year transfer time of flight, Starship can deliver nearly six tonnes of payload mass to Uranus using aerocapture. With a longer time of flight and additional refueling launches, mission masses greater than fifty tonnes can be delivered to Uranus orbit. By using Starship to deploy a spacecraft and probe of a similar design as UOP, the reduced transfer times can facilitate an arrival at Uranus well before equinox, and can enable science phases of up to ten years. Performing the insertion burn with Starship also increases the Δv available for the science tour. Using the UOP architecture would make the mission compatible with both Falcon Heavy and Starship, thereby reducing risk. Alternatively, the additional payload mass that can be deployed to Uranus with Starship can enhance the orbiter and probe architecture beyond the current design, potentially allowing for a larger instrument suite, additional probes, and even a secondary spacecraft. To this end, a Uranus Flagship mission using Starship presents a higher-risk, yet potentially greater-science-return option that could become viable if financial conditions permit. 2025 IEEE Aerospace Conference, 1-8 March, Big Sky, MT, USA

Forecasting Research Trends Using Knowledge Graphs and Large Language Models

Fri, 12 Sep 2025 00:00:00 GMT

Forecasting Research Trends Using Knowledge Graphs and Large Language Models Tomczak, Maciej; Park, Yang Jeong; Hsu, Chia‐Wei; Brown, Payden; Massa, Dario; Sankowski, Piotr; Li, Ju; Papanikolaou, Stefanos Since ancient times, oracles (e.g., Delphi) has the ability to provide useful visions of where the society is headed, based on key event correlations and educated guesses. Currently, foundation models are able to distill and analyze enormous text-based data that can be used to understand where societal components are headed in the future. This work investigates the use of three large language models (LLM) and their ability to aid the research of nuclear materials. Using a large dataset of Journal of Nuclear Materials papers spanning from 2001 to 2021, models are evaluated and compared with perplexity, similarity of output, and knowledge graph metrics such as shortest path length. Models are compared to the highest performer, OpenAI's GPT-3.5. LLM-generated knowledge graphs with more than 2 × 105 nodes and 3.3 × 105 links are analyzed per publication year, and temporal tracking leads to the identification of criteria for publication innovation, controversy, influence, and future research trends.

Assessing Cloud Feedbacks Over the Atlantic With Bias‐Corrected Downscaling

Mon, 16 Jun 2025 00:00:00 GMT

Assessing Cloud Feedbacks Over the Atlantic With Bias‐Corrected Downscaling Liu, Shuchang; Zeman, Christian; Schär, Christoph Clouds exert a significant impact on global temperatures and climate change. Cloud‐radiativefeedback (CRF) is one of the major sources of climate change uncertainty. Understanding CRF is thereforecrucial for accurate climate projections. Biases like the double‐ITCZ problem in Global Climate Models(GCMs) hamper precise climate projections. Here, we explore a bias‐corrected downscaling method toconstrain the cloud feedback uncertainties in the tropical and sub‐tropical Atlantic region. We use regionalclimate model (RCM) simulations with convection permitting resolution, driven by debiased driving fields fromthree different global climate models (GCMs). Bias‐corrected downscaling significantly reduces biases in ITCZintensity and position, eliminating the double‐ITCZ bias across all six experiments (three GCMs for historicaland future periods). We explore the new methodology's potential to investigate the CRF in comparison to that ofthe driving GCMs. Results indicate that additional GCMs and RCMs are necessary for a more comprehensiveuncertainty estimation and more conclusive results, while our simulations suggest a potentially narrower rangeof CRF over the tropical and subtropical Atlantic, primarily due to an improved representation of stratocumulusclouds. Our study highlights the potential of bias‐corrected downscaling in constraining the uncertainty ofsimulations and estimates of cloud feedback and equilibrium climate sensitivity. The results advocate for furthersimulations with additional RCMs and domains for a more comprehensive analysis.

Adaptation of Aglycosylated Monoclonal Antibodies for Improved Production in Komagataella phaffii

Sat, 01 Feb 2025 00:00:00 GMT

Adaptation of Aglycosylated Monoclonal Antibodies for Improved Production in Komagataella phaffii Yang, Yuchen; Dalvie, Neil C; Brady, Joseph R; Naranjo, Christopher A; Lorgeree, Timothy; Rodriguez‐Aponte, Sergio A; Johnston, Ryan S; Tracey, Mary K; Elenberger, Carmen M; Lee, Eric; Tié, Mark; Love, Kerry R; Love, J Christopher Monoclonal antibodies (mAbs) are a major class of biopharmaceuticals manufactured by well-established processes using Chinese Hamster Ovary (CHO) cells. Next-generation biomanufacturing using alternative hosts like Komagataella phaffii could improve the accessibility of these medicines, address broad societal goals for sustainability, and offer financial advantages for accelerated development of new products. Antibodies produced by K. phaffii, however, may manifest unique molecular quality attributes, like host-dependent, product-related variants, that could raise potential concerns for clinical use. We demonstrate here conservative modifications to the amino acid sequence of aglycosylated antibodies based on the human IgG1 isotype that minimize product-related variations when secreted by K. phaffii. A combination of 2–3 changes of amino acids reduced variations across six different aglycosylated versions of commercial mAbs. Expression of a modified sequence of NIST mAb in both K. phaffii and CHO cells showed comparable biophysical properties and molecular variations. These results suggest a path toward the production of high-quality mAbs that could be expressed interchangeably by either yeast or mammalian cells. Improving molecular designs of proteins to enable a range of manufacturing strategies for well-characterized biopharmaceuticals could accelerate global accessibility and innovations.

Modulation of antigen delivery and lymph node activation in nonhuman primates by saponin adjuvant saponin/monophosphoryl lipid A nanoparticle

Mon, 25 Nov 2024 00:00:00 GMT

Modulation of antigen delivery and lymph node activation in nonhuman primates by saponin adjuvant saponin/monophosphoryl lipid A nanoparticle Yousefpour, Parisa; Zhang, Yiming J; Maiorino, Laura; Melo, Mariane B; Arainga Ramirez, Mariluz A; Kumarapperuma, Sidath C; Xiao, Peng; Silva, Murillo; Li, Na; Michaels, Katarzyna K; Georgeson, Erik; Eskandarzadeh, Saman; Kubitz, Michael; Groschel, Bettina; Qureshi, Kashif; Fontenot, Jane; Hangartner, Lars; Nedellec, Rebecca; Love, J Christopher; Burton, Dennis R; Schief, William R; Villinger, Francois J; Irvine, Darrell J Saponin-based vaccine adjuvants are potent in preclinical animal models and humans, but their mechanisms of action remain poorly understood. Here, using a stabilized HIV envelope trimer immunogen, we carried out studies in nonhuman primates (NHPs) comparing the most common clinical adjuvant aluminum hydroxide (alum) with saponin/monophosphoryl lipid A nanoparticles (SMNP), an immune-stimulating complex–like adjuvant. SMNP elicited substantially stronger humoral immune responses than alum, including 7-fold higher peak antigen-specific germinal center B-cell responses, 18-fold higher autologous neutralizing antibody titers, and higher levels of antigen-specific plasma and memory B cells. Positron emission tomography and computed tomography imaging in live NHPs showed that, unlike alum, SMNP promoted rapid antigen accumulation in both proximal and distal lymph nodes (LNs). SMNP also induced strong type I interferon transcriptional signatures, expansion of innate immune cells, and increased antigen-presenting cell activation in LNs. These findings indicate that SMNP promotes multiple facets of the early immune response relevant for enhanced immunity to vaccination.

Vaccines combining slow release and follicle targeting of antigens increase germinal center B cell diversity and clonal expansion

Wed, 18 Jun 2025 00:00:00 GMT

Vaccines combining slow release and follicle targeting of antigens increase germinal center B cell diversity and clonal expansion Rodrigues, Kristen A; Zhang, Yiming J; Lam, Jonathan; Aung, Aereas; Morgan, Duncan M; Romanov, Anna; Maiorino, Laura; Yousefpour, Parisa; Gibson, Grace; Ozorowski, Gabriel; Gregory, Justin R; Amlashi, Parastoo; Van, Richard; Buckley, Maureen; Ward, Andrew B; Schief, William R; Love, J Christopher; Irvine, Darrell J Vaccine adjuvants play important roles in shaping the humoral response to immunization. Here, we analyzed mechanisms of action of a clinically relevant combination adjuvant strategy, where phosphoserine (pSer)–tagged immunogens bound to aluminum hydroxide (alum) adjuvant, promoting prolonged antigen release to draining lymph nodes, are combined with a saponin nanoparticle adjuvant termed SMNP, which alters lymph flow and antigen entry into lymph nodes. When used with a stabilized HIV envelope trimer antigen in mice, this combined adjuvant approach promoted substantial enhancements in germinal center and antibody responses relative to either adjuvant alone. Using single-cell RNA and B cell receptor sequencing, we found that the alum-pSer/SMNP combination augmented the clonal expansion and diversity of the germinal center B cell repertoire, coincident with an increased proportion of S-phase germinal center B cells and expression of positive selection markers. Moreover, we found that the combination adjuvant approach, but not alum-pSer delivery or SMNP alone, promoted accumulation of intact antigen on follicular dendritic cells, reflecting integrated effects of slow antigen delivery and altered lymph node uptake. Genetic ablation of Cr1/2 expression by follicular dendritic cells eliminated antigen accumulation and hampered the antigen-specific germinal center response, supporting antigen delivery to these cells as a key mechanism of the improved response elicited by this combination adjuvant. These results demonstrate how adjuvants with complementary mechanisms of action affecting vaccine biodistribution and kinetics can enhance humoral immunity.

Accelerating cell culture media development using Bayesian optimization-based iterative experimental design

Tue, 01 Jul 2025 00:00:00 GMT

Accelerating cell culture media development using Bayesian optimization-based iterative experimental design Narayanan, Harini; Hinckley, Joshua A; Barry, Rachel; Dang, Brendan; Wolffe, Lenna A; Atari, Adel; Tseng, Yuen-Yi; Love, J Christopher Optimizing operational conditions for complex biological systems used in life sciences research and biotechnology is an arduous task. Here, we apply a Bayesian Optimization-based iterative framework for experimental design to accelerate cell culture media development for two applications. First, we show that this approach yields new compositions of media with cytokine supplementation to maintain the viability and distribution of human peripheral blood mononuclear cells in the culture. Second, we apply this framework to optimize the production of three recombinant proteins in cultivations of K.phaffii. We identified conditions with improved outcomes for both applications compared to the initial standard media using 3–30 times fewer experiments than that estimated for other methods such as the standard Design of Experiments. Subsequently, we also demonstrated the extensibility of our approach to efficiently account for additional design factors through transfer learning. These examples demonstrate how coupling data collection, modeling, and optimization in this iterative paradigm, while using an exploration-exploitation trade-off in each iteration, can reduce the time and resources for complex optimization tasks such as the one demonstrated here.

Emerging immunomodulatory strategies for cell therapeutics

Wed, 01 Mar 2023 00:00:00 GMT

Emerging immunomodulatory strategies for cell therapeutics Chua, Corrine Ying Xuan; Jiang, Allen Yujie; Eufrásio-da-Silva, Tatiane; Dolatshahi-Pirouz, Alireza; Langer, Robert; Orive, Gorka; Grattoni, Alessandro Cellular therapies are poised to transform the field of medicine by restoring dysfunctional tissues and treating various diseases in a dynamic manner not achievable by conventional pharmaceutics. Spanning various therapeutic areas inclusive of cancer, regenerative medicine, and immune disorders, cellular therapies comprise stem or non-stem cells derived from various sources. Despite numerous clinical approvals or trials underway, the host immune response presents a critical impediment to the widespread adoption and success of cellular therapies. Here, we review current research and clinical advances in immunomodulatory strategies to mitigate immune rejection or promote immune tolerance to cellular therapies. We discuss the potential of these immunomodulatory interventions to accelerate translation or maximize the prospects of improving therapeutic outcomes of cellular therapies for clinical success.

Long-Time Quantum–Classical Correspondence for Open Systems in Trace Norm

Thu, 21 Aug 2025 00:00:00 GMT

Long-Time Quantum–Classical Correspondence for Open Systems in Trace Norm Li, Zhenhao We consider a frictionless system coupled to an external Markovian environment. The quantum and classical evolution of such systems are described by the Lindblad and the Fokker–Planck equation, respectively. We show that when such a system is given by an at most quadratically growing Hamiltonian and at most linearly growing real jump functions, the quantum and classical evolutions remain close on time scales much longer than Ehrenfest time. In particular, we show that the evolution of a density matrix by the Lindblad equation is close in trace norm to the quantization of the corresponding evolution by the Fokker–Planck equation. Such agreement improves upon recent results (Galokowski and Zworski in Classical quantum correspondence in Lindblad evolution, 2024. arXiv:2403.09345 ; Hernández et al. in Decoherence ensures classicality beyond the Ehrenfest time as ħ → 0 , 2023. arXiv:2306.13717 , Hernández et al. in The limit of open quantum systems with general Lindbladians: vanishing noise ensures classicality beyond the ehrenfest time, 2023. arXiv:2307.05326 ), which proved long-time agreement in weaker norms.

Search for vector-like leptons with long-lived particle decays in the CMS muon system in proton-proton collisions at √s = 13 TeV

Wed, 20 Aug 2025 00:00:00 GMT

Search for vector-like leptons with long-lived particle decays in the CMS muon system in proton-proton collisions at √s = 13 TeV Chekhovsky, V.; Hayrapetyan, A.; Makarenko, V.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D. A first search is presented for vector-like leptons (VLLs) exclusively decaying into a light long-lived pseudoscalar boson and a standard model τ lepton. The pseudoscalar boson is assumed to have a mass below the τ+τ− threshold, so that it decays exclusively into two photons. It is identified using the CMS muon system. The analysis is carried out using a data set of proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS experiment in 2016–2018, corresponding to an integrated luminosity of 138 fb−1. Selected events contain at least one pseudoscalar boson decaying electromagnetically in the muon system and at least one hadronically decaying τ lepton. No significant excess of data events is observed compared to the background expectation. Upper limits are set at 95% confidence level on the vector-like lepton production cross section as a function of the VLL mass and the pseudoscalar boson mean proper decay length. The observed and expected exclusion ranges of the VLL mass extend up to 700 and 670 GeV, respectively, depending on the pseudoscalar boson lifetime.

Percolation effects on fracture in ductile-phase toughened oxide coatings

Tue, 25 Mar 2025 00:00:00 GMT

Percolation effects on fracture in ductile-phase toughened oxide coatings Gupta, Isha; Kpamegan, Aliya K.; Vaidyanathan, Annika M. L.; Cordero, Zachary C. The toughness and damage behaviors of ductile-phase toughened oxide coatings were characterized as the reinforcement volume fraction varied across the percolation threshold. The coatings, consisting of Ni particles in a borate glass-ceramic matrix, showed a rising resistance curve, with the extent of stable crack growth increasing with Ni content. While initiation toughness was relatively insensitive to reinforcement topology, peak toughness increased sharply once the Ni reinforcement percolated, reaching a maximum value of ~ 160 J/m2 in an interpenetrating composite coating with 35 vol% Ni. This toughness is sufficiently high to resist failure in the target application of rocket engine turbomachinery, where coatings must withstand rapid thermal transients upon engine startup and shutdown. Characterization of the crack path confirmed that this toughening increment corresponded to a transition from crack deflection to crack bridging as the dominant toughening mechanism. The implications of these results on design of ductile-phase toughened coatings are discussed. Graphical abstract Double-cantilever beam specimens with the ductile-phase toughened oxide coating as an interlayer between the two beams

AI Challenge for Satellite Pattern-of-Life Identification: Dataset, Design and Results

Mon, 04 Aug 2025 00:00:00 GMT

AI Challenge for Satellite Pattern-of-Life Identification: Dataset, Design and Results Siew, Peng M.; Solera, Haley E.; Lavezzi, Giovanni; Roberts, Thomas G.; Jang, Daniel; Baldsiefen, David; Tran, Binh; Yeung, Christopher; Johnson, Kurtis; Metzger, Nathan; Porcher, Francois; Haik, Isaac; Rodriguez-Fernandez, Victor; Folcik, Zachary; Price, Jeffrey Despite the availability of extensive historical data on Earth-orbiting objects, artificial intelligence (AI) adoption in space domain awareness remains limited. To address this gap, the 2024 MIT ARCLab Prize for AI Innovation in Space challenged participants to develop AI models for characterizing satellite pattern-of-life (PoL) in Geostationary Earth Orbit. The challenge focused on developing machine learning models capable of classifying behavioral patterns and detecting key transition events in multivariate time-series data. The challenge dataset comprised of 2402 satellite trajectories spanning six months with a two-hour temporal resolution. The data are generated using high-fidelity satellite propagators based on simulated trajectories, Vector Covariance Message data, and two-line elements. This dataset features diverse operational behaviors and propulsion systems, providing a robust foundation for AI analysis. The challenge attracted over 100 teams worldwide, with more than 350 submissions showcasing a diverse range of AI approaches, including deep learning architectures (CNNs, LSTMs, transformers), gradient-boosting techniques (XGBoost, CatBoost), and hybrid models. The top performing teams demonstrated AI’s effectiveness in PoL characterization, with Hawaii2024 achieving an F2 score of 0.952 on the partial test set using a CNN-LSTM hybrid approach, followed closely by Millennial-IUP and QR_Is that utilized XGBoost with tailored transition-labeling and gradient-boosted decision tree with a model-stacking strategy, respectively. This paper presents an analysis of the competition’s dataset, evaluation methodology, and top-performing solutions.

Analysis of smart imaging runtime

Thu, 14 Aug 2025 00:00:00 GMT

Analysis of smart imaging runtime Athey, Thomas; Sawmya, Shashata; Meirovitch, Yaron; Schalek, Richard; Potocek, Pavel; Chandok, Ishaan; Peemen, Maurice; Lichtman, Jeff; Samuel, Aravinthan; Shavit, Nir Smart microscopy is a new imaging approach that involves rapid imaging, prediction of important subregions, then selective re-imaging. This approach has been validated in reducing imaging beam time in electron microscopy connectomics, but the speedup depends on various imaging workflow parameters. Here we present the first runtime analysis of traditional vs. smart microscopy and show how these parameters can magnify, or diminish potential time savings. We provide a GUI application that calculates the theoretical time savings of smart microscopy from user input parameters describing their imaging workflow. Finally, we measure end-to-end runtime of SmartEM acquisition on an electron microscope to demonstrate two strategies for faster acquisition: mixed-precision neural networks and parallelization of microscope and support computer operations.

The ππ scattering amplitude at large Nc

Thu, 14 Aug 2025 00:00:00 GMT

The ππ scattering amplitude at large Nc Baeza-Ballesteros, Jorge; Hernández, Pilar; Romero-López, Fernando We study the scaling of meson-meson scattering amplitudes with the number of colors, Nc. We use lattice calculations in a theory with Nf = 4 degenerate flavors, with Nc = 3 – 6 and pion mass Mπ ≈ 560 MeV. We focus on three different scattering channels, two of which have the same quantum numbers as some tetraquark candidates recently found at LHCb: the T cs 0 0 2900 , T c s ¯ 0 + + 2900 , T c s ¯ 0 0 2900 and T cs 1 0 2900 states. Finite-volume energies are extracted using a large set of operators, containing two-particle operators with the form of two pions or two vector mesons, and local tetraquark operators. The resulting energy spectra is used to constrain the infinite-volume scattering amplitude by means of Lüscher’s quantization condition. We consider polynomial parametrizations of the phase shift, as well as one-loop chiral perturbation theory (ChPT) predictions. We find that our lattice results follow the expected Nc scaling and are sensitive to subleading Nc corrections. In addition, we constrain the scaling of different combinations of low-energy constants from matching to large Nc ChPT. The results for the channel corresponding to a π + D s + − K + D + state show evidence of a virtual bound state with energy Evirtual = 1.63(10)Mπ for Nc = 3, while this pole disappears at Nc > 3. This may be connected to the exotic states found in experiment.

Semi-automated last touch detection for out-of-bounds possession decisions in football

Wed, 27 Aug 2025 00:00:00 GMT

Semi-automated last touch detection for out-of-bounds possession decisions in football Wang, Henry; Mills, Katie; Billingham, Johsan; Robertson, Sam; Hosoi, A. E. Football referees must make quick and accurate decisions in unforgiving environments. In parallel, advances in optical tracking have created new avenues for technology-assisted officiating. Using skeletal and ball tracking data, we present a novel diphase framework for Semi-automated Last Touch detection, designed to help referees adjudicate out-of-bounds possession decisions where player and ball occlusion may pose challenges. The proposed methodology uses a touch probability model to find the decision frame of the last touch before the ball goes out-of-bounds, and rules-based or supervised learning algorithms predict the player responsible for the touch. Leveraging principles of kinematics, human anthropometry, and machine learning, the models predict the correct possession decision with up to 82.5% accuracy on a test dataset of duels from the 2022 FIFA World Cup, including over 90% for aerial duels. Our results represent potential improvements in human performance reported in previous literature and provide a baseline benchmark for future studies.

Small radius inclusive jet production at the LHC through NNLO+NNLL

Fri, 01 Aug 2025 00:00:00 GMT

Small radius inclusive jet production at the LHC through NNLO+NNLL Generet, Terry; Lee, Kyle; Moult, Ian; Poncelet, Rene; Zhang, Xiaoyuan The study of hadronic jets and their substructure at hadronic colliders is crucial for improving our understanding of QCD, and searching for new physics. As such, there has been a significant effort to improve their theoretical description. In the small radius limit, inclusive jet production exhibits a universal factorization, enabling the resummation of logarithms which greatly stabilizes theoretical predictions. In this paper, we show how to combine a recently introduced framework for small-R resummation with the Stripper subtraction formalism for fragmentation, enabling next-to-next-to-leading order calculations of small-R inclusive jet production for a wide variety of processes at the LHC. We extract the two-loop constants for the jet functions, enabling for the first time next-to-next-to-leading logarithmic resummation matched to next-to-next-to-leading order perturbative calculation. We compare with CMS data for small-R jet production, and find that our results greatly improve the accuracy of the predictions at small-R, and stabilize the perturbative convergence and error estimates at larger R. Our approach is applicable to a wide class of jet substructure observables exhibiting similar factorization theorems, opening the door to an NNLO jet substructure program at the LHC.

Endosomolytic Peptides Enable the Cellular Delivery of Peptide Nucleic Acids

Mon, 11 Nov 2024 00:00:00 GMT

Endosomolytic Peptides Enable the Cellular Delivery of Peptide Nucleic Acids Giancola, JoLynn B.; Raines, Ronald T. Precision genetic medicine enlists antisense oligonucleotides (ASOs) to bind to nucleic acid targets important for human disease. Peptide nucleic acids (PNAs) have many desirable attributes as ASOs but lack cellular permeability. Here, we use an assay based on the corrective splicing of an mRNA to assess the ability of synthetic peptides to deliver a functional PNA into a human cell. We find that the endosomolytic peptides L17E and L17ER4 are highly efficacious delivery vehicles. Co-treatment of a PNA with low micromolar L17E or L17ER4 enables robust corrective splicing in nearly all treated cells. Peptide–PNA conjugates are even more effective. These results enhance the utility of PNAs as research tools and potential therapeutic agents.

Archive Labeling Sequences

Fri, 22 Aug 2025 00:00:00 GMT

Archive Labeling Sequences Khovanova, Tanya; Marton, Gregory What follows is the story of a family of integer sequences, which started life as a Google interview puzzle back in the previous century when VHS video tapes were in use.

Rivers Influence Reef Pass Formation in the Society Islands

Sat, 14 Jun 2025 00:00:00 GMT

Rivers Influence Reef Pass Formation in the Society Islands Gillen, Megan N; Ashton, Andrew D; Perron, J Taylor Reef passes are deep, navigable channels dissecting coral reefs around volcanic islands. Many reef passes are located offshore of large island river basins, suggesting a potential causal relationship. To clarify the mechanisms that form and maintain reef passes, we quantify the relationships between reef pass location and drainage basin size in the Society Islands. River basins draining toward reef passes are larger than those draining toward unbroken reef flats, suggesting that rivers help create and sustain reef passes. The correlation between reef passes and large rivers weakens for older islands, suggesting that oceanographic processes increasingly maintain passes as islands age and subside. We propose two river-driven reef pass formation mechanisms: reef incision, in which rivers erode into reefs during sea-level lowstands, and reef encroachment, in which corals growing in lower-elevation submerged river valleys preferentially drown during periods of rapid sea-level rise, leaving gaps in the accreting reef.

“Lab‐Quakes”: Quantifying the Complete Energy Budget of High‐Pressure Laboratory Failure

Thu, 28 Aug 2025 00:00:00 GMT

“Lab‐Quakes”: Quantifying the Complete Energy Budget of High‐Pressure Laboratory Failure Ortega‐Arroyo, Daniel; O'Ghaffari, Hoagy; Peč, Matěj; Gong, Zheng; Fu, Roger R; Ohl, Markus; Cattania, Camilla; Plümper, Oliver Understanding the interplay of various energy sinks during seismic fault slip is essential for advancing earthquake physics and improving hazard assessment. However, quantifying the energy consumed by major dissipative processes remains a challenge. In this study, we investigate energy partitioning during laboratory earthquakes (“lab-quakes”) by performing general shear stick-slip experiments on synthetic granitic cataclasites at elevated confining pressure. Using ultrasound, microstructural, and novel magnetism-based thermal analyses, we independently quantified the energy allocated to seismic radiation, new surfaces, and heat dissipation. These estimates showed good agreement with far-field measurements of mechanical work during the lab-quake. Our findings revealed that under the experimental conditions the majority of the released energy (68%–98%) is dissipated as heat, while seismic radiation accounts for 1%–8%, and the creation of new surfaces consumes <1%–32%. Microstructural observations indicate pre-failure deformation, which includes comminution and development of the principal slip zone, significantly influences energy partitioning. This effect is further evident in the measured shear stress drops, where events with higher stress drops proportionally emitted more energy as seismic waves. This study is the first to constrain the full energy budget of lab-quakes from an observational standpoint, providing critical insights into the dynamics of fault rupture and energy dissipation processes.

A High-Precision Analytical Technique for Dissolved N2 Isotopes in Aquatic Systems: Biogeochemical Applications and Determination of Solubility Equilibrium Isotope Effects

Tue, 17 Jun 2025 00:00:00 GMT

A High-Precision Analytical Technique for Dissolved N2 Isotopes in Aquatic Systems: Biogeochemical Applications and Determination of Solubility Equilibrium Isotope Effects McPaul, Katelyn; Wankel, Scott D.; Seltzer, Alan M. Rationale The isotopic composition of dissolved dinitrogen gas (δ15N-N2) in water can offer a powerful constraint on the sources and pathways of nitrogen cycling in aquatic systems. However, because of the large presence of atmosphere-derived dissolved N2 in these systems, high-precision (on the order of 0.001‰) measurements of N2 isotopes paired with inert gas measurements are required to disentangle atmospheric and biogeochemical signals. Additionally, the solubility equilibrium isotope fractionation of N2 and its temperature and salinity dependence are underconstrained at this level of precision. Methods We introduce a new technique for sample collection, processing, and dynamic dual-inlet mass spectrometry allowing for high-precision measurement of δ15N-N2 and δ(N2/Ar) with simultaneous measurement of δ(40Ar/36Ar) and δ(Kr/N2) in water. We evaluate the reproducibility of this technique and employ it to redetermine the solubility equilibrium isotope effects for dissolved N2 across a range of temperatures and salinities. Results Our technique achieves measurement reproducibility (1σ) for δ15N-N2 (0.006‰) and δ(N2/Ar) (0.41‰) suitable for tracing biogeochemical nitrogen cycling in aquatic environments. Through a series of air–water equilibration experiments, we find a N2 solubility equilibrium isotope effect (ε = α/1000 − 1, where α = (29N2/28N2)dissolved/(29N2/28N2)gas) in water of ε(‰) = 0.753 − 0.004•T where T is the temperature (°C), with uncertainties on the order of 0.001‰ over the temperature range of ~2°C–23°C and salinity range of ~0–30 psu. We find no apparent dependence of ε on salinity. Conclusions Our new method allows for high-precision measurements of the isotopic composition of dissolved N2 and Ar, and dissolved N2/Ar and Kr/N2 ratios, within the same sample. Pairing measurements of N2 with inert gases facilitates the quantification of excess N2 from biogeochemical sources and its isotopic composition. This method allows for a wide range of applications in marine, coastal, and freshwater environments to characterize and quantitatively constrain potential nitrogen-cycling sources and pathways and to differentiate between physical and biological isotope signals in these systems.

Linking Lattice Strain and Fractal Dimensions to Non‐monotonic Volume Changes in Irradiated Nuclear Graphite

Tue, 12 Aug 2025 00:00:00 GMT

Linking Lattice Strain and Fractal Dimensions to Non‐monotonic Volume Changes in Irradiated Nuclear Graphite Sprouster, David J; Fayfar, Sean; Rai, Durgesh K; Campbell, Anne; Ilavsky, Jan; Snead, Lance L; Khaykovich, Boris Graphite's resilience to high temperatures and neutron damage makes it vital for nuclear reactors, yet irradiation alters its microstructure, degrading key properties. We used small- and wide-angle X-ray scattering to study neutron-irradiated fine-grain nuclear graphite (Grade G347A) across varied temperatures and fluences. Results show significant shifts in internal strain and porosity, correlating with radiation-induced volume changes. Notably, porosity volume distribution (fractal dimensions) follows non-monotonic volume changes, suggesting a link to the Weibull distribution of fracture stress.

Computing Skinning Weights via Convex Duality

Thu, 25 Sep 2025 00:00:00 GMT

Computing Skinning Weights via Convex Duality Solomon, J; Stein, O We study the problem of optimising for skinning weights through the lens of convex duality. In particular, we show that the popular bounded biharmonic weight (BBW) model for skinning is dual to a non-negative least-squares problem, which is amenable to efficient solution via iterative algorithms; the final weights are then recoverable via a closed-form expression. Our formulation maintains convexity and is provably equivalent to the original problem. We also provide theoretical discussion giving intuition for the dual problem in the smooth case. Our final algorithm, which can be implemented in a few lines of code, achieves efficient convergence times relative to generic quadratic programming tools applied to the primal problem, without nonconvex formulations, relaxations or specialised optimisation techniques.

Saving and Letting Live

Thu, 31 Jul 2025 00:00:00 GMT

Saving and Letting Live Byrne, Thomas There is a metaphysical difference between person Akilling person B and A merely letting B die. There isalso a metaphysical difference between A saving B andA merely letting B live. This paper argues that the meta-physical difference between saving and letting live givesrise to a moral difference. It then puts that moral differ-ence to work: for example, it accounts for the long-feltmoral difference between failing to rescue a drowningchild and failing to donate $4000 to Oxfam (sufficientfor them, in the aggregate, to prevent a child’s death).

Enhancement of Superconductivity in WP via Oxide-Assisted Chemical Vapor Transport

Sun, 28 Sep 2025 00:00:00 GMT

Enhancement of Superconductivity in WP via Oxide-Assisted Chemical Vapor Transport Campbell, Daniel J.; Lin, Wen-Chen; Collini, John; Eo, Yun Suk; Anand, Yash; Saha, Shanta; Graf, David; Zavalij, Peter Y.; Paglione, Johnpierre Tungsten monophosphide (WP) has been reported to superconduct below 0.8 K, and theoretical work has predicted an unconventional Cooper pairing mechanism. Here we present data for WP single crystals grown by means of chemical vapor transport (CVT) of WO3, P, and I2. In comparison to synthesis using WP powder as a starting material, this technique results in samples with substantially decreased low-temperature scattering and favors a more three-dimensional morphology. We also find that the resistive superconducting transitions in these samples begin above 1 K. Variation in Tc is often found in strongly correlated superconductors, and its presence in WP could be the result of influence from a competing order and/or a non-s-wave gap.

Molecular Imbalances Between Striosome and Matrix Compartments Characterize the Pathogenesis and Pathophysiology of Huntington’s Disease Model Mouse

Tue, 02 Sep 2025 00:00:00 GMT

Molecular Imbalances Between Striosome and Matrix Compartments Characterize the Pathogenesis and Pathophysiology of Huntington’s Disease Model Mouse Morigaki, Ryoma; Yoshida, Tomoko; Fujikawa, Joji; Crittenden, Jill R.; Graybiel, Ann M. The pathogenesis and pathophysiology of Huntington’s disease (HD) are still incompletely understood, despite the remarkable advances in identifying the molecular effects of the Htt mutation in this disease. Clinical positron emission tomography studies suggest that phosphodiesterase 10A (PDE10A) declines earlier than dopamine D1 and D2 receptors in HD, indicating that it might serve as a key molecular marker in understanding disease mechanisms. In movement disorders, mutations in the genes encoding PDE10A and G-protein α subunit (Gαolf), both critical cAMP regulators in striatal spiny projection neurons, have been linked to chorea and dystonia. These observations highlight the potential importance of striatal cyclic AMP (cAMP) signaling in these disorders, but how such dysfunction could come is unknown. Here, we suggest that a key to understanding signaling dysfunction might be to evaluate these messenger systems in light of the circuit-level compartmental organization of the caudoputamen, in which there is particular vulnerability of the striosome compartment in HD. We developed machine learning algorithms to define with high precision and reproducibility the borders of striosomes in the brains of Q175 knock-in (Q175KI) HD mice from 3–12 months of age. We demonstrate that the expression of multiple molecules, including Gαolf, PDE10A, dopamine D1 and D2 receptors, and adenosine A2A receptors, is significantly reduced in the striosomes of Q175KI mice as compared to wildtype controls, across 3, 6, and 12 months of age. By contrast, mu-opioid receptor (MOR1) expression is uniquely upregulated, suggesting a compartment-specific and age-dependent shift in molecular profiles in the Q175KI HD mouse model caudoputamen. These differential changes may serve as a useful platform to determine factors underlying the greater vulnerability of striatal projection neurons in the striosomes than in the matrix in HD.

Field-Scale Rice Area and Yield Mapping in Sri Lanka with Optical Remote Sensing and Limited Training Data

Tue, 02 Sep 2025 00:00:00 GMT

Field-Scale Rice Area and Yield Mapping in Sri Lanka with Optical Remote Sensing and Limited Training Data Özdoğan, Mutlu; Wang, Sherrie; Ghose, Devaki; Fraga, Eduardo; Fernandes, Ana; Varela, Gonzalo Rice is a staple crop for over half the world’s population, and accurate, timely information on its planted area and production is crucial for food security and agricultural policy, particularly in developing nations like Sri Lanka. However, reliable rice monitoring in regions like Sri Lanka faces significant challenges due to frequent cloud cover and the fragmented nature of smallholder farms. This research introduces a novel, cost-effective method for mapping rice-planted area and yield at field scales in Sri Lanka using optical satellite data. The rice-planted fields were identified and mapped using a phenologically tuned image classification algorithm that highlights rice presence by observing water occurrence during transplanting and vegetation activity during subsequent crop growth. To estimate yields, a random forest regression model was trained at the district level by incorporating a satellite-derived chlorophyll index and environmental variables and subsequently applied at the field level. The approach has enabled the creation of two decades (2000–2022) of reliable, field-scale rice area and yield estimates, achieving map accuracies between 70% and over 90% and yield estimates with less than 20% error. These highly granular results, which are not available through traditional surveys, show a strong correlation with government statistics. They also demonstrate the advantages of a rule-based, phenology-driven classification over purely statistical machine learning models for long-term consistency in dynamic agricultural environments. This work highlights the significant potential of remote sensing to provide accurate and detailed insights into rice cultivation, supporting policy decisions and enhancing food security in Sri Lanka and other cloud-prone regions.

Generalized Pitman–Stanley Polytope: Vertices and Faces

Mon, 09 Dec 2024 00:00:00 GMT

Generalized Pitman–Stanley Polytope: Vertices and Faces Dugan, William T.; Hegarty, Maura; Morales, Alejandro H.; Raymond, Annie In 1999, Pitman and Stanley introduced the polytope bearing their name along with a study of its faces, lattice points, and volume. The Pitman–Stanley polytope is well-studied due to its connections to probability, parking functions, the generalized permutahedra, and flow polytopes. Its lattice points correspond to plane partitions of skew shape with entries 0 and 1. Pitman and Stanley remarked that their polytope can be generalized so that lattice points correspond to plane partitions of skew shape with entries 0 , 1 , … , m . Since then, this generalization has been untouched. We study this generalization and show that it can also be realized as a flow polytope of a grid graph. We give multiple characterizations of its vertices in terms of plane partitions of skew shape and integer flows. For a fixed skew shape, we show that the number of vertices of this polytope is a polynomial in m whose leading term, in certain cases, counts standard Young tableaux of a skew shifted shape. Moreover, we give formulas for the number of faces, as well as generating functions for the number of vertices.

From stellar light to astrophysical insight: automating variable star research with machine learning

Thu, 24 Jul 2025 00:00:00 GMT

From stellar light to astrophysical insight: automating variable star research with machine learning Audenaert, Jeroen Large-scale photometric surveys are revolutionizing astronomy by delivering unprecedented amounts of data. The rich data sets from missions such as the NASA Kepler and TESS satellites, and the upcoming ESA PLATO mission, are a treasure trove for stellar variability, asteroseismology and exoplanet studies. In order to unlock the full scientific potential of these massive data sets, automated data-driven methods are needed. In this review, I illustrate how machine learning is bringing asteroseismology toward an era of automated scientific discovery, covering the full cycle from data cleaning to variability classification and parameter inference, while highlighting the recent advances in representation learning, multimodal datasets and foundation models. This invited review offers a guide to the challenges and opportunities machine learning brings for stellar variability research and how it could help unlock new frontiers in time-domain astronomy.

Hidden causality in Modern Greek

Mon, 09 Jun 2025 00:00:00 GMT

Hidden causality in Modern Greek Tsilia, Anastasia This paper explores the syntax and semantics of an attitudinal construction in Modern Greek (mg), where an attitude verb takes an accusative object followed by a complement clause. Building on existing syntactic literature (e.g., Hadjivassiliou et al. in 13th international symposium on theoretical and applied linguistics, Aristotle University of Thessaloniki, Thessaloniki, pp. 70–80, 2000; Kotzoglou in Reading Working Papers in Linguistics 6:39–56, 2002; Kotzoglou in Selected papers on theoretical and applied linguistics from 22nd ISTAL, Aristotle University of Thessaloniki, Thessaloniki, pp. 299–315, 2017; Kotzoglou and Papangeli in New horizons in the analysis of raising and control, Springer, Dordrecht, pp. 111–131, 2007), I show that the accusative object is base-generated higher than the lower clause. Yet, I show that it semantically behaves as if it is part of the intensionalized argument of the attitude verb, giving rise to de dicto readings (Tsilia in Proceedings of Sinn und Bedeutung 27, pp. 655–673, 2023). Building on this and on a causal semantic requirement associated with the accusative object, I suggest a clausal analysis of the phenomenon. More specifically, under this analysis the accusative object is the subject of a small intermediate vp clause headed by a silent proleptic cause, which then takes the complement clause as its object. This contributes to the literature suggesting that hidden clauses are cross-linguistically attested and can solve intensionality paradoxes (den Dikken et al. in Non-propositional intentionality, Oxford Academic, Oxford, pp. 46–94, 2018), as well as to the literature on prolepsis (Davies in Language 81:645–665, 2005; Salzmann in The Wiley-Blackwell companion to syntax, Blackwell, Malden, vol. 5, pp. 3203–3245, 2017a; Deal in Semantics and Linguistic Theory 28:622–648, 2018; Dawson and Deal in Proceedings of Sinn und Bedeutung 23, pp. 329–346, 2019) showing that proleptic constructions may have varying interpretations and syntactic analyses cross-linguistically.

Type II RR string fields and exotic diffeomorphisms

Fri, 05 Sep 2025 00:00:00 GMT

Type II RR string fields and exotic diffeomorphisms Mamade, Raji A.; Zwiebach, Barton We study the theory of massless fields of type II strings arising from the string field theory that uses two string fields, a physical one and an extra one that allows the writing of an action, but whose degrees of freedom ultimately decouple. The mechanism allowing the description of the self-dual five-form of type IIB, anticipated by Sen, is used by the SFT to describe all Ramond-Ramond forms in type IIB and IIA in a manifestly duality-invariant way. We find explicit expressions for the leading terms in the gauge transformation of the RR fields and focus on diffeomorphisms, which are exotic for both the physical and the extra fields, perhaps as needed to describe propagating degrees of freedom that do not gravitate. The algebra of diffeomorphisms includes field-dependent structure constants and only closes on-shell, as predicted by the type II SFT gauge algebra.

Maintenance of core temperature in SCUBA divers in cold water: contributions of anthropometrics, suit type, and sex

Thu, 04 Sep 2025 00:00:00 GMT

Maintenance of core temperature in SCUBA divers in cold water: contributions of anthropometrics, suit type, and sex Orman, Tucker; Bradbury, Karleigh E.; Grosshennig, Tim; Perez, Makayla; Möller, Fabian N.; Dujić, Željko; Lovering, Andrew T. Maintenance of core temperature (Tc) is vital for health and physiological function while SCUBA diving in cold water, but there is little research investigating the influence of anthropometrics, suit type, and sex on the rate of change in Tc during real-world diving conditions. We measured the rate of change in Tc (telemetric pill) and thermal sensation (Ts; Young questionnaire) in 62 participants (32 female) before and after non-decompression SCUBA dives using open circuit apparatus breathing air at varied depths and durations in cold water (~ 10 °C). Twenty-three participants wore drysuits (11F), and 39 participants wore wetsuits (21F). There was a significant effect of suit type on the rate of change in Tc, with those in wetsuits having a greater decrease in Tc than those in drysuits. However, there was no effect of suit type on the rate of change in Ts. In wetsuit and drysuit groups, there were significant associations between Tc/min and BSA/BM, BMI, and BM. Estimated body fat % (BF%) was significantly associated with the rate of change in Tc in the wetsuit group only. When separated by sex, there were significant associations with all the anthropometric variables and the rate of change in Tc in the female participants, but only with BM in the wetsuit males. These results suggest that drysuits offer greater thermal protection compared to wetsuits in 10 °C water, and anthropometrics should be considered when selecting the degree of thermal protection, especially for female divers.

Major-element, trace-element and sulfur-isotope evidence for arc-like magmatism in the 4.0–2.9 Ga Acasta Gneiss Complex

Fri, 22 Aug 2025 00:00:00 GMT

Major-element, trace-element and sulfur-isotope evidence for arc-like magmatism in the 4.0–2.9 Ga Acasta Gneiss Complex Beaudry, Patrick; Jagoutz, Oliver; Bauer, Ann M.; Rezeau, Hervé; Reimink, Jesse R.; Grove, Timothy L.; Izon, Gareth; Ono, Shuhei The Acasta Gneiss Complex (AGC) in northwestern Canada comprises Earth’s oldest known evolved crust, with zircon U–Pb ages up to 4.03 Ga. Several pulses of crustal generation and metamorphism are preserved in tonalitic and granitic gneisses spanning over one billion years, along with mafic and ultramafic rocks of unknown age. Major elements, trace elements and radiogenic isotope signatures have been invoked to suggest that these rocks preserve the local onset of horizontal tectonic processes. However, the behavior and influence of volatiles, which have a defining role in modern arc magmatism, remain unconstrained. Here we combine new whole-rock major- and trace-element data with multiple sulfur isotope analyses in 4.0–2.9 Ga Acasta gneisses and spatially associated mafic and ultramafic rocks to investigate the petrogenesis of the AGC. We use a recently-published major element-based melt hygrometer to estimate dissolved water contents for all published plagioclase-saturated Acasta meta-igneous rocks, and find modes at < 0.5 wt.% and 5 wt.% H2O, similar to modern arc magmas. Tholeiitic and calc-alkaline trends are both present, with the former being more prominent in the oldest (ca. 4.0 Ga) samples and in mafic rocks. Zircon trace element oxybarometry reveals a shift towards more oxidized magmatic conditions by 3.75 Ga. Sulfur isotopes record a limited range in δ34S values, suggesting a common igneous end-member at ~ + 1 ‰, and positively correlate with calculated H2O contents, with more positive values (up to + 5‰) appearing in the Paleoarchean (< 3.6 Ga). The Eoarchean (4.0–3.6 Ga) δ34S values are consistent with a precursor Hadean crust having an enriched sulfur isotope signature, possibly resulting from hydrous alteration or from isotopic fractionation during its formation. The temporal progression to more positive δ34S values is consistent with a shift towards more hydrous and oxidized magmatic differentiation. Most samples have near-zero Δ33S that fall along a mass-dependent fractionation (MDF) array, but one 3.5 Ga metasedimentary sample has a negative MIF Δ33S signature of -0.60 ± 0.01 ‰. Additionally, two granitic gneisses dated at 3.3 and 2.9 Ga preserve small positive MIF Δ33S values of + 0.08 ± 0.02 ‰, which could reflect recycling of sedimentary material via subduction by 3.3 Ga. Overall, our data indicate that the Acasta Gneiss Complex preserves several modes of crustal generation evolving over time, with an increasing importance of deep hydrous magmatism by 3.75 Ga and of sedimentary inputs by 3.3 Ga.

The Future of Drug Delivery

Tue, 24 Jan 2023 00:00:00 GMT

The Future of Drug Delivery Gao, Jingjing; Karp, Jeffrey M; Langer, Robert; Joshi, Nitin Drug delivery technologies have been proven to improve treatment outcomes in many ways, including enhancing therapeutic efficacy, reducing toxicity, increasing patient compliance, and enabling entirely new medical treatments. As the therapeutic landscape has evolved from small-molecule drugs to a new generation of therapeutics including proteins, peptides, monoclonal antibodies, nucleic acids, and even live cells, drug delivery technologies have also evolved to meet their unique delivery needs.

Altered DNA repair pathway engagement by engineered CRISPR-Cas9 nucleases

Tue, 07 Mar 2023 00:00:00 GMT

Altered DNA repair pathway engagement by engineered CRISPR-Cas9 nucleases Chauhan, Vikash P; Sharp, Phillip A; Langer, Robert CRISPR-Cas9 introduces targeted DNA breaks that engage competing DNA repair pathways, producing a spectrum of imprecise insertion/deletion mutations (indels) and precise templated mutations (precise edits). The relative frequencies of these pathways are thought to primarily depend on genomic sequence and cell state contexts, limiting control over mutational outcomes. Here, we report that engineered Cas9 nucleases that create different DNA break structures engage competing repair pathways at dramatically altered frequencies. We accordingly designed a Cas9 variant (vCas9) that produces breaks which suppress otherwise dominant nonhomologous end-joining (NHEJ) repair. Instead, breaks created by vCas9 are predominantly repaired by pathways utilizing homologous sequences, specifically microhomology-mediated end-joining (MMEJ) and homology-directed repair (HDR). Consequently, vCas9 enables efficient precise editing through HDR or MMEJ while suppressing indels caused by NHEJ in dividing and nondividing cells. These findings establish a paradigm of targeted nucleases custom-designed for specific mutational applications.

Hydrogels for RNA delivery

Mon, 20 Mar 2023 00:00:00 GMT

Hydrogels for RNA delivery Zhong, Ruibo; Talebian, Sepehr; Mendes, Bárbara B; Wallace, Gordon; Langer, Robert; Conde, João; Shi, Jinjun RNA-based therapeutics have shown tremendous promise in disease intervention at the genetic level, and some have been approved for clinical use, including the recent COVID-19 messenger RNA vaccines. The clinical success of RNA therapy is largely dependent on the use of chemical modification, ligand conjugation or non-viral nanoparticles to improve RNA stability and facilitate intracellular delivery. Unlike molecular-level or nanoscale approaches, macroscopic hydrogels are soft, water-swollen three-dimensional structures that possess remarkable features such as biodegradability, tunable physiochemical properties and injectability, and recently they have attracted enormous attention for use in RNA therapy. Specifically, hydrogels can be engineered to exert precise spatiotemporal control over the release of RNA therapeutics, potentially minimizing systemic toxicity and enhancing in vivo efficacy. This Review provides a comprehensive overview of hydrogel loading of RNAs and hydrogel design for controlled release, highlights their biomedical applications and offers our perspectives on the opportunities and challenges in this exciting field of RNA delivery.

The Thermal Reactivity and Molecular Diversity of Particulate Organic Carbon in the Amazon River Mainstem

Wed, 18 Jun 2025 00:00:00 GMT

The Thermal Reactivity and Molecular Diversity of Particulate Organic Carbon in the Amazon River Mainstem Rosengard, Sarah Z.; Mauro S. Moura, Jose; Spencer, Robert G. M.; Johnson, Carl; McNichol, Ann; Boehman, Brenna; Galy, Valier The Amazon River mobilizes one of the largest fluxes of particulate organic carbon (POC) fromland to coastal ocean sediments, playing an important role in the long‐term sequestration of biospheric organiccarbon in the ocean. Ramped oxidation (RPO) analyses of suspended sediments collected from the AmazonRiver mainstem, Solimões River, Madeira River, and Tapajós River presented an opportunity to parse riverinePOC by thermal reactivity, extract the activation energy distributions of specific biomolecular pools in thesesamples, and characterize the molecular diversity of POC across the floodplain. The thermal reactivity dataimply that POC from the Amazon River basin spans a wide but relatively homogenous activation energy rangeacross samples, suggesting that the degradation history of the organic carbon comprising riverine suspendedparticles is relatively constant across depths within the mainstem and different tributary locations. Couplingactivation energy distributions to stable and radiocarbon isotopic analyses shows that ca. 85% of mainstem POCderives from a range of partially degraded terrestrial sources, likely organic matter from mineral soil horizons,and that a similar range of soil sources influences the biomolecular diversity in tributary samples. In agreementwith earlier assessments, ca. 10% of the riverine POC flux is fresh vegetation and up to 5% of it is petrogenicorganic matter. Expanded RPO analyses of samples across the Amazon river‐to‐ocean continuum wouldprovide an opportunity to track the fate of these different organic matter pools downstream that is uniquelydifferent from, but complementary to, past compound‐specific and bulk analyses of riverine POC.

Overcoming barriers to patient adherence: the case for developing innovative drug delivery systems

Mon, 27 Mar 2023 00:00:00 GMT

Overcoming barriers to patient adherence: the case for developing innovative drug delivery systems Baryakova, Tsvetelina H; Pogostin, Brett H; Langer, Robert; McHugh, Kevin J Poor medication adherence is a pervasive issue with considerable health and socioeconomic consequences. Although the underlying reasons are generally understood, traditional intervention strategies rooted in patient-centric education and empowerment have proved to be prohibitively complex and/or ineffective. Formulating a pharmaceutical in a drug delivery system (DDS) is a promising alternative that can directly mitigate many common impediments to adherence, including frequent dosing, adverse effects and a delayed onset of action. Existing DDSs have already positively influenced patient acceptability and improved rates of adherence across various disease and intervention types. The next generation of systems have the potential to instate an even more radical paradigm shift by, for example, permitting oral delivery of biomacromolecules, allowing for autonomous dose regulation and enabling several doses to be mimicked with a single administration. Their success, however, is contingent on their ability to address the problems that have made DDSs unsuccessful in the past. Provided to the PMC Covid-19 Collection by Springer Nature

Rousseau's Freedom as Recognition

Thu, 19 Jun 2025 00:00:00 GMT

Rousseau's Freedom as Recognition Perilla, Julian To yearn for freedom is to want to be seen by others as someone. Rousseau, I believe, held such a conception of freedom, alongside his intricate theory of human passions. This essay examines how freedom relates to such passions, and in particular, to the Rousseauian notion of amour-propre. Importantly, the aim here is both interpretive and positive. The essay seeks to locate Rousseau within the old republican tradition in a manner that parts ways with most contemporary readings of Rousseau. But, in doing so, it argues that republican freedom essentially involves a particular status and the recognition of such status by others. On this Rousseauian view, one is free to the extent that others see one as a limit to their arbitrary interference and as entitled to interfere with them non-arbitrarily. Finally, republican freedom, so understood, is shown to be essential to meeting the demands of healthy amour-propre, thereby bringing Rousseau's political and psychological theories closer together.

Electric Field Inhomogeneity in Colloidal QD‐LEDs

Fri, 13 Jun 2025 00:00:00 GMT

Electric Field Inhomogeneity in Colloidal QD‐LEDs Srinivasan, Shreyas; Zhang, Ruiqi; Dillender, Mike; Nguyen, Thienan; Laitz, Madeleine; Kim, Taehyung; Kim, Kwang‐Hee; Kim, Tae‐Gon; Bawendi, Moungi; Bulović, Vladimir It is demonstrated that the electroluminescent layer in a colloidal quantum dotlight emitting diode (QD-LED), formed by stochastic methods such as spin-coating, incorporates morphological thickness inhomogeneities, resulting inlocal electric ﬁeld variations. These inhomogeneities can be directly visualizedand quantiﬁed using confocal micro-photoluminescence (PL) and micro-electroluminescence (EL), as showed in QD-LEDs with stochastically processedInP/ZnSe/ZnS colloidal quantum dots (QDs). Around 5% of the device showsEL darkspots under forward bias and PL hotspots under photoexcitation,with a strong spatial correlation between these features. The PL hotspots(EL darkspots) correspond to thicker regions in the stochastically-processedQD ﬁlm. This thickness variation leads to two distinct QD sub-populationsresponding diﬀerently to optical excitation. Time and energy-resolved spectraldiﬀusion measurements reveal that most excitons belong to a “more-mobile”sub-population with fast energy transfer and short, electric ﬁeld-dependentlifetimes, while a smaller fraction belongs to a “less-mobile” sub-populationwith slower energy transfer and longer, electric ﬁeld-independentlifetimes. The “less-mobile” excitons correlate with thicker QD regions. Theseﬁndings shed light on the local electric ﬁeld inhomogeneity in QD-LEDs,oﬀering insights into device operation, possible degradation mechanisms,and strategies for developing stochastically-processed micro-QD-LEDs.

Addressing Favorable and Challenging Flexible Plastic Packaging Waste Flows: A Material Flow Analysis

Thu, 05 Jun 2025 00:00:00 GMT

Addressing Favorable and Challenging Flexible Plastic Packaging Waste Flows: A Material Flow Analysis Makarova, Oksana A; Ravi, Basuhi; Sobkowicz, Margaret J; Masato, Davide; Olivetti, Elsa A The majority of post-consumer flexible plastic packaging (FPP) in the United States ends up in landfills and incinerators. Thisrepresents a significant material loss because FPP, also referred to as plastic films or foils, comprises up to half of all plasticpackaging. Since FPP encompasses a diverse range of products with varying recycling potentials, improving material recoveryrates requires a detailed understanding of the composition and quantities of used films. This study quantifies post-consumerFPP flows in the US for 2021 and estimates the fraction most suitable for mechanical recycling. We conducted a material flowanalysis (MFA) by reconciling publicly available data on packaging film generation and recycling from the US and comparableeconomies. We then categorized post-consumer FPP into three broad categories based on factors affecting the quality of the re-sulting mechanically recycled material. Our analysis reveals that only 3%–8% of the estimated 5–15 million metric tonnes of post-consumer film were recycled in 2021. Furthermore, at most 40% of the FPP could be readily mechanically recyclable, while up tohalf would be deemed non-recoverable due to techno-economic constraints. The actual proportions of challenging-to-recycle andnon-recoverable FPP might be even higher, underscoring the need for updated studies on film generation and waste compositionto assess the feasibility of scaling up nationwide film recycling.

Initiation of Sediment Resuspension by Combined Wave‐Current Conditions in an Artificial Seagrass Meadow

Sun, 08 Jun 2025 00:00:00 GMT

Initiation of Sediment Resuspension by Combined Wave‐Current Conditions in an Artificial Seagrass Meadow Zhao, Chuyan; Nepf, Heidi Laboratory experiments examined the impact of current on ripple formation and the onset ofwave‐driven resuspension within an artificial seagrass meadow modeled after Zostera marina. Within themeadow, the current was less than or equal to the wave velocity. Meadows were constructed with three shootdensities: 247, 455 and 962 stems/m2, and each shoot had six flexible blades. The sediment bed, consisting of65 μm spherical grains, was initially 1.4 cm thick, allowing ripple and scour hole formation. The formation ofwave‐orbital ripples was dependent on meadow density and current magnitude. Over bare beds and sparsemeadows, ripples were present and not impacted by the addition of current, such that the wave velocityresuspension threshold with current was the same as that in pure wave conditions. In medium‐density meadows,the addition of current reduced ripple height due to plant‐generated turbulence. As current increased, ripple sizeand ripple‐generated turbulence decreased, requiring a higher wave velocity to resuspend sediment. That is, formedium density meadows, the critical wave velocity increased as the current velocity increased. Finally, indense meadows, no ripples formed and resuspension was driven by a critical value of plant‐induced turbulence,which was proportional to the total velocity (current plus wave velocity), such that as the current velocityincreased, the critical wave velocity decreased. A model predicting the critical wave velocity for the densemeadow was derived based on the assumption that resuspension was driven by a critical level of stem‐generatedturbulence.

Thermal and Dimensional Stability of Photocatalytic Material ZnPS3 Under Extreme Environmental Conditions

Fri, 27 Jun 2025 00:00:00 GMT

Thermal and Dimensional Stability of Photocatalytic Material ZnPS3 Under Extreme Environmental Conditions Mukherjee, Abhishek; Santamaría‐García, Vivian J; Wlodarczyk, Damian; Somakumar, Ajeesh K; Sybilski, Piotr; Siebenaller, Ryan; Rowe, Emmanuel; Narayanan, Saranya; Susner, Michael A; Lozano‐Sanchez, L Marcelo; Suchocki, Andrzej; Palma, Julio L; Boriskina, Svetlana V Zinc phosphorus trisulﬁde (ZnPS 3 ), a promising material for photocatalysisand energy storage, is shown in this study to exhibit remarkable stabilityunder extreme conditions. Its optical and structural properties are exploredunder high pressure and cryogenic temperatures using photoluminescence(PL) spectroscopy, Raman scattering, and density functional theory (DFT). Theexperimental results identify a pressure-induced phase transition starting at6.75 GPa and stabilizing by 12.5 GPa, after which ZnPS 3 demonstrates robuststability across a broad pressure range up to 24.5 GPa. DFT calculationssupport these observations and further predict a semiconductor-to-semimetaltransition at 100 GPa, while PL measurements reveal defect-assisted emissionthat quench under pressure due to enhanced non-radiative recombination. Atcryogenic temperatures, PL quenching intensiﬁes as non-radiative processesdominate, driven by a rising Grüneisen parameter and reduced phononpopulation. Cryogenic X-ray diﬀraction (XRD) also reveals a high meanthermal expansion coeﬃcient (TEC) of (4.369 ± 0.393) × 10−5 K−1 , amongthe highest reported for 2D materials. This unique combination of tunableelectronic properties under low pressure and high thermal sensitivity makesZnPS3 a strong candidate for sensing applications in extreme environments.

Formulation and Calibration of CATKE, a One‐Equation Parameterization for Microscale Ocean Mixing

Mon, 21 Apr 2025 00:00:00 GMT

Formulation and Calibration of CATKE, a One‐Equation Parameterization for Microscale Ocean Mixing Wagner, Gregory LeClaire; Hillier, Adeline; Constantinou, Navid C; Silvestri, Simone; Souza, Andre; Burns, Keaton J; Hill, Chris; Campin, Jean‐Michel; Marshall, John; Ferrari, Raffaele We describe CATKE, a parameterization for fluxes associated with small‐scale or “microscale”ocean turbulent mixing on scales between 1 and 100 m. CATKE uses a downgradient formulation that dependson a prognostic turbulent kinetic energy (TKE) variable and a diagnostic mixing length scale that includes adynamic convective adjustment (CA) component. With its dynamic convective mixing length, CATKE predictsnot just the depth spanned by convective plumes but also the characteristic convective mixing timescale, animportant aspect of turbulent convection not captured by simpler static CA schemes. As a result, CATKE candescribe the competition between convection and other processes such as shear‐driven mixing and baroclinicrestratification. To calibrate CATKE, we use Ensemble Kalman Inversion to minimize the error between 21large eddy simulations (LESs) and predictions of the LES data by CATKE‐parameterized single columnsimulations at three different vertical resolutions. We find that CATKE makes accurate predictions of bothidealized and realistic LES compared to microscale turbulence parameterizations commonly used in climatemodels.

A GPU‐Based Ocean Dynamical Core for Routine Mesoscale‐Resolving Climate Simulations

Mon, 21 Apr 2025 00:00:00 GMT

A GPU‐Based Ocean Dynamical Core for Routine Mesoscale‐Resolving Climate Simulations Silvestri, Simone; Wagner, Gregory L; Constantinou, Navid C; Hill, Christopher N; Campin, Jean‐Michel; Souza, Andre N; Bishnu, Siddhartha; Churavy, Valentin; Marshall, John; Ferrari, Raffaele We describe an ocean hydrostatic dynamical core implemented in Oceananigans optimized forGraphical Processing Unit (GPU) architectures. On 64 A100 GPUs, equivalent to 16 computational nodes incurrent state‐of‐the‐art supercomputers, our dynamical core can simulate a decade of near‐global oceandynamics per wall‐clock day at an 8‐km horizontal resolution; a resolution adequate to resolve the ocean'smesoscale eddy field. Such efficiency, achieved with relatively modest hardware resources, suggests thatclimate simulations on GPUs can incorporate fully eddy‐resolving ocean models. This removes a major sourceof systematic bias in current IPCC coupled model projections, the parameterization of ocean eddies, andrepresents a major advance in climate modeling. We discuss the computational strategies, focusing on GPU‐specific optimization and numerical implementation details that enable such high performance.

A new upper bound for the growth factor in Gaussian elimination with complete pivoting

Wed, 26 Feb 2025 00:00:00 GMT

A new upper bound for the growth factor in Gaussian elimination with complete pivoting Bisain, Ankit; Edelman, Alan; Urschel, John The growth factor in Gaussian elimination measureshow large the entries of an LU factorization can be rel-ative to the entries of the original matrix. It is a keyparameter in error estimates, and one of the most fun-damental topics in numerical analysis. We produce anupper bound of 𝑛 0.2079 ln 𝑛+0.91 for the growth factor inGaussian elimination with complete pivoting — the firstimprovement upon Wilkinson’s original 1961 bound of2 𝑛 0.25 ln 𝑛+0.5.

Does U.S. Immigration Policy Facilitate Financial Misconduct?

Sun, 29 Jun 2025 00:00:00 GMT

Does U.S. Immigration Policy Facilitate Financial Misconduct? Dai, Ruiting; Dong, Xuanjun; Shroff, Nemit; Tan, Qin We examine whether U.S. immigration policy, specifically the H-1B visa program, affects the likelihood of financial misconduct. We argue that employers have leverage over employees on H-1B visas because such employees must maintain H-1B–eligible employment to legally reside in the United States. We posit that companies relying on H-1B visas to hire workers in accounting roles have an increased ability to misreport their financial statements due to the greater costs H-1B employees face if they are unexpectedly fired for not following the demands of their bosses or for blowing the whistle on misconduct. Using the sharp reduction in the H-1B visa cap in 2004 as a shock to such employment, we find that companies that relied on this visa program for accounting roles pre-shock experience a 2.3 percentage point decline in accounting irregularities post-shock. Cross-sectional tests show that the reduction in irregularities is greater in companies where H-1B employees have (1) a greater influence on financial reporting or (2) fewer job opportunities. In addition, the relation between H-1B visa use and irregularities is stronger in companies whose investors are more focused on near-term earnings targets. We corroborate our findings using the outcome of H-1B visa lotteries as shocks to such employment.

Data‐Driven Modeling of 4D Ocean and Coastal Acidification in the Massachusetts and Cape Cod Bays From Surface Measurements

Tue, 03 Jun 2025 00:00:00 GMT

Data‐Driven Modeling of 4D Ocean and Coastal Acidification in the Massachusetts and Cape Cod Bays From Surface Measurements Champenois, B; Bastidas, C; LaBash, B; Sapsis, TP A significant portion of atmospheric CO2 emissions is absorbed by the ocean, resulting inacidified seawater and altered carbonate composition that is harmful to marine life. Despite detrimental effects,assessing ocean and coastal acidification (OCA) is difficult due to the scarcity of in situ measurements and thehigh costs of computational modeling. We develop a parsimonious data‐driven framework to model indicatorsof OCA and test it in the Massachusetts Bay and Stellwagen Bank, a region with fishing and tourism industriesaffected by OCA. First, we trained a neural network to predict in‐depth fields for temperature and salinity(x, y, z) using surface quantities from satellites and in situ measurements (x, y). The relationship between 2Dsurface and 3D properties is captured through the in‐depth modes and coefficients obtained from principalcomponent analysis applied to a high‐resolution historical reanalysis data set. Next, we used Bayesianregression methods to estimate region‐specific relationships for in‐depth total alkalinity (TA), dissolvedinorganic carbon (DIC), and aragonite saturation state (ΩAr) as functions of temperature, salinity, andchlorophyll. Lastly, 4D daily field predictions are generated from surface measurements with a spatialresolution of 4 km horizontally and 45 sigma levels vertically. The model's performance is evaluated usingwithheld measurements across depths, locations, and seasons with RMSEs of 1.59°C, 0.31 PSU,37.54 μmol⋅kg-1, and 0.42 for temperature, salinity, TA, DIC, and ΩAr , respectively, at onewithheld location. The framework is useful for understanding OCA and includes uncertainty quantification for future planning and optimal sensor placement.

Arsenic Accumulation in Microbial Biomass and the Interpretation of Signals of Early Arsenic‐Based Metabolisms

Fri, 13 Jun 2025 00:00:00 GMT

Arsenic Accumulation in Microbial Biomass and the Interpretation of Signals of Early Arsenic‐Based Metabolisms Madrigal‐Trejo, David; Baldes, Matthew J; Tamura, Nobumichi; Klepac‐Ceraj, Vanja; Bosak, Tanja Carbonaceous particles that concentrate arsenic in microbialites as old as ~3.5 Ga are similar to As-rich organic globules in mod-ern microbialites. The former particles have been interpreted as tracers of As cycling by early microbial metabolisms. However,it is unclear if arsenic accumulation is a consequence of biological activity or passive postmortem binding of arsenic by organicmatter during diagenesis in volcanically influenced, As-rich environments. Here, we address this uncertainty by evaluating theconcentrations, speciation, and detectability of As in active or heat-killed biofilms formed by cyanobacteria or anoxygenic pho-tosynthetic microbes exposed to environmentally relevant concentrations of As(III) or As(V) (50 μM to 3 mM). The genomes ormetagenomes of these biofilms contain genes involved in detoxifying or energy-yielding As metabolisms. Biomass accumulatesAs from the solution in a concentration-dependent manner and with a preference for oxidized As(V) over As(III). Autoclaved bio-mass accumulates As even more strongly than active biomass, likely because living biofilms actively detoxify As. Active biofilmsoxidize and reduce As and accumulate both As(III) and As(V), whereas a small fraction of As(V) can be reduced in inactive bio-films that bind As during diagenesis. Arsenic enrichments in the biomass are detectable by X-ray based spectroscopy techniques(XRF, EPMA-WDS) that are commonly used to analyze geological materials. These findings enable the reconstruction of pastactive and passive interactions of microbial biomass with arsenic in fossilized microbial biofilms and microbialites from the earlyEarth.

Sensor-Agnostic, LSTM-Based Human Motion Prediction Using sEMG Data

Tue, 02 Sep 2025 00:00:00 GMT

Sensor-Agnostic, LSTM-Based Human Motion Prediction Using sEMG Data Koo, Bon Ho; Siu, Ho Chit; Petersen, Lonnie G. The use of surface electromyography (sEMG) for conventional motion classification and prediction has had limitations due to sensor hardware differences. With the popularization of deep learning-based approaches to the application of motion prediction, this study explores the effects that different hardware sensor platforms have on the performance of a deep learning neural network trained to predict the one-degree-of-freedom (DoF) angular trajectory of a human. Two different sEMG sensor platforms were used to collect raw data from subjects conducting exercises, which was used to train a neural network designed to predict the future angular trajectory of the arm. The results show that the raw data originating from different sensor hardware with different configurations (including the communication method, data acquisition unit (DAQ) usage, electrode configuration, buffering method, preprocessing method, and experimental variables like the sampling frequency) produced bi-LSTM networks that performed similarly. This points to the hardware-agnostic nature of such deep learning networks.

Engineering kinetics of TLR7/8 agonist release from bottlebrush prodrugs enables tumor-focused immune stimulation

Wed, 19 Apr 2023 00:00:00 GMT

Engineering kinetics of TLR7/8 agonist release from bottlebrush prodrugs enables tumor-focused immune stimulation Bhagchandani, Sachin H; Vohidov, Farrukh; Milling, Lauren E; Tong, Evelyn Yuzhou; Brown, Christopher M; Ramseier, Michelle L; Liu, Bin; Fessenden, Timothy B; Nguyen, Hung V-T; Kiel, Gavin R; Won, Lori; Langer, Robert S; Spranger, Stefani; Shalek, Alex K; Irvine, Darrell J; Johnson, Jeremiah A Imidazoquinolines (IMDs), such as resiquimod (R848), are of great interest as potential cancer immunotherapies because of their ability to activate Toll-like receptor 7 (TLR7) and/or TLR8 on innate immune cells. Nevertheless, intravenous administration of IMDs causes severe immune-related toxicities, and attempts to improve their tissue-selective exposure while minimizing acute systemic inflammation have proven difficult. Here, using a library of R848 “bottlebrush prodrugs” (BPDs) that differ only by their R848 release kinetics, we explore how the timing of R848 exposure affects immune stimulation in vitro and in vivo. These studies led to the discovery of R848-BPDs that exhibit optimal activation kinetics to achieve potent stimulation of myeloid cells in tumors and substantial reductions in tumor growth following systemic administration in mouse syngeneic tumor models without any observable systemic toxicity. These results suggest that release kinetics can be tuned at the molecular level to provide safe yet effective systemically administered immunostimulant prodrugs for next-generation cancer immunotherapies.

A microneedle vaccine printer for thermostable COVID-19 mRNA vaccines

Wed, 24 Apr 2024 00:00:00 GMT

A microneedle vaccine printer for thermostable COVID-19 mRNA vaccines vander Straeten, Aurélien; Sarmadi, Morteza; Daristotle, John L; Kanelli, Maria; Tostanoski, Lisa H; Collins, Joe; Pardeshi, Apurva; Han, Jooli; Varshney, Dhruv; Eshaghi, Behnaz; Garcia, Johnny; Forster, Timothy A; Li, Gary; Menon, Nandita; Pyon, Sydney L; Zhang, Linzixuan; Jacob-Dolan, Catherine; Powers, Olivia C; Hall, Kevin; Alsaiari, Shahad K; Wolf, Morris; Tibbitt, Mark W; Farra, Robert; Barouch, Dan H; Langer, Robert; Jaklenec, Ana Decentralized manufacture of thermostable mRNA vaccines in a microneedle patch (MNP) format could enhance vaccine access in low-resource communities by eliminating the need for a cold chain and trained healthcare personnel. Here we describe an automated process for printing MNP Coronavirus Disease 2019 (COVID-19) mRNA vaccines in a standalone device. The vaccine ink is composed of lipid nanoparticles loaded with mRNA and a dissolvable polymer blend that was optimized for high bioactivity by screening formulations in vitro. We demonstrate that the resulting MNPs are shelf stable for at least 6 months at room temperature when assessed using a model mRNA construct. Vaccine loading efficiency and microneedle dissolution suggest that efficacious, microgram-scale doses of mRNA encapsulated in lipid nanoparticles could be delivered with a single patch. Immunizations in mice using manually produced MNPs with mRNA encoding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein receptor-binding domain stimulate long-term immune responses similar to those of intramuscular administration.

Topical application of Lactobacilli successfully eradicates Pseudomonas aeruginosa biofilms and promotes wound healing in chronic wounds

Wed, 01 Nov 2023 00:00:00 GMT

Topical application of Lactobacilli successfully eradicates Pseudomonas aeruginosa biofilms and promotes wound healing in chronic wounds Li, Zhihao; Zhang, Sixuan; Zuber, Flavia; Altenried, Stefanie; Jaklenec, Ana; Langer, Robert; Ren, Qun Chronic wounds are difficult to treat due to the presence of biofilm which prevents wound healing. Pseudomonas aeruginosa is one of the most common pathogens found in chronic wounds and conventional treatment strategies have been ineffective in the eradication of its biofilm, without harming the surrounding healthy tissue at the same time. Here, we introduced an innovative approach applying the probiotic product Bio-K+ (containing three lactobacilli) topically as an antimicrobial and antibiofilm agent. We identified lactic acid as the main active component. While antibiotics and antiseptics such as silver-ions only demonstrated limited efficacy, Bio-K+ was able to completely eradicate mature P. aeruginosa biofilms established in an in-vitro and ex-vivo human skin model. Furthermore, it demonstrated biocompatibility in the co-culture with human dermal fibroblasts and accelerated the migration of fibroblasts in a cell migration assay promoting wound healing. To enhance clinical practicability, we introduced Bio-K+ into the hydrocolloid dressing Aquacel, achieving sustained release of lactic acid and biofilm eradication. This new treatment approach applying probiotics could represent a major improvement in the management of chronic wounds and can be extended in treating other biofilm-associated infections.

Combinatorial development of nebulized mRNA delivery formulations for the lungs

Mon, 20 Nov 2023 00:00:00 GMT

Combinatorial development of nebulized mRNA delivery formulations for the lungs Jiang, Allen Y; Witten, Jacob; Raji, Idris O; Eweje, Feyisayo; MacIsaac, Corina; Meng, Sabrina; Oladimeji, Favour A; Hu, Yizong; Manan, Rajith S; Langer, Robert; Anderson, Daniel G Inhaled delivery of mRNA has the potential to treat a wide variety of diseases. However, nebulized mRNA lipid nanoparticles (LNPs) face several unique challenges including stability during nebulization and penetration through both cellular and extracellular barriers. Here we develop a combinatorial approach addressing these barriers. First, we observe that LNP formulations can be stabilized to resist nebulization-induced aggregation by altering the nebulization buffer to increase the LNP charge during nebulization, and by the addition of a branched polymeric excipient. Next, we synthesize a combinatorial library of ionizable, degradable lipids using reductive amination, and evaluate their delivery potential using fully differentiated air–liquid interface cultured primary lung epithelial cells. The final combination of ionizable lipid, charge-stabilized formulation and stability-enhancing excipient yields a significant improvement in lung mRNA delivery over current state-of-the-art LNPs and polymeric nanoparticles.

Nanoparticle‐Mediated Delivery of Anti‐PU.1 siRNA via Localized Intracisternal Administration Reduces Neuroinflammation

Thu, 22 Feb 2024 00:00:00 GMT

Nanoparticle‐Mediated Delivery of Anti‐PU.1 siRNA via Localized Intracisternal Administration Reduces Neuroinflammation Ralvenius, William T; Andresen, Jason L; Huston, Margaret M; Penney, Jay; Bonner, Julia Maeve; Fenton, Owen S; Langer, Robert; Tsai, Li‐Huei Neuroinflammation is a hallmark of neurodegenerative disorders including Alzheimer's disease (AD). Microglia, the brain's immune cells, express many of the AD‐risk loci identified in genome wide association studies and present a promising target for anti‐inflammatory RNA therapeutics but are difficult to transfect with current methods. Here, several lipid nanoparticle (LNP) formulations are examined, and a lead candidate that supports efficient RNA delivery in cultures of human stem cell‐derived microglia‐like cells (iMGLs) and animal models of neuroinflammation is identified. The lead microglia LNP (MG‐LNP) formulation shows minimal toxicity and improves delivery efficiency to inflammatory iMGLs, suggesting a preference for delivery into activated microglia. Intraperitoneal injection of the MG‐LNP formulation generates widespread expression of the delivered reporter construct in all organs, whereas local intracisternal injection directly into the cerebrospinal fluid leads to preferential expression in the brain. It is shown that LNP‐mediated delivery of siRNA targeting the PU.1 transcription factor, a known AD‐risk locus, successfully reduces PU.1 levels in iMGLs and reduces neuroinflammation in mice injected with LPS and in CK‐p25 mice that mimic the chronic neuroinflammation seen in AD patients. The LNP formulation represents an effective RNA delivery vehicle when applied intrathecally and can be broadly utilized to test potential neuroinflammation‐directed gene therapies.

CRISPR–Cas9 delivery strategies for the modulation of immune and non-immune cells

Wed, 16 Oct 2024 00:00:00 GMT

CRISPR–Cas9 delivery strategies for the modulation of immune and non-immune cells Alsaiari, Shahad K; Eshaghi, Behnaz; Du, Bujie; Kanelli, Maria; Li, Gary; Wu, Xunhui; Zhang, Linzixuan; Chaddah, Mehr; Lau, Alicia; Yang, Xin; Langer, Robert; Jaklenec, Ana CRISPR–Cas9 genome editing technology is a promising tool for genetically engineering immune cells and modulating immune systems. Although ex vivo genome editing of immune cells has reached clinical trials, in vivo application is still restricted by the instability and inefficient delivery of CRISPR–Cas9 components to immune cells through circulation. In this Review, we summarize ex vivo and in vivo strategies to deliver CRISPR–Cas9 components to both non-immune and immune cells. We review the progress made in non-immune cells because it offers insights that can be applied to advancing research in immune cells. We also discuss principles and challenges of immune system modulation using CRISPR–Cas9 genome editing technology.

Degradable poly(β-amino ester) microparticles for cleansing products and food fortification

Mon, 01 Jan 2024 00:00:00 GMT

Degradable poly(β-amino ester) microparticles for cleansing products and food fortification Zhang, Linzixuan; Xiao, Ruiqing; Jin, Tianyi; Pan, Xinyan; Fransen, Katharina A; Alsaiari, Shahad K; Lau, Alicia; He, Ruizhe; Han, Jooli; Pedretti, Benjamin J; Yeo, Jing Ying; Yang, Xin; Olsen, Bradley D; Alexander-Katz, Alfredo; Smith, Zachary P; Langer, Robert; Jaklenec, Ana Microplastic pollution is a pressing global crisis caused by the extensive use of nondegradable microplastic materials in daily activities. One effective approach to mitigate this issue is to replace nondegradable plastics with degradable materials that have properties amendable for targeted applications. Here we present the development of a degradable microparticle (MP) platform based on a poly(β-amino ester) (PAE) that degrades into sugar and amino acid derivatives. This PAE MP platform showed functional replacement of nondegradable microplastics used in cleansing products and food fortification. In cleansing products, PAE MPs effectively enhanced the cleansing efficiency of a representative rinse-off product and showed effective removal of potentially toxic elements, as an alternative of traditional nondegradable microbeads. In food fortification, PAE MPs provided robust protection for multiple essential vitamins and minerals against extensive cooking and storage conditions with rapid nutrient release in a simulated human digestion system. Collectively, these PAE MPs present a potential platform to replace microplastic usage on a global scale in many applications.

Leveraging next-generation materials for cancer neuroscience therapies in the central nervous system

Mon, 22 Apr 2024 00:00:00 GMT

Leveraging next-generation materials for cancer neuroscience therapies in the central nervous system Bernstock, Joshua D; Johnston, Benjamin R; Friedman, Gregory K; Chiocca, EA; Langer, Robert; Srinivasan, Shriya S Interdisciplinary strategies bridging oncology, neuroscience, bioelectronics and materials science will facilitate the development of next-generation therapies and devices for cancers of the central nervous system.

On‐Patient Temporary Medical Record for Accurate, Time‐Sensitive Information at the Point of Care

Thu, 18 Apr 2024 00:00:00 GMT

On‐Patient Temporary Medical Record for Accurate, Time‐Sensitive Information at the Point of Care Collins, Joe; Han, Jooli; Sarmadi, Morteza; Allison‐Logan, Stephanie; Straeten, Aurelien vander; Perkinson, Collin F; Acolaste, Sarah; Kanelli, Maria; Daristotle, John; Karchin, Ari; Henderson, Mitchell; Cruz, Mache; Artzi, Dolev; Alsaiari, Shahad K; Zhang, Linzixuan; Levy, Lauren; Wood, Lowell; Jing, Lihong; McHugh, Kevin J; Bawendi, Moungi G; Langer, Robert; Jaklenec, Ana Accurate medical recordkeeping is important for personal and public health. Conventional forms of on‐patient medical information, such as medical alert bracelets or finger‐markings, may compromise patient privacy because they are readily visible to other people. Here, the development of an invisible, temporary, and easily deployable on‐patient medical recordkeeping system is reported. Information is stored in unique patterns of spatially distributed near‐infrared (NIR) fluorescent quantum dots (QDs), which are delivered to the skin using dissolvable microneedle arrays. The patterns are invisible to the naked eye but detectable with an infrared camera, which can extract information with >98% accuracy using automated pattern recognition software. By encapsulating NIR QDs in an FDA‐approved biodegradable polymer, biodegradation rates can be tuned so that the encoded medical information can be conveyed in both a spatial and temporal manner, with some components fading within 100 days and others persisting for 6 months. This may be particularly useful for administering a series of vaccinations or treatments by indicating if enough time has passed for the patient to receive the next dose. Importantly, this system contains no personal information, does not require connection to a centralized database, and is not visible to the naked eye, ensuring patient privacy.

Evaluation of optimally windowed chirp signals in industrial rheological measurements: method development and data processing

Fri, 15 Aug 2025 00:00:00 GMT

Evaluation of optimally windowed chirp signals in industrial rheological measurements: method development and data processing Perego, Alessandro; Vadillo, Damien C.; Mills, Matthew J. L.; Das, Mohua; McKinley FRS, Gareth H. The optimally windowed chirp (OWCh) methodology offers an alternative to traditional discrete frequency sweeps, acquiring complete rheological spectra in seconds while preserving data density and accuracy. For thermorheologically simple materials, OWCh accelerates data collection, enabling rapid creation of time–temperature superposition (tTS) master curves, potentially saving hours of instrument time. For mutating materials, such as those undergoing curing, OWCh facilitates detailed rheological characterization of viscoelastic properties throughout these transition events. We implemented OWCh within an industrial analytical research framework using commercially available rheometers. This integration is enhanced by two custom Python packages, piblin and hermes-rheo, which streamline and automate analysis of rheological datasets. For thermorheologically simple materials, this framework reduces tTS master curve data collection time by 40% while increasing data density by an order of magnitude. For mutating materials, we leverage the mutation number to design OWCh waveforms, effectively probing the characteristic timescale of fast thermomechanical transitions during curing experiments.

Exponential Speedups for Quantum Walks in Random Hierarchical Graphs

Fri, 01 Aug 2025 00:00:00 GMT

Exponential Speedups for Quantum Walks in Random Hierarchical Graphs Balasubramanian, Shankar; Li, Tongyang; Harrow, Aram W. There are few known exponential speedups for quantum algorithms and these tend to fall into even fewer families. One speedup that has mostly resisted generalization is the use of quantum walks to traverse the welded-tree graph, due to Childs, Cleve, Deotto, Farhi, Gutmann, and Spielman. We show how to generalize this to a large class of hierarchical graphs in which the vertices are grouped into “supervertices” which are arranged according to a d-dimensional lattice. Supervertices can have different sizes, and edges between supervertices correspond to random connections between their constituent vertices. The hitting times of quantum walks on these graphs are related to the localization properties of zero modes in certain disordered tight binding Hamiltonians. The speedups range from superpolynomial to exponential, depending on the underlying dimension and the random graph model. We also provide concrete realizations of these hierarchical graphs, and introduce a general method for constructing graphs with efficient quantum traversal times using graph sparsification.

Mean robust optimization

Thu, 28 Nov 2024 00:00:00 GMT

Mean robust optimization Wang, Irina; Becker, Cole; Van Parys, Bart; Stellato, Bartolomeo Robust optimization is a tractable and expressive technique for decision-making under uncertainty, but it can lead to overly conservative decisions when pessimistic assumptions are made on the uncertain parameters. Wasserstein distributionally robust optimization can reduce conservatism by being data-driven, but it often leads to very large problems with prohibitive solution times. We introduce mean robust optimization, a general framework that combines the best of both worlds by providing a trade-off between computational effort and conservatism. We propose uncertainty sets constructed based on clustered data rather than on observed data points directly thereby significantly reducing problem size. By varying the number of clusters, our method bridges between robust and Wasserstein distributionally robust optimization. We show finite-sample performance guarantees and explicitly control the potential additional pessimism introduced by any clustering procedure. In addition, we prove conditions for which, when the uncertainty enters linearly in the constraints, clustering does not affect the optimal solution. We illustrate the efficiency and performance preservation of our method on several numerical examples, obtaining multiple orders of magnitude speedups in solution time with little-to-no effect on the solution quality.

Forced Gas Convection for Uniform Freezing of Lyophilization Vials

Tue, 29 Jul 2025 00:00:00 GMT

Forced Gas Convection for Uniform Freezing of Lyophilization Vials Burcat, Steven J.; Kadambi, Rohan P.; Stratta, Lorenzo; Braatz, Richard D.; Pisano, Roberto; Slocum, Alexander H.; Trout, Bernhardt L. Purpose Conventional shelf-freezing in pharmaceutical lyophilization suffers from batch variation and is potentially incompatible with emerging continuous lyophilization systems. This work presents a forced gas convective freezing chamber for suspended vials in cross-flow to improve the quality of the freezing process and meet the continuous lyophilization needs. Methods First, computational fluid dynamics simulations were performed to determine key process parameters. Then, physical chambers were built to meet these requirements. Sets of twenty 10R vials containing 3 mL of aqueous solution were frozen to characterize the per-vial heat transfer. Additionally, a novel nucleation technique was investigated where conditioned vials were exposed to an impulse of < - 30 ∘ C gas. Finally, frozen vials were completely dried in 12 h in an attached vacuum chamber. Results The chambers conditioned vials from 25 ∘ C to −1 ∘ C in under 20 min, with final vial temperatures varying by less than 0.5 ∘ C. The impulse technique induced nucleation in all vials within 30 s without significantly cooling them. After nucleation, the system accessed slow (0.05 g/min) and rapid (1.0 g/min) solidification rates, as well as post-solidification procedures including typical ramp and hold protocols. Dried vials had residual moisture below 2.5 wt% and showed no signs of collapse. Conclusions This freezing chamber was demonstrated to track gas temperature setpoints as low as −50 ∘ C within ±1 ∘ C and induce nucleation in all vials virtually simultaneously, enabling excellent control of the freezing process. The chamber’s cooling via forced convection and its available front and back faces make it compatible with integration into a continuous lyophilization system.

EMT-ciliary signaling in quasi-mesenchymal-stem-like cells drives therapeutic resistance and is a druggable vulnerability in triple-negative breast cancer

Tue, 26 Aug 2025 00:00:00 GMT

EMT-ciliary signaling in quasi-mesenchymal-stem-like cells drives therapeutic resistance and is a druggable vulnerability in triple-negative breast cancer Tessier, Camille E.; Derrien, Jennifer; Dupuy, Aurore M. M.; Pelé, Thomas; Moquet, Martin; Roul, Julie; Douillard, Elise; El Harrif, Camille; Pinson, Xavier; Le Gallo, Matthieu; Godey, Florence; Tas, Patrick; Viel, Roselyne; Grasset, Eloïse Cancer therapeutic resistance is mediated, in part, by phenotypic heterogeneity and the plasticity of tumor cells, the latter being enabled by epithelial–mesenchymal transition (EMT). However, EMT in human cancer therapeutic response remains poorly understood. We developed patient-derived organoids (PDOs) from human triple-negative breast cancer (TNBC) and investigated their response to chemotherapy. We found that chemotherapy treatment kills the bulk of tumor cells in PDOs, but there is selective survival of malignant cells that had activated an EMT program, entered a quasi-mesenchymal, stem cell-like state and display primary cilia. We developed a family of small-molecule inhibitors of ciliogenesis and show that treatment with these inhibitors, or genetic ablation of primary cilia, is sufficient to suppress this chemoresistance via NFκB-induced cell death. We conclude that an EMT–ciliary signaling axis induces chemoresistance in quasi-mesenchymal ciliated stem-like cells to help tumors evade chemotherapy and represents a druggable vulnerability in human TNBC.

Pre-Clinical Models of Heart Failure with Preserved Ejection Fraction: Advancing Knowledge for Device Based Therapies

Mon, 25 Aug 2025 00:00:00 GMT

Pre-Clinical Models of Heart Failure with Preserved Ejection Fraction: Advancing Knowledge for Device Based Therapies Langer, Nina; Escher, Andreas; Ozturk, Caglar; Stephens, Andrew F.; Roche, Ellen T.; Granegger, Marcus; Kaye, David M.; Gregory, Shaun D. Heart failure with preserved ejection fraction (HFpEF) is a growing health problem worldwide, accounting for half of all heart failure cases. HFpEF patients present with diverse underlying causes and symptoms, making diagnosis and treatment challenging. Current pharmacological therapies are inadequate, while approved device-based therapies have shown limited success due to patient heterogeneity. This underscores the need for improved pre-clinical models, critical for guiding the design and development of effective therapeutic devices. This paper presents an overview of current pre-clinical HFpEF models, including in-silico, in-vitro, ex-vivo, and in-vivo approaches, aimed at advancing the understanding of HFpEF physiology and the development of device-based therapies. We examined each model's ability to replicate key HFpEF characteristics, discuss their respective strengths and limitations, and highlight their role in supporting the creation of clinically relevant solutions. Additionally, the potential of emerging advancements is explored.

A new approach to plurals-of-politeness and their number agreement

Mon, 25 Aug 2025 00:00:00 GMT

A new approach to plurals-of-politeness and their number agreement Kaur, Gurmeet; Sinha, Yash Plural DPs, which indicate politeness or honorification towards a singular referent, have received significant attention in the literature. Unlike regular plurals that always trigger plural agreement, these DPs, which we call plurals-of-politeness/PoPs, can trigger singular agreement on some probes in some languages. Moreover, the distribution of singular agreement is subject to certain constraints. Expanding the class of PoPs to include not only pronominals but also nominals, which are crosslinguistically rarer and have received relatively less attention, this paper offers a new analysis of agreement with PoPs. We propose a structure of PoPs, in which the pl feature in a PoP is embedded further inside the DP than the pl feature in a regular plural. The core idea is that a probe that can access the pl feature in a regular plural can sometimes fail to do so in a PoP, resulting in singular agreement. This analysis can derive all the constraints on singular agreement with PoPs, which existing accounts of agreement with PoPs are unable to do. Additionally, by examining nominal and pronominal PoPs together, we provide the first unified account of DP-internal and external agreement with PoPs.

Gallium and Indium Selective Sulfidation and Vapor Phase Transport from e-Waste Feedstocks

Mon, 25 Aug 2025 00:00:00 GMT

Gallium and Indium Selective Sulfidation and Vapor Phase Transport from e-Waste Feedstocks Benderly-Kremen, Ethan; Daehn, Katrin; Allanore, Antoine Gallium (Ga) and indium (In) share similarities in their chemical behavior, their dilute presence in waste electronics (e-waste), and recycling rates close to 0% from such streams. Designing processes to extract gallium from LED chips and indium from LCD screens simultaneously reveals the potential and necessary distinctions for a flexible process based on elemental sulfur reactivity, which can be applied to both feedstocks. Whereas Ga- and In-compounds found in e-waste (gallium nitride, GaN; indium tin oxide, ‘ITO’) are recalcitrant to dissolution in aqueous feedstocks, the reaction with sulfur gas to form volatile sulfides may support their selective extraction from prepared e-waste. Process conditions for selective sulfidation are herein informed from thermodynamics and demonstrated experimentally. Vapor phase transport of the volatile sulfides is a powerful means to collect and enrich gallium and indium. Practical implementation likely calls for physical separation approaches to disassemble e-waste, remove excess material (epoxy, glass, metallic leads, and housing) from LED chips, and expose the ITO layer within LCD screens.

Nonlinear conjugate gradient methods: worst-case convergence rates via computer-assisted analyses

Thu, 22 Aug 2024 00:00:00 GMT

Nonlinear conjugate gradient methods: worst-case convergence rates via computer-assisted analyses Das Gupta, Shuvomoy; Freund, Robert M.; Sun, Xu A.; Taylor, Adrien We propose a computer-assisted approach to the analysis of the worst-case convergence of nonlinear conjugate gradient methods (NCGMs). Those methods are known for their generally good empirical performances for large-scale optimization, while having relatively incomplete analyses. Using our computer-assisted approach, we establish novel complexity bounds for the Polak-Ribière-Polyak (PRP) and the Fletcher-Reeves (FR) NCGMs for smooth strongly convex minimization. In particular, we construct mathematical proofs that establish the first non-asymptotic convergence bound for FR (which is historically the first developed NCGM), and a much improved non-asymptotic convergence bound for PRP. Additionally, we provide simple adversarial examples on which these methods do not perform better than gradient descent with exact line search, leaving very little room for improvements on the same class of problems.

A multi-modal network equilibrium model considering captive travelers and mode correlation

Mon, 08 Apr 2024 00:00:00 GMT

A multi-modal network equilibrium model considering captive travelers and mode correlation Wang, Guangchao; Song, Defeng; Qi, Hang; Zhou, Juanhua; He, Zhengbing In making daily commuting trips, a part of travelers, which are called captive travelers, rely on one transport mode due to a lack of access or affordability to other transport modes. To account for the effect of such captive travelers on network equilibrium performances, this paper proposes a multi-modal network equilibrium (MMNE) model that accounts for the captive travelers and the correlations between modes and between routes. First, a hybrid mode choice model is developed by integrating the dogit and nested logit (NL) models. The hybrid dogit–NL (DNL) model has smaller direct and cross elasticity than the NL model, it alleviates the property of irrelevant from independent alternatives and takes the dogit and NL modal splits as bounds. Second, the path-size logit (PSL) model is adopted for predicting travelers’ route choices with overlapping routes. The DNL–PSL MMNE model is formulated as a mathematical programming problem that admits an equivalent and unique solution. Then, a partial linearization algorithm with the Barzilai–Borwein (BB) step sizes is developed. The numerical results reveal that captive travelers lead to lower sensitivity toward transport policies and may cause higher network total travel time; while the perception of mode similarity may impair the overall attractiveness of modes with a high degree of similarity. The observations indicate that to promote green transportation, policy efforts should be made to make use of or adjust the captivity structure and produce diversified perceptions of and preferences for different green transport modes. The BB step sizes are suggested for low travel demand cases when solving the combined travel choice problems. Further, extensions of the DNL model with bundle captivities are discussed. The results of the paper help improve the network equilibrium prediction and support transport policymaking.

Addressing Grid Convergence and Log-Layer Mismatch in Wall Modeled Large Eddy Simulations of Geophysical Flows Over Rough Surfaces and Canopies

Thu, 28 Aug 2025 00:00:00 GMT

Addressing Grid Convergence and Log-Layer Mismatch in Wall Modeled Large Eddy Simulations of Geophysical Flows Over Rough Surfaces and Canopies Shin, E. Y.; Yang, X. I. A.; Howland, M. F. Wall modeled large eddy simulations are the primary scale-resolving method used to investigate boundary layer meteorology. Wall models are used to parameterize momentum, heat, and other exchanges at the surface to achieve computationally efficient predictions given the very high Reynolds numbers of planetary boundary layers and the importance of small-scales near the surface. However, wall modeled large eddy simulations can be contaminated by log-layer mismatch, where the prediction of wall shear stress (friction velocity) deviates from the intended value. It is not clear how this log-layer mismatch in boundary layers depends on parameters that represent unresolved roughness elements and on the computational setup. This study elucidates how log-layer mismatch depends on the roughness length, displacement distance, matching velocity filtering strength, and vertical grid resolution using 135 channel flow, 24 conventionally neutral boundary layer, and 12 truly neutral boundary layer wall modeled large eddy simulations. The results demonstrate two sources of log-layer mismatch. First, a spurious correlation between the friction velocity and the fluctuation of the matching velocity causes log-layer mismatch that increases with roughness length, displacement distance, and increasing grid resolution. This log-layer mismatch can be eliminated by filtering the matching velocity, but the filter timescale necessary to eliminate the error depends on the roughness parameters and grid resolution. Second, an additional source of log-layer mismatch is identified, depending on the displacement distance. This mechanism of log-layer mismatch is not alleviated by filtering the matching velocity. An analytical model of this log-layer mismatch mechanism is derived and validated against the large eddy simulations. The results demonstrate that the analytical model is able to predict the magnitude of this log layer mismatch based on a priori information about the simulation to within the uncertainty of the von Kármán constant.

Effective last-mile delivery using reinforcement learning and social media-based traffic prediction in underdeveloped megacities

Sun, 17 Aug 2025 00:00:00 GMT

Effective last-mile delivery using reinforcement learning and social media-based traffic prediction in underdeveloped megacities Rabelo, Luis; Rincón-Guio, Cristian; Laynes, Valeria; Gutierrez-Franco, Edgar; Bhat, Vasanth; Zamora-Aguas, Juan; Elkamel, Marwen This paper presents a framework for effective last-mile delivery in underdeveloped megacities by combining social media, machine learning, and reinforcement learning. Leveraging a Graph Convolutional Networks and a Long Short-Term Memory model for traffic prediction, the framework incorporates multimodal data sources, such as social media sentiment analysis, to provide real-time insights into traffic dynamics. By framing the delivery problem as a Markov Decision Process, reinforcement learning dynamically adapts routing decisions to obtain delivery efficiency, reduce delays, and minimize fuel consumption. A case study in Bogotá demonstrates the framework’s effectiveness in mitigating urban traffic challenges. This work highlights the transformative potential of integrating adaptive learning technologies to address urban logistics’ environmental, economic, and operational complexities. Future research explores advanced methodologies, including multi-agent systems and transformer-based architectures, to further enhance scalability and adaptability in dynamic urban environments.

Spatiotemporally constrained 3D reconstruction from biplanar digital subtraction angiography

Sun, 01 Jun 2025 00:00:00 GMT

Spatiotemporally constrained 3D reconstruction from biplanar digital subtraction angiography Frisken, Sarah; Gopalakrishnan, Vivek; Chlorogiannis, David D.; Haouchine, Nazim; Cafaro, Alexandre; Golby, Alexandra J.; Wells III, William M.; Du, Rose Purpose Our goal is to reconstruct 3D cerebral vessels from two 2D digital subtraction angiography (DSA) images acquired using a biplane scanner. This could provide intraoperative 3D imaging with 2–5 × spatial and 20 × temporal resolution of 3D magnetic resonance angiography, computed tomography angiography (CTA), or rotational DSA. Because many interventional radiology suites have biplane scanners, our method could be easily integrated into clinical workflows. Methods We present a constrained 3D reconstruction method that utilizes vessel centerlines, radii, and the flow of contrast agent through vessels from DSA. The reconstructed volume samples ‘vesselness’ at each voxel, i.e., its probability of containing a vessel. We present evaluation metrics which we used to optimize reconstruction parameters and evaluate our method on synthetic data. We provide preliminary results on clinical data. To handle clinical data, we developed a software tool for extracting vessel centerlines, radii, and contrast arrival times from clinical DSA. We provide an automated method for registering DSA to CTA which allows us to compare reconstructed vessels with vessels extracted from CTA. Result Our method reduced reconstruction artifacts in vesselness volumes for both synthetic and clinical data. In synthetic DSA, where 3D ground-truth vessel centerlines are available, our constrained reconstruction method improved accuracy, selectivity, and Dice scores with two views compared to existing sparse reconstruction methods with up to 16 views. Conclusion Incorporating additional constraints into 3D reconstruction can successfully reduce artifacts introduced when a complex 3D structure like the brain vasculature is reconstructed from a small number of 2D views.

Enhancing the Functionality of Immunoisolated Human SC‐βeta Cell Clusters through Prior Resizing

Thu, 11 Jan 2024 00:00:00 GMT

Enhancing the Functionality of Immunoisolated Human SC‐βeta Cell Clusters through Prior Resizing Bochenek, Matthew A; Walters, Ben; Zhang, Jingping; Fenton, Owen S; Facklam, Amanda; Kroneková, Zuzana; Pelach, Michal; Engquist, Elise N; Leite, Nayara C; Morgart, Alex; Lacík, Igor; Langer, Robert; Anderson, Daniel G The transplantation of immunoisolated stem cell derived beta cell clusters (SC‐β) has the potential to restore physiological glycemic control in patients with type I diabetes. This strategy is attractive as it uses a renewable β‐cell source without the need for systemic immune suppression. SC‐β cells have been shown to reverse diabetes in immune compromised mice when transplanted as ≈300 µm diameter clusters into sites where they can become revascularized. However, immunoisolated SC‐β clusters are not directly revascularized and rely on slower diffusion of nutrients through a membrane. It is hypothesized that smaller SC‐β cell clusters (≈150 µm diameter), more similar to islets, will perform better within immunoisolation devices due to enhanced mass transport. To test this, SC‐β cells are resized into small clusters, encapsulated in alginate spheres, and coated with a biocompatible A10 polycation coating that resists fibrosis. After transplantation into diabetic immune competent C57BL/6 mice, the “resized” SC‐β cells plus the A10 biocompatible polycation coating induced long‐term euglycemia in the mice (6 months). After retrieval, the resized A10 SC‐β cells exhibited the least amount of fibrosis and enhanced markers of β‐cell maturation. The utilization of small SC‐β cell clusters within immunoprotection devices may improve clinical translation in the future.

Drinkable in situ-forming tough hydrogels for gastrointestinal therapeutics

Tue, 27 Feb 2024 00:00:00 GMT

Drinkable in situ-forming tough hydrogels for gastrointestinal therapeutics Liu, Gary W; Pickett, Matthew J; Kuosmanen, Johannes LP; Ishida, Keiko; Madani, Wiam AM; White, Georgia N; Jenkins, Joshua; Park, Sanghyun; Feig, Vivian R; Jimenez, Miguel; Karavasili, Christina; Lal, Nikhil B; Murphy, Matt; Lopes, Aaron; Morimoto, Joshua; Fitzgerald, Nina; Cheah, Jaime H; Soule, Christian K; Fabian, Niora; Hayward, Alison; Langer, Robert; Traverso, Giovanni Pills are a cornerstone of medicine but can be challenging to swallow. While liquid formulations are easier to ingest, they lack the capacity to localize therapeutics with excipients nor act as controlled release devices. Here we describe drug formulations based on liquid in situ-forming tough (LIFT) hydrogels that bridge the advantages of solid and liquid dosage forms. LIFT hydrogels form directly in the stomach through sequential ingestion of a crosslinker solution of calcium and dithiol crosslinkers, followed by a drug-containing polymer solution of alginate and four-arm poly(ethylene glycol)-maleimide. We show that LIFT hydrogels robustly form in the stomachs of live rats and pigs, and are mechanically tough, biocompatible and safely cleared after 24 h. LIFT hydrogels deliver a total drug dose comparable to unencapsulated drug in a controlled manner, and protect encapsulated therapeutic enzymes and bacteria from gastric acid-mediated deactivation. Overall, LIFT hydrogels may expand access to advanced therapeutics for patients with difficulty swallowing.

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Mon, 23 Jun 2025 00:00:00 GMT

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials Fu, Chu‐Liang; Cheng, Mouyang; Hung, Nguyen Tuan; Rha, Eunbi; Chen, Zhantao; Okabe, Ryotaro; Carrizales, Denisse Córdova; Mandal, Manasi; Cheng, Yongqiang; Li, Mingda Thermoelectric materials oﬀer a promising pathway to directly convertwaste heat to electricity. However, achieving high performance remainschallenging due to intrinsic trade-oﬀs between electrical conductivity, theSeebeck coeﬃcient, and thermal conductivity, which are further complicatedby the presence of defects. This review explores how artiﬁcial intelligence (AI)and machine learning (ML) are transforming thermoelectric materials design.Advanced ML approaches including deep neural networks, graph-basedmodels, and transformer architectures, integrated with high-throughputsimulations and growing databases, eﬀectively capture structure-propertyrelationships in a complex multiscale defect space and overcome the “curse ofdimensionality”. This review discusses AI-enhanced defect engineering strate-gies such as composition optimization, entropy and dislocation engineering,and grain boundary design, along with emerging inverse design techniquesfor generating materials with targeted properties. Finally, it outlines futureopportunities in novel physics mechanisms and sustainability, highlightingthe critical role of AI in accelerating the discovery of thermoelectric materials.

Intracellular proteomics and extracellular vesiculomics as a metric of disease recapitulation in 3D-bioprinted aortic valve arrays

Wed, 28 Feb 2024 00:00:00 GMT

Intracellular proteomics and extracellular vesiculomics as a metric of disease recapitulation in 3D-bioprinted aortic valve arrays Clift, Cassandra L; Blaser, Mark C; Gerrits, Willem; Turner, Mandy E; Sonawane, Abhijeet; Pham, Tan; Andresen, Jason L; Fenton, Owen S; Grolman, Joshua M; Campedelli, Alesandra; Buffolo, Fabrizio; Schoen, Frederick J; Hjortnaes, Jesper; Muehlschlegel, Jochen D; Mooney, David J; Aikawa, Masanori; Singh, Sasha A; Langer, Robert; Aikawa, Elena In calcific aortic valve disease (CAVD), mechanosensitive valvular cells respond to fibrosis- and calcification-induced tissue stiffening, further driving pathophysiology. No pharmacotherapeutics are available to treat CAVD because of the paucity of (i) appropriate experimental models that recapitulate this complex environment and (ii) benchmarking novel engineered aortic valve (AV)–model performance. We established a biomaterial-based CAVD model mimicking the biomechanics of the human AV disease-prone fibrosa layer, three-dimensional (3D)–bioprinted into 96-well arrays. Liquid chromatography–tandem mass spectrometry analyses probed the cellular proteome and vesiculome to compare the 3D-bioprinted model versus traditional 2D monoculture, against human CAVD tissue. The 3D-bioprinted model highly recapitulated the CAVD cellular proteome (94% versus 70% of 2D proteins). Integration of cellular and vesicular datasets identified known and unknown proteins ubiquitous to AV calcification. This study explores how 2D versus 3D-bioengineered systems recapitulate unique aspects of human disease, positions multiomics as a technique for the evaluation of high throughput–based bioengineered model systems, and potentiates future drug discovery.

Dual‐Wavelength Vat Photopolymerization With Dissolvable, Recyclable Support Structures

Mon, 02 Jun 2025 00:00:00 GMT

Dual‐Wavelength Vat Photopolymerization With Dissolvable, Recyclable Support Structures Diaco, Nicholas S; Thrasher, Carl J; Hughes, Max M; Zhou, Kevin A; Durso, Michael N; Yap, Saechow; Macfarlane, Robert J; Hart, A John Vat photopolymerization (VP) additive manufacturing (AM) is valued for itsspeed, precision, and material versatility. However, its requirement forsupport structures limits printable geometries, complicates post-processing,and generates non-recyclable waste when typical thermoset resins are used.Here, a wavelength-selective resin system for VP that enables single-vat,multi-material printing with dissolvable supports is introduced. Exposure tovisible light produces a rigid, dissolvable thermoplastic, while UV light formsa crosslinked thermoset resistant to dissolution. This process, termedselective solubility vat photopolymerization (SSVP), eliminates the geometricconstraints imposed by conventional VP methods, facilitating the creation ofcomplex objects with supports that are removable using green and food-safesolvents such as D-limonene and ethyl acetate, as well as mineral oil.Post-print heat treatment tunes crosslink density and solubility. Dissolvedsupports can be recycled into fresh resin and reprinted without mechanicalproperty loss, oﬀering a practical, scalable route to reducing waste.Additionally, SSVP provides spatial control of dissolution kinetics, enablingprogrammable 3D dissolution proﬁles. By enabling the integration ofdissolvable and insoluble regions in a single print, SSVP sets the stage forfully automated and more sustainable AM workﬂows.

Recent advances in nanoparticulate RNA delivery systems

Mon, 04 Mar 2024 00:00:00 GMT

Recent advances in nanoparticulate RNA delivery systems Witten, Jacob; Hu, Yizong; Langer, Robert; Anderson, Daniel G Nanoparticle-based RNA delivery has shown great progress in recent years with the approval of two mRNA vaccines for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and a liver-targeted siRNA therapy. Here, we discuss the preclinical and clinical advancement of new generations of RNA delivery therapies along multiple axes. Improvements in cargo design such as RNA circularization and data-driven untranslated region optimization can drive better mRNA expression. New materials discovery research has driven improved delivery to extrahepatic targets such as the lung and splenic immune cells, which could lead to pulmonary gene therapy and better cancer vaccines, respectively. Other organs and even specific cell types can be targeted for delivery via conjugation of small molecule ligands, antibodies, or peptides to RNA delivery nanoparticles. Moreover, the immune response to any RNA delivery nanoparticle plays a crucial role in determining efficacy. Targeting increased immunogenicity without induction of reactogenic side effects is crucial for vaccines, while minimization of immune response is important for gene therapies. New developments have addressed each of these priorities. Last, we discuss the range of RNA delivery clinical trials targeting diverse organs, cell types, and diseases and suggest some key advances that may play a role in the next wave of therapies.

On-patient medical record and mRNA therapeutics using intradermal microneedles

Mon, 24 Feb 2025 00:00:00 GMT

On-patient medical record and mRNA therapeutics using intradermal microneedles Han, Jooli; Kanelli, Maria; Liu, Yang; Daristotle, John L; Pardeshi, Apurva; Forster, Timothy A; Karchin, Ari; Folk, Brandon; Murmann, Lukas; Tostanoski, Lisa H; Carrasco, Sebastian E; Alsaiari, Shahad K; Wang, Erika Yan; Tran, Khanh; Zhang, Linzixuan; Eshaghi, Behnaz; Levy, Lauren; Pyon, Sydney; Sloane, Charles; Lin, Stacey Qiaohui; Lau, Alicia; Perkinson, Collin F; Bawendi, Moungi G; Barouch, Dan H; Durand, Frédo; Langer, Robert; Jaklenec, Ana Medical interventions often require timed series of doses, thus necessitating accurate medical record-keeping. In many global settings, these records are unreliable or unavailable at the point of care, leading to less effective treatments or disease prevention. Here we present an invisible-to-the-naked-eye on-patient medical record-keeping technology that accurately stores medical information in the patient skin as part of microneedles that are used for intradermal therapeutics. We optimize the microneedle design for both a reliable delivery of messenger RNA (mRNA) therapeutics and the near-infrared fluorescent microparticles that encode the on-patient medical record-keeping. Deep learning-based image processing enables encoding and decoding of the information with excellent temporal and spatial robustness. Long-term studies in a swine model demonstrate the safety, efficacy and reliability of this approach for the co-delivery of on-patient medical record-keeping and the mRNA vaccine encoding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This technology could help healthcare workers make informed decisions in circumstances where reliable record-keeping is unavailable, thus contributing to global healthcare equity.

Insights Into Summertime Surface Ozone Formation From Diurnal Variations in Formaldehyde and Nitrogen Dioxide Along a Transect Through New York City

Mon, 12 May 2025 00:00:00 GMT

Insights Into Summertime Surface Ozone Formation From Diurnal Variations in Formaldehyde and Nitrogen Dioxide Along a Transect Through New York City Tao, Madankui; Fiore, Arlene M; Karambelas, Alexandra; Miller, Paul J; Valin, Lukas C; Judd, Laura M; Tzortziou, Maria; Whitehill, Andrew; Teora, Amanda; Tian, Yuhong; Civerolo, Kevin L; Tong, Daniel; Ma, Siqi; Adamo, Susana B; Holloway, Tracey Estimating tropospheric ozone (O3) production from observations is challenging but possible given the close coupling of O3 with formaldehyde (HCHO) and nitrogen dioxide (NO2), two remotely sensed air pollutants. The previous reliance on once-daily satellite overpasses highlights the need to study diurnal changes and surface-column relationships. Using surface observations, Pandora spectrometer retrievals, and a high-resolution (1.33 km) air quality model (WRF-CMAQ), we characterize diurnal patterns of HCHO and NO2 at seven locations along an upwind-downwind pathway through New York City during June–August 2018. Diurnal patterns of limited surface HCHO measurements suggest biogenic emission influence, while a bimodal surface NO2 pattern indicates the impact of local anthropogenic nitrogen oxides emissions. Details of these patterns vary by site: an afternoon NO2 spike at New Haven (CT) indicates traffic emissions, while a delayed daily HCHO peak at Westport (CT) relative to other sites likely reflects sea breeze dynamics. Peak column concentrations generally lag surface peaks by about four hours, occurring at 9–10 a.m. for morning NO2 (from Pandora and WRF-CMAQ) and around 4 p.m. for midday HCHO (from WRF-CMAQ). TROPOMI overpass time at 1:30 p.m. misses peak column HCHO and NO2 concentrations. A box model (F0AM) constrained with site-level observations and WRF-CMAQ fields indicates 1–9 ppb hr−1 higher noontime local O3 production rates on three sets of paired high- versus mid-to-low-O3 days. F0AM sensitivity analyses on these six days suggest a predominantly transitional O3 formation regime at urban and downwind sites, differing at some sites from the NOx-saturated regime diagnosed for summertime average conditions via the weekday-weekend effect.

Seeing the Fictional

Tue, 03 Jun 2025 00:00:00 GMT

Seeing the Fictional Khoo, Justin When we see a movie or a play, do we see the fictional entities and events depicted? On the one hand, it seems incredibly natural tothink we do. For instance, it seems obvious that one thing that differentiates Smith, who watches Star Wars, from Bob, who merelyreads the novelization of Star Wars, is that Smith, but not Bob, has seen Darth Vader kill Obi-Wan Kenobi. Yet, no philosophersworking on fiction think this is literally true. And they have good reasons to be skeptical. For, if you have seen Darth Vader killObi-Wan Kenobi, then it seems to follow that Darth Vader must have killed Obi-Wan Kenobi, in which case, it follows that bothwere at one point living, flesh-and-blood, entities. But if Darth Vader is a flesh and blood being, then he must be spatiotemporallylocated, in which case, where is he? In this paper, I argue that we do in fact literally see (and hear) fictional entities when we seefilms. I do so in three stages. First, I argue against various error theories that attempt to account for the intuitions that we do seefictional entities in film. Then, I sketch a metaphysics of fictional entities, which vindicates our genuinely seeing them. Finally, Iexplore some of the interesting controversies and objections raised to this ontology of the fictional.

Why Schonland Failed in His Search for Runaway Electrons From Thunderstorms

Thu, 22 May 2025 00:00:00 GMT

Why Schonland Failed in His Search for Runaway Electrons From Thunderstorms Chilingarian, A; Williams, E; Hovsepyan, G; Mkrtchyan, H B.F.J. Schonland, advised and encouraged by C.T.R. Wilson, made two unsuccessful searches forrunaway electrons from thunderstorms in the 1930s. These findings stand in marked contrast with researchresults over the last decade and ironically set this field of research back many decades. Schonland's lack ofsuccess is traced to gamma ray attenuation in the atmosphere above Johannesburg (1,780 m MSL) and to hisrestriction to nine thunderstorms.

Advanced Oral Delivery Systems for Nutraceuticals

Wed, 11 Jun 2025 00:00:00 GMT

Advanced Oral Delivery Systems for Nutraceuticals Yang, Xin; Zhang, Linzixuan; Zheng, Zhiling; Langer, Robert; Jaklenec, Ana Oral delivery is the most preferred route for nutraceuticals due to its convenience and high patient compliance. However, bioavailability is often compromised by poor solubility, instability, and first‐pass metabolism in the gastrointestinal tract. This review examines current and emerging oral delivery platforms designed to overcome these barriers and enhance nutraceutical efficacy. Traditional carriers—proteins, lipids, and carbohydrates—highlighting their delivery mechanisms and limitations, are first explored. Advancements in material science have led to novel platforms such as biodegradable polymers, metal–organic frameworks (MOFs), metal–polyphenol networks (MPNs), and 3D printing technologies. Biodegradable polymers improve stability and enable controlled release of bioactives. MOFs offer high surface area and tunable porosity for encapsulating and protecting sensitive compounds. MPNs provide biocompatible, stimuli‐responsive systems for targeted nutrient delivery. Meanwhile, 3D printing facilitates the fabrication of personalized delivery systems with precise control over composition and release kinetics, especially when integrated with artificial intelligence (AI) for precision nutrition. By comparing traditional and next‐generation strategies, this review outlines key design principles for optimizing oral delivery systems. The transformative potential of these innovations is underscored to improve the bioavailability and therapeutic outcomes of nutraceuticals, ultimately advancing personalized and targeted nutrition solutions.

Voices of Nanomedicine: Blueprint Guidelines for Collaboration in Addressing Global Unmet Medical Needs

Fri, 10 Jan 2025 00:00:00 GMT

Voices of Nanomedicine: Blueprint Guidelines for Collaboration in Addressing Global Unmet Medical Needs Prasad, Rajendra; Ghosh, Arnab; Patel, Vinay; Peng, Berney; Mendes, Bárbara B; Win, Eaint Honey Aung; Delogu, Lucia Gemma; Wong, Joyce Y; Pischel, Kristin J; Bellare, Jayesh R; Bar-Shir, Amnon; Thakor, Avnesh S; Parak, Wolfgang J; Bhujwalla, Zaver M; Zhang, Yu Shrike; Kommineni, Nagavendra; Rotello, Vince M; Cai, Weibo; Lammers, Twan; Odom, Teri W; Padmanaban, Govindarajan; Peer, Dan; Lovell, Jonathan F; Srivastava, Rohit; Langer, Robert; Conde, João The “Voices” under this Perspective underline the importance of interdisciplinary collaboration and partnerships across several disciplines, such as medical science and technology, medicine, bioengineering, and computational approaches, in bridging the gap between research, manufacturing, and clinical applications. Effective communication is key to bridging team gaps, enhancing trust, and resolving conflicts, thereby fostering teamwork and individual growth toward shared goals. Drawing from the success of the COVID-19 vaccine development, we advocate the application of similar collaborative models in other complex health areas such as nanomedicine and biomedical engineering. The role of digital technology and big data in healthcare innovation is highlighted along with the necessity for specialized education in collaborative practices. This approach is decisive in advancing healthcare solutions, leading to improved treatment and patient outcomes.

Biological Cohesion of Sediment Bed Diminishes Net Deposition of Fine Non‐Cohesive Particles Over Bare Bed and Within Model Emergent Canopies

Mon, 12 May 2025 00:00:00 GMT

Biological Cohesion of Sediment Bed Diminishes Net Deposition of Fine Non‐Cohesive Particles Over Bare Bed and Within Model Emergent Canopies Park, Hyoungchul; Nepf, Heidi This study investigated how Extracelluar Polymetric Substances (EPS) produced bymicroorganisms influenced particle deposition to a sediment bed. The particle deposition decreased withincreasing EPS, because the EPS filled the pore spaces between individual sediment grains, reducing theporosity of the sediment bed. With decreased porosity, newly deposited particles could not settle in between thegrains of the bed, so that particles were more exposed to the flow, making resuspension easier and leading todecreased deposition. For the same level of bio‐cohesion, increasing the near‐bed turbulence diminisheddeposition. For the vegetated channel, as bio‐cohesion increased, particles were easily resuspended aroundindividual stems due to the enhanced exposure effect, expanding the regions where deposition was excluded andleading to a more heterogeneous spatial distribution of deposition. The effect of EPS was negligible for thesmallest velocity magnitude, for which all particles deposited, and for largest velocity magnitude, for whichmost particles were resuspended.

Record‐High Ozone in the Austral Mid‐Latitude Tropopause Region Driven by Dynamical and Chemical Effects of the 2019 Sudden Stratospheric Warming

Sat, 10 May 2025 00:00:00 GMT

Record‐High Ozone in the Austral Mid‐Latitude Tropopause Region Driven by Dynamical and Chemical Effects of the 2019 Sudden Stratospheric Warming Zhang, Selena; Solomon, Susan; Zhang, Jun; Kinnison, Douglas In January 2020, tropopause‐level ozone in the austral mid‐latitudes was the highest everobserved in the available Microwave Limb Sounder data record since 2004. Two extreme events preceded thisanomaly: the Australian Black Summer fires and the 2019 sudden stratospheric warming (SSW), raising thequestion of how these disruptions influenced Southern Hemisphere ozone. Here, we investigate the dynamicaland chemical contributions to the ozone anomaly using a chemistry‐climate model and satellite observations.We find that downward transport of polar ozone‐enriched air due to the SSW later spread equatorward. Suchtransport together with photochemical ozone production from emissions of wildfires (fueled by dry and hotconditions previously attributed to the SSW) increased tropopause‐level ozone by up to 30 ppb, with transport asthe dominant factor (around 80%). While chemical ozone production from wildfires is well‐recognized, ourresults highlight that SSWs can greatly influence mid‐latitude ozone through dynamical effects.

Pure Event Semantics

Wed, 28 May 2025 00:00:00 GMT

Pure Event Semantics Schwarzschild, Roger In a pure event semantics for natural language, the domain of quantification and predication is limited to events and states. I offerpure event semantic analyses of several phenomena, some of which have not been treated before in formal semantics. In the pureevent semantics sketched in the second section, nouns are state predicates, and this provides the starting point for the analyses.The phenomena involve grammatical number, the mass-count distinction, adjectival modification, count adjectives, diminutives,lexical plurals, duals, and mass gender. In the conclusion, there is a brief discussion of potential metaphysical or psychologicalramifications of doing semantics this way.

The Grice Is Right: Grice's Non‐Cooperation Problem and the Structure of Conversation

Mon, 26 May 2025 00:00:00 GMT

The Grice Is Right: Grice's Non‐Cooperation Problem and the Structure of Conversation Berstler, Sam H. P. Grice seemed to rest his theory of conversational implicature on the assumption that speakers aim to cooperatively exchangeinformation with each other. In the real world, speakers often don’t. Does one of the most influential theories in 20th-centuryphilosophy of language rest on a mistake? Yes—but not in the way that philosophers have thought. I argue that Grice shouldhave rested his theory on a different assumption: that speakers aim to appear to aim to cooperatively exchange informationwith each other. This proposal dissolves Grice’s Non-Cooperation Problem but preserves Grice’s central insights about the natureof conversational implicatures. More generally, it enables the Gricean to illuminate the structure of many non-cooperative orotherwise “non-ideal” conversations.

My Struggles and Dreams as a Chemical Engineer

Mon, 03 Mar 2025 00:00:00 GMT

My Struggles and Dreams as a Chemical Engineer Langer, Robert My career has not been straightforward. Although I am a chemical engineer, and I'm proud of that, I took a path from chemistry and engineering to one that also involved experimental biology and medicine. This was very unusual many decades ago. In so doing, I met with rejection and ridicule early in my career. However, by going down that path, I was able to make discoveries and inventions that I hope have saved and improved lives, and I've been able to train a great number of people who are going down the road I began traveling over many years ago.

An In Situ Curing, Shear‐Responsive Biomaterial Designed for Durable Embolization of Microvasculature

Tue, 11 Mar 2025 00:00:00 GMT

An In Situ Curing, Shear‐Responsive Biomaterial Designed for Durable Embolization of Microvasculature Pham, Quynh P; Groom, Jeffrey V; Sadasivan, Chander; Fiorella, David J; Madoff, David C; Guo, Lee‐Jae; Fornaciari, Michael; Guertin, Courtney; Wiltsey, Craig; Core, Lee; Merlo, Jonathan; Wustenberg, William; Virmani, Renu; Arthur, Adam S; Langer, Robert S; Whitesides, George M; Sharma, Upma Endovascular embolization is a minimally‐invasive technique whereby blood vessels supplying pathological structures are selectively occluded with various embolic agents. In many scenarios, it is desirable for the embolic to distally penetrate to the level of the microvasculature, which maximizes devascularization. Existing agents exhibit inconsistent distal penetration and have other limitations including tendency for proximal reflux, patient pain during infusion, lack of fluoroscopic radiopacity, potential for catheter adhesion, susceptibility to recanalization, and other usability challenges. NeoCast is an in situ curing, solvent‐free, non‐adhesive biomaterial composed of polydimethylsiloxane, bismuth trioxide, and fumed silica that possesses shear‐responsive properties enabling manual injectability through commercially‐available microcatheters with large and small diameter lumens. Here, embolization performance with and without flow arrest, in both arterial and venous preclinical anatomies is reported. NeoCast reproducibly achieves a rate of distal penetration with microvascular occlusion that is superior to existing agents, exhibits excellent fluoroscopic visibility, and provides durable occlusion. There is mild inflammation when NeoCast is infused into blood vessels and absence of neurotoxicity when implanted directly into brain tissue. The engineered NeoCast material is poised to become a next‐generation, liquid embolic agent for applications in which distal microvascular occlusion is desired.

A constitutive neural network for incompressible hyperelastic materials

Wed, 20 Aug 2025 00:00:00 GMT

A constitutive neural network for incompressible hyperelastic materials Lee, Sanghee; Bathe, Klaus-Jürgen We propose a B-spline-based constitutive neural network to model the mechanical behavior of incompressible isotropic materials. The theoretical foundation of this network is the Sussman-Bathe model which interpolates tension–compression test data points and recovers the strain energy function. Our neural network uses regression to self-optimize the knot configurations of the B-splines and to determine a twice differentiable curve of the material response that is closely aligned with the given data points. We address datasets displaying physically complicated behaviors. Through the patch test validation of the constitutive model and illustrative example solutions, we highlight the flexibility inherent in spline-based models and the automated approximation capabilities enabled by neural networks.

Bounds on the Ground State Energy of Quantum p-Spin Hamiltonians

Mon, 01 Sep 2025 00:00:00 GMT

Bounds on the Ground State Energy of Quantum p-Spin Hamiltonians Anschuetz, Eric R.; Gamarnik, David; Kiani, Bobak T. We consider the problem of estimating the ground state energy of quantum p-local spin glass random Hamiltonians, the quantum analogues of widely studied classical spin glass models. Our main result shows that the maximum energy achievable by product states has a well-defined limit (for even p) as n → ∞ and is E product ∗ = 2 log p in the limit of large p. This value is interpreted as the maximal energy of a much simpler so-called Random Energy Model, widely studied in the setting of classical spin glasses. The proof of the limit existing follows from an extension of Fekete’s Lemma after we demonstrate near super-additivity of the (normalized) quenched free energy. The proof of the value follows from a second moment method on the number of states achieving a given energy when restricting to an ϵ -net of product states. Furthermore, we relate the maximal energy achieved over all states to a p-dependent constant γ p , which is defined by the degree of violation of a certain asymptotic dependence ansatz over graph matchings. We show that the maximal energy achieved by all states E ∗ p in the limit of large n is at most γ p E product ∗ . We also prove using Lindeberg’s interpolation method that the limiting E ∗ p is robust with respect to the choice of the randomness and, for instance, also applies to the case of sparse random Hamiltonians. This robustness in the randomness extends to a wide range of random Hamiltonian models including SYK and random quantum max-cut.

Riemannian Adaptive Regularized Newton Methods with Hölder Continuous Hessians

Wed, 21 May 2025 00:00:00 GMT

Riemannian Adaptive Regularized Newton Methods with Hölder Continuous Hessians Zhang, Chenyu; Jiang, Rujun This paper presents strong worst-case iteration and operation complexity guarantees for Riemannian adaptive regularized Newton methods, a unified framework encompassing both Riemannian adaptive regularization (RAR) methods and Riemannian trust region (RTR) methods. We comprehensively characterize the sources of approximation in second-order manifold optimization methods: the objective function’s smoothness, retraction’s smoothness, and subproblem solver’s inexactness. Specifically, for a function with a μ -Hölder continuous Hessian, when equipped with a retraction featuring a ν -Hölder continuous differential and a θ -inexact subproblem solver, both RTR and RAR with 2 + α regularization (where α = min { μ , ν , θ } ) locate an ( ϵ , ϵ α / ( 1 + α ) ) -approximate second-order stationary point within at most O ( ϵ - ( 2 + α ) / ( 1 + α ) ) iterations and at most O ~ ( ϵ - ( 4 + 3 α ) / ( 2 ( 1 + α ) ) ) Hessian-vector products with high probability. These complexity results are novel and sharp, and reduce to an iteration complexity of O ( ϵ - 3 / 2 ) and an operation complexity of O ~ ( ϵ - 7 / 4 ) when α = 1 .

Effect of Die Bearing Geometry on Extrudability of High-Strength AA6082 Alloy with Cu

Mon, 25 Aug 2025 00:00:00 GMT

Effect of Die Bearing Geometry on Extrudability of High-Strength AA6082 Alloy with Cu Wang, Xiaoying; Khan, Muhammad S.; Wells, Mary A.; Poole, Warren J.; Parson, Nick This study investigated the impact of die bearing geometry on the surface cracking behavior, of a high strength AA6xxx alloy. Experimental and numerical methods were employed, along with differential scanning calorimetry tests to determine the material’s solidus temperature. Four different die geometries were employed in both the extrusion trial and the simulation. Extrusion trials were conducted for each die geometry over a range of extrusion speeds with the resulting surface defects being examined using SEM. The findings indicate that die bearing geometry significantly affects surface morphology and crack occurrence. Choked dies enabled crack-free extrusion at higher speeds, particularly a 12 mm choked bearing with a 1° angle, outperforming a 25 mm flat bearing and zero-bearing die. The 35 mm choked bearing achieved crack-free extrusion even at maximum extrusion speed, yielding smoother surfaces than the other dies. Numerical simulations demonstrated the differences in stress states using different die bearing geometries, showing that the choked bearings alter the stress state at the die corner to cause a transition from high tensile stress to lower tensile or compressive stress. The extrusion limit diagrams for different die bearings were also constructed based on the extrusion trial data to provide guidance for choosing appropriate extrusion parameters for future studies. This study adds a valuable contribution to the existing literature by shedding light on the role of die bearing geometry in controlling surface morphology and surface crack formation, providing important insights that can be used to optimize the extrusion process.

Single cells are compactly and accurately described as fractional Kelvin-Voigt materials

Mon, 25 Aug 2025 00:00:00 GMT

Single cells are compactly and accurately described as fractional Kelvin-Voigt materials Das, Mohua; Waeterloos, Jarno L.; Clasen, Christian; McKinley, Gareth H. The mechanobiology of single cells plays a crucial role in various biological processes, including embryonic development, cancer treatment, and wound healing. This study highlights the use of the fractional Kelvin-Voigt model (FKVM)—a viscoelastic model consisting of two Scott Blair elements in parallel—to compactly and accurately characterize single-cell rheology. Unlike traditional power law models, which primarily capture the key features of the mechanical response at long timescales, the FKVM effectively captures both short- and long-timescale mechanical responses with a minimal number of constitutive parameters. Experimental small-amplitude oscillatory shear (SAOS) data for dividing canine kidney cells, creep data of human K562 erythroleukemic cells, and creep recovery data of blastomere cytoplasm are all analyzed to showcase the accuracy and versatility of the FKVM. Additionally, for the first time, the continuous relaxation and retardation spectra corresponding to the fractional differential formulation of the FKVM are derived. These results establish a comprehensive framework for predictive analysis of single-cell rheology in both the time and frequency domains. Graphical abstract

Gray matter abnormalities in sight deprivation and sight restoration

Tue, 12 Aug 2025 00:00:00 GMT

Gray matter abnormalities in sight deprivation and sight restoration Pedersini, Caterina A.; Fracasso, Alessio; Dogar, Amna; Rokers, Bas; Sinha, Pawan Blindness provides a unique model for investigating brain plasticity in response to sensory deprivation. While structural changes in both gray and white matter have been widely documented, particularly in cases of early or congenital visual deprivation, gray matter studies have traditionally focused on cortical thickness, often finding cortical thickening in posterior regions. However, other aspects of gray matter integrity, such as cortical myelin content, remain underexplored. In this study, we examined the effects of visual deprivation on cortical structure in a cohort of early blind individuals who received eye surgery during adolescence, expanding beyond conventional measures to include cortical thickness, curvature, and T1-weighted signal intensity. This multi-faceted approach offers a more comprehensive view of cortical adaptations to early sensory deprivation. While blindness offers valuable insights into sensory-driven brain plasticity, an intriguing and unresolved question is whether structural plasticity reverses after sight restoration, enabling typical visual processing circuits to develop despite the initial period of deprivation. To address this, we assessed the effect of sight-recovering eye surgery on gray matter changes. Critically, individuals in this cohort received surgery after the closure of the sensitive period for visual development. We did not find evidence of gray matter changes after surgery. However, in a previous study conducted on the same cohort, we reported that notable plasticity in white matter emerged in this same population. These results suggest that white matter may potentially serve as a biomarker of structural plasticity following sight restoration, even beyond the sensitive developmental window.

Efficacy and Safety of Toludesvenlafaxine Hydrochloride Sustained‐Release Tablets in Depression With Anhedonia: A Single‐Arm, Multicenter Clinical Study

Tue, 06 May 2025 00:00:00 GMT

Efficacy and Safety of Toludesvenlafaxine Hydrochloride Sustained‐Release Tablets in Depression With Anhedonia: A Single‐Arm, Multicenter Clinical Study Wang, San-wang; Mi, Wei-feng; Hao, Xiao-nan; Liu, Xiao-xing; Wen, Xin; Zhao, Min; Jiang, Hai-feng; Wang, Wen-zheng; Li, Tao; Tan, Zhong-Lin; Chen, Song; Lv, Wen; Ning, Yu-ping; Zhou, Yan-ling; Chen, Ying-mei; Tang, Xiang-dong; Li, Bin; Liu, Yang; Ma, Xian-cang; Dong, Ying–ying; Chen, Yun-chun; Wang, Hui-ling; Huang, Yong-lan; Zhang, Hua; Lu, Lin Toludesvenlafaxine hydrochloride sustained-release tablets, as China’s first independently developed chemical Class 1 innovative drug with independent intellectual property rights for the treatment of depression and a new molecular entity, represent a novel triple reuptake inhibitor (TRI) with specific target selectivity for serotonin (5-HT), norepinephrine (NE), and dopamine (DA). This single-arm, multicenter clinical study aimed to evaluate the efficacy and safety of toludesvenlafaxine in alleviating anhedonia symptoms in patients with major depressive disorder (MDD). A total of 123 patients aged 18–65 years were enrolled between April 2023 and April 2024 and received an 8-week treatment with toludesvenlafaxine sustained-release tablets (80–160 mg/day). The primary efficacy endpoint was the change in the total score of the Dimensional Anhedonia Rating Scale (DARS) at weeks 2, 4, and 8. Significant improvements in DARS scores were observed, with mean changes from baseline of 8.4 (95% CI [6.4, 10.4], p < 0.0001), 14.1 (95% CI [12.0, 16.2], p < 0.0001), and 20.4 (95% CI [18.0, 22.9], p < 0.0001), respectively. Additionally, after 8 weeks of treatment, plasma levels of neurotrophic factors, including mature brain-derived neurotrophic factor (mBDNF) (t = 28.78, p < 0.0001), pro-BDNF (t = 27.71, p < 0.0001), and vascular endothelial growth factor (VEGF) (t = 31.07, p < 0.0001), were significantly increased, and the plasma level of IGF-1 was not significantly changed (t = 0.35, p = 0.7269). No association was found between the percentage of changes in neurotrophic factors and the percentage of symptom improvements. Toludesvenlafaxine was generally well-tolerated, with treatment-emergent adverse events (AEs) (TEAEs) reported in 83.7% of participants and treatment-related AEs (TRAEs) in 76.4%. These findings indicate that toludesvenlafaxine hydrochloride sustained-release tablets are safe, well-tolerated, and effective in alleviating anhedonia symptoms in patients with depression.

Is Deuterium Sequestering by Reactive Carbon Atoms an Important Mechanism to Reduce Deuterium Content in Biological Water?

Wed, 14 May 2025 00:00:00 GMT

Is Deuterium Sequestering by Reactive Carbon Atoms an Important Mechanism to Reduce Deuterium Content in Biological Water? Seneff, Stephanie; Nigh, Greg; Kyriakopoulos, Anthony M. Deuterium is a natural heavy isotope of hydrogen, having a neutron as well as a proton. Deuterium disrupts ATP synthesis inmitochondria, causing increased production of reactive oxygen species and reduced synthesis of ATP. Gut microbes likely playa significant role in providing deuterium depleted short chain fatty acids (SCFAs) to human colonocytes through hydrogengas recycling. The production of deuterium depleted (deupleted) nutrients necessarily leaves behind deuterium enriched water,unless there is a process that can sequester deuterium in small molecules that are excreted through the feces. Here, we provideevidence that a small number of classes of uniquely structured carbon-nitrogen rings and bis-allylic carbon atoms in certainbiologically active small molecules may play a crucial role in sequestering deuterium for export into feces or urine. Specifically,we have identified the imidazole ring present in histidine, histamine, and microbial derivatives of histidine, the tetraterpenoidlutein, bilirubin and the derivatives urobilinogen and stercobilinogen produced by gut microbes, and the bis-allylic carbons inpolyunsaturated fatty acids as likely candidates for sequestering deuterium and thereby reducing the deuterium levels in thewater-based medium. Normally, carbon atoms never exchange their bound protons with deuterons from the medium, but all theabove classes of molecules are important exceptions to this rule, as has been shown experimentally.

Surrogate-Assisted Adaptive Experimentation for Fused Filament Fabrication Process Optimization

Mon, 15 Sep 2025 00:00:00 GMT

Surrogate-Assisted Adaptive Experimentation for Fused Filament Fabrication Process Optimization Mojumder, Satyajit; Liao, Shuheng; Liu, Wing K. Fused Filament Fabrication (FFF) is an advanced manufacturing process that requires precise control of multiple parameters, including nozzle temperature, print speed, and layer height. Due to the complexity of this high-dimensional process design space, experimental evaluations are often constrained. A key challenge in FFF is understanding how these parameters influence print quality and identifying optimal process conditions efficiently. This study addresses this challenge by developing a physics-based thermal model for FFF, implemented using a graphics processing unit-accelerated finite element method. The model is calibrated and validated against experimental thermal data for printing polylactic acid (PLA). It is then used to investigate the effects of nozzle temperature, print speed, bed temperature, and layer thickness on print quality by developing a cooling rate metric. A series of simulations is conducted within the process window using the physics-based model, and the resulting data are analyzed with SHapley Additive exPlanations to understand the influence of process parameters on print quality. The results indicate that layer height is the most critical factor affecting the quality of tensile samples. To enhance process optimization, a surrogate model is trained and optimized using data generated from the physics-based model, enabling the identification of an optimal processing window for PLA. By combining physics-based and data-driven modeling, this approach accelerates thermal prediction in the FFF process, facilitating the study of high-dimensional design spaces and the optimization of material-specific printing parameters. The proposed methodology provides a scalable framework for improving the efficiency and quality of extrusion-based additive manufacturing processes, demonstrating its potential for broader applications in process optimization.

Origins and Alteration of Ediacaran Carbonates Recording the Shuram Excursion in Oman

Wed, 14 May 2025 00:00:00 GMT

Origins and Alteration of Ediacaran Carbonates Recording the Shuram Excursion in Oman Bergmann, Kristin D; Osburn, Magdalena R; Anderson, Noah T; Hayhow, Claire; Wilcots, Julia; Cantine, Marjorie D; Fischer, Woodward W; Bonifacie, Magali The Shuram excursion is the largest known negative carbon isotope excursion in Earth's history.Recognized globally, it follows the Ediacaran Gaskiers glaciation and precedes a marked increase in thediversity and complexity of the earliest macroscopic multicellular organisms in the fossil record. A key questionis whether this excursion reflects a primary perturbation to the carbon cycle, which would provide crucialinsights into the environmental conditions shaping the earliest animals, or whether it is largely an artifact of laterdiagenetic alteration. To evaluate the extent of diagenesis in these rocks and constrain how much of theexcursion reflects a primary signal, we investigate the sedimentology and geochemistry of carbonate strata inOman using a variety of techniques spanning multiple spatial and temporal scales. Our multi‐faceted analysisidentifies and characterizes four modes of diagenetic alteration, with sediment‐buffered conditions andauthigenic carbonate precipitation as the dominant processes. However, the degree of alteration is insufficient toaccount for the range of marine sedimentologic and geochemical trends across the carbon isotope excursion.This suggests that, even with evidence of diagenesis, the rocks preserve a measurable record of changingconditions in both terrestrial and marine environments, offering unique insights into Earth's systems during apivotal time in early animal evolution.

Preeclampsia is Associated with Altered Expression of Ferroptosis Biomarkers in Placental but not Maternal Vasculature

Wed, 06 Aug 2025 00:00:00 GMT

Preeclampsia is Associated with Altered Expression of Ferroptosis Biomarkers in Placental but not Maternal Vasculature Ng, Shu-Wing; Ng, Allen C.; Ng, Michelle C.; Ng, Shu-Kay; Arcuri, Felice; Genega, Elizabeth M.; Watkins, Jaclyn C.; Roberts, Drucilla J.; House, Michael D.; O’Tierney-Ginn, Perrie F.; Jacobsen, Daniel P.; Staff, Anne C.; Norwitz, Errol R. Ferroptosis, an iron-dependent mechanism of programmed cell death, has been implicated in the pathogenesis of preeclampsia (PE). Here, we investigate the expression of key ferroptosis biomarkers in placental and decidua basalis tissues. Immunohistochemical (IHC) staining showed high expression of the ferroptosis suppressor, ferroptosis-suppressor protein 1 (FSP1), and the end product malondialdehyde (MDA), in healthy CD31-positive placental endothelium. The staining of all three markers was significantly reduced in PE placentas (P = 0.028). In vitro studies showed that an immortalized endometrial endothelial cell line, and its fetal counterpart, human umbilical vein endothelial cells, are intrinsically highly resistant to erastin-induced ferroptotic cell death compared with trophoblast, endometrial epithelial, and stromal fibroblast cell types. FSP1 was specifically expressed in the endometrial endothelial cells. Both FSP1 and another ferroptosis suppressor protein, GPX4, were degraded when the cells underwent ferroptotic cell death. Interestingly, staining of these same markers in maternal decidua basalis tissues did not show endothelium-specific staining, and no significant difference in staining was noted between healthy and PE tissues. Since previous studies have shown that endometrial cells can activate ferroptosis to produce pro-angiogenic cytokines, we posit that healthy placental endothelial cells activate ferroptosis, as evidenced by high MDA, to promote vasculature development without undergoing cell death, whereas PE placentas show reduced ferroptosis and vasculature underdevelopment. In contrast, both healthy and PE decidua basalis tissues were considered to be in a resting stage with regard to ferroptosis. Further studies are warranted to investigate how ferroptosis is regulated in both healthy and PE pregnancies.

Design, Modeling, and Control of a Soft Robotic Diaphragm‐Assist Device in a Respiratory Simulator

Mon, 28 Apr 2025 00:00:00 GMT

Design, Modeling, and Control of a Soft Robotic Diaphragm‐Assist Device in a Respiratory Simulator Quevedo‐Moreno, Diego; Lee, Sang‐Yoep; Tagoe, Jonathan; Emani, Vishnu; Bonnemain, Jean; Roche, Ellen T The diaphragm is a critical muscle for respiration, responsible for up to 70% ofthe inspiratory effort. Standard treatment for patients with severe diaphragmdysfunction is permanently tethering the airway to a mechanical ventilator, whichgreatly impacts patient autonomy and quality of life. Soft robots are ideal to assistin complex biological functions, such as diaphragm contraction. This articleintroduces a soft robotic diaphragm-assist device designed as a therapeutictreatment for diaphragm dysfunction, moreover a clinically relevant respiratorysimulator is designed and proposed as a validation and testing tool for thistreatment. The device uses fabric-based pneumatic actuators to provide targetedmechanical assistance during inhalation. A two-step control system is imple-mented to optimize synchronization and support: 1) detecting breath intentionfrom the pleural pressure signal to trigger the device and 2) regulating thedevice’s input pressure to assist in inhalation. Using the respiratory simulator,the device demonstrated the ability to restore pleural and abdominal pressuresand signiﬁcantly increased transdiaphragmatic pressure during simulated con-ditions of diaphragm dysfunction. This research advances the ﬁeld of softrobotics in respiratory care, providing a foundational platform for the develop-ment of next-generation therapeutic devices aimed at improving the quality of lifefor patients with diaphragm dysfunction.

MeshModule: A Playful Modular Mesh System for Creative Construction

Sat, 27 Sep 2025 00:00:00 GMT

MeshModule: A Playful Modular Mesh System for Creative Construction Youn, Hye Jun; Sara, Serena; Ishii, Hiroshi MeshModule is a modular construction platform composed of soft, 3D-printed mesh units designed for rapid prototyping of interactive, reconfigurable structures. Each module integrates a flexible mesh body with interlocking connectors, enabling assemblies that are both structurally robust and mechanically compliant. By varying infill patterns, material properties (PLA, TPU, and conductive filament), and geometries, MeshModule supports a range of mechanical behaviors, including bending and folding. The system also accommodates embedded electronics for responsive functionality, making it suitable for applications in wearable computing, education, and interactive art installations. Inspired by tactile learning toolkits, MeshModule fosters hands-on creativity, inclusivity, and scalable interaction design. This work demonstrates how soft digital fabrication can expand the boundaries of modular systems, enabling expressive, accessible, and programmable physical interfaces. UIST Adjunct ’25, Busan, Republic of Korea

POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation

Sat, 27 Sep 2025 00:00:00 GMT

POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation Han, Evans Xu; Zhang, Alice; Zhu, Haiyi; Shen, Hong; Liang, Paul Pu; Hsieh, Jane State-of-the-art visual generative AI tools hold immense potential to assist users in the early ideation stages of creative tasks — offering the ability to generate (rather than search for) novel and unprecedented (instead of existing) images of considerable quality that also adhere to boundless combinations of user specifications. However, many large-scale text-to-image systems are designed for broad applicability, yielding conventional output that may limit creative exploration. They also employ interaction methods that may be difficult for beginners. Given that creative end-users often operate in diverse, context-specific ways that are often unpredictable, more variation and personalization are necessary. We introduce POET, a real-time interactive tool that (1) automatically discovers dimensions of homogeneity in text-to-image generative models, (2) expands these dimensions to diversify the output space of generated images, and (3) learns from user feedback to personalize expansions. An evaluation with 28 users spanning four creative task domains demonstrated POET’s ability to generate results with higher perceived diversity and help users reach satisfaction in fewer prompts during creative tasks, thereby prompting them to deliberate and reflect more on a wider range of possible produced results during the co-creative process. Focusing on visual creativity, POET offers a first glimpse of how interaction techniques of future text-to-image generation tools may support and align with more pluralistic values and the needs of end-users during the ideation stages of their work. UIST ’25, Busan, Republic of Korea

Text2Texture: Generating 3D-Printed Models with Textures based on Text and Image Prompts

Sat, 27 Sep 2025 00:00:00 GMT

Text2Texture: Generating 3D-Printed Models with Textures based on Text and Image Prompts Yin, Joshua; Faruqi, Faraz; Nisser, Martin To support users’ understanding of physical properties in 2D images, we propose Text2Texture, a webtool that converts 2D color images into textured 3D objects ready for 3D printing. This is achieved by extracting depth information using a monocular estimator, extracting local texture information using a fine-tuned stable diffusion model, and superimposing these macro- and micro-scale geometries to produce a composite 3D model with color, depth and texture. Images can be uploaded directly or generated via text prompt, and we print a variety of objects generated using each approach to suggest applications in physicallizing virtual worlds, adding haptic cues to photographs, and conveying information about scale in images. UIST Adjunct ’25, Busan, Republic of Korea

Integrating Motion Sensing into 3D-Printed Bending Structures

Sun, 28 Sep 2025 00:00:00 GMT

Integrating Motion Sensing into 3D-Printed Bending Structures Li, Mingming; Li, Jiaji; Chen, Haotian; Cao, Dingning; Sahin, Karla; Mueller, Stefanie We present a design and fabrication method for converting static 3D models into motion-capable, self-sensing structures using multi-material FDM 3D printing. Our method allows users to configure deformation behaviors, automatically generate printable circuits, and fabricate interactive objects using 3D printing in a single step without post-assembly or manual sensor integration. The 3D-printed circuits enable real-time detection of bending motions through a time-division multiplexing (TDM) circuit scheme. We demonstrate the effectiveness of our approach through sensing performance evaluation and several application examples. UIST Adjunct ’25, Busan, Republic of Korea

EI-Lite: Electrical Impedance Sensing for Micro-gesture Recognition and Pinch Force Estimation

Sun, 28 Sep 2025 00:00:00 GMT

EI-Lite: Electrical Impedance Sensing for Micro-gesture Recognition and Pinch Force Estimation Zhu, Junyi; Xu, Tianyu; Wang, Jiayu; Guan, Emily; Moon, JaeYoung; Morvan, Stiven; Shin, D; Cola?o, Andrea; Mueller, Stefanie; Ahuja, Karan; Luo, Yiyue; Chatterjee, Ishan Micro-gesture recognition and fine-grain pinch press enables intuitive and discreet control of devices, offering significant potential for enhancing human-computer interaction (HCI). In this paper, we present EI-Lite, a lightweight wrist-worn electrical impedance sensing device for micro-gesture recognition and continuous pinch force estimation. We elicit an optimal and simplified device architecture through an ablation study on electrode placement with 13 users, and implement the elicited designs through 3D printing. We capture data on 15 participants on (1) six common micro-gestures (plus idle state) and (2) index finger pinch forces, then develop machine learning models that interpret the impedance signals generated by these micro-gestures and pinch forces. Our system is capable of accurate recognition of micro-gesture events (96.33% accuracy), as well as continuously estimating the pinch force of the index finger in physical units (Newton), with the mean-squared-error (MSE) of 0.3071 (or mean-force-variance of 0.55 Newtons) over 15 participants. Finally, we demonstrate EI-Lite’s applicability via three applications in AR/VR, gaming, and assistive technologies. UIST ’25, Busan, Republic of Korea