Emissive Surface Traps Lead to Asymmetric Photoluminescence Line Shape in Spheroidal CsPbBr3 Quantum Dots

The morphology of quantum dots plays an important role in governing their photophysics. Here, we explore the photoluminescence of spheroidal CsPbBr₃ quantum dots synthesized via the room-temperature trioctylphosphine oxide/PbBr₂ method. Despite photoluminescence quantum yields nearing 100%, these spheroidal quantum dots exhibit an elongated red photoluminescence tail not observed in typical cubic quantum dots synthesized via hot injection. We explore the origins of this elongated red tail through structural and optical characterization including small-angle X-ray scattering, transmission electron microscopy and time-resolved, steady-state, and single quantum dot photoluminescence. From these measurements we conclude that the red tail originates from emissive traps. We show that treating spheroidal quantum dots with phenethylammonium bromide decreases the line shape asymmetry and increases passivation–consistent with emissive traps due to polar facets.This work, and the roles of J.K., S.G., B.F.H, R.M., D.M.L., J.N.P., M.F.T., M.P., S.Y., G.D. and D.S.G were primarily supported by the National Science Foundation under the STC IMOD Grant (No. DMR2019444). B.F.H. and D.M.L. acknowledge support from the National Science Foundation through the Graduate Research Fellowship Program (NSF-GRFP) under Grant No. DGE 2040434. R.J.E.W. carried out streak camera measurements and was supported by the Office of Naval Research (ONR N000-14-20- 1-2191) and the Momental Foundation via the Mistletoe Fellowship. The authors acknowledge the use of facilities and instruments at the Photonics Research Center (PRC) at the Department of Chemistry, University of Washington, as well as that at the Research Training Testbed (RTT), part of the Washington Clean Energy Testbeds system. Part of this work was carried out at the Molecular Analysis Facility, a National Nanotechnology Coordinated Infrastructure site at the University of Washington which is supported in part by the National Science Foundation (NNCI-1542101), the Molecular Engineering & Sciences Institute, and the Clean Energy Institute. TEM was carried out at the Facility for Electron Microscopy of Materials at the University of Colorado Boulder (CU FEMM, RRID: SCR_019306). J.K. acknowledges David M. Jonas (professor, University of Colorado Boulder) for discussion regarding potential causes of an elongated red photoluminescence tail in quantum dots. D.M.L. acknowledges use of the SasView application for fitting SAXS data. SasView was originally developed under NSF award DMR-0520547 and contains code developed with funding from the European Union’s Horizon 2020 research and innovation program under the SINE2020 project, grant agreement No 654000. B.F.H. acknowledges Olivia F. Bird (graduate student, University of Colorado Boulder) and Sophia M. Click (postdoctoral researcher, University of Colorado Boulder) for discussions related to TEM image segmentation and size analysis using Trainable Weka Segmentation in ImageJ.https://pubs.acs.org/doi/full/10.1021/acs.nanolett.4c0499

Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning

With the growing computational capabilities of microcontroller units (MCUs), edge devices can now support machine learning models. However, deploying decentralised federated learning (DFL) on such devices presents key challenges, including intermittent connectivity, limited communication range, and dynamic network topologies. This paper proposes a novel framework, bilayer Gossip Decentralised Parallel Stochastic Gradient Descent (GD PSGD), designed to address these issues in resource-constrained environments. The framework incorporates a hierarchical communication structure using Distributed Kmeans (DKmeans) clustering for geographic grouping and a gossip protocol for efficient model aggregation across two layers: intra-cluster and inter-cluster. We evaluate the framework's performance against the Centralised Federated Learning (CFL) baseline using the MCUNet model on the CIFAR-10 dataset under IID and Non-IID conditions. Results demonstrate that the proposed method achieves comparable accuracy to CFL on IID datasets, requiring only 1.8 additional rounds for convergence. On Non-IID datasets, the accuracy loss remains under 8\% for moderate data imbalance. These findings highlight the framework's potential to support scalable and privacy-preserving learning on edge devices with minimal performance trade-offs.http://arxiv.org/abs/2501.0481

ADAPTIVE IE: Investigating the Complementarity of Human-AI Collaboration to Adaptively Extract Information on-the-fly

Proceedings of the 31st International Conference on Computational Linguistics, January 2025, Abu Dhabi, UAEInformation extraction (IE) needs vary over time, where a flexible information extraction (IE) system can be useful. Despite this, existing IE systems are either fully supervised, requiring expensive human annotations, or fully unsupervised, extracting information that often do not cater to user`s needs. To address these issues, we formally introduce the task of “IE on-the-fly”, and address the problem using our proposed Adaptive IE framework that uses human-in-the-loop refinement to adapt to changing user questions. Through human experiments on three diverse datasets, we demonstrate that Adaptive IE is a domain-agnostic, responsive, efficient framework for helping users access useful information while quickly reorganizing information in response to evolving information needs.We sincerely thank the anonymous reviewers and the UMD CLIP members—Wichayaporn Wongkamjan, Zongxia Li, Nishant Balepur, Trista Cao, and Calvin Bao—for their valuable feedback and constructive comments on the draft. We also extend our gratitude to Shramay Palta and Yoo Yeon Sung for their support in shaping the interface and assisting with the pilot studies. This work, led by Ishani, was supported by the Adobe Research Gift Fund, the Global Terrorism Database (GTD) research team at the University of Maryland, and the Intelligence Advanced Research Projects Activity (IARPA) through the BETTER (Better Extraction from Text Towards Enhanced Retrieval) program. Previously, Michelle was funded by the COE grant and her work was done before joining Amazon. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies.https://aclanthology.org/2025.coling-main.392

Dynamic Imprints of Colliding-wind Dust Formation from WR 140

Carbon-rich Wolf–Rayet (WR) binaries are a prominent source of carbonaceous dust that contribute to the dust budget of galaxies. The "textbook" example of an episodic dust-producing WR binary, WR 140 (HD 193793), provides us with an ideal laboratory for investigating the dust physics and kinematics in an extreme environment. This study is among the first to utilize two separate JWST observations, from Cycle 1 ERS (2022 July) and Cycle 2 (2023 September), to measure WR 140's dust kinematics and confirm its morphology. To measure the proper motions and projected velocities of the dust shells, we performed a novel point-spread function (PSF) subtraction to reduce the effects of the bright diffraction spikes and carefully aligned the Cycle 2 to the Cycle 1 images. At 7.7 μm, through the bright feature common to 16 dust shells (C1), we find an average dust shell proper motion of 390 ± 29 mas yr⁻¹, which equates to a projected velocity of 2714 ± 188 km s⁻¹ at a distance of 1.64 kpc. Our measured speeds are constant across all visible shells and consistent with previously reported dust expansion velocities. Our observations not only prove that these dusty shells are astrophysical (i.e., not associated with any PSF artifact) and originate from WR 140, but also confirm the "clumpy" morphology of the dust shells, in which identifiable substructures within certain shells persist for at least 14 months from one cycle to the next. These results support the hypothesis that clumping in the wind collision region is required for dust production in WR binaries.The work of E.P.L. is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the U.S. National Science Foundation. J.L.H. acknowledges support from the National Science Foundation under award AST-1816944. T.O. acknowledges support by the Japan Society for the Promotion of Science (JSPS) KAKENHI grant No. JP24K07087. N.D.R. is grateful for support from the Cottrell Scholar Award #CS-CSA-2023-143 sponsored by the Research Corporation for Science Advancement. J.S.-B. acknowledges the support received from the UNAM PAPIIT project IA 105023. C.M.P.R. acknowledges support from NASA Chandra Theory grant TM3-24001X. This material is based upon work supported by NASA under award number 80GSFC24M0006 and based on observations made with the NASA/ESA/CSA James Webb Space Telescope. The data were obtained from the Mikulski Archive for Space Telescopes at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract number NAS 5-03127 for JWST. These observations are associated with programs #3823 and #1349. Support for program #3823 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-03127. We thank the anonymous reviewer for insightful feedback that improved the quality of this manuscript. We thank Christopher Packham and Mason Leist for their valuable discussions about the MIRI PSF subtraction.https://iopscience.iop.org/article/10.3847/2041-8213/ad9aa

GPS-Health: A Novel Analytic Infrastructure for Capturing, Visualizing, and Analyzing Multi-Level, Multi-Domain Geographically Distributed Social Determinants of Health

Background Health disparities across a range of conditions and outcomes exist across the life course and are driven by the uneven geographic distribution of multidimensional social determinants of health (SDOH). Previous multidimensional measures of SDOH (e.g. Area Deprivation Index, Social Vulnerability Index, Social Deprivation Index) collapse multiple measures into a single summary value applied to everyone living within a predefined map unit, engendering construct and internal validity issues.Methods We present a new SDOH data approach: the Geographic Patterns of Social Determinants of Health (GPS-Health). We use a theoretical framework weaving together kyriarchy, intersectionality, and structural violence to select SDOH domains that can elucidate how individuals experience multidimensional spatial distributions of SDOH. We apply the approach to Maryland.Results Our dataset includes 2,369,365 property parcels, from which we calculate distances to 8 types of SDOH exact locations.Discussion GPS-Health will aid in the understanding of how the SDOH influence individual health outcomes.SJH is funded on a NIDDK institutional training grant: 5T32DK098107-09. All authors are investigators at the University of Maryland-Institute for Health Computing, which is supported by funding from Montgomery County, Maryland and The University of Maryland Strategic Partnership: MPowering the State, a formal collaboration between the University of Maryland, College Park and the University of Maryland, Baltimore. EMD is a member of the United States Preventive Services Task Force (USPSTF), this article does not necessarily represent the views and policies of the USPSTF. Research reported in this publication was supported by the National on Minority Health and Health Disparities (R01MD015716 [TTN]): the content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.https://www.medrxiv.org/content/10.1101/2025.01.03.25319962v

Impact of the Introduced Rainbow Darter, Etheostoma caeruleum on the Microhabitat Use of Native Darters

The Rainbow darter, Etheostoma caeruleum is an introduced species that has spread rapidly in the Potomac River drainage. However, the reason for this rapid spread and the impact of E. caeruleum on other species of both native and nonnative darters has not been determined. This study examines how the abundance E. caeruleum affects the microhabitat use of E. blennioides, E. flabellare, and E. olmstedi within the Monocacy River drainage. Snorkeling was used as a method to observe and measure the microhabitat use of darters across eight locations. Sites where E. caeruleum were present had significantly low population levels of E. olmstedi. E. flabellare experienced a habitat shift towards habitats with larger substrates, increased depths, and slower bottom velocities with an increasing proportion of E. caeruleum. The microhabitat use of E. blennioides remained consistent across all sites, regardless of the relative abundance of E. caeruleum. This study suggests E. caeruleum are outcompeting native species, specifically E. flabellare, for their preferred habitat

Artificial Intelligence for Cognitive Systems: Deep Learning, Neuro- symbolic Integration, and Human-Centric Intelligence

Artificial intelligence quickly changed from a theory to a practical power - it spreads through every part of modern life. As people go from specific uses to more general kinds of intelligence, they must face a main change. This change involves what machines do and how people think about intelligence. The book, Cognitive AI - From Deep Learning to Artificial General Intelligence, looks at that change. This writing serves a wide, serious group of people - it is for graduate students and researchers in artificial intelligence and cognitive science. Educators along with industry workers also read this to get a better grasp of the path from current AI systems to future cognitive architectures. We do not just list technologies. We deal with the concepts, morals, technical issues as well as societal problems that sit at the core of creating machines that think. The chapters lay out this story bit by bit; they start with basic learning systems. They move to cognitive modeling and designs. The book finishes with important questions about governance, combining fields along with how people will work in the future. Throughout the text, the reader learns about current subjects. Some of these are large language models, explaining how systems work, reasoning with symbols plus networks, the safety of general artificial intelligence, and people working with machines. I appreciate the researchers, collaborators along with students who inspired this work. The growing group of thinkers also recognizes that making intelligent systems requires scientific exactness and philosophical thought. My hope is that this book guides plus starts talks for anyone who wants AI to develop responsibly and creatively.https://www.deepscienceresearch.com/dsr/catalog/book/20

BiasLab: Toward Explainable Political Bias Detection with Dual-Axis Annotations and Rationale Indicators

We present BiasLab, a dataset of 300 political news articles annotated for perceived ideological bias. These articles were selected from a curated 900-document pool covering diverse political events and source biases. Each article is labeled by crowdworkers along two independent scales, assessing sentiment toward the Democratic and Republican parties, and enriched with rationale indicators. The annotation pipeline incorporates targeted worker qualification and was refined through pilot-phase analysis. We quantify inter-annotator agreement, analyze misalignment with source-level outlet bias, and organize the resulting labels into interpretable subsets. Additionally, we simulate annotation using schema-constrained GPT-4o, enabling direct comparison to human labels and revealing mirrored asymmetries, especially in misclassifying subtly right-leaning content. We define two modeling tasks: perception drift prediction and rationale type classification, and report baseline performance to illustrate the challenge of explainable bias detection. BiasLab's rich rationale annotations provide actionable interpretations that facilitate explainable modeling of political bias, supporting the development of transparent, socially aware NLP systems. We release the dataset, annotation schema, and modeling code to encourage research on human-in-the-loop interpretability and the evaluation of explanation effectiveness in real-world settings.Dr. Goldwasser provided guidance and funding for the original MTurk pilot phasehttp://arxiv.org/abs/2505.1608

A Node on the Constellation: The Role of Feminist Makerspaces in Building and Sustaining Alternative Cultures of Technology Production

Feminist makerspaces offer community led alternatives to dominant tech cultures by centering care, mutual aid, and collective knowledge production. While prior CSCW research has explored their inclusive practices, less is known about how these spaces sustain themselves over time. Drawing on interviews with 18 founders and members across 8 U.S. feminist makerspaces as well as autoethnographic reflection, we examine the organizational and relational practices that support long-term endurance. We find that sustainability is not achieved through growth or institutionalization, but through care-driven stewardship, solidarity with local justice movements, and shared governance. These social practices position feminist makerspaces as prefigurative counterspaces - sites that enact, rather than defer, feminist values in everyday practice. This paper offers empirical insight into how feminist makerspaces persist amid structural precarity, and highlights the forms of labor and coalition-building that underpin alternative sociotechnical infrastructures.http://arxiv.org/abs/2507.2232

Do Civil Servants Serve the Constitution or the President?

The Trump chaos has brought a key constitutional principle to the fore: What happens when bureaucrats believe the president is not living up to his pledge to the Constitution? Sunil Dasgupta talks with Hamilton College, NY, Associate Professor of Sociology Jamie Lee Kucinskas about her new book, The Loyalty Trap: Conflicting Loyalties of Civil Servants Under Increasing Autocracy, where she reports prescient findings from 127 interviews she conducted with civil servants during the first Trump administration. https://www.amazon.com/dp/0231208154?ref=cm_sw_r_ffobk_cp_ud_dp_ZVNC2RT3GWFDR9A3Q2GD&ref_=cm_sw_r_ffobk_cp_ud_dp_ZVNC2RT3GWFDR9A3Q2GD&social_share=cm_sw_r_ffobk_cp_ud_dp_ZVNC2RT3GWFDR9A3Q2GD&bestFormat=true&previewDohEventScheduleTesting=C&csmig=1 Music by Anna Rubin.https://open.spotify.com/episode/3FmG8vbBWes9zQODwQc4x