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A multi-objective permittivity optimization for object classification at the speed of light
No full textThis paper presents a numerical demonstration of the use of the adjoint method for permittivity optimization to design a dielectric medium capable of object classification at the speed of light. In a two-dimensional setup, the system comprises an input waveguide, a design region, and three output ports made of a lossless dielectric material. The design medium is optimized to guide light into specific output ports based on the type and variation of scatterers placed between the input waveguide and the design region. For proof of concept, scatterers derived from the MNIST dataset's digits 0, 1, and 2 are used to represent different object classes with varying shapes and sizes. The optimization process dynamically adjusts the material distribution within the design region to maximize classification performance. The final structure achieved a classification accuracy of 96.3%, with light successfully directed to the correct output port corresponding to each scatterer class. This work demonstrates the potential of permittivity optimization for developing advanced photonic devices capable of ultrafast object recognition, paving the way for future research in three-dimensional designs and more complex classification tasks.The authors gratefully acknowledge the support of the College of Engineering and Information Technology (COEIT) at the University of Maryland, Baltimore County (UMBC) for providing internal funding that made this research possible.http://iopscience.iop.org/article/10.1088/2632-2153/ae139
MediNet: Self-Supervised Framework for Multimodal Analysis and Patient Care in IoMT
No full textMedical data analysis presents major challenges due to multimodal characteristics, real-time processing demands, and scalability constraints. Existing methods face limitations in managing data heterogeneity and generating timely outputs, which restrict their applicability in clinical environments. This study introduces MediNet, a self-supervised framework that addresses these challenges by integrating multimodal analysis, temporal monitoring, and decentralized processing within the Internet of Medical Things (IoMT). MediNet employs an adaptive self-supervised learning strategy, cross-modal contrastive learning, and edge computing to enable efficient real-time analytics. Temporal data streams are processed using dynamic monitoring modules for anomaly detection, while multimodal integration supports personalized patient care. The framework was implemented in PyTorch and evaluated on the BraTS 2021, CheXpert, ISIC 2018, and MIMIC-IV datasets using an NVIDIA A100 GPU. Experimental results show that MediNet consistently outperforms baseline models, achieving a generalization performance of 94.8% on BraTS 2021 and an inference latency of 74 ms on ISIC 2018.https://ieeexplore.ieee.org/abstract/document/1118003
Getting a Degree in a System not Built for Them: Few Student Parents get Help from their Parents when Paying for College
No full textOne in five students at community and four-year colleges in the United States are raising children while trying to earn their degrees—and this number may grow as access to abortion becomes more limited. Many student parents find themselves in precarious economic positions, and are often on their own to pay for college. As we found in a new study of students at two public four-year universities, fewer than 1 in 10 (9%) student parents got financial help from their own parents to pay for college tuition or living expenses. By contrast, nearly two-thirds (64%) of childless students received financial help from their parents.This material is based upon work supported by the National Science Foundation under grant no. 1947603, and a University of North Carolina at Greensboro Advancing Research Summer Award Grant and Faculty Research Grant, as administered by the Office of Sponsored Programs.https://contemporaryfamilies.utah.edu/publications/posts/2025/april/student-parents-brief-report.ph
Double Header: Peter Boyko for MCPS SMOB
No full textGuest Host Lorena Treviño of Walter Johnson High School talks with NorthwestHigh School junior Peter Boyko, one of two finalists for the Student Member of the Montgomery County Board of Education in 2025-26. The SMOB is one of eight on the county school board, nearly co-equal with other generally elected members, but voted in by MCPS secondary school students only. Music for this episode comes from Adam Bobrow. Suvarna Insta: @peterforsmob.https://open.spotify.com/episode/13zsV7ZACR0UQ1jtvBzds
Post-traumatic stress disorder, trauma and parenting stress: an individual participant data meta-analysis
No full textBackground: Parental post-traumatic stress disorder (PTSD) symptoms are associated with heightened parenting stress, but it is unknown whether this relation depends on the timing (childhood or adulthood) and type of trauma (interpersonal or non-interpersonal). In survivors of childhood interpersonal trauma, PTSD and parenting stress may be more strongly intertwined. Objective: This study examined whether the relation between parental PTSD and parenting stress is moderated by childhood interpersonal trauma. Findings are supplemented with information on the process of performing an individual participant data meta-analysis (IPDMA) and lessons learned. Methods: Using one-stage IPDMA, data from published studies and unpublished datasets were synthesized and analysed using multilevel linear regression. Results: Twelve datasets were included (N = 1249: 92.5% female, M age = 32.8 years, 53.8% ethnic minority). Significant and positive main effects of PTSD and childhood interpersonal trauma on parenting stress were consistently found across studies. A moderating effect of childhood interpersonal trauma on the relation between PTSD and parenting stress was not found, but this finding may be impacted by limited data coverage. The proportion of individual-level variance in parenting stress explained by the model with main and interaction effects while controlling for education level was small to medium (R² = .12, p = .003). Conclusion: This study is the first to investigate relations among parental childhood interpersonal trauma, PTSD, and parenting stress across studies using IPDMA methodology. Despite limitations in data coverage, its findings demonstrated that links among childhood interpersonal trauma, PTSD, and parenting stress were robust across populations and settings. This implies PTSD symptom reduction may be beneficial in reducing parenting stress, regardless of whether the parent experienced childhood interpersonal trauma. Additionally, lessons learned and suggestions for how IPDMA can bring the field of trauma and PTSD research forward are presented. Individual participant data meta-analysis (IPDMA) was used to analyse 12 datasets. The objective was to test whether post-traumatic stress disorder (PTSD) symptoms had a stronger effect on parenting stress when parents were survivors of childhood interpersonal trauma.Parents with more PTSD symptoms and parents who were survivors of childhood interpersonal trauma, had more parenting stress. That means reducing PTSD symptoms can probably help parents have less parenting stress. A stronger effect of PTSD on parenting stress in childhood interpersonal trauma survivors was not found, but this may be explained by data limitations.Extended information on process, methods and lessons learned is provided, to inform and inspire other researchers to consider using IPDMA methodology. Individual participant data meta-analysis (IPDMA) was used to analyse 12 datasets. The objective was to test whether post-traumatic stress disorder (PTSD) symptoms had a stronger effect on parenting stress when parents were survivors of childhood interpersonal trauma. Parents with more PTSD symptoms and parents who were survivors of childhood interpersonal trauma, had more parenting stress. That means reducing PTSD symptoms can probably help parents have less parenting stress. A stronger effect of PTSD on parenting stress in childhood interpersonal trauma survivors was not found, but this may be explained by data limitations. Extended information on process, methods and lessons learned is provided, to inform and inspire other researchers to consider using IPDMA methodology.This work was supported by a Utrecht University Dynamics of Youth Invigoration Grant, which provided financial support to Laurien Meijer.https://www.tandfonline.com/doi/full/10.1080/20008066.2025.253890
VAR-PZ: Constraining the Photometric Redshifts of Quasars using Variability
No full textThe Vera C. Rubin Observatory LSST is expected to discover tens of millions of new Active Galactic Nuclei (AGNs). The survey's exceptional cadence and sensitivity will enable UV/optical/NIR monitoring of a significant fraction of these objects. The unprecedented number of sources makes spectroscopic follow-up for the vast majority of them unfeasible in the near future, so most studies will have to rely on photometric redshifts estimates which are traditionally much less reliable for AGN than for inactive galaxies. This work presents a novel methodology to constrain the photometric redshift of AGNs that leverages the effects of cosmological time dilation, and of the luminosity and wavelength dependence of AGN variability. Specifically, we assume that the variability can be modeled as a damped random walk (DRW) process, and adopt a parametric model to characterize the DRW timescale (τ) and asymptotic amplitude of the variability (SF∞) based on the redshift, the rest-frame wavelength, and the AGN luminosity. We construct variability-based photo-z priors by modeling the observed variability using the expected DRW parameters at a given redshift. These variability-based photometric redshift (VAR-PZ) priors are then combined with traditional SED fitting to improve the redshift estimates from SED fitting. Validation is performed using observational data from the SDSS, demonstrating significant reduction in catastrophic outliers by more than 10% in comparison with SED fitting techniques and improvements in redshift precision. The simulated light curves with both SDSS and LSST-like cadences and baselines confirm that, VAR-PZ will be able to constrain the photometric redshifts of SDSS-like AGNs by bringing the outlier fractions down to below 7% from 32% (SED-alone) at the end of the survey.We gratefully acknowledge the support of the ANID BASAL project FB210003 (S.S.S., R.J.A., T.A., F.E.B., C.M., T.M. and C.R.), FONDECYT Regular 1231718 (S.S.S. and R.J.A.), 1240105 (T.A.), 1241005 (F.E.B.), 1230345 (C.R) and ANID Millennium Science Initiative AIM23-0001 (T.A., F.E.B.). S.S.S. acknowledges the travel support from the Royal Astronomical Society to attend the meeting ‘Supermassive Black Hole studies in the Legacy Survey of Space and Time’ in Durham, UK. T.T.A acknowledges support from NASA ADAP Grant 80NSSC24K0692. A.B. acknowledges support from the Australian Research Council (ARC) Centre of Excellence for Gravitational Wave Discovery (OzGrav), through project number CE230100016. DD acknowledges PON R& I 2021, CUP E65F21002880003, and Fondi di Ricerca di Ateneo (FRA), linea C, progetto TORNADO. A.B.K. and D.I. acknowledge funding provided by the University of Belgrade - Faculty of Mathematics (the contract 451-03-136/2025-03/200104) through the grants by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia. C.M. acknowledges support from Fondecyt Iniciacion grant 11240336. C.G.B. acknowledges support from the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and the Secretaría de Ciencia y Tecnología de la Universidad Nacional de Córdoba (SeCyT). C.M. acknowledges support from FONDECYT Iniciacion grant 11240336. D.M. acknowledges financial support from CAPES – Finance Code 001. D.D. and M.F. acknowledge the financial contribution from PRIN-MIUR 2022 and from the Timedomes grant within the "INAF 2023 Finanziamento della Ricerca Fondamentale". W.N.B. acknowledges the support of USA NSF grant AST-2407089. S.E.I.B. is supported by the Deutsche Forschungsgemeinschaft (DFG) under Emmy Noether grant number BO 5771/1-1. S.P. is supported by the international Gemini Observatory, a program of NSF 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, on behalf of the Gemini partnership of Argentina, Brazil, Canada, Chile, the Republic of Korea, and the United States of America. C.R. acknowledges support from SNSF Consolidator grant F01−13252 and the China-Chile joint research fund. M.J.T. acknowledges funding from UKRI grant ST/X001075/1. Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web site is http://www. sdss.org/. The SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions. The Participating Institutions are the American Museum of Natural History, Astrophysical Institute Potsdam, University of Basel, University of Cambridge, Case Western Reserve University, University of Chicago, Drexel University, Fermilab, the Institute for Advanced Study, the Japan Participation Group, Johns Hopkins University, the Joint Institute for Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences (LAMOST), Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, Ohio State University, University of Pittsburgh, University of Portsmouth, Princeton University, the United States Naval Observatory, and the University of Washington.http://arxiv.org/abs/2509.1330
Quantum thermodynamics of Gross-Pitaevskii qubits
No full textWhat are the resources that can be leveraged for a thermodynamic device to exhibit genuine quantum advantage? Typically, the answer to this question is sought in quantum correlations. In the present work, we show that quantum Otto engines that operate with nonlinear qubits significantly outperform linear engines. To this end, we develop a comprehensive thermodynamic description of nonlinear qubits starting with identifying the proper thermodynamic equilibrium state. We then show that for ideal cycles as well as at maximum power the efficiency of the nonlinear engine is significantly higher. Interestingly, nonlinear dynamics can be thought of as an effective description of a correlated, complex quantum many body system. Hence, our findings corroborate common wisdom, while at the same time propose a new design of more efficient quantum engines.S.D. acknowledges support from the John Templeton Foundation under Grant No. 63626. This work was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Quantum Information Science program in Chemical Sciences, Geosciences, and Biosciences, under Award No. DE-SC0025997.http://arxiv.org/abs/2510.1259
Classification of global aerosol types and its radiative effects using Aerosol Robotic Network (AERONET) data
No full textThe present study performed classification global aerosols based on particle linear depolarization ratio (PLDR) and single scattering albedo (SSA) provided from AErosol RObotic NETwork (AERONET) Version 3.0 and Level 2.0 inversion products of 171 AERONET sites located in six continents. Current methodology could distinguish effectively between dust and non-dust aerosols using PLDR and SSA. These selected sites include dominant aerosol types such as, pure dust (PD), dust dominated mixture (DDM), pollution dominated mixture (PDM), very weakly absorbing (VWA), strongly absorbing (SA), moderately absorbing(MA), and weakly absorbing (WA). Biomass-burning aerosols which are associated with black carbon are assigned as combinations of WA, MA and SA. The key important findings show the sites in the Northern African region are predominantly influenced by PD, while south Asian sites are characterized by DDM as well as mixture of dust and pollution aerosols. Urban and industrialized regions located in Europe and North American sites are characterized by VWA, WA, and MA aerosols. Tropical regions, including South America, South-east-Asia and southern African sites which prone to forest and biomass-burning, are dominated by SA aerosols. The study further examined the impacts by radiative forcing for different aerosol types. Among the aerosol types, SA and VWA contribute with the highest (30.14 ± 8.04 Wm⁻²) and lowest (7.83 ± 4.12 Wm⁻²) atmospheric forcing, respectively. Consequently, atmospheric heating rates are found to be highest by SA (0.85 K day⁻¹) and lowest by VWA aerosols (0.22 Kday⁻¹). The current study provides a comprehensive report on aerosol optical, micro-physical and radiative properties for different aerosol types across six continents.The authors are thankful to the anonymous Reviewers for providing constructive comments and suggestions which have strengthened to improve the quality of the manuscript significantly. The AERONET data (Version 3.0 and Level 2.0) used in the present work are taken from 171 sites across the globe which constitutes 6 continents (Africa, Asia, Australia, Europe, North and South America) from the website: https://aeronet.gsfc.nasa.gov and the authors are thankful to the PI, Co-PIs and their staff of the respective AERONET sites who maintain the data for scientific use. We also acknowledge for using global Land Used and Land cover products in the current work from the European Space Agency (ESA), France Climate Change Initiative (CCI) data. Among the authors, SM and SSN thank the Ministry of Earth Sciences, Government of India for providing financial support under the project grant number: MoES/16/02/2021-RDESS.https://www.sciencedirect.com/science/article/pii/S135223102500505
Practical aspects of providing pixel-level spectral Rrs error covariance in satellite ocean color products
No full textWe previously established a derivative-based approach to generate a pixel-level spectral error covariance matrix in satellite-retrieved remote sensing reflectance, ∑Rᵣₛ. However, one practical issue is the delivery of the products without increasing the file size by an order of magnitude or more, considering that for N sensor spectral bands, there are N × (N+1)/2 covariance matrix elements to be specified at each pixel. The issue becomes more pertinent for hyperspectral imaging spectroradiometers such as the Ocean Color Instrument (OCI) on NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem mission (PACE), which has 286 bands, resulting in ∼40,000 unique elements in ∑Rᵣₛ per pixel that would lead to a ∼60 GB Level-2 file for one 5-min granule. As a first step to tackle the issue, we took OCI and Moderate Resolution Imaging Spectroradiometer (MODIS) data to explore the possibility of approximating ∑Rᵣₛ using a third-degree polynomial, thereby decreasing the memory overhead to 4×N numbers. We found that ∑Rᵣₛ derived from the polynomial fitting matches well with the original value, with the difference smaller than 5%. We then compared the relative uncertainty in two derived ocean color data products (chlₐ and K(490)) calculated using the original fully computed ∑Rᵣₛ and then using the polynomial model approximation for ∑Rᵣₛ, finding the absolute difference between the two approaches to be smaller than 0.5%. These evaluations suggest the polynomial approximation of ∑Rᵣₛ is suitable without degrading the scientific quality. By including the coefficients derived from polynomial fitting instead of the full error covariance matrix, a typical 5-min Level-2 file for OCI decreases from ∼60 GB to a more practical ∼1.7 GB.The author(s) declare that financial support was received for the research and/or publication of this article. NASA Terra and Aqua Senior Review for MODIS algorithm maintenance and the NASA PACE Project.https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2025.1670390/ful
Towards Equitable AI: Detecting Bias in Using Large Language Models for Marketing
No full textThe recent advances in large language models (LLMs) have revolutionized industries such as finance, marketing, and customer service by enabling sophisticated natural language processing tasks. However, the broad adoption of LLMs brings significant challenges, particularly in the form of social biases that can be embedded within their outputs. Biases related to gender, age, and other sensitive attributes can lead to unfair treatment, raising ethical concerns and risking both company reputation and customer trust. This study examined bias in finance-related marketing slogans generated by LLMs (i.e., ChatGPT) by prompting tailored ads targeting five demographic categories: gender, marital status, age, income level, and education level. A total of 1,700 slogans were generated for 17 unique demographic groups, and key terms were categorized into four thematic groups: empowerment, financial, benefits and features, and personalization. Bias was systematically assessed using relative bias calculations and statistically tested with the Kolmogorov-Smirnov (KS) test against general slogans generated for any individual. Results revealed that marketing slogans are not neutral; rather, they emphasize different themes based on demographic factors. Women, younger individuals, low-income earners, and those with lower education levels receive more distinct messaging compared to older, higher-income, and highly educated individuals. This underscores the need to consider demographic-based biases in AI-generated marketing strategies and their broader societal implications. The findings of this study provide a roadmap for developing more equitable AI systems, highlighting the need for ongoing bias detection and mitigation efforts in LLMs.http://arxiv.org/abs/2502.1283