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  • AI & Machine Learning, Biology, Computing, Data & AI, Life Sciences
    Syn4MD: Aiding Medical Diagnosis through Image Synthesis and Classification
    Abstract Medical trainees depend on diverse visual reference material to develop diagnostic pattern-recognition skills, yet such material is often limited in diversity and accessibility. This paper presents a classifier-in-the-loop generative framework for synthesising realistic histopathology images: a Stable Diffusion v1.5 model is fine-tuned using Low-Rank Adaptation (LoRA) on the PathMNIST dataset, consisting of nine colorectal […]
    Kanishk Choudhary
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    August 3, 2026
  • Biology, Chemistry, Life Sciences, Physical Sciences
    DiaBreath: Multivariate Analysis of a Non-Selective Low-Cost Metal Oxide (MOX) Sensor Array for Breath-Based Diabetes Screening
    Abstract The number of diabetes patients is increasing worldwide, but many cases stay undiagnosed in low-resource regions. The A1C blood test is invasive and costly, therefore it is often not available in these regions. In this research, DiaBreath is proposed as a low-cost noninvasive screening system based on exhaled breath analysis. Volatile organic compounds (VOCs) […]
    Woo Sung Choi
    |
    July 24, 2026
  • Computing, Data & AI, Data Science, Economics, Social Sciences, Humanities & Policy
    A Statistical Physics Approach to Market Dynamics: Regime Shifts in Digital vs. Local Vendor Choice
    Abstract Digital commerce platforms compete with local vendors under frictions of time, price, and visibility. We test whether an interpretable choice model with reinforcement and social influence can yield substantial changes in aggregate market share as control parameters vary. We simulate repeated customer choice among vendors using a utility function that combines vendor attributes (price, […]
    Amaira Goyal
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    July 12, 2026
  • AI & Machine Learning, Computing, Data & AI
    Predicting Limited Service Zones Using GIS-Integrated Machine Learning: A Case Study of Three Cities
    Abstract Local businesses are important to neighborhood service access, but access to these services is limited in some areas. This study uses GIS and machine learning to identify possible limited service zones for restaurants and supermarkets across Dublin, Pleasanton, and Livermore in Alameda County, California. The model dataset included 1,134 Alameda County census block groups, […]
    Mandy Yuan
    |
    July 8, 2026

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NHSJS Reports ›

  • Electrical Engineering, Engineering
    Predictive Yaw System Control of Wind Turbines Through Long Short Term Memory Neural Networks
    Abstract Wind turbine yaw control seeks to maintain alignment between the rotor and incoming wind direction while limiting the energy and mechanical costs associated with nacelle movement. Predictive control using machine learning based wind direction forecasts may potentially improve this trade off by anticipating changes instead of responding to observed misalignment. This study evaluates whether […]
    Adarsh Devakottai Raghavan
    |
    October 26, 2026
  • Materials Science, Physical Sciences
    Current Challenges with Transverse Thermal and Electrical Conductivities of Carbon Nanotubes
    Abstract The transverse thermal and electrical conductivities (TTC and TEC) of various common carbon nanotubes (CNTs) are currently still being researched due to difficulties in understanding the research question, resulting in a gap in the general understanding of CNTs. A common problem researchers face is isolating the extreme anisotropic properties of CNTs from other factors […]
    Andy Liang
    |
    October 26, 2026
  • Biology, Genetics, Life Sciences
    Comparative Effects of Beta vulgaris on Food-Deprivation Response in Wild-Type and DAF-16 Mutant Caenorhabditis elegans
    Abstract Food deprivation is a physiological stressor in Caenorhabditis elegans in which DAF-16/FoxO contributes to survival. This study examined whether exposure to a 0.05% Beta vulgaris (beetroot) preparation altered cross-sectional live-population estimates during food deprivation in wild-type N2 and CF1038 daf-16(mu86) I worms. Three independent trials were conducted using the same four experimental groups and […]
    Keiona Nadig
    |
    October 25, 2026
  • Economics, Policy, Social Sciences, Humanities & Policy
    Market Factors Associated with Short-Selling Dynamics Following GameStop 2021 Short Squeeze Event
    Abstract The January 2021 GameStop (GME) event was an event driven by coordinated trading of investors resulting in one of the most extreme events of market volatility in the stock markets. The event revealed the susceptibility of institutional short-selling towards systemic risk and drew significant attention. The goal of this study is to determine the […]
    Aditri Inamdar
    |
    October 25, 2026
  • Health Sciences, Medicine
    Exploring the Possibilities of Using Radiotherapy and Immunotherapy Synergistically in Combination for the Treatment of Cancer Solid Tumors: Mechanistic and Clinical Evidence
    Abstract Radiotherapy is a treatment used to control localized tumors. Immunotherapy is effective only in a subset of patients, as many tumors are “cold,” meaning they are not immunosensitive characterized by limited pre-existing antitumor immune activity, often associated with low T-cell infiltration, reduced antigen presentation, weak inflammatory signaling, or an immunosuppressive microenvironment. Radiation can combat […]
    Asmi Jain
    |
    October 25, 2026

Life Sciences ›

  • AI & Machine Learning, Computing, Data & AI, Life Sciences, Neuroscience
    Deep Learning Classification of Psychiatric Disorders from Resting-State EEG: A Multi-Disorder Study Using the TDBRAIN Dataset
    Abstract Background: Modern diagnosis of psychiatric disorders often includes subjective techniques across clinicians, such as interviews and the self-reporting of symptoms, which yield inconsistent results. However, Electroencephalography (EEG) can complement these current methods, offering a non-invasive and standardized measurement of biological signals. This study evaluates the accuracy of deep learning models in classification of psychiatric […]
    Aashni Katari
    |
    October 23, 2026

Health Sciences ›

Physical Sciences ›

Computing, Data & AI ›

Engineering ›

Earth & Environment ›

Mathematics & Statistics ›

Social Sciences, Humanities & Policy ›

  • Social Sciences, Social Sciences, Humanities & Policy
    Economic Barriers to Family Formation and Demographic Trends in Smolensk Oblast: A Pilot Survey of High-School Students
    Abstract The Smolensk Oblast faces persistent demographic decline, with birth rates falling from 10.6‰ in 2015 to 5.8‰ in 2023 and sustained youth out-migration to more developed regions. Despite federal and regional family support programs, these trends continue. This pilot study explores whether economic barriers (income and housing) are perceived as more significant obstacles to […]
    Egor Udra, Artem Sekachev
    |
    October 18, 2026

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