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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

Most Discussed ›

NHSJS Reports ›

  • Earth & Environment, Environmental Science, Health Sciences, Public Health
    Literature Review on Particulate Matter–Mediated Aging and Age-Related Diseases
    Abstract Although the respiratory and cardiovascular effects of particulate matter (PM) are well known, their role as a promoter of biological aging remains undetermined. This review examines the literature to assess how chronic PM exposure is incorporated into the molecular trajectory of aging and if it relates to a range of age-related pathologies. A systematic […]
    Dameun Kim
    |
    October 30, 2026
  • Physical Sciences, Physics
    Quantum Simulation of Photoinduced Excitation Dynamics Relevant to Photovoltaic Systems Using Open Quantum Models
    Abstract This study asks whether a simplified driven two level model can quantitatively reproduce coherent excitation dynamics of a localized photoactive transition, evaluated through agreement with analytical Rabi oscillations with an error threshold below 1%. A Python simulation using QuTip was developed to reproduce photoinduced excitation dynamics. This was then used to validate the characteristic […]
    Adarsh Devakottai Raghavan
    |
    October 30, 2026
  • Computing, Data & AI, Data Science
    Effectiveness of Data Sampling Strategies for Maritime AIS Analytics: A One-Day Gulf of Mexico Study
    Abstract Automatic Identification Systems (AIS) generate millions of vessel positions per day, so training machine learning (ML) models on complete datasets is expensive. Prior AIS reduction work has evaluated trajectory simplification on downstream tasks; however, no reviewed study has compared multiple competing ping-level sampling strategies across multiple downstream ML tasks and anomaly-label definitions within one […]
    Dhruv Kothari, Mehek Kothari
    |
    October 30, 2026
  • Materials Science, Physical Sciences
    Which Battery Chemistry Will Pave the Way for EVs? A Comparison Between Different Battery Chemistries for Electric Vehicles
    Abstract Electric Vehicles (EVs) have become very popular recently due to their increased availability. However, these vehicles have severe drawbacks, such as reduced range compared to internal combustion engine (ICE) vehicles. In this paper, ten battery chemistries, five current and five experimental, are analysed to determine which one is the most appropriate for electric vehicles […]
    Rodolfo Humberto Mendiola López
    |
    October 30, 2026
  • Bioinformatics, Biology, Life Sciences
    AlphaFold 3 Guided Computational Design of Candidate Peptide Binders to VIM-2
    Abstract Zinc-dependent metallo-β-lactamases contribute to carbapenem resistance, motivating the search for molecules that engage their catalytic sites. This study developed an AlphaFold 3 (AF3)-guided workflow to design and prioritize 25-residue candidate peptide binders to VIM-2. The search objective combined predicted aligned error, burial of six specified receptor residues and balanced burial of two catalytic zinc […]
    Caleb Seojun Kim
    |
    October 29, 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 ›

  • Engineering, Mechanical Engineering
    Modeling Temporal Dynamics for Cavitation-Induced Valve Plate Failure Detection in Hydraulic Pumps
    Abstract This study investigates the use of machine learning for fault detection of cavitation-induced valve plate failures in hydraulic piston pumps using multivariate sensor data. We compared  non-sequential models with engineered lagged features to sequence-based deep learning models that explicitly include temporal dependencies using an established experimental dataset. Long Short-Term Memory (LSTM) networks achieved the […]
    Aidan Lee
    |
    October 28, 2026

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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