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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
    |
    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 ›

  • Management, Social Sciences, Humanities & Policy
    Optimising the Drug Supply Chain Using Blockchain
    Abstract Falsified medicines kill patients who believe they are being treated. In low- and middle-income countries, the World Health Organization puts the share of substandard or falsified medical products at about one in ten. An antibiotic with too little active ingredient doesn’t clear the infection that it was prescribed for. Track-and-trace still depends on paper […]
    Siddesh Jayaraman
    |
    October 16, 2026
  • Health Sciences, Medicine
    The Effect of Voiding Position on Urination Parameters: A Preliminary, Fixed-Order Uroflowmetric Comparison of Sitting and Standing in Healthy Men
    Abstract Lower urinary tract symptoms (LUTS) affect millions of aging men worldwide. Voiding position is a modifiable behavioral factor that may influence urinary flow parameters. However, its effects remain poorly characterized due to conflicting prior studies. This study used uroflowmetry to compare urination parameters between sitting and standing positions in fifteen healthy men aged 16-20, […]
    Brian Kim
    |
    October 16, 2026
  • Engineering, Mechanical Engineering
    Thermal Efficiency of Ammonia-Diesel Dual Fuel Engines: An Experimental Investigation
    Abstract Due to the ongoing depletion of fossil fuels and the mounting interest in minimizing greenhouse gas emissions, studies on alternative fuels for internal combustion engines have received significant attention. Ammonia has emerged as a candidate because it is carbon-free, has a high energy density per volume, and has an established infrastructure for production and […]
    Advik Basaiwala
    |
    October 16, 2026
  • Bioinformatics, Life Sciences
    In Silico Identification of DYRK1A-Binding Lead Compounds Relevant to Alzheimer’s Disease
    Abstract Alzheimer’s disease is associated with amyloid-β deposition, tau pathology, neuroinflammation, and progressive cognitive decline. This study asked whether a predefined set of MolPort compounds could be prioritized as structural lead candidates for the kinase DYRK1A. A computational workflow combined DoGSiteScorer and PrankWeb pocket prediction, Pharmit pharmacophore screening, SwissDock docking with the Attracting Cavities engine, […]
    James Xu
    |
    October 15, 2026
  • AI & Machine Learning, Computing, Data & AI
    Stochastic Biomass Forecasting of Golden Tilefish Using the Deep Galerkin Method
    Abstract Accurate biomass forecasting is important for sustainable fisheries management where population dynamics are influenced by environmental variability. In this study, a biomass model is developed for Golden Tilefish (Lopholatilus chamaeleonticeps) using a stochastic Gompertz growth model with multiplicative environmental noise.  Biomass forecasts were generated through Monte Carlo simulation. The Deep Galerkin Method (DGM), a […]
    Aidan Lee
    |
    October 15, 2026

Life Sciences ›

  • Biochemistry, Life Sciences
    Colorimetric Assay of Commercial Lactase Solution Under Different Storage and Solution Conditions
    Abstract Protein stability depends on storage temperature, solution composition, and concentration. This study tested how a 25 mg/mL solution prepared with commercial β-galactosidase (lactase) powder preserved its activity after a short room-temperature exposure and whether glycerol, a common protein stabilizer, helped retain activity under the same temperature treatment. Each of the three independently prepared blocks […]
    Tonny Chen
    |
    September 30, 2026

Health Sciences ›

  • AI & Machine Learning, Computing, Data & AI, Health Sciences, Medicine
    Developing and Evaluating AI Models for Classifying Bone Tumors Using X-ray Imaging
    Abstract As the core algorithms and underlying infrastructure for artificial intelligence (AI) have become mature, it is critical to integrate state-of-the-art AI capabilities across various science and engineering disciplines to solve societal problems, particularly those involving labor-intensive, repetitive tasks with learnable outcomes. One emerging area for AI integration is radiology. X-ray imaging is a primary […]
    Keith Shi
    |
    October 16, 2026

Physical Sciences ›

  • Physical Sciences, Physics
    Bohmian Diagnostics of Wave-Packet Structure and Classical Emergence
    Abstract Bohmian mechanics provides an alternate interpretation of quantum mechanics, where particles have definite trajectories, allowing us to study the correspondence principle. Correspondence is usually framed in terms of n, but it does not consider the superpositions built on the basis. This study examines two families: Gaussian packets (family A) with width  σ = 2n […]
    Arunabh Pratik, Elliott Tammaro
    |
    October 14, 2026

Computing, Data & AI ›

  • AI & Machine Learning, Computing, Data & AI, Health Sciences, Medicine
    Developing and Evaluating AI Models for Classifying Bone Tumors Using X-ray Imaging
    Abstract As the core algorithms and underlying infrastructure for artificial intelligence (AI) have become mature, it is critical to integrate state-of-the-art AI capabilities across various science and engineering disciplines to solve societal problems, particularly those involving labor-intensive, repetitive tasks with learnable outcomes. One emerging area for AI integration is radiology. X-ray imaging is a primary […]
    Keith Shi
    |
    October 16, 2026

Engineering ›

  • Aerospace Engineering, Engineering
    Improving Single-Engine Aircraft Safety Through Evolutionary Neural Networks
    Abstract Engine failure in a single-engine aircraft removes all thrust and leaves the pilot with one option: glide as far as possible while looking for a place to land. Standard practice is to hold a fixed best-glide speed taken from the aircraft handbook, but holding a constant target by hand is difficult, and earlier work […]
    Arkar Tan
    |
    October 8, 2026

Earth & Environment ›

Mathematics & Statistics ›

Social Sciences, Humanities & Policy ›

  • AI & Machine Learning, Computing, Data & AI, Finance, Social Sciences, Humanities & Policy
    Improving the Performance of Long-Term Stock Investments with a Two-Stage LLM Filtering Framework
    Abstract Large language models are increasingly being used in creating investment strategies. However, most studies that create a pipeline, feed news and financial reports in a single prompt to the LLMs. This can reduce relevant signals. To address this limitation, we developed a two-stage filtering framework which uses news articles to select a candidate stock […]
    Jathin Battepati, Rohan Fernandes, Aaryan Parikh, Sahasra Chappidi, Sanil Nirmale, Simran Bhasin, Rohan Sugate, Huifang Qin
    |
    October 12, 2026

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