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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
    |
    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 ›

  • Economics, Social Sciences, Humanities & Policy
    Examining Median Hourly Wage Differences Between Housed and Homeless Workers Through Descriptive Analysis
    Abstract This observational and cross-sectional study aims to examine the correlation between housing status and hourly wages within the United States, using public microdata from the American Community Survey through IPUMS from 2018 to 2023, while controlling for education, race, sex, and age. Housing inequality is a rising issue in the United States that inhibits […]
    Samstuta Nukala
    |
    August 13, 2026
  • AI & Machine Learning, Computing, Data & AI
    Register Classification of Pedagogical and Commentarial Sanskrit Under Data Scarcity: A Domain-Specific BERT Approach
    Abstract Morphologically rich languages pose challenges for Natural Language Processing (NLP). With highly inflected morphology and sandhi, and under data scarcity, Sanskrit presents a challenge for building natural language processing tools. The default solution for such languages is generic multilingual models, which do not fully solve the problem because Sanskrit is poorly represented in their […]
    Vikrant Venkatesan
    |
    August 13, 2026
  • AI & Machine Learning, Computing, Data & AI, Earth & Environment, Remote Sensing
    Beyond Accuracy: A Cost Aware Hybrid Loss Function Reduces Wildfire Misclassification Cost By 63.7%
    Mukil Iniyan Senthil Kumar1, Satva Patel21 Minnetonka High School2 Chaska High School Abstract Background/Objective: Fires are burning through the United States, causing billions in total damages. Most of these damages come from rare and large fires. Convolutional Neural Networks (CNN) are used to classify wildland fires based on remote sensing data, and most treat all […]
    Mukil Iniyan Senthil Kumar
    |
    August 12, 2026
  • Earth & Environment, Environmental Science
    Removal of Dissolved Copper and Zinc from Schuylkill River Sediment Leachate Using Commercially Available Wood-Based Biochar: A Pilot Study
    Abstract Background/Objective: Urban stormwater runoff delivers dissolved copper (Cu) and zinc (Zn) into receiving waterways at concentrations that frequently exceed EPA freshwater aquatic life criteria of 9 μg/L for Cu and 120 μg/L for Zn. Most published biochar adsorption studies use distilled water as the test matrix, likely overestimating removal efficiency where competing ions and […]
    Gavin Zeyuan Zhao
    |
    August 11, 2026
  • AI & Machine Learning, Computing, Data & AI
    Lightweight Probability-Level Fusion for Occlusion-Robust Human Activity Recognition from RGB and Skeleton Data
    Abstract Human activity recognition (HAR) models often degrade when people or body parts are occluded. This study evaluates whether a lightweight probability-level fusion of RGB and skeleton predictions can improve action recognition under synthetic occlusion. We use frozen pretrained C3D and PoseC3D expert streams on UCF-101 split 1. Each stream produces a video-level 101-dimensional class-probability […]
    Marcus Guo
    |
    August 11, 2026

Life Sciences ›

Health Sciences ›

  • AI & Machine Learning, Computing, Data & AI, Data Science, Health Sciences, Sports Science
    A PCA-Based Framework for Injury Risk Profiling Using Basketball Training and Biomechanical Datasets
    Abstract Athlete monitoring for injury surveillance in basketball generates a large amount of data pertaining to player health and training. A number of collected variables may be correlated, which makes injury risk analysis challenging. In this study, a Principal Component Analysis (PCA) based framework was developed for injury risk profiling and evaluated using three publicly […]
    Sidhant Paruchuri
    |
    August 10, 2026

Physical Sciences ›

Computing, Data & AI ›

  • AI & Machine Learning, Computing, Data & AI, Earth & Environment, Sustainability
    Environmental Suitability Modeling for Solar Installations Using Convolutional Neural Networks
    Abstract As technology has increased, energy demand has also increased. Conventional methods of producing energy also produce harmful byproducts that damage the environment. Due to this issue, people have turned to renewable energy sources like solar power as an alternative. However, few consider the environmental impact of these solar panels. Most studies evaluate the production […]
    Aria Mitra
    |
    August 12, 2026

Engineering ›

  • Aerospace Engineering, Engineering
    Comparative Performance Analysis of Hollow and Annular Combustors in Rotating Detonation Engines
    Abstract Rotating detonation engines (RDEs) have emerged as a promising propulsion technology, offering superior thermodynamic efficiency over conventional Brayton-cycle engines due to their utilization of detonation combustion. Annular combustors (with inner and outer walls) are typically used in RDEs. However, hollow—lacking an inner wall—combustors are emerging as a promising alternative due to their potential mitigation […]
    Sidh Pandya
    |
    February 4, 2026

Earth & Environment ›

  • AI & Machine Learning, Computing, Data & AI, Earth & Environment, Sustainability
    Environmental Suitability Modeling for Solar Installations Using Convolutional Neural Networks
    Abstract As technology has increased, energy demand has also increased. Conventional methods of producing energy also produce harmful byproducts that damage the environment. Due to this issue, people have turned to renewable energy sources like solar power as an alternative. However, few consider the environmental impact of these solar panels. Most studies evaluate the production […]
    Aria Mitra
    |
    August 12, 2026

Mathematics & Statistics ›

  • Mathematics, Mathematics & Statistics
    Numerical Exploration of HOBO vs. QUBO: Using Sudoku as a Benchmark
    Abstract Sudoku, with its complex combinatorial structure, provides a natural NP-hard benchmark for testing optimization models. In this study, we quantitatively compare Quadratic Unconstrained Binary Optimization (QUBO) and Higher-Order Binary Optimization (HOBO). While QUBO is compatible with quantum computers, it is often evaluated on classical simulators known as quantum simulators which calculates with tensor network […]
    Naoaki Mochida
    |
    February 24, 2026

Social Sciences, Humanities & Policy ›

  • Economics, Social Sciences, Humanities & Policy
    Climate, Wealth, and the Share of Roads that Are Bike Lanes Across Cities
    Abstract This paper explores how local climate is related to the creation of urban cycling systems. We examine an international sample of cities to establish whether such elements as temperature and precipitation are related to the degree of committed bike infrastructure. With the help of OpenStreetMap data, in the form of the OSMnx, and climate […]
    Meha Agrawal
    |
    July 16, 2026

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