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  • 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 […]
  • 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) […]
  • Economics, Social Sciences, Humanities & Policy
    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, […]
  • AI & Machine Learning, Computing, Data & AI
    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, […]
  • AI & Machine Learning, Computing, Data & AI
    Abstract Automated detection of Parkinson’s Disease (PD) from speech presents a low-cost, non-invasive screening tool, but its reliability across languages and recording conditions is uncertain. This study evaluated whether speech-based PD detection could transfer across diverse datasets that differ in language, recording conditions, and tasks under limited exposure to the target dataset. We investigated model […]
  • Health Sciences, Public Health
    Abstract  Marching band competitions require members to perform under pressure after long periods of time waiting before they start the first note of their performance. This study examines the competitive environment of marching band performance and its effects on performers’ emotional states. In particular, the waiting process before performance may influence how nervous, excited, or […]
  • Physical Sciences, Physics
    Abstract The core-cusp problem remains an important problem in the understanding of dark matter halo structures. This paper aims to use mixed tracer Zhang 2024 sources of the rotation curve of the Andromeda Galaxy (M31) to compare the cuspy Navarro-Frenk-White (NFW) and cored Isothermal dark matter density models. We model the galaxy using multiple functions […]
  • Aerospace Engineering, Engineering
    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 […]
  • Earth & Environment, Environmental Science
    Abstract Microplastics are a global environmental concern with widespread impacts on marine ecosystems. Predicting oceanic microplastic concentration remains underexplored, as most machine-learning approaches focus on regional settings and rely on features not consistently available worldwide. We propose a global framework that uses universally available spatial inputs (latitude, longitude, ocean, month) augmented with 256-dimensional satellite-derived geo-embeddings. […]
  • Mathematics, Mathematics & Statistics
    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 […]
  • Economics, Social Sciences, Humanities & Policy
    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 […]

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