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  • AI & Machine Learning, Biology, Computing, Data & AI, Life Sciences
    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 […]
  • Biology, Chemistry, Life Sciences, Physical Sciences
    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) […]
  • Computing, Data & AI, Data Science, 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, […]
  • Biomedical Engineering, Engineering
    Abstract Obesity is a growing global health crisis, affecting approximately one in eight individuals worldwide. Glucagon-like peptide-1 (GLP-1) receptor agonism is an established target in obesity therapy, but as monotherapy it has limitations, including loss of lean mass and a plateau in weight reduction. Combination strategies pairing GLP-1 receptor agonism with a second mechanism have […]
  • Policy, Social Sciences, Humanities & Policy
    Abstract When governments pick winners, markets often fail. The history of US transportation policy reveals a recurring pattern in which efforts to accelerate technological transitions undermine competitive fairness. This pattern is consistent with predictable process equity failures defined as breakdowns in procedural fairness and structural neutrality within market competition. The objective of this paper is […]
  • Economics, Finance, Social Sciences, Humanities & Policy
    Abstract Credit invisibility is a major challenge to financial inclusion, particularly for blue-collar migrant workers who have regular but non-registered income. These groups are excluded by traditional credit-scoring systems, which rely on bank records. This paper examines the potential of linking machine learning models that are developed using alternative data to enhance accuracy and fairness […]
  • AI & Machine Learning, Computer Science, Computing, Data & AI
    Abstract Alzheimer’s disease is a progressive neurodegenerative disorder that remains the leading cause of dementia and currently has no cure. Early detection is imperative to slow the disease’s onset, which remains challenging without widely accessible screening technologies. Machine learning offers a promising approach to classifying Alzheimer’s disease using patterns in cognitive, functional, behavioral, medical, and […]
  • Materials Science, Physical Sciences
    Abstract Hydrogen energy is interesting as a clean fuel for the future, while it also concerns regarding its safety problem being raised. Generally, gas hydrogen always keeps expensive high-pressure tanks, has a low energy density, and is able to potentially explosion situation. Liquid hydrogen also has a low safety and high cost to transport and […]
  • Biology, Earth & Environment, Environmental Science, Life Sciences
    Abstract Background/Objective: International wildlife trade monitoring relies on accurate reporting from both importing and exporting nations. However, regulations built on this data often prove inadequate, as gaps in records allow disease risks to slip through the cracks. This study investigated discrepancies in United States live mammal import tracking data in the CITES Trade Database between […]
  • AI & Machine Learning, Computing, Data & AI, Data Science, Health Sciences, Sports Science
    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 […]
  • AI & Machine Learning, Computer Science, Computing, Data & AI
    Abstract Crop disease identification is critical for our global food security as crop diseases cost the global economy approximately $220 billion every year. While machine learning is a practical solution for classification, there has been a lack of research in comparing different architectures. This study compares four architectures for 13-class crop disease classification across four […]
  • 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 […]
  • Biology, Earth & Environment, Environmental Science, Life Sciences
    Abstract Background/Objective: International wildlife trade monitoring relies on accurate reporting from both importing and exporting nations. However, regulations built on this data often prove inadequate, as gaps in records allow disease risks to slip through the cracks. This study investigated discrepancies in United States live mammal import tracking data in the CITES Trade Database between […]
  • 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 […]

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