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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, […]
  • Bioinformatics, Biology, Life Sciences
    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 […]
  • Health Sciences, Public Health
    Abstract Background: Per the Centers for Medicare & Medicaid Services (CMS), national health spending has reached $5.3 trillion dollars or 18.0% of GDP in 2024. Since 2021, hospitals are required to share pricing, but the results obtained vary significantly.Objective: The aim of this research is to explain eight platforms designed for price transparency, give a […]
  • Health Sciences, Life Sciences, Neuroscience, Psychology
    Abstract Introduction. Music, despite having little apparent biological value, can evoke pleasure and strong physical responses such as chills. Research has linked this to the mesolimbic reward system and dopaminergic signaling in the striatum. This narrative review examines the neural mechanisms of musical pleasure, focusing on reward circuitry, dopamine, and prediction. Methods. PubMed and Google […]
  • AI & Machine Learning, Computing, Data & AI, Health Sciences, Medicine
    Abstract Oral Diseases pose a major health burden to the world. Diagnosis of Oral Diseases and in particular Periodontal Disease or Gingivitis is expensive, and uneven and inaccessible to a lot of people. Deep learning approaches can help in quick screening and initial diagnosis of Periodontal disease that can help accessibility and lower costs. Previous […]
  • Social Sciences, Social Sciences, Humanities & Policy
    Abstract This is a qualitative pilot study that explores the ways that Korean adolescents told and interpreted their schooling experiences across selective educational contexts in South Korea and the United States. Rather than treating the Korean and U.S. educational contexts as directly comparable national systems, this study places emphasis on three Korean students’ experiences in […]
  • AI & Machine Learning, Computing, Data & AI, Life Sciences, Neuroscience
    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 […]
  • Engineering, Mechanical Engineering
    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 […]
  • Social Sciences, Social Sciences, Humanities & Policy
    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 […]

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