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Resonance-Induced Therapeutic Technique for Skin Cancer Cells.
Ultrasound Med Biol
January 2025
Institute of Biomedical Technologies, Auckland University of Technology, Auckland City, 1010, Auckland, New Zealand. Electronic address:
Objective: This study aims to evaluate the viability of a hypothesis for selective targeting of skin cancer cells by exploiting the spectral gap with healthy cells using analytical and numerical simulation.
Methods: The spectral gap was first identified using a viscoelastic dynamic model, with the physical and mechanical properties of healthy and cancerous skin cells deduced from previous experimental studies conducted on cell lines. The outcome of the analytical simulation was verified numerically using modal and harmonic analysis.
Quantum mixed-state self-attention network.
Neural Netw
January 2025
Mechanical, Electrical and Information Engineering College, Putian University, Putian, 351100, China.
Attention mechanisms have revolutionized natural language processing. Combining them with quantum computing aims to further advance this technology. This paper introduces a novel Quantum Mixed-State Self-Attention Network (QMSAN) for natural language processing tasks.
View Article and Find Full Text PDFOral configuration-dependent variability of the metrics of exhaled respiratory droplets during a consecutive coughing event.
Comput Methods Programs Biomed
January 2025
Faculty of Engineering Sciences, Kyushu University, Fukuoka, Japan.
Background And Objective: Coughing events are eruptive sources of virus-laden droplets/droplet nuclei. These increase the risk of infection in susceptible individuals during airborne transmission. The oral cavity functions as an exit route for exhaled droplets.
View Article and Find Full Text PDFChange surface regression for nonlinear subgroup identification with application to warfarin pharmacogenomics data.
Biometrics
January 2025
Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Singapore.
Pharmacogenomics stands as a pivotal driver toward personalized medicine, aiming to optimize drug efficacy while minimizing adverse effects by uncovering the impact of genetic variations on inter-individual outcome variability. Despite its promise, the intricate landscape of drug metabolism introduces complexity, where the correlation between drug response and genes can be shaped by numerous nongenetic factors, often exhibiting heterogeneity across diverse subpopulations. This challenge is particularly pronounced in datasets such as the International Warfarin Pharmacogenetic Consortium (IWPC), which encompasses diverse patient information from multiple nations.
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