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Abstract Chronic wounds represent a longstanding clinical problem due to impaired angiogenesis due to insufficient activation of vascular endothelial growth factor receptor 2 (VEGFR2). In this investigation, we used comp...

Abstract Accurate monitoring and prediction of Chlorophyll-a (Chl-a) concentrations are critical for protecting desalination systems from algal blooms. This study presents an advanced framework employing the Graph Neural...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Abstract Nanofluids have emerged as promising heat transfer media due to their superior thermal performance associated to conventional fluids, yet their behavior under mutual impacts of radiation, heat source/sink, and m...

Abstract Internet of Things (IoT) is increasingly realized through large scale deployments of heterogeneous devices and gateways operating under strict energy budgets and interference limited links, which motivates relia...

Abstract Human social behaviors involve complex interactions between individuals, and understanding how interbrain neural activity reflects and predicts these interactions is critical for advancing social cognitive neuro...

Abstract Quantum Machine Learning (QML) is emerging as a promising technology for tackling complex computational challenges, although its practical implementation faces significant obstacles owed to the inherent noise in...

Abstract This paper presents an intelligent coordinated control framework for a hybrid standalone microgrid integrating solar photovoltaic, wind, and battery energy storage systems. The proposed Radial Basis Function Neu...

Abstract Collaborative filtering and neural recommendation models have advanced substantially over the past decade, yet they frequently struggle to capture the fine-grained structure of user preferences and the rich, mul...

Abstract The growing deployment of grid-connected voltage source inverters (GC-VSIs) in the smart grids poses some significant issues that include harmonic distortion, grid impedance fluctuations, nonlinear loading, and ...

Abstract Vision Transformers have demonstrated strong performance across diverse visual tasks; however, their high computational cost due to long token sequences remains a critical challenge. Sequence reduction via pooli...

Abstract Argument annotation in medical drug reviews is a challenging task due to noisy user-generated content, domain-specific terminology, and subjective expressions of medication efficacy and adverse effects. While ar...

Abstract The importance of fear level detection in affective computing using physiological signals has not been extensively explored. Accurately detecting fear responses facilitates real-time emotional monitoring and imp...