Eye irritation (EI) toxicity poses critical challenges in chemical safety assessment, demanding alternatives to ethically contentious animal testing. We present the first integrative framework combining computational prediction with experimental vali...
Brain-controlled systems have experienced significant advancements in overall performance, largely driven by continuous optimization and innovation in electroencephalography (EEG) acquisition experimental paradigms and decoding algorithms. However, t...
Recent advances in Deep Reinforcement Learning (DRL) have opened new avenues for sport research. DRL allows virtual agents to learn and solve complex tasks with minimal input, which means that models can be trained with little or no data collection. ...
Clinical pharmacology and therapeutics
Sep 1, 2025
In silico trials, utilizing mathematical models calibrated with clinical data, present a transformative approach to expedite drug development. We propose a virtual trial framework for chronic Hepatitis B, accurately simulating clinical protocols, pat...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Motor control requires sensory feedback, and the nature of this feedback has implications for the tasks of the central nervous system (CNS): for an approximately linear mechanical system (e.g., a freely standing person, a rider on a bicycle), if the ...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
This paper presents the D-type distributed iterative learning control protocol to synchronize fractional-order competitive neural networks with time delay within a finite time frame. Firstly, the input sharing strategy of such desired competitive neu...
While machine learning has gained traction in toxicological assessments, the limited data availability requires the quantification of uncertainty of in silico predictions for reliable decision-making. This study addresses the challenge of predicting ...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
This study examines the global Mittag-Leffler synchronization (GMLS) problem for fractional-order Clifford-valued neural networks (FOCLVNNs) including transmission delays and impulses. Firstly, a novel kind of FOCLVNNs is developed that incorporates ...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
DNA logic circuits are essential building blocks for molecular computers. Traditional molecular logic circuits primarily use basic gate circuits as computational units, achieving complex functions via multiple cascades. However, even simple logical f...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Uncertainties are the main obstacle to improving the control performance of nonlinear systems. To address this challenge, this paper proposes a fixed-time adaptive neural network compensation control method for a class of high-order nonlinear systems...
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