AIMC Topic: Computer Simulation

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Should Artificial Intelligence Play a Durable Role in Biomedical Research and Practice?

International journal of molecular sciences
During the last decade, artificial intelligence (AI) was applied to nearly all domains of human activity, including scientific research. It is thus warranted to ask whether AI thinking should be durably involved in biomedical research. This problem w...

Multibody system dynamics for bio-robotic design and simulation based on inching-locomotion caterpillar's gait: MBD-ILAR method.

Bioinspiration & biomimetics
Inching-locomotion caterpillars (ILAR) inspire the design of 'inch-worm' robots with biomimicry features, that can be adapted to different environments, such as natural, man-made, or other planets. Therefore, this work defines a novel mathematical me...

Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.

PLoS computational biology
Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous f-I curves and spike frequency adaptation are known to place single neurons in optimal coding regimes when facing changing stimuli. Yet, it is still u...

A novel strategy for the MPPT in a photovoltaic system via sliding modes control.

PloS one
This paper proposes a robust maximum power point tracking algorithm based on a super twisting sliding modes controller. The underlying idea is solving the classical trajectory tracking control problem where the maximum power point defines the referen...

Neurocontrol for fixed-length trajectories in environments with soft barriers.

Neural networks : the official journal of the International Neural Network Society
In this paper we present three neurocontrol problems where the analytic policy gradient via back-propagation through time is used to train a simulated agent to maximise a polynomial reward function in a simulated environment. If the environment inclu...

AI-Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Aortic stenosis (AS) is the most common valvular heart disease in developed countries. High-fidelity preclinical models can improve AS management by enabling therapeutic innovation, early diagnosis, and tailored treatment planning. However, their use...

Deep Learning Prediction of Drug-Induced Liver Toxicity by Manifold Embedding of Quantum Information of Drug Molecules.

Pharmaceutical research
PURPOSE: Drug-induced liver injury, or DILI, affects numerous patients and also presents significant challenges in drug development. It has been attempted to predict DILI of a chemical by in silico approaches, including data-driven machine learning m...

Toward Dose Prediction at Point of Design.

Journal of medicinal chemistry
Human dose prediction (HDP) is a useful tool for compound optimization in preclinical drug discovery. We describe here our exclusively in silico HDP strategy to triage compound designs for synthesis and experimental profiling. Our goal is a model tha...

Output sampling synchronization and state estimation in flux-charge domain memristive neural networks with leakage and time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This paper theoretically explores the coexistence of synchronization and state estimation analysis through output sampling measures for a class of memristive neural networks operating within the flux-charge domain. These networks are subject to const...

A simple remedy for failure modes in physics informed neural networks.

Neural networks : the official journal of the International Neural Network Society
Physics-informed neural networks (PINNs) have shown promising results in solving a wide range of problems involving partial differential equations (PDEs). Nevertheless, there are several instances of the failure of PINNs when PDEs become more complex...