AIMC Topic: Computer Simulation

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iDVEIP: A computer-aided approach for the prediction of viral entry inhibitory peptides.

Proteomics Jan 23, 2024
With the notable surge in therapeutic peptide development, various peptides have emerged as potential agents against virus-induced diseases. Viral entry inhibitory peptides (VEIPs), a subset of antiviral peptides (AVPs), offer a promising avenue as e...
Virus Internalization COVID-19 COVID-19 Drug Treatment Computer Simulation Machine Learning Software Humans SARS-CoV-2 Antiviral Agents Peptides Computational Biology
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Designing optimal behavioral experiments using machine learning.

eLife Jan 23, 2024
Computational models are powerful tools for understanding human cognition and behavior. They let us express our theories clearly and precisely and offer predictions that can be subtle and often counter-intuitive. However, this same richness and abili...
Machine Learning Computer Simulation Humans Cognition Bayes Theorem Awareness
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A magnetic multi-layer soft robot for on-demand targeted adhesion.

Nature communications Jan 20, 2024
Magnetic soft robots have shown great potential for biomedical applications due to their high shape reconfigurability, motion agility, and multi-functionality in physiological environments. Magnetic soft robots with multi-layer structures can enhance...
Tissue Adhesions Motion Computer Simulation Humans Magnetic Phenomena Robotics Physical Phenomena
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Forward dynamics computational modelling of a cyclist fall with the inclusion of protective response using deep learning-based human pose estimation.

Journal of biomechanics Jan 19, 2024
Single bicycle crashes, i.e., falls and impacts not involving a collision with another road user, are a significantly underestimated road safety problem. The motions and behaviours of falling people, or fall kinematics, are often investigated in the ...
Humans Computer Simulation Bicycling Deep Learning Accidents, Traffic Motion
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Systematic review using a spiral approach with machine learning.

Systematic reviews Jan 17, 2024
With the accelerating growth of the academic corpus, doubling every 9 years, machine learning is a promising avenue to make systematic review manageable. Though several notable advancements have already been made, the incorporation of machine learnin...
Computer Simulation Machine Learning Systematic Reviews as Topic
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Pattern recognition in the nucleation kinetics of non-equilibrium self-assembly.

Nature Jan 17, 2024
Inspired by biology's most sophisticated computer, the brain, neural networks constitute a profound reformulation of computational principles. Analogous high-dimensional, highly interconnected computational architectures also arise within information...
Pattern Recognition, Automated Kinetics Microscopy, Atomic Force DNA Neural Networks, Computer Microscopy, Fluorescence Computer Simulation
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Segmenting mechanically heterogeneous domains via unsupervised learning.

Biomechanics and modeling in mechanobiology Jan 13, 2024
From biological organs to soft robotics, highly deformable materials are essential components of natural and engineered systems. These highly deformable materials can have heterogeneous material properties, and can experience heterogeneous deformatio...
Machine Learning Computer Simulation Biomechanical Phenomena Unsupervised Machine Learning Robotics
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State identification for a class of uncertain switched systems by differential neural networks.

Network (Bristol, England) Jan 11, 2024
This paper presents a non-parametric identification scheme for a class of uncertain switched nonlinear systems based on continuous-time neural networks. This scheme is based on a continuous neural network identifier. This adaptive identifier guarante...
Neural Networks, Computer Algorithms Humans Nonlinear Dynamics Uncertainty Computer Simulation Gait
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Designing a use-error robust machine learning model for quantitative analysis of diffuse reflectance spectra.

Journal of biomedical optics Jan 11, 2024
SIGNIFICANCE: Machine learning (ML)-enabled diffuse reflectance spectroscopy (DRS) is increasingly used as an alternative to the computation-intensive inverse Monte Carlo (MCI) simulation to predict tissue's optical properties, including the absorpti...
Neural Networks, Computer Computer Simulation Spectrum Analysis Monte Carlo Method Phantoms, Imaging
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Distributed continuous-time accelerated neurodynamic approaches for sparse recovery via smooth approximation to L-minimization.

Neural networks : the official journal of the International Neural Network Society Jan 10, 2024
This paper develops two continuous-time distributed accelerated neurodynamic approaches for solving sparse recovery via smooth approximation to L-norm minimization problem. First, the L-norm minimization problem is converted into a distributed smooth...
Neural Networks, Computer Computer Simulation Consensus
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