AIMC Topic: Physics

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Machine learning coarse-grained potentials of protein thermodynamics.

Nature communications Sep 15, 2023
A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach this prob...
Machine Learning Thermodynamics Physics Ataxia Telangiectasia Mutated Proteins Molecular Dynamics Simulation
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Physics-informed neural networks to solve lumped kinetic model for chromatography process.

Journal of chromatography. A Sep 9, 2023
Numerical method is widely used for solving the mechanistic models of chromatography process, but it is time-consuming and hard to response in real-time. Physics-informed neural network (PINN) as an emerging technology combines the structure of neura...
Physics Chromatography Neural Networks, Computer Kinetics Computer Simulation
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Enhancing neurodynamic approach with physics-informed neural networks for solving non-smooth convex optimization problems.

Neural networks : the official journal of the International Neural Network Society Aug 25, 2023
This paper proposes a deep learning approach for solving non-smooth convex optimization problems (NCOPs), which have broad applications in computer science, engineering, and physics. Our approach combines neurodynamic optimization with physics-inform...
Neural Networks, Computer Problem Solving Physics Computer Simulation Algorithms
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Prediction of fluid flow in porous media by sparse observations and physics-informed PointNet.

Neural networks : the official journal of the International Neural Network Society Aug 9, 2023
We predict steady-state Stokes flow of fluids within porous media at pore scales using sparse point observations and a novel class of physics-informed neural networks, called "physics-informed PointNet" (PIPN). Taking the advantages of PIPN into acco...
Physical Phenomena Porosity Neural Networks, Computer Physics
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Physics-Guided Generative Adversarial Networks for Sea Subsurface Temperature Prediction.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Sea subsurface temperature, an essential component of aquatic wildlife, underwater dynamics, and heat transfer with the sea surface, is affected by global warming in climate change. Existing research is commonly based on either physics-based numerica...
Physics China Neural Networks, Computer Temperature Machine Learning
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Predicting 3D soft tissue dynamics from 2D imaging using physics informed neural networks.

Communications biology May 18, 2023
Tissue dynamics play critical roles in many physiological functions and provide important metrics for clinical diagnosis. Capturing real-time high-resolution 3D images of tissue dynamics, however, remains a challenge. This study presents a hybrid phy...
Vocal Cords Physics Dogs Algorithms Neural Networks, Computer Imaging, Three-Dimensional Animals
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Physics-informed neural networks for transcranial ultrasound wave propagation.

Ultrasonics Apr 28, 2023
Transcranial ultrasound imaging has been playing an increasingly important role in the non-invasive treatment of brain disorders. However, the conventional mesh-based numerical wave solvers, which are an integral part of imaging algorithms, suffer fr...
Physics Ultrasonic Waves Skull Neural Networks, Computer Computer Simulation
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Physics-Informed Deep-Learning For Elasticity: Forward, Inverse, and Mixed Problems.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 24, 2023
Elastography is a medical imaging technique used to measure the elasticity of tissues by comparing ultrasound signals before and after a light compression. The lateral resolution of ultrasound is much inferior to the axial resolution. Current elastog...
Elasticity Deep Learning Physics Phantoms, Imaging Elastic Modulus
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Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows.

Proceedings of the National Academy of Sciences of the United States of America Mar 29, 2023
Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance and nutrient delivery, as well as edema in pathological conditions such as stroke. However, existing in vivo techniques are limited to sparse velocit...
Physics Blood Flow Velocity Animals Artificial Intelligence Rheology Neural Networks, Computer Mice Brain
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Machine learning for evolutionary-based and physics-inspired protein design: Current and future synergies.

Current opinion in structural biology Mar 21, 2023
Computational protein design facilitates the discovery of novel proteins with prescribed structure and functionality. Exciting designs were recently reported using novel data-driven methodologies that can be roughly divided into two categories: evolu...
Machine Learning Physics Databases, Protein Proteins
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