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UnknownData driven inference for the repulsive exponent of the Lennard-Jones potential in molecular dynamics simulations.
The Lennard-Jones (LJ) potential is a cornerstone of Molecular Dynamics (MD) simulations and among the most widely used computational kernels in science. The LJ potential models atomistic attraction and repulsion with century old prescribed parameters (q = 6, p = 12, respectively), originally relate...
S-EPMC5707428 | biostudies-literature
UnknownGenerative learning for forecasting the dynamics of high-dimensional complex systems.
We introduce generative models for accelerating simulations of high-dimensional systems through learning and evolving their effective dynamics. In the proposed Generative Learning of Effective Dynamics (G-LED), instances of high dimensional data are down sampled to a lower dimensional manifold that ...
S-EPMC11480383 | biostudies-literature
UnknownEfficient collective swimming by harnessing vortices through deep reinforcement learning.
Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fi...
S-EPMC6003313 | biostudies-literature
UnknownScientific multi-agent reinforcement learning for wall-models of turbulent flows.
The predictive capabilities of turbulent flow simulations, critical for aerodynamic design and weather prediction, hinge on the choice of turbulence models. The abundance of data from experiments and simulations and the advent of machine learning have provided a boost to turbulence modeling efforts....
S-EPMC8931082 | biostudies-literature
UnknownBayesian selection for coarse-grained models of liquid water.
The necessity for accurate and computationally efficient representations of water in atomistic simulations that can span biologically relevant timescales has born the necessity of coarse-grained (CG) modeling. Despite numerous advances, CG water models rely mostly on a-priori specified assumptions. ...
S-EPMC6331618 | biostudies-literature
UnknownThe mouse retina in 3D: quantification of vascular growth and remodeling.
The mouse retina has become a prominent model for studying angiogenesis. The easy access and well-known developmental progression have significantly propelled our ability to examine and manipulate blood vessels in vivo. Nonetheless, most studies have restricted their evaluations to the superficial p...
S-EPMC8077100 | biostudies-literature
UnknownThe stress-free state of human erythrocytes: Data-driven inference of a transferable RBC model.
The stress-free state (SFS) of red blood cells (RBCs) is a fundamental reference configuration for the calibration of computational models, yet it remains unknown. Current experimental methods cannot measure the SFS of cells without affecting their mechanical properties, whereas computational postul...
S-EPMC10147838 | biostudies-literature
UnknownStructure and response to flow of the glycocalyx layer.
The glycocalyx is a sugar-rich layer located at the luminal part of the endothelial cells. It is involved in key metabolic processes and its malfunction is related to several diseases. To understand the function of the glycocalyx, a molecular level characterization is necessary. In this article, we ...
S-EPMC3907246 | biostudies-literature
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