Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
Absolute Receptor Occupancy, Not Rate of Decline, Predicts Relapse. [PDF]
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europepmc +1 more source
Structured generative modelling of earthquake response spectra with hierarchical latent variables in hyperbolic geometry. [PDF]
Wright A, Fayaz J.
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The effect of a familiarization critical speed testing session on critical speed determination during treadmill running. [PDF]
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Simulation Study of a Hyperbolic Linear Ion Trap with Asymmetric Curvature Radii. [PDF]
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Integral Betti signatures of brain, climate and financial networks compared to hyperbolic, Euclidean and spherical models. [PDF]
Caputi L, Pidnebesna A, Hlinka J.
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Soliton dynamics in the stochastic nonlinear Schrödinger equation with self-phase modulation and multiplicative white noise. [PDF]
Shehab MF, Ahmed HM, Hussein HH.
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