Robust spatial phase prediction from paired intensities using multi-scale wavelets and aberration sensing network. [PDF]
Huang Y, Zhang H, He Y, Yang Z, Liu X.
europepmc +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Study on electromagnetic characteristics of cylindrical hole defect in variable parameter traction motor shaft based on eddy current effect. [PDF]
Song M +7 more
europepmc +1 more source
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
Decrypting the Unusual Structure and σ-Hole Interactions of the XC(NO<sub>2</sub>)<sub>3</sub> (X=F, Cl, Br, and I) Compounds Using Quasi-Atomic Orbitals. [PDF]
Guidez EB.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Safe image transmission with hybrid quantum key-genetic encryption via spatial modulation assisted NOMA. [PDF]
Thennavan S, Jayapalan A.
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Sparse Bayesian multidimensional scaling(s). [PDF]
Sheth A, Smith A, Holbrook AJ.
europepmc +1 more source
Self‐Sensing Artificial‐Muscle‐Empowered Humanlike Perception, Interaction, and Positioning
The proposed self‐sensorized artificial muscle (SSAM) can sense its length change as small as 0.01 mm via a seamlessly integrated multi‐segment induction coil. The SSAM provides accurate length information regardless of its loadings, driving pressure, or muscle design, adequate for robust data‐driven feedback control.
Houping Wu +6 more
wiley +1 more source

