A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas +4 more
wiley +1 more source
Revealing Protein–Protein Interactions Using a Graph Theory‐Augmented Deep Learning Approach
This study presents a fast, cost‐efficient approach for classifying protein–protein interactions by integrating graph‐theory parametrization with deep learning (DL). Multiscale features extracted from graph‐encoded polarized‐light microscopy (PLM) images enable accurate prediction of binding strengths.
Bahar Dadfar +5 more
wiley +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
How do plant demographic and ecological traits combined with social dynamics and human traits affect woody plant selection for medicinal uses in Benin (West Africa)? [PDF]
Ahoyo CC +5 more
europepmc +1 more source
Corrigendum: Identifying hotspots of woody plant diversity and their relevance with home ranges of the critically endangered gibbon (Nomascus hainanus) across forest landscapes within a tropical nature reserve. [PDF]
Li X, Zhang Z, Long W, Zang R.
europepmc +1 more source
Woody plant taxonomic, functional, and phylogenetic diversity decrease along elevational gradients in Andean tropical montane forests: Environmental filtering and arrival of temperate taxa. [PDF]
Bañares-de-Dios G +8 more
europepmc +1 more source
Oligocene and early Miocene phytolits from CRP-2/2A and CRP-3, Victoria Land Basin, Antarctica [PDF]
Thorn, V. C.
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