Results 101 to 110 of about 2,888 (202)
A comprehensive EEG dataset for investigating visual touch perception. [PDF]
Smit S +5 more
europepmc +1 more source
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova +2 more
wiley +1 more source
Intelligent diagnosis of major depressive disorder with edge convolution and contrastive learning. [PDF]
Long D, Zhu C, Xiong L, Long Z, Dong F.
europepmc +1 more source
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Machine learning-based model for triage-stage prediction of emergency department disposition. [PDF]
Yoshimura K, Moriguchi T.
europepmc +1 more source
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley +1 more source
Beyond Static Assessment: A Proof-of-Concept Evaluation of Functional Data Analysis for Assessing Physiological Responses to High-Intensity Effort. [PDF]
Odriozola A +4 more
europepmc +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Interpretable Machine Learning for Identifying Key Variables Influencing Gold Recovery and Grade. [PDF]
Devasahayam S.
europepmc +1 more source
Sol–gel‐derived ZnO–rGO hybrid nanoparticles enable Al7075 powder‐metallurgy composites to achieve concurrent gains in hardness and thermal conductivity while markedly lowering friction and wear. The hybrid architecture couples ZnO‐based load support with rGO‐assisted lamellar sliding and heat spreading, revealing a promising route toward lightweight ...
Bunyamin Aksakal +3 more
wiley +1 more source

