Results 191 to 200 of about 166,792,772 (228)
Interpretable deep neural network identifies robust biomarkers for diseases with mechanistic insights from omics data. [PDF]
Hu X, Ma Y, Ming R, Zhang H, Jiang H.
europepmc +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Probing the binding stability of organic UV filters to human SLC transporters using AlphaFold and molecular dynamics simulations. [PDF]
Xing R +7 more
europepmc +1 more source
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
Energy evolution and catastrophic instability of excavated consequent slopes: A cusp catastrophe-based criterion and gradient-anchoring reinforcement strategy. [PDF]
Liu Z +7 more
europepmc +1 more source
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source
Online TCP Throughput Map Maintenance Under Budget-Constrained Vehicular Sensing. [PDF]
Hu W, Ohsita Y, Shimonishi H.
europepmc +1 more source
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
Self-supervised graph contrastive learning for scRNA-seq clustering. [PDF]
Wu T.
europepmc +1 more source

