The effect of simulation-based laboratory training on undergraduate nursing students' clinical skill, satisfaction, and self-confidence. [PDF]
Altinbas BC +8 more
europepmc +1 more source
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling +15 more
wiley +1 more source
Nursing Students' Satisfaction and Self-Confidence After Short-Term Clinical Preparation: A Cross-Sectional Study. [PDF]
Alhejaili AA +6 more
europepmc +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 more
wiley +1 more source
The Mediating Role of Self-Confidence in Medical Students' Attitudes and Clinical Performance Toward People with Disability. [PDF]
Yazbeck Karam VG +5 more
europepmc +1 more source
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Effect of video-based education on practical skills and self-confidence in citation writing among nursing students: A pre-experimental design. [PDF]
Amro N, Qtait M, Dar Soboh Y.
europepmc +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
Developing Traits of Self-Confidence and Intrinsic Motivation in Students with Severe Special Educational Needs in Physical Education Lessons. [PDF]
Garbenis S, Kaffemaniene I.
europepmc +1 more source

