Results 181 to 190 of about 3,242,957 (257)
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Content Validity of a Patient-Reported Measure of Postoperative Recovery. [PDF]
Mueller MG +11 more
europepmc +1 more source
Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen +14 more
wiley +1 more source
Taking Fun Seriously: A Scoping Review of Frameworks, Outcomes, and Definitions of Fun in Education. [PDF]
Stacey SK +9 more
europepmc +1 more source
NeuroVisio SyncPatch integrates skin‐conformal electromyography (EMG) electrodes with camera‐tracked markers to jointly assess muscle activity and three‐dimensional knee kinematics during rehabilitation. Parallel feedback pathways provide real‐time kinematic guidance during movement and post‐trial neuromuscular feedback.
Bohyung Choi +11 more
wiley +1 more source
The cognitive work of acute care nurses: A hybrid model concept analysis. [PDF]
Benjamin E +4 more
europepmc +1 more source
Molecular doping of conjugated polymers is fundamentally constrained by thermodynamic phase behavior. This Perspective reframes doping efficiency and stability in terms of miscibility limits, binodals, and solvus boundaries, highlighting the role of effective interaction parameters and charge transfer.
Somayeh Kashani +10 more
wiley +1 more source
The association between nonverbal fluency and anomia treatment outcomes in people with post-stroke aphasia. [PDF]
Schwen Blackett D +4 more
europepmc +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source

