Results 171 to 180 of about 4,718,637 (273)

Major Adverse Cognitive Events (MACE-Cog): A New "MACE" Framework for Cognitive Outcomes in Cardiovascular Diseases and Stroke. [PDF]

open access: yesCirculation
Ganesh A   +19 more
europepmc   +1 more source

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

open access: yesAdvanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter   +10 more
wiley   +1 more source

Incidence of dementia and mild cognitive impairment in two Indigenous Bolivian cohorts. [PDF]

open access: yesAlzheimers Dement
Gatz M   +18 more
europepmc   +1 more source

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

open access: yesAdvanced Engineering Materials, EarlyView.
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

Non‐Additive Criteria Assessment in Sustainability Evaluation of High Entropy Alloys: A Toxicity‐Weighted Framework

open access: yesAdvanced Engineering Materials, EarlyView.
Sustainability assessment requires methodologies that appropriately distinguish between additive and non‐additive material properties. A toxicity‐weighted scoring system is developed and applied that accounts for the disproportionate influence of highly toxic constituents through nonlinear weighting functions, providing more realistic estimates than ...
Seth Mehalic   +2 more
wiley   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
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

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