Results 231 to 240 of about 1,662,275 (307)
3D investigation and modeling of the geometric effects on porosity in packed beds
Abstract In porous beds, physical boundaries restrict particle arrangement, leading to inhomogeneous porosity. This paper reports on the porosity profiles that are the result of geometric effects on monodisperse packed beds in cylindrical and cubic arrangements. Special focus is given to the influence of edges and corners in cubic geometries.
Bastian Oldach +3 more
wiley +1 more source
Extending BEHRT to UK Biobank: assessing transformer model performance in clinical prediction. [PDF]
Yildiz Y, Nenadic G, Jani M, Jenkins DA.
europepmc +1 more source
Abstract Generating hydrogel beads pertains to many engineering applications. We examined two alginate‐based fluids at three concentrations of alginate, cAG$$ {c}_{\mathrm{AG}} $$. We used the “Map of Misery” to determine which material property (viscosity, elasticity, and inertia) drives droplet formation.
Conor G. Harris +5 more
wiley +1 more source
Abstract This article demonstrates the integration of in‐line mass spectrometry as a process analytical technology (PAT) tool with model‐based soft sensors in a continuous filtration‐drying carousel system for solid–liquid separation (SLS) of crystal slurries.
Inyoung Hur +3 more
wiley +1 more source
BabelFSH-a toolkit for an effective HL7 FHIR-based terminology provision. [PDF]
Wiedekopf J +3 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Enhancing Safe Orthopedic Rehabilitation: Evaluating Documentation Practices for Mobilization and Weight-Bearing Protocols. [PDF]
Ali AS, Oladeji EO, Kainth GS.
europepmc +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Modifying Diagnostic Terminology May Promote Evidence-Based Care.
Nainar SMH.
europepmc +1 more source

