Results 101 to 110 of about 6,074,244 (344)

A National Library and Museum of the History of Chemistry and Cognate Arts and Sciences [PDF]

, 1900
Fred. Hoffmann
openalex   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

Advanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi, Saeed Kamarian, Mahdi Bodaghi, Saeed Saber‐Samandari, Jung‐il Song   +4 more
wiley   +1 more source

The U.S. National Library of Medicine and standards for electronic health records: One thing led to another. [PDF]

Inf Serv Use, 2022
McDonald CJ, Humphreys BL.
europepmc   +1 more source

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

Advanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

Fungal contaminants of indoor air in the National Library of Greece

Aerobiologia, 2020
I. Pyrri, Efstathia Tripyla, Anna Zalachori, Maria Chrysopoulou, A. Parmakelis, E. Kapsanaki-Gotsi   +5 more
semanticscholar   +1 more source

Donald A.B. Lindberg and the U.S. National Library of Medicine transformed biomedical and health informatics. [PDF]

Inf Serv Use, 2022
Miller RA, Shortliffe EH.
europepmc   +1 more source

The National Central Library [PDF]

, 1935

openalex   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

The multiple dimensions of expanded access to health information: Don Lindberg and the U.S. National Library of Medicine. [PDF]

Inf Serv Use, 2022
Humphreys BL.
europepmc   +1 more source