Results 151 to 160 of about 3,256,358 (354)

Warp-X: a new exascale computing platform for beam-plasma simulations

, 2018
Turning the current experimental plasma accelerator state-of-the-art from a promising technology into mainstream scientific tools depends critically on high-performance, high-fidelity modeling of complex processes that develop over a wide range of space ...
Almgren, A., Bell, J., Ge, L., Grote, D. P., Hogan, M., Kononenko, O., Lehe, R., Myers, A., Ng, C., Park, J., Ryne, R., Shapoval, O., Thevenet, M., Vay, J. -L., Zhang, W.   +14 more
core   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +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

Exploring and retrieving sequence and metadata for species across the tree of life with NCBI Datasets

Scientific Data
To explore complex biological questions, it is often necessary to access various data types from public data repositories. As the volume and complexity of biological sequence data grow, public repositories face significant challenges in ensuring that the
Nuala A. O’Leary, Eric Cox, J. Bradley Holmes, W. Ray Anderson, Robert Falk, Vichet Hem, Mirian T. N. Tsuchiya, Gregory D. Schuler, Xuan Zhang, John Torcivia, Anne Ketter, Laurie Breen, Jonathan Cothran, Hena Bajwa, Jovany Tinne, Peter A. Meric, Wratko Hlavina, Valerie A. Schneider   +17 more
doaj   +1 more source

National Reference Library Plans [PDF]

, 1956
H. G. Thornton, Diego R. Martín
openalex   +1 more source

National strategy for health research and innovation [PDF]

, 2013
In 2011, the Malta Council for Science and Technology (MCST) commissioned the Development of a dedicated strategy for health research and innovation in line with its mandate from Government to identify areas of national priority and design and to also ...
Cassingena Harper, Jennifer, Castillo, Nadine, Cordina, Gordon, Lapira, Alec, Mifsud, Janet, Saliba Scerri, Ramona, Sammut, Nicholas, Scerri, Christian A.   +7 more
core  

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

The roles of the US National Library of Medicine and Donald A.B. Lindberg in revolutionizing biomedical and health informatics. [PDF]

J Am Med Inform Assoc, 2021
Miller RA, Shortliffe EH.
europepmc   +1 more source

The National Library of Television [PDF]

, 1967
Lillian G. Brown
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