Results 121 to 130 of about 864,739 (333)
, 2017 This study was conducted to determine the effects of almond (Terminalia catappa L.) fruit parts (hull and drupe) extracts on key enzymes (arginase, angiotensin-1-converting enzyme, α-amylase and α-glucosidase) relevant to erectile dysfunction, type-2 ...
Stephen Adeniyi Adefegha +3 more
semanticscholar +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.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
A Submersible Power Station: Part B Propulsion Systems
Journal of Marine Science and EngineeringNuclear power continues to be a great promise in the green revolution, as it is a cost-effective, low-emission, and safer alternative to fossil fuels that is capable of continuous operation.
Jon Serna +4 more
doaj +1 more source
Internship at Hull and Hull LLP
, 2020 Over the summer of 2020 I completed a remote internship at Hull & Hull LLP, an estates law firm in Toronto, for the SASAH experiential learning course. Hull & Hull handles estates and trusts litigation. I worked on digitizing charts for a passing of accounts (which is a court audit of a fiduciary’s accounting) for which there have been a considerable ...
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Hulls of Linear Codes over Non-Unitary Rings of Four Elements
MathematicsIn this paper, we explore the hull of linear codes over the non-unitary rings of order four, namely E, I and H. Initially, we determine the binary associated codes of the hull over each ring; then, we characterize the hulls in terms of these codes ...
Sarra Manseri +3 more
doaj +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
The Interoperability Challenge in DFT Workflows Across Implementations
Advanced Intelligent Discovery, EarlyView.Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source