Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Research on the impact of traditional Chinese medicine registration innovation-oriented policies and enterprises performance: an empirical analysis based on listed enterprises in China. [PDF]
Front Public HealthLv J, Lu K, Xie M, Sun W, Liu Y.
europepmc +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
Advanced Intelligent Discovery, EarlyView.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
The Impact of Green FinTech Promote Corporate Carbon Neutrality: Evidence from the Perspective of Financing Incentives and Scale Quality. [PDF]
Entropy (Basel)Zhuang L, Wu C.
europepmc +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
Can data assetization drive high-quality enterprise development?-Evidence from China's "Specialized, refined, unique, and innovative" SMEs. [PDF]
PLoS OneLi L, Zhu J.
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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
The Influence of the Site of Recording and Benchtop and Portable NIRS Equipment on Predicting the Sensory Properties of Iberian Ham. [PDF]
FoodsRevilla I +7 more
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Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context
Agribusiness, EarlyView.
Alexis H. Villacis
wiley +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley +1 more source