Results 201 to 210 of about 8,744,702 (255)

Machine learning-based thermoelectric materials screening with physical consistency and uncertainty propagation. [PDF]

PLoS One
Ahmad A, Qureshi MN, Algamdi SA, Faisal S.   +3 more
europepmc   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Precision targeting using machine learning to optimize medication therapy management delivery in value-based care: A quasi-experimental study using real-world evidence. [PDF]

J Manag Care Spec Pharm
Zamran M, Kirkham H, Henschel T, Witt EA, Wonders P, Gill NW.   +5 more
europepmc   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Electrolyte Additive Strategies in Aqueous Zn‐Ion Batteries: Recent Advances and Prospects

Advanced Science, EarlyView.
This article provides a comprehensive overview of the current status and future development directions of AZIBs electrolyte additives in three aspects: stabilizing zinc anodes (uniform deposition, inhibition of dendritic crystals), protecting cathodes (structural stability, inhibition of dissolution), and enhancing electrolyte stability (wider ...
Yuanze Yu, Hongmin Liu, Long Fan, Huakun Liu, Shixue Dou, Guoxiu Wang, Nana Wang, Zhongchao Bai   +7 more
wiley   +1 more source

Thymosin Alpha‐1 Provides Direct Neuroprotection by Engaging the Orexin Receptor HCRTR1 to Suppress Neuronal Necroptosis

Advanced Science, EarlyView.
In this study, we unveil a thymus‐brain endocrine axis wherein Tα1 engages HCRTR1 to inhibit RIPK3‐mediated necroptosis. This study nominates the Tal‐HCRTR1‐RIPK3 axis as a potent and clinically translatable therapeutic target for stroke and neurodegeneration.
Xinmei Kang, Shisi Wang, Liubin Zhang, Mengyan Hu, Xiaotao Su, Yuxin Liu, Qin Qin, Haotong Yi, Liling Yuan, Wei Cai, Lei Wei, Zhengqi Lu   +11 more
wiley   +1 more source

The Role of Artificial Intelligence and Machine Learning in Revolutionizing Probiotic Research. [PDF]

Microorganisms
Nori R, Shariati P.
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source