Results 241 to 250 of about 36,817,910 (309)

Modular design and supervisory control for enhanced economic resilience in continuous pharmaceutical manufacturing

AIChE Journal, EarlyView.
Abstract Conventional continuous plants use fixed‐capacity equipment, resulting in high capital risk and suboptimal performance under fluctuating demands. To address these, this study proposes an integrated framework for modular process design and supervisory control capable of adapting to demand uncertainty for long‐term economic viability.
T. Asrav, M. Alvarado‐Morales, G. Sin
wiley   +1 more source

Strategic evaluation on capacity development : strengthening the core and the periphery; organizational case study of the Peru Economic and Social Research [PDF]

, 2008
Arsenault, Mariane, Rojas, Katrina
core  

Learning regime‐dependent governing equations: A symbolic decision tree approach

AIChE Journal, EarlyView.
Abstract Many chemical engineering systems are governed by mechanisms that switch across operating regimes, making the data‐driven discovery of regime‐dependent governing equations essential for predictive modeling, optimization, and control. We propose symbolic decision trees for the data‐driven discovery of regime‐dependent governing equations.
Ilias Mitrai, Tongjia Liu, Gabriel E. Sanoja   +2 more
wiley   +1 more source

Short-Term Exposure to Ambient Air Pollution and Hospitalization Risks and Costs on Type 2 Diabetes With Three Typical Comorbidities in Sichuan, China: A Time-Stratified Case-Crossover Study. [PDF]

Geohealth
Jiang W, Chen H, Zhou Y, Li H, Lian L, Yang L.   +5 more
europepmc   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

Short-term gaseous and particulate air pollution exposure and risk of acute kidney injury: a 12-year case-crossover study [2013-2024] in Guangzhou, China. [PDF]

J Thorac Dis
Chen Y, Liang Z, Zhang K, Cao W, Chen Y, Zhou C, Dong G, Sun B, Cheng ZJ.   +8 more
europepmc   +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

Association between short-term air pollution exposure and the risk of fatal recurrence within 1 year in patients with first-episode acute hemorrhagic stroke: a time-stratified case-crossover study. [PDF]

Front Public Health
Gu X, Liu J, Wang H, Hou D, Li A, Xu L, He J.   +6 more
europepmc   +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