Simulation with Monte Carlo methods to focus quality improvement efforts on interventions with the greatest potential for reducing PACU length of stay: a cross-sectional observational study. [PDF]
BMJ Open QualJones JH, Fleming N.
europepmc +1 more source
The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry
Agribusiness, EarlyView.ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley +1 more source
A Comparison of Green, Delta, and Monte Carlo Methods to Select an Optimal Approach for Calculating the 95% Confidence Interval of the Population-attributable Fraction: Guidance for Epidemiological Research. [PDF]
J Prev Med Public HealthLee S +6 more
europepmc +1 more source
AI in chemical engineering: From promise to practice
AIChE Journal, EarlyView.Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
Advanced Intelligent Discovery, EarlyView.We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
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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
Dynamic Shrinkage Priors for Large Time-Varying Parameter Regressions Using Scalable Markov Chain Monte Carlo Methods. [PDF]
Stud Nonlinear Dyn EconomHauzenberger N, Huber F, Koop G.
europepmc +1 more source