Results 151 to 160 of about 141,407 (267)

Return‐To‐Work and Working Status After Surgery for Gastric and Esophageal Cancer: A Prospective Observational Study

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
In this multicenter prospective study of 158 working‐age patients undergoing curative‐intent surgery for gastric or esophageal cancer, 78.5% were working at 18 months. Postoperative appetite loss, financial difficulties, and ≥ 10% weight loss at 6 months were associated with non‐working status.
Kentaro Goto   +18 more
wiley   +1 more source

Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization

open access: yesAIChE Journal, EarlyView.
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son   +4 more
wiley   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

open access: yesAdvanced 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

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced 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

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