Results 141 to 150 of about 2,962 (254)

Protection Motivation Theory and Farmers' Participation in Futures Markets: Evidence From Germany

open access: yesAgribusiness, EarlyView.
ABSTRACT This study examines why German farmers show limited adoption of commodity futures contracts despite substantial price volatility, applying Protection Motivation Theory (PMT) to understand the cognitive processes driving participation decisions in futures markets. Survey data from 303 German farmers collected in 2024 were analyzed using Partial
Hendrik Wever   +2 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

Applying a NIOSH Industry and Occupation Coding tool to evaluate occupational risk of SARS-CoV-2 infection in pregnant women. [PDF]

open access: yesDiscov Public Health
Liu CL   +6 more
europepmc   +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

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

open access: yesAdvanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta   +3 more
wiley   +1 more source

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