Results 111 to 120 of about 15,449 (210)

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

open access: yesAgribusiness, 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

Food Prices and Inflation Expectations in New Zealand

open access: yesAgribusiness, EarlyView.
ABSTRACT Food prices are conspicuous, and spending on food constitutes a considerable share of household expenditure. In this study, we use partially identified Bayesian structural vector autoregression models to analyze the effects of food price shocks on core inflation and 1‐ and 5‐year inflation expectations in New Zealand.
Puneet Vatsa   +2 more
wiley   +1 more source

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

Effects of Outsourced Agricultural Extension Services on the Technical Efficiency and Financial Returns of Soybean Farms in Northern Cameroon

open access: yesAgribusiness, EarlyView.
ABSTRACT In the agricultural landscape of most developing countries, the last decade has witnessed the expansion of outsourced agricultural extension services. Private firms and nongovernmental organizations focused on delivering agricultural extension and advisory services to farmers have emerged.
Boris D. Soh Wenda   +3 more
wiley   +1 more source

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

open access: yesAIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

open access: yesAdvanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee   +3 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia   +1 more
wiley   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

open access: yesAdvanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc   +8 more
wiley   +1 more source

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