Results 141 to 150 of about 38,192 (305)
ABSTRACT Using survey and discrete choice experiment data, we examined US specialty crop growers' preferences for marketing contract attributes in the context of emerging blockchain‐based technologies and expanding traceability initiatives. Results show that farmers preferred traditional written contracts but might be willing to accept digital ...
Elizabeth Canales +3 more
wiley +1 more source
Sustainability trends and consumer perceived risks towards private labels
Vitally Cherenkov +7 more
doaj +1 more source
In order to be more successful and achieve higher profits, supermarket chains have recognized and used the possibility of creating their own brands. Creating private labels, modeled after manufacturer’s products, enables differentiation from competitors,
Zdravko Tolušić +2 more
doaj
Measures of store loyalty in French food retailing [PDF]
Store loyalty is an important issue for retailers since it defines one way in which consumers are attached to stores. However, store loyalty is not unidimensional and there are different ways of measuring it.
Valérie Orozco, Fabian Bergès
core
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Portuguese Retailers’ Motivations to Adopt Front of Pack Nutrition Labels: A Qualitative Analysis
Nutrition is an important food marketing differentiation criterion. There is growing evidence of the relation between diets and health conditions. Thus there is a potential conflict between industry and public health authorities over the use of nutrition
Souza Monteiro, Diogo M. +2 more
core +1 more source
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng +4 more
wiley +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
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
Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source

