Results 61 to 70 of about 7,018 (228)
Hydrogen‐powered aviation offers a transformative pathway to zero‐emission flight by eliminating in‐flight CO2 emissions. Key considerations include propulsion systems (fuel cells and hydrogen combustion), cryogenic storage and insulation challenges, infrastructure and cost barriers, and supply‐chain constraints.
Mubasshira +4 more
wiley +1 more source
Abstract Outsourcing pest and disease control (PDC) has grown rapidly worldwide, especially in developing countries. Although numerous studies have investigated various advantages of outsourcing PDC, little is known about its impact on pesticide expenditure.
Pengcheng Wang +2 more
wiley +1 more source
ABSTRACT Using a lab‐in‐the‐field experiment, we investigate how providing information about food miles and pesticide residue influences willingness to pay (WTP) for potatoes among 407 shoppers in Taiwan, split between a supermarket and a farmers market.
Chiu‐Lin Huang +3 more
wiley +1 more source
ABSTRACT The cocoa‐chocolate value chain faces significant environmental and social challenges, driving firms to adopt sustainability strategies ranging from individual practices to third‐party certifications. This study investigates the factors associated with these strategies by analyzing 304 cocoa‐chocolate companies using firm‐level data from the ...
Stella Marschner +3 more
wiley +1 more source
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani +3 more
wiley +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar +3 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
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
Impact of Biomimetic Pinna Shape Variation on Clutter Echoes: A Machine Learning Approach
Bats with dynamic ear structures navigate dense, echo‐rich environments, yet the echoes they receive are highly random. This study shows that machine learning can reliably detect structural signatures in these seemingly chaotic biosonar signals. The results open new directions for biologically inspired sensing, where time‐varying receiver shapes ...
Ibrahim Eshera +2 more
wiley +1 more source

