Results 181 to 190 of about 649,643 (307)
Testing the Marketing Performance of German Wheat Farmers
ABSTRACT This paper analyses the marketing performance of wheat farmers in Germany. Wheat sales data from 465 individual farms over a 12‐year period are used to test against different market benchmarks. Market benchmarks are constructed by simulating passive trading agents using regional wheat prices.
Franziska Potts, Jens‐Peter Loy
wiley +1 more source
ABSTRACT Market‐based solutions are increasingly tested to address aflatoxin issues in peanuts in developing countries. Although previous studies have found that Haitian grocery store shoppers are willing to pay a 21% premium for peanut butter with levels of aflatoxin that meet international standards, no information is available for the much larger ...
Phendy Jacques +2 more
wiley +1 more source
Consumer Preferences for Craft Beer: The Interplay of Localness and Advertising Language
ABSTRACT This study explores the influence of the language of the label, origin of production, and origin of brewing ingredients on Croatian consumers' preferences and willingness to pay for organic craft beer. Employing an online survey and a choice experiment among 223 Croatian alcohol consumers, we find that while there's a willingness to pay a ...
Marija Cerjak +2 more
wiley +1 more source
Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks. [PDF]
Wei Q, Chen T, Xu R, He Y, Gui L.
europepmc +1 more source
Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren +6 more
wiley +1 more source
Analysis and prediction of the critical regions of antimicrobial peptides based on conditional random fields. [PDF]
Chang KY, Lin TP, Shih LY, Wang CK.
europepmc +1 more source
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang +5 more
wiley +1 more source
Sparse reconstruction of compressive sensing MRI using cross-domain stochastically fully connected conditional random fields. [PDF]
Li E +4 more
europepmc +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
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla +4 more
wiley +1 more source

