Results 81 to 90 of about 153,497 (234)

Heterogeneity in Food Price Inflation Convergence Across the EU: Evidence From Club Dynamics and Structural Breaks

Agribusiness, EarlyView.
ABSTRACT This study examines food price inflation rate convergence among EU27 Member States from 2005 to 2024, focusing on structural breaks, external shocks, and regional disparities. Using panel unit root tests and club convergence analysis, the findings reveal no overall convergence but identify multiple convergence clubs.
Tibor Bareith, Imre Fertő
wiley   +1 more source

Does a Specialized Niche Market Vegetable Processor Enjoy Bargaining Power?

Agribusiness, EarlyView.
ABSTRACT Agribusiness companies may achieve competitive advantage through specialization within niche markets. One such niche is the fresh‐cut fruit and vegetable market, which has been steadily growing in Germany. This study examines whether the specialization of a German fresh‐cut producer grants it with market power within this niche market.
Nikolas Bublik, Franziska Mittag, Laura Hellstern, Sebastian Hess   +3 more
wiley   +1 more source

Animal‐Based Brands Taking the Plant‐Based Opportunity: A Tasting Experiment Exploring Consumer Acceptance of Plant‐Based Brand Extensions

Agribusiness, EarlyView.
ABSTRACT This study investigates how consumer taste and brand equity perceptions shape the acceptance of plant‐based milk products. Using a blind/informed tasting experiment, we evaluated consumers' willingness to buy (WTB) and taste perception of a plant‐based milk alternative produced by a traditional dairy brand, compared with competing plant‐based ...
Federico Parmiggiani, Mirta Casati, Elena Castellari, Fosca Vezzulli, Veronica Vitali, Milena Lambri, Claudio Soregaroli   +6 more
wiley   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Flexible Memory: Progress, Challenges, and Opportunities

Advanced Intelligent Discovery, EarlyView.
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan, Sen Chen, Minghui Guo, Ziliang Cui, Yujie Du, Jing Liu   +5 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Mirror-symmetry-induced pseudospin filtering of phonons in graphene nanoribbons

New Journal of Physics
Unlike electrons, phonons do not have the charge and spin degrees of freedom. Consequently, it is a big challenge for the control of phonon currents and the design of quantum phonon devices due to the lack of versatile degrees of freedom.
Xiaobin Chen, Shiyu Cui, Yizhi Hu, Kun Yan   +3 more
doaj   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
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

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

Advanced 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