Results 101 to 110 of about 5,039 (291)
The Relationship Between Interest Rates and Agricultural Commodity Price Dynamics
Agribusiness, EarlyView.ABSTRACT The U.S. Federal Reserve has undertaken several interest rate interventions in the past decade. This study explores the relationship between U.S. corn and soybean prices and Federal Reserve monetary policy interventions, in the short and long run.
Zhining Sun, Ani L. Katchova
wiley +1 more source
How Competitive Is Myanmar's Rice Sector? A Comparison of Production Costs and Efficiency
Agribusiness, EarlyView.ABSTRACT This paper analyzes the cost competitiveness of rice production in Myanmar by examining production costs, cost efficiency, and the potential effect of improving cost efficiency on the country's global competitiveness. To achieve this, we conduct a comparative analysis of production costs among major rice‐producing countries and estimate the ...
Nandar Aye Chan +3 more
wiley +1 more source
, 2017 In this article, a yaw channel controller with linear active disturbance rejection control is proposed for high-performance attitude tracking of an unmanned helicopter.
Rui Ma +4 more
core +1 more source
Agribusiness, EarlyView.ABSTRACT The US hemp market is a new and nascent industry that has been devoid of research for about half a century. This study examined the effects of exogenous shock on price at each phase of the value chain—Farm (hemp biomass), and its impact on prices at other phases of the value chain—Intermediary Processor (crude cannabidiol hemp) and Final ...
Solomon Odiase +2 more
wiley +1 more source
Cost Pass‐Through in Crisis: Evidence From the German Malt‐Beer Supply Chain
Agribusiness, EarlyView.Abstract Global agri‐food supply chains are increasingly exposed to geopolitical shocks, climate volatility, and market consolidation, factors that disrupt traditional price relationships and reshape market power dynamics. Nowhere is this more visible than in the brewing sector, where agricultural raw materials meet complex industrial processing and ...
Nikolas Bublik, Lukáš Čechura
wiley +1 more source
AIChE Journal, EarlyView.Abstract Electrification of distillation offers a promising route to reducing scope‐1 emissions from one of the chemical industry's most energy‐intensive unit operations. However, conventional adiabatic columns are dynamically inflexible: Long, energy‐intensive start‐ups make shutdown and restart impractical under variable electricity prices and ...
Samuel Mercer, Michael Baldea
wiley +1 more source
Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization
AIChE Journal, EarlyView.Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son +4 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.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
Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source