Results 171 to 180 of about 419,487 (262)

Hemp Cultivation and Crop Diversification: Implications for Ecosystem Services in Kentucky

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT This study examines the ecosystem benefits of expanding hemp cultivation by assessing its impact on crop diversity. Using scenario‐based simulations and fixed‐effect panel regressions with county‐level data in Kentucky, we find that increased hemp acreage tends to enhance crop diversity, improving water quality and bird diversity.
Yunsun Park, Seong D. Yun, Brandy E. Phipps, Tyler Mark, Craig Schluttenhofer   +4 more
wiley   +1 more source

Trump Tariffs 2.0: Assessing the Impacts on US Distilled Spirits Imports

Agribusiness, EarlyView.
ABSTRACT The proposed 25% tariff on Mexico and Canada could have significant repercussions on US imports of distilled spirits. This study estimates US import demand across various spirit categories (e.g., tequila, whiskey) and assesses the potential impact of the proposed tariff.
Andrew Muhammad
wiley   +1 more source

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

Agribusiness, EarlyView.
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
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

SMCTC: Sequential Monte Carlo in C++

Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms are used very widely in the tracking and signal processing literature.
Adam M. Johansen
core  

Multifactor Risk Stratification for Post‐Transplant Alcohol Relapse Using Abstinence, Psychosocial, and Socioeconomic Factors

Annals of Gastroenterological Surgery, EarlyView.
Alcohol relapse after liver transplantation is difficult to predict using abstinence duration alone. We developed a multifactor model integrating abstinence duration, psychosocial risk (SIPAT), and socioeconomic context (AUC 0.70). This approach may support individualized risk assessment and tailored follow‐up intensity; external validation is needed ...
Ayato Obana, Garren Montgomery, Miho Akabane, Matthew Hamilton, Navdeep Singh, Musab Alebrahim, Austin Schenk, Sylvester Black, Kenneth Washburn, Khalid Mumtaz   +9 more
wiley   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

Raquianestesia em paciente anticoagulado

São Paulo Medical Journal
Fernando Lima Coutinho, Marcos Gonçalves Magalhães, Rodrigo Machado Saldanha, Mariana M. P. Neves, Fernando P. Araújo, José Francisco N. P. Neves   +5 more
doaj   +1 more source

Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Advanced Intelligent Discovery, EarlyView.
This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley   +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