Results 61 to 70 of about 81,631 (193)

Beyond the Ban—Shedding Light on Smallholders' Price Vulnerability in Indonesia's Palm Oil Industry

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT The Indonesian government imposed a palm oil export ban in April 2022 to address rising cooking oil prices. This study explores oil palm smallholders' vulnerability to the policy using descriptive statistics, Lasso, and post‐Lasso OLS regressions.
Charlotte‐Elena Reich   +3 more
wiley   +1 more source

Climate Change Agricultural Comparative Advantage and the US Trade Balance

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT Current science indicates that warming and elevated atmospheric CO2 will have ambiguous results for crop productivity depending on crop type and geographic location, whereas increased heat stress makes livestock and human labor less productive.
Elizabeth A. Fraysse   +2 more
wiley   +1 more source

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

open access: yesAgribusiness, 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

Robotic Versus Laparoscopic Anatomic Liver Resection: Comparison of Perioperative Outcomes—A Systematic Review and Meta‐Analysis

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Minimally invasive anatomic liver resection (AR) including major hepatectomy and liver parenchyma‐sparing AR is technically complex and demanding. This systematic review with meta‐analysis including 15 studies comparing 2042 robotic AR and 2129 laparoscopic AR patients demonstrated largely comparable perioperative outcomes and partly better outcomes ...
Yutaro Kato   +3 more
wiley   +1 more source

Transient modeling of extraction columns: Parameter estimation, uncertainty analysis, and operation optimization

open access: yesAIChE Journal, EarlyView.
Abstract Despite extensive modeling efforts in extraction research, transient column models are rarely applied in industry due to concerns regarding parameter identifiability and model reliability. To address this, we analyzed uncertainty propagation from estimated parameters in a previously introduced column model and assessed identifiability via ill ...
Andreas Palmtag   +2 more
wiley   +1 more source

Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization

open access: yesAIChE Journal, EarlyView.
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed   +4 more
wiley   +1 more source

Sequential Monte Carlo with likelihood tempering and parallel implementation for uncertainty quantification

open access: yesAIChE Journal, EarlyView.
Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi   +2 more
wiley   +1 more source

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

open access: yesAIChE Journal, EarlyView.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman   +3 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

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