Results 181 to 190 of about 341,299 (226)

Response to the Letter to the Editor Entitled "Interleukin-18: A Critical Culprit in Inflammatory Renal Disease". [PDF]

open access: yesKidney Int Rep
Barbir EB   +9 more
europepmc   +1 more source

Rethinking Perioperative Corticosteroids in Esophageal Cancer Surgery: Evidence From an Integrative Meta‐Analysis

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Esophagectomy remains a highly invasive procedure associated with substantial postoperative morbidity. Pulmonary complications, anastomotic leakage, and in‐hospital mortality are of particular concern. Perioperative corticosteroids are often administered to attenuate excessive inflammatory responses; however, the clinical impact in ...
Tomohiko Yasuda   +4 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

3D investigation and modeling of the geometric effects on porosity in packed beds

open access: yesAIChE Journal, EarlyView.
Abstract In porous beds, physical boundaries restrict particle arrangement, leading to inhomogeneous porosity. This paper reports on the porosity profiles that are the result of geometric effects on monodisperse packed beds in cylindrical and cubic arrangements. Special focus is given to the influence of edges and corners in cubic geometries.
Bastian Oldach   +3 more
wiley   +1 more source

Letter to the Editor: Reply to Topkan et al. [PDF]

open access: yesClin Transl Radiat Oncol
Dou S, Zhu G.
europepmc   +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

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