Results 211 to 220 of about 452,551 (268)

Prognostic Significance of Portal Vein Tumor Thrombus in Pancreatic Ductal Adenocarcinoma Treated With Chemoradiotherapy

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim To examine the significance of portal vein tumor thrombus (PVTT) as a prognostic factor for patients with pancreatic ductal adenocarcinoma (PDAC) treated with chemoradiotherapy (CRT) followed by surgery. Methods The study retrospectively examined 313 patients with borderline resectable (BR) or locally advanced (LA) PDAC who underwent CRT ...
Aoi Hayasaki   +9 more
wiley   +1 more source

Chebyshev centers and radii for sets induced by quadratic matrix inequalities. [PDF]

open access: yesMath Control Signal Syst
Shakouri A, van Waarde HJ, Camlibel MK.
europepmc   +1 more source

Technoeconomic and sustainability analysis of batch and continuous crystallization for pharmaceutical manufacturing

open access: yesAIChE Journal, EarlyView.
Abstract In pharmaceutical industries, continuous manufacturing methods have already been well established to improve productivity and process intensification. However, to better understand the trade‐offs of continuous crystallizers over the existing batch production systems, a robust technoeconomic cost and sustainability analysis is necessary to ...
Jungsoo Rhim, Zoltan K. Nagy
wiley   +1 more source

Seed micromorphology and calcium oxalate crystal characterization as taxonomic traits in selected species of the genus Impatiens L. [PDF]

open access: yesSci Rep
Rewicz A   +8 more
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

open access: yesAdvanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob   +2 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced 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

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

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