Results 181 to 190 of about 1,088,040 (302)
Numerical Exploration of Thermal Shock Resistance in MgO–C Refractories
Advanced Engineering Materials, EarlyView.A mesostructure‐resolved numerical framework is developed to evaluate the thermal shock resistance of MgO–C refractories. By modeling interface debonding under rapid temperature changes and introducing a modified thermal shock parameter that accounts for mesocracks, the study shows how graphite content and aggregate size influence thermal shock ...
Jishnu Vinayak Gopi +3 more
wiley +1 more source
Time efficiency, geometric accuracy, and clinical impact of AI-assisted contouring of organs at risk in head and neck cancer radiotherapy. [PDF]
Acta OncolSøbstad JM +5 more
europepmc +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Advanced Engineering Materials, EarlyView.Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
A dual-layer quality assurance approach leveraging dose prediction for efficient review of automated contours of organs at risk in the brain in radiotherapy. [PDF]
Phys Imaging Radiat OncolPoel R +8 more
europepmc +1 more source
Advanced Engineering Materials, EarlyView.This study reports the development of antibacterial ceramic scaffolds derived from natural bovine bone. The bones were processed through sequential boiling and hydrogen peroxide treatment to remove organic matter, producing porous, mineral‐rich scaffolds.
Mohamad Hassan Taherian +6 more
wiley +1 more source
Deep learning based multi-organ segmentation of organs-at-risk
In recent years, deep learning (DL) methods have been increasingly applied to improve the automation and accuracy of organ-at-risk (OAR) segmentation in radiotherapy planning. Among these, convolutional neural networks (CNNs), particularly U-Net and its extensions, have shown significant advantages over manual contouring by offering greater consistency,
openaire +1 more source
Advanced Functional Materials, EarlyView.In this work, a magnetic core‐shell catalyst (HOF‐on‐Fe3O4/ZIF‐67) is successfully synthesized, consisting of a metal–organic framework (ZIF‐67) with magnetic Fe3O4 as the core and a porous hydrogen‐bonded organic framework (HOF) as the shell. The catalyst efficiently activated peroxymonosulfate, resulting in rapid and effective removal of water ...
Yingying Du +4 more
wiley +1 more source
A semi-automated workflow for cohort-wise preparation of radiotherapy data for dose-response modeling, including autosegmentation of organs at risk. [PDF]
J Appl Clin Med PhysMövik L +5 more
europepmc +1 more source
Advanced Functional Materials, EarlyView.The separation of Helium gas from natural gas is challenging but highly important. MIL‐116(Ga), a “non‐porous” metal–organic framework is used as a molecular sieve to separate He from CH4. Druse‐like MIL‐116(Ga) particles are integrated into polysulfone mixed matrix membranes.
Ayisha Komal +10 more
wiley +1 more source