Study on Influence of Mechanical Behavior of AZ31 Magnesium Alloy Based on GTN Damage Modeling.

Damage mechanisms are a key factor in materials science and are essential for understanding and predicting the behavior of materials under complex loading conditions. In this paper, the influence of different directions, different rates and different model parameters on the mechanical behavior of AZ31 magnesium alloy during the tensile process is investigated based on the secondary development of the VUMAT user subroutine based on the GTN damage model and verified by the tensile experiments at different loading rates and in different directions. The results show that AZ31 magnesium alloy exhibits significant differences in mechanical properties in radial and axial stretching, where the yield strength is lower in the radial direction than in the axial direction, and the elongation is the opposite.

Automated Detection and Differentiation of Stanford Type A and Type B Aortic Dissections in CTA Scans Using Deep Learning.

Background/objectives: To develop and validate a model system using deep learning algorithms for the automatic detection of type A aortic dissection (AD), and differentiate it from normal and type B AD patients.

Methods: In this retrospective study, a deep learning model is developed, based on aortic computed tomography angiography (CTA) scans of 498 patients using training, validation and test sets of 398, 50 and 50 patients, respectively. An independent test set of 316 patients is used to validate and evaluate its performance.

Transcriptomic Analysis of Wheat Under Multi LED Light Conditions.

Light is a vital environmental cue that profoundly influences the development of plants. LED lighting offers significant advantages in controlled growth environments over fluorescent lighting. Under monochromatic blue LED light, wheat plants exhibited reduced stature, accelerated spike development, and a shortened flowering period with increased blue light intensity promoting an earlier heading date.

Effects of Dietary Protein Levels on Digestion, Metabolism, Serum Biochemical Indexes, and Rumen Microflora of Lanzhou Fat-Tailed Sheep.

This study aimed to investigate the effect of varying levels of dietary protein on digestion, metabolism, serum biochemical indexes, and rumen microflora in Lanzhou fat-tailed sheep. A total of twenty 8-month-old healthy rams with an initial average body weight (BW 25.16 ± 1.

Design, synthesis, and evaluation of the pharmacological activity of novel NMDA receptor antagonists based on the germacrone scaffold.

The NMDA receptor has long attracted researchers' attention due to its potential as a drug target and its central role in the central nervous system. The NMDA receptor is a ligand-gated and voltage-dependent ion channel widely distributed in the central nervous system. In this study, we employed a drug design strategy combining "molecular assembly" and "combinatorial chemistry.