Non-Equal Contributions of Different Elements and Atomic Bonds to the Strength and Deformability of a Multicomponent Metallic Glass ZrCuAl.

Multicomponent metallic glasses (MGs) are a fascinating class of advanced alloys known for their exceptional properties such as limit-approaching strength, high hardness and corrosion resistance, and near-net-shape castability. One important question regarding these materials that remains unanswered is how the different elements and atomic bonds within them control their strength and deformability. Here, we present a detailed visual and statistical analysis of the behaviors of various elements and atomic bonds in the ZrCuAl (at%) MG during a uniaxial tensile test (in the z-direction) simulated using molecular dynamics.

Integration of Diffusion Transformer and Knowledge Graph for Efficient Cucumber Disease Detection in Agriculture.

In this study, a deep learning method combining knowledge graph and diffusion Transformer has been proposed for cucumber disease detection. By incorporating the diffusion attention mechanism and diffusion loss function, the research aims to enhance the model's ability to recognize complex agricultural disease features and to address the issue of sample imbalance efficiently. Experimental results demonstrate that the proposed method outperforms existing deep learning models in cucumber disease detection tasks.