Improving Graph Convolutional Network with Learnable Edge Weights and Edge-Node Co-Embedding for Graph Anomaly Detection.

The era of Industry 4.0 is gradually transforming our society into a data-driven one, which can help us uncover valuable information from accumulated data, thereby improving the level of social governance. The detection of anomalies, is crucial for maintaining societal trust and fairness, yet it poses significant challenges due to the ubiquity of anomalies and the difficulty in identifying them accurately.

A Joint Scheduling Scheme for WiFi Access TSN.

In the context of Industry 4.0, industrial production equipment needs to communicate through the industrial internet to improve the intelligence of industrial production. This requires the current communication network to have the ability of large-scale equipment access, multiple communication protocols/heterogeneous systems interoperability, and end-to-end deterministic low-latency transmission.

Glutathione-depletion reinforced enzyme catalytic activity for photothermal assisted bacterial killing by hollow mesoporous CuO.

The emergence and prevalence of drug-resistant bacteria caused by the overuse of antibiotics pose new challenges to the treatment of bacterial infections. In this work, hollow mesoporous CuO nanozymes (HM-CuO nanozymes) as excellent antibacterial agents were prepared by a template method. The synthesized HM-CuO nanozymes exhibit peroxidase-like catalytic activity, which can efficiently catalyze HO to generate toxic reactive oxygen species (ROS), causing fatal damage to bacteria.