The team proposed a Byzantine-Resilient and Verifiable Aggregation for Differentially Private Federated Learning based on three proposed primary methods that demonstrate a great compatibility.

Neuroblastoma (NB), the most prevalent extracranial solid tumor in children, poses a significant therapeutic challenge due to its metastasis and high heterogeneity. A recent study leveraging single-cell RNA sequencing (scRNA-seq) has uncovered vital molecular mechanisms underlying NB's progression and metastasis, shedding light on potential therapeutic targets. The research analyzed primary tumors and matched metastases from NB patients, revealing a 'starter' subpopulation of tumor cells responsible for initiating metastasis. By applying various analytical approaches, including evolutionary trajectory analysis and cell-state differentiation prediction, the study delineated the transcriptional landscape of NB and identified a signature associated with poor prognosis.

A research team led by Prof. JIANG Hailong, Prof. LUO Yi, and Prof. JIANG Jun from the University of Science and Technology of China (USTC) discovered a metal-organic framework (MOF) that suppress charge recombination, which is a major challenge in photocatalytic overall water splitting.

This review begins by introducing the development history of optical neural networks (ONNs) and the mathematical models of optical artificial neurons. It explores the differences in constructing ONNs using various optical components. Next, it presents recent key research on both non-integrated and integrated ONNs. Finally, the review analyzes the performance of different ONN types in terms of computing capacity, integration, reconfigurability, nonlinearity, etc. It also discusses the challenges various ONNs may face in future development.