A team of researchers from Peking University and the Chinese Academy of Sciences has made a breakthrough in quantum photonics by demonstrating a method to generate large-scale entangled states—known as cluster states—directly on a chip using optical microresonators. Their work, detailed in Light: Science & Applications, achieves a 60-mode cluster state, an order of magnitude larger than previous on-chip demonstrations.

A novel approach called Counterfactual Synthetic Minority Oversampling Technique (SMOTE) has been developed to tackle the persistent issue of imbalanced data in healthcare. Traditional models trained on imbalanced datasets often overlook rare but critical conditions, such as diseases, leading to biased predictions. By combining SMOTE with counterfactual generation, Counterfactual SMOTE creates synthetic data points near decision boundaries while minimizing noise. This method significantly enhances model performance, enabling better detection of rare conditions without overwhelming false positives. Tested across 24 healthcare datasets, Counterfactual SMOTE outperforms existing methods, offering a robust solution for improving medical diagnostics and extending to other fields.

A recent study introduces an advanced anomaly-based intrusion detection system (IDS) designed to address the increasing cyber threats targeting Internet of Things (IoT) devices. By combining machine learning (ML) and deep learning (DL) models with particle swarm optimization (PSO) for feature selection, the system achieves remarkable performance. Tested on the RT_IoT2022 dataset, the system's top performer, CatBoost, achieved an impressive 99.85% accuracy, making it one of the most accurate IDS solutions for IoT environments. This innovation offers a powerful tool to detect and classify complex attacks in real-time, enhancing cybersecurity for resource-constrained IoT networks.

A team of scientists led by Prof. LIU Zhaoping at the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences, in collaboration with researchers from the University of Chicago and other institutions, has developed zero thermal expansion (ZTE) materials. This innovation has achieved nearly 100% voltage recovery in aging lithium-ion batteries (LIBs), as detailed in a study published in Nature.

Grading Chinese compositions is often time-consuming and inconsistent. A recent study explores the ELion system, a collaboration between East China Normal University and Microsoft Research Asia, developed to enhance automated essay scoring and feedback generation. It examines the system’s evolution through multiple stages, integrating AI-driven assessment tools. By addressing key challenges in composition grading, this study provides insights into the transformative potential of AI in Chinese language education.