Guangzhou, China — A pioneering study published in Science Bulletin introduces an innovative data management framework that integrates AI and blockchain technology to address critical challenges in multicenter randomized controlled trials (RCTs). An international collaboration led by Professor Haotian Lin from Zhongshan Ophthalmic Center, Sun Yat-sen University and Professor Tien Yin Wong from Tsinghua University, alongside researchers from other leading institutions, has developed a framework, which aims to improve data integrity, objectivity, and operational efficiency in clinical trials.

The study overcomes a decades-old limitation in quantum sensing by a substantial margin.

In one out of five DAOs, a single contributor held enough tokens to make decisions alone, according to a study from the Complexity Science Hub (CSH)—raising questions about how democratic these systems truly are.

A research team from the Institute of Modern Physics (IMP), Chinese Academy of Sciences (CAS), has developed a machine learning (ML) model enhanced with expert knowledge to classify eight types of faults in superconducting radio-frequency (SRF) cavities at the China Accelerator Facility for superheavy Elements (CAFE2) facility. This model helps operators quickly identify fault patterns after incidents, speeding recovery and supporting long-term stable SRF accelerator operation.