In many modern sciences, data often exist on curved geometric spaces rather than flat planes, posing challenges for traditional statistical tools. These curved spaces are called Riemannian manifolds. Researchers from Pusan National University and Seoul National University have developed the “Huber mean,” a new method for robustly analyzing data on Riemannian manifolds. This study offers a powerful way to calculate averages that remain accurate even when data contain noise or outliers.

In a study published in SCIENCE CHINA Earth Sciences, researchers from Nanjing Normal University developed a unified mathematical model and a six-category classification system for coastal tipping points. By integrating land-sea interactions and multi-scale processes, the framework analyzes 91 global cases, highlighting spatial heterogeneity and urging advances in data fusion, modeling, and adaptive management to address irreversible shifts in these vulnerable systems.

Researchers explored how machine learning and quantum computing can be used to improve early detection of chronic kidney disease, aiming to develop faster, more accurate diagnostic tools for clinicians.

A computer that can calculate hundreds of scientific tasks simultaneously and thus helps provide a solution to key social challenges: this is the new IT heart of Paderborn University. The ‘Otus’ supercomputer was put into operation at the Paderborn Center for Parallel Computing (PC2) on Monday 10 November. From now onwards, researchers all over Germany can use it to run challenging computer simulations and conduct scientific enquiry at the highest level.