A research team at The Hong Kong University of Science and Technology (HKUST) has analyzed 40 years of data covering around 1,500 tropical cyclones and discovered that average rain rates surge by more than 20% in the 60 hours before landfall. The study is also the first to clearly identify the physical mechanisms behind this increase, showing that rising humidity over coastal areas and enhanced land-sea frictional contrasts strengthen convection, intensifying rainfall ahead of landfall. The results provide valuable insights for improving coastal disaster preparedness and early‑warning systems.

A research team led by Professor Jo-Woon Chong of SKKU, in collaboration with Texas Tech University, has identified—through EEG analysis—the impact of fragrance on consumers’ emotions, memory, and deep emotional connections with luxury brands.

Researchers at Hokkaido University studied 56 japonica rice cultivars from across Japan and discovered that they contain unique beneficial fats.

In theTibetan Plateau, organophosphate tri-esters (tri-OPEs) and di-OPEs in soil and biota of a typical terrestrial food chain (plant–plateau pika–eagle) have been simultaneously identified with trophic dilution behavior. Differential metabolism—weak in plants versus strong in plateau pika and eagle—likely drove this pattern, highlighting metabolism's key role in OPE trophic transfer.

An Osaka Metropolitan University-led research team used hourly precipitation data from 1981 to 2020 and spatial modeling to predict extreme precipitation events for the next 100 years in Japan.

A research team from The Hong Kong University of Science and Technology (HKUST) has developed GrainBot, an AI-enabled toolkit that automatically extracts and quantifies multiple microstructural features from microscopy images. Designed to meet the growing need for data-driven and autonomous research workflows in materials science, the tool provides a systematic method for converting complex image information into quantitative data, thereby accelerating the discovery and development of next-generation materials.

Accurate crowd monitoring is crucial for guiding emergency evacuations. Non-repetitive scanning LiDAR systems are affordable and offer wide coverage, but their sparse and discontinuous depth data limit practical use. A study from Doshisha University introduces a color-guided depth completion method to reconstruct missing 3D information. The researchers also created a simulated dataset to support the evaluation of future depth reconstruction approaches.