Non-structural disaster measures, including early warnings and evacuation systems, helped improve coastal resilience and reduce storm-surge impacts in Macau, report researchers at Science Tokyo. After analyzing the city’s responses to three major typhoons, which included resident interviews, evaluations of early warning systems, evacuation procedures, and other typhoon mitigation efforts, the study found that earlier issuance of typhoon warnings, color-coded storm-surge alerts, and government-led evacuation guidance significantly improved public trust and reduced disaster impacts.

CardioNVT is an end-to-end deep learning platform for rapid, immunostaining-free assessment of cardiomyocyte nuclear ploidy in situ. Using only DAPI-stained heart sections, it segments cardiomyocyte nuclei, tracks them across z-stack planes, reconstructs 3D nuclear volumes, and infers ploidy from volume measurements, enabling scalable studies of cardiac development, remodeling, and repair.

Studying physics can be very useful – even when it comes to machine learning. A digital ‘super-brain’ with built-in knowledge of the fundamental laws of nature can speed up the development of optical components for everything from quantum computers to eyeglass or camera lenses according to a new study from Chalmers University of Technology in Sweden.

“When we fed the super-brain information about the laws of physics, it immediately got much smarter. Our calculations now take one tenth of the time previously required,” says Philippe Tassin, professor at the Department of Physics and Astronomy, Chalmers University of Technology.

The Japan Science and Technology Agency has selected winners for the fifth Marie Sklodowska Curie Award for young female researchers together with the Embassy of the Republic of Poland. The award honors Marie Sklodowska’s great contribution and achievements to the development of science and technology across the world, and will inspire more active participation in this field by Japanese female researchers.

Speculative decoding is a technique used to speed up large language models (LLMs), but existing approaches were mostly developed for English and are less effective in other languages. Now, researchers from Japan have developed ADASPEC, a speculative decoding framework that automatically generates language-specific training data and adapts its vocabulary during inference. Tested across seven languages and seven tasks, ADASPEC consistently outperformed existing methods while remaining practical and efficient for real-world multilingual applications.

The goal of merging intelligent computers directly with the human body, whether for continuous health monitoring or controlling advanced prosthetics, has long been stalled by a fundamental physical conflict. A new review article in the International Journal of Extreme Manufacturing details how purely rigid architectures are shifted toward soft, brain-inspired electronics that can sense, store, and process information while mechanically conforming to biological tissues.