Discovering relatedness outside of a topical issue helps diverse groups to overcome differences and develop action for social change. The Kobe University addition to educational theory offers a framework to analyze and promote intersectional learning.

A research team led by Haruyo Yamamoto, Chisa Nakashima, and Atsushi Otsuka from Department of Dermatology, Kindai University Faculty of Medicine, in collaboration with the Faculty of Engineering at Kindai University and other institutions, has developed a diagnostic system that uses artificial intelligence (AI) to accurately identify the type of facial pigmented lesions and support laser treatment decisions. A paper on this study was published online in Cureus, an international medical journal on June 5, 2025.

Imaging data from Japan’s Himawari-8 and -9 meteorological satellites have been successfully used to monitor temporal changes in Venus’ cloud-top temperature, revealing unseen patterns in the temperature structure of various waves. A team led by the University of Tokyo collated infrared images from 2015–25 to estimate brightness temperatures on day to year scales. The results demonstrate that meteorological satellites can serve as additional eyes to access the Venusian atmosphere from space and complement future observations from planetary missions and ground-based telescopes.

Grant-free communication schemes are a promising way to connect massive numbers of IoT devices, but they can suffer from interference and uneven performance. Researchers from Japan have made progress in addressing this challenge by developing a detailed mathematical model of how these schemes perform under various conditions. Their findings reveal a key trade-off between network fairness and optimal performance, offering insights for designing future 5G and 6G systems that support smart cities and connected healthcare.

A new study of over 3,000 Japanese firms reveals that companies often set overly ambitious earnings targets after previously missing their goals—an effort to restore investor confidence. This strategic move, known as “organizational impression management,” helps firms manage market perceptions despite the risk of repeated failure. The research also finds that institutional investors, analysts, and board diversity can temper this behavior, offering fresh insight into corporate communication and investor relations.

Mouse models are central to drug development, including treatments for neurological disorders, such as Parkinson’s disease. In a new eNeuro publication, researchers from OIST’s Neuronal Rhythms in Movement Unit introduce a mouse motion capture method which provides very high-resolution measurement of mouse movement. Their marker-based approach avoids the need for extensive data processing with AI or machine learning, and can capture high-quality data on complex movement, such as running or climbing.

A Nagoya University team has overcome one of the key limitations of X-ray technology by making the mirror using only a single-crystal piezoelectric thin wafer instead of the usual two-part structure. Using this technique, they changed X-ray beam size by more than 3,400 times. This improved dynamic range massively improves both imaging and analysis, improving the efficiency of advanced techniques and massively enhancing workflows.

A group of researchers have observed images from the James Webb Space Telescope. The images were like a time machine, allowing the researchers to understand how these galaxies built their disks over history and compare this to how our own Milky Way formed. 

Researchers at the University of Tokyo have demonstrated that the strength of synaptic connections in the cerebral cortex varies during sleep, influenced by synaptic learning rules and neuronal activity. Using simulations, they identified conditions under which “sleep learning” may occur. These findings could deepen our understanding of the relationship between sleep and learning/memory and help elucidate the mechanisms of brain disorders linked to sleep disturbances.

Osaka Metropolitan University researchers have developed an AI model that can detect the presence of fatty liver disease from chest X-ray images.