One of the research lines of the group of the EHU-University of the Basque Country is seeking solutions to generate districts or neighbourhoods whose annual net energy consumption is close to zero. Using machine learning techniques, Dr Milagros Álvarez has achieved greater accuracy in energy demand estimates and in the assessment of retrofitting strategies to reduce thermal consumption on the neighbourhood level.

Tokyo, Japan – Researchers from Tokyo Metropolitan University have studied the relationship between numerical information in our vision, and how it affects our perception of space. Volunteers were asked to identify the center of lines and squares filled with numbers; how far they were from the true center revealed unexpected biases. Crucially, their work with squares showed how our perception of space is a complex interplay between “object-based” processing and our processing of numerical information.

A joint research team from NIMS, Tokyo University of Science, and Kobe University has developed a new artificial intelligence (AI) device that exploits ion behavior to perform information processing. The team succeeded in reducing the computational load to about 1/100 of that required for conventional deep learning. The technology is expected to contribute to enhancing the information processing performance of "edge AI" operating directly on terminal equipment (an edge device). This research was published in ACS Nano on October 14, 2025.

China has moved from patchy, post-crisis biosafety rules to a unified legal regime anchored by the 2020 Biosecurity Law, yet fragmentation, weak risk intelligence and poor inter-agency coordination still leave gaps that could be exploited by novel pathogens, synthetic biology or geopolitical tension.  Historical review shows three phases: 1949-2002 built basic disease reporting and plant-quarantine systems but relied on paper records; 2003-2019 introduced internet-based surveillance, BSL-3/4 laboratories and alignment with WHO’s International Health Regulations after the SARS shock; 2020-present elevated biosafety to national-security status, enacted the Biosecurity Law and poured funds into diagnostics, vaccines and bio-economic R&D during COVID-19.  These steps created the skeleton of a modern system, but four structural weaknesses persist: strategic plans lack operational road-maps and AI-enabled foresight; the legal framework offers no clear dispute-resolution or accountability mechanisms; organisational silos among health, agriculture, science and military agencies hamper horizontal coordination; and public awareness plus professional training remain patchy, weakening compliance culture.

This study systematically elucidates the drug resistance mechanisms of five highly pathogenic viruses, proposes five innovative anti-resistance strategies, and integrates artificial intelligence technology to establish a next-generation antiviral drug research and development framework, thereby providing critical theoretical support and transformative pathways for addressing clinical challenges associated with drug resistance.