Okayama University of Science and Minghsin University of Science and Technology sign MOA for double degree program
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Updates every hour. Last Updated: 19-Dec-2025 18:11 ET (19-Dec-2025 23:11 GMT/UTC)
Okayama University of Science (OUS) in Japan and Minghsin University of Science and Technology (MUST) in Taiwan have signed a Memorandum of Agreement (MOA) to establish a double degree program in semiconductor studies. The agreement, building on a 40-year partnership between the two institutions, will allow students to earn bachelor’s degrees from both universities. Under the program, students begin at OUS to learn semiconductor fundamentals and language skills before advancing to MUST, home of the world’s first Semiconductors School. The initiative aims to cultivate globally minded engineers and strengthen industry–academia collaboration in Okayama and Taiwan. At the signing ceremony held on October 23 at OUS, leaders from both universities and semiconductor companies expressed strong support for developing a joint talent base that will contribute to regional and global semiconductor innovation.
Researchers have developed miniature magnetic robots that mimic fish behavior, working together as coordinated swarms to deliver drugs precisely and efficiently to tissue. The breakthrough could transform treatment of conditions where individual tiny robots lack sufficient coverage area for effective therapy.
With the rapid advancements in computer technology and bioinformatics, the prediction of protein-ligand binding sites has become a central component of modern drug discovery and development. Traditional experimental methods are often constrained by long experimental cycles and high costs; therefore, the development of accurate and efficient computational methods is of paramount significance for conserving time and cost. This review comprehensively summarizes the methodological advancements and current applications in the field of screening for druggable protein target sites, systematically comparing the fundamental principles, advantages, and disadvantages of four main categories of methods: structure- and sequence-based methods, machine learning-based methods, binding site feature analysis methods, and druggability assessment methods. Subsequently, by integrating classic case studies, this paper elaborately discusses the technical support and theoretical guidance afforded by the screening of protein druggable target sites for drug discovery and drug repositioning. Finally, this paper thoroughly explores the current challenges inherent in the field of protein-ligand binding site prediction, with a particular focus on future technological trends, systematically elucidating the developmental prospects and potential applications of these predictive methods.