A team of researchers from Beihang University and Truth Memory Corporation has fabricated a 1 Kbit spin-orbit torque magnetic random access memory (SOT-MRAM) chip with an implemented physical unclonable function (PUF). Published in Engineering, the new PUF shows high reliability, reconfigurability, and resistance to machine-learning attacks, offering a potential solution for Internet of Things (IoT) security issues.

Traditional teaching methods may not fully prepare students for the digital era. A recent discussion explores how AI-driven strategies can enhance learning outcomes and engagement. It examines adaptive learning platforms, intelligent tutoring systems, and AI-assisted assessments, highlighting their role in personalizing instruction and improving student performance. By integrating these technologies, educators can reshape modern classrooms. This discussion provides insights into the transformative potential of AI in education.

A study published in Engineering provides a comprehensive review of actuation and locomotion methods for miniature underwater robots (MURs). Titled "Actuation and Locomotion of Miniature Underwater Robots: A Survey," the research summarizes key propulsion technologies, evaluates their advantages and challenges, and explores future trends in MUR development for underwater exploration and marine applications.

Emotions play a critical role in international students’ intercultural adjustment processes. A critical review by a researcher from Beijing Foreign Studies University examines the evolution of research on this topic. Initially focused on the concept of “culture shock,” the field now explores the personal growth value and sociocultural complexities of emotions. The study emphasizes the importance of taking a more inclusive conceptual horizon of emotions in empowering international students and advancing intercultural education programs to promote global social transformation.

The rapid advancement of artificial intelligence (AI) has significantly increased the computational load on data centers, resulting in substantial carbon emissions. To mitigate these emissions, future data centers should be strategically planned and operated to fully utilize renewable energy resources while meeting growing computational demands. This study aims to investigate how much carbon emission reduction can be achieved by using a carbon-oriented demand response to guide the optimal planning and operation of data centers. An empirical study based on the proposed models is conducted on real-world data from China. The results from the empirical analysis show that newly constructed data centers are recommended to be built in Gansu Province, Ningxia Hui Autonomous Region, Sichuan Province, Inner Mongolia Autonomous Region, and Qinghai Province, accounting for 57% of the total national increase in server capacity. 33% of the computational load from Eastern China should be transferred to the West, which could reduce the overall load carbon emissions by 26%.

Energy sector decarbonization is a key battleground in China’s march toward carbon neutrality, and understanding what it means and takes is crucial for its policy-making and sustainable implementation. Here we analyze the structural challenges and review the necessary supporting technologies and systems of energy sector decarbonization in China. This work could achieve a better understanding of technology development and deployment, and to make more thoughtful policy recommendations.