AIMR researchers used micro-focused ARPES to identify domain-specific surface states in antiferromagnetic NdSb that disappear above 16 K. This suggests bulk spin order induces these states through symmetry-breaking, potentially enabling control of surface electrons for applications in spintronics and quantum technologies.

In a paper published in Research, a team of scientists present a new circuit design to display quantum two-player games. Compared with the classical algorithms to solve two-player game, the algorithm for the two-player games is dependent on continuous-time quantum walk, and exhibits quantum advantage. Besides, such design of quantum two-player games has been realized on the circuit networks according to the analogy between the wave function of the Schrödinger equation and the voltage in Kirchhoff's law.

Transfer learning, as a new machine learning methodology, may solve problems in related but different domains by using existing knowledge, and it is often applied to transfer training data from another domain for model training in the case of insufficient training data. In recent years, an increasing number of researchers who engage in brain-computer interface (BCI), have focused on using transfer learning to make most of the available electroencephalogram data from different subjects, effectively reducing the cost of expensive data acquisition and labeling as well as greatly improving the learning performance of the model. This paper surveys the development of transfer learning and reviews the transfer learning approaches in BCI. In addition, according to the “what to transfer” question in transfer learning, this review is organized into three contexts: instance-based transfer learning, parameter-based transfer learning, and feature-based transfer learning. Furthermore, the current transfer learning applications in BCI research are summarized in terms of the transfer learning methods, datasets, evaluation performance, etc. At the end of the paper, the questions to be solved in future research are put forward, laying the foundation for the popularization and in-depth research of transfer learning in BCI.

Chronic jet lag causes drastically different effects on male and female metabolism in mice, say researchers from Kyushu University. The study, published in the journal, Biology of Sex Differences, found that the body clocks of female mice are more easily disrupted than the clocks of male mice, and revealed opposing metabolic effects; jet-lagged male mice gained weight and developed glucose intolerance, while jet-lagged females lost weight compared to female mice without jet lag.

Scientists have long held that electricity is carried by individual electrons with discrete charges moving in a metal, even in the case of electrons clumped into quasiparticles. However, “strange metals” fail to obey this paradigm. Researchers have observed a radical quantum blurring of electrons in strange metal into a featureless liquid, potentially pointing toward a new theory of electrical transport.

By coring the seabed at 850 m water depth in Disko Bay off Greenland's west coast, researchers from the University of Copenhagen have obtained the first historical record of plastic pollution in Greenland. The new data suggest a link to local socio-economic development and represent a step towards developing a common method for analyzing and mapping global microplastic pollution.

This comprehensive review analyzes cutting-edge tools and technologies in modern pharmaceutical research, focusing on artificial intelligence, multi-omics technologies, and experimental methods. The study highlights how computational methods enhance drug discovery efficiency, while omics technologies provide systematic frameworks for investigating drug mechanisms. The integration of these advanced approaches has enabled more diverse and personalized treatment strategies, though challenges remain in drug development complexity, cost-effectiveness, and operational feasibility.