In a newly published research article in Space: Science & Technology, an international team of researchers from the Aerospace Information Research Institute, Chinese Academy of Sciences; the Italian National Institute for Nuclear Physics (INFN); the China Academy of Space Technology; the National Astronomical Observatories, Chinese Academy of Sciences; the Yunnan Observatories, Chinese Academy of Sciences; and the China University of Geosciences jointly presents a detailed account of the successful deployment of the INRRI laser retroreflector on the lunar farside by the Chang’e-6 mission.

An article in the Soil Science Society of America Journal proposes a classification framework to help scientists better understand lunar soils. This emerging science of “planetary pedology,” the study and classification of soils beyond Earth, could help future missions select the best sites for construction, resource extraction and potentially cultivation, thereby supporting long-term, sustainable human settlement on the Moon.

A new study published in Big Earth Data develops explainable Random Forest models to predict stream total nitrogen (TN) and total phosphorus (TP) concentrations using upstream catchment characteristics derived from openly accessible environmental datasets. The results show that the models provide robust predictions for TN, while reduced and spatial covariates help mitigate overfitting and improve model interpretability, demonstrating the potential of explainable machine learning for regional nutrient monitoring.

In a paper published in ENGINEERING Management, researchers from Shanghai University and Tsinghua University propose a cross-city transfer learning framework that enables rapid planning of shared e-scooter parking stations in new cities without requiring local operational data. Using operational data from 25 European cities and multi-source open-space data, the study demonstrates that a multi-dimensional urban similarity matching strategy, integrating socio-economic, POI distribution, and spatial structure features, achieves more stable and generalizable predictions than conventional geographic or economic grouping methods, with the TOP-3 similarity match yielding the best overall performance.

A research team led by Dr. Seo, Jae hwa at Korea Electrotechnology Research Institute (KERI) Advanced Semiconductor Research Center, working with Professor Yoon, Young jun’s team at Gyeongkuk National University, has achieved Korea’s first demonstration of a silicon carbide (SiC)-based betavoltaic cell designed to generate electricity for more than 50 years without recharging or replacement even in extreme environments such as space and the polar regions. The findings have drawn international attention, having been published in the International Journal of Energy Research, a leading global journal in the energy field ranked in the top 3.6% by JCR and second in its subject category.

In a recent study published in Space: Science & Technology, a research team from Simon Fraser University and the University of Calgary, for the first time, adopted the brain vital signs framework to monitor cognitive and neurophysiological function in astronauts participating in a 17‑day mission to the International Space Station.