A research team led by Prof. WAN Yinhua from the Institute of Process Engineering has developed a machine learning framework to analysis virus filtration processes in therapeutic protein purification. The new method enables intelligent identification of critical parameters affecting virus retention efficiency and provides predictive guidance for process optimization.
A research team led by Prof. WANG Shuqiang from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences introduced a Prior-Guided Adversarial Learning with Hypergraph (PALH) model for predicting abnormal connections in Alzheimer's disease.
A research team led by Prof. HUANG Qunying from the Hefei Institutes of Physical Science and the Shenyang National Laboratory for Materials Science, has achieved nearly defect-free bonding between China low activation martensitic steel and an oxide dispersion-strengthened alloy using the hot compression bonding method.
Researchers from the Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, the Institute National de la Recherche Scientifique, Canada, and Northwest University, developed a single-shot compressed upconversion photoluminescence lifetime imaging (sCUPLI) system for high-speed imaging.
A research team led by Prof. PAN Shilie at the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has developed the fluorooxoborate crystal NH4B4O6F (ABF)—offering aneffective solution to the practical challenges of VUV NLO materials.
A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has developed a novel Hg-based chalcogenide HGSC—featuring linear [Hg3Se2] building units. The team systematically investigated the crystal's structure, optical properties, and thermal response behavior.
Researchers from the Xishuangbanna Tropical Botanical Garden (XTBG) of the Chinese Academy of Sciences identified a rare natural compound derived from the Teak tree (Tectona grandis) which works in two distinct ways to combat diabetes and lipid disorders.
A research team led by Prof. ZHU Yongguan, a member of the Chinese Academy of Sciences (CAS) at the CAS Research Center for Eco-Environmental Sciences, has identified the mechanisms by which sponge city construction significantly enhances urban plant diversity.
A research team led by Prof. SONG Jinming from the Institute of Oceanology of the Chinese Academy of Sciences clarified differences in the "seamount effect" across two cruises over M4 Seamount in the Western Pacific, finding that seamounts promoted OMZ expansion to a certain extent.
A research team led by Prof. XIAO Kai from the Yantai Institute of Coastal Zone Research of the Chinese Academy of Sciences, has systematically elucidated the transformation and transport processes of nutrients in intertidal groundwater. The team employed a combined methodological approach, including multi-depth groundwater sampling, dynamic monitoring, stable isotope tracing, and multivariate statistical analysis. Their findings provide scientific evidence to deepen understanding of the terrestrial drivers of nearshore eutrophication.
A research team led by Prof. LI Xiangxian from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed a new deep learning model that significantly enhances both the accuracy and interpretability of roadside air pollutant forecasts.
A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences has developed a new method combining deep learning with physical radiative transfer modeling to improve the retrieval of atmospheric aerosol properties from complex satellite observations, supporting high-resolution, near-real-time monitoring of haze and dust events.
A research team led by Prof.YU Xuefeng from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences developed a knowledge-driven multi-agent and robot system (MARS) for end-to-end autonomous materials discovery.
A research team from the Institute of Metal Research has developed an efficient, stable, atomic-scale catalyst for carbon monoxide (CO) oxidation. This advance offers promising strategies for environmental catalysis and designing low-cost, high-performance catalysts.
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