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. ZHANG Shihua from the Academy of Mathematics and Systems Science has proposed a new computational tool, STAGATE, to decipher tissue substructures from spatial resolved transcriptomics. The model uses artificial intelligence technology to integrate spatial location information and gene expression profile of spatial spots. In this algorithm, a graph attention autoencoder is introduced, with a graph attention mechanism in the middle hidden layer, which can learn the heterogeneous similarities between neighboring spots adaptively.
Researchers from the University of Science and Technology of China revealed that not all forms of quantum nonlocality guarantee intrinsic randomness. They demonstrated that violating two-input Bell inequalities is both necessary and sufficient for certifying randomness, but this equivalence breaks down in scenarios involving multiple inputs.
A research team led by Prof. ZHANG Zhirong from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences developed a novel sensor that enables simultaneous, highly sensitive detection of multiple stable heavy isotopes in exhaled carbon dioxide.
A research team led by Academician YU Shuhong from the University of Science and Technology of China reported a new strategy for preparing the nacre-like ceramic-metal composites (ceramets) based on deformable alumina microspheres coated with nickel salt. These materials have excellent bending strength and fracture toughness, and can be mass-produced in various shapes through simple techniques.
A research group led by Prof. ZHOU Yongjin from the Dalian Institute of Chemical Physics of the Chinese Academy of Sciences, collaborating with researchers from the Naval Medical University, has achieved the biosynthesis of the antiviral ingredient lignan glycoside in yeast Saccharomyces cerevisiae.
A study led by Prof. LIU Feng from the Institute of Zoology of the Chinese Academy of Sciences has identified a crucial role for the tryptophan-aspartic acid (WD) repeat protein 5 (Wdr5) in maintaining the survival and genomic integrity of hematopoietic stem and progenitor cells (HSPCs) during embryonic development.
A new study led by Dr. TIAN Ye's research team at the Institute of Genetics and Developmental Biology reveals that chronic mitochondrial stress in neurons promotes serotonin release via TMBIM-2-dependent calcium oscillations, which in turn activates the mitochondrial unfolded protein response in the intestine.
A research team led by Prof. LUAN Fubo from the Research Center for Eco-Environmental Sciences of the Chinese Academy of Sciences, has uncovered a novel mechanism involving a ternary surface complex on titanium dioxide (TiO₂) that improves the simultaneous removal of arsenic (As) and uranium (U) from contaminated groundwater.
A breakthrough study using ground-penetrating radar has identified the optimal planting density for Mongolia pine plantations in China's arid regions, offering a science-backed solution to combat tree die-offs threatening anti-desertification efforts.
A research team, led by Prof. MENG Qingyan from the Aerospace Information Research Institute of the Chinese Academy of Sciences, has successfully developed the Global Spatiotemporal Fusion Model (GLOSTFM), a high-efficiency spatiotemporal fusion model that utilizes multi-source satellite data. By integrating thermal infrared and microwave observations from the Fengyun-3D satellite, GLOSTFM enhances the spatiotemporal resolution of land surface temperature data.
A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences, has made strides in the theoretical design of nonlinear optical (NLO) materials by leveraging machine learning techniques.
A research team led by Prof. GE Ziyi from the Ningbo Institute of Materials Technology and Engineering from the Chinese Academy of Sciences has developed a low-crystallinity guest acceptor, D-IDT, using a tin-free direct C–H activation method, which was incorporated as a third component into binary organic solar cells (OSCs). This finding resulted in a stable OSC with a power conversion efficiency of 19.92%.
Researchers from the Ningbo Institute of Materials Technology and Engineering of the Chinese Academy of Sciences, have leveraged artificial intelligence to design a novel series of Fe-based amorphous alloys. These materials exhibit both ultra-high saturation magnetization (Bs) and ultra-low coercivity (Hc), offering potential to improve the energy efficiency and performance of high-frequency, high-power electronic devices.
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