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.
A collaborated team led by researchers from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has successfully developed advanced semiconductor-based radiation detectors, significantly improving their performance for use in extreme environments.
A research team led by Prof. SHEN Baogen, Member of the Chinese Academy of Sciences who comes from the Ningbo Institute of Materials Technology and Engineering of CAS, has achieved multilevel spin-based modulation of magnetoresistance in high-performance organic spin valve (OSV) devices.
Prof. LIN Zhenyang at Hongkong University of Science and Technology and Prof. LIU Guosheng at Shanghai Institute of Organic Chemistry of the Chinese Academy of Sciences described how a copper-bound tert-butoxy radical intermediate facilitates site- and enantio-selectively oxidation of C(sp3)-H on a range of alkenes and alkynes.
A research team led by Prof. WAN Yinhua from the Institute of Process Engineering (IPE) of the Chinese Academy of Sciences has developed a dual-functional reverse osmosis (RO) membrane with enhanced antibacterial and antiadhesion properties. The membrane demonstrates broad-spectrum, sustained antibacterial activity, as well as resistance to various foulants. These properties make it suitable for water purification, seawater desalination, and high-salinity wastewater treatment, among other applications.
An international team led by Prof. John Speakman from the Shenzhen Institutes of Advanced Technology of the Chinese Academy of Sciences derived a predictive model by combining classical statistics and machine learning for total energy expenditure, providing a more objective way to assess the validity of food intake records.
A new technology developed by the Single-Cell Center at Qingdao Institute of Bioenergy and Bioprocess Technology of the Chinese Academy of Sciences, in collaboration with several institutions, is poised to transform the discovery of microbial species and enzymes with specific in situ metabolic functions.
Recently, Dr. HUANG Pu from the Nanjing Institute of Geology and Palaeontology of the Chinese Academy of Sciences, in collaboration with other researchers, reported a new species of Zosterophyllum, Z. baoyangense, from the Lower Devonian of Guizhou Province. They also compiled a multi-morphological-character dataset of zosterophyllopsids from the late Silurian to Early Devonian and revealed divergent life-history strategies within this group.
In a recent study, an international team of scientists, led by Prof. Dr. ZHANG Wenxia from the Institute of Atmospheric Physics of the Chinese Academy of Sciences, provided an overview of the characteristics and impacts of the most notable extreme events of the year 2024, including rainfall and flooding, tropical cyclones, and droughts.
A research team led by Prof. DONG Erbao from the University of Science and Technology of China of the Chinese Academy of Sciences, collaborating with Prof. YU Xinge from the City University of Hong Kong, developed a novel tactile perception method based on the structural color of flexible grating structural color.
In many Asian regions, especially in China, agricultural fields are typically small, scattered, and lack of clear boundaries, which complicates effective crop distribution and agricultural analysis using remote sensing technology. Now, a research group from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, addressed this challenge with a novel dual-branch deep learning model (DBL) they developed.
A joint research team from Hefei Institutes of Physical Science of the Chinese Academy of Sciences has successfully developed a continuous cryogenic pellet injection system for tokamak fueling. This innovative system addresses key technical challenges associated with cryogenic ice formation, pellet cutting, and launching.
A team of researchers from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed an innovative green pesticide formulation that promises to enhance pest control while prioritizing safety for both crops and the environment.
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