Recently, a research group led by Prof. XIE Pinhua from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, analyzed long-term trend of ozone in the Yangtze River Delta (YRD) using multi-source data and numerical models. Their studies identified key synoptic weather patterns (SWPs) linked to severe ground-level ozone pollution and established the relationship between SWPs evolution and persistent heavy ozone pollution in terms of ozone formation and transport.
A team of researchers led by Professor XIE Chengjun and Associate Professor ZHANG Jie at the Hefei Institutes of Physical Science (HFIPS) of the Chinese Academy of Sciences (CAS), developed an innovative Decoupled Feature Learning (DFL) framework inspired by causal inference to address the challenge of distribution bias in crop pest recognition.
Half a month later, ZHOU Haijin, an engineer from AIOFM, Hefei Institutes of Physical Science returned to Science Island from Ny-Ålesund Arctic. Now, his mission is to receive everyday data transmitted from the Yellow River Station and Zeppelin Station in Ny-Ålesund Arctic. During the past two weeks, he has completed on-site maintenance of the ground-based Differential Optical Absorption Spectrometer (DOAS) which was independently developed by his team and installed in Ny-Ålesund, Arctic in 2010 to detect meteorological element and to reveal mechanism of natural phenomenon.
A research team led by Prof. MENG Guowen and Prof. HAN Fangming from the Hefei Institutes of Physical Science (HFIPS) of the Chinese Academy of Sciences (CAS), along with Prof. WEI Bingqing from the University of Delaware and Prof. LI Xiaoyan from Tsinghua University, constructed high-density three-dimensional carbon tube nanoarray electrodes for use in line-filtering capacitors, showcasing immense potential as high-performance miniaturized filter devices.
Recently, a research team led by Prof. CHU Yannan from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences adopted methionine regulation strategy and found that esophageal cancer cells can be identified by two volatile organic compounds (VOCs) with the help of untargeted analysis by gas chromatography-mass spectrometry (GC-MS).