Recently, Prof. GAO Xiaoming’s team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, developed a novel photoacoustic spectroscopy (PAS)-based sensor that enabled simultaneous, highly sensitive detection of CO2, CH4, and N2O, with improved long-term measurement accuracy.
In a recent review published in Biotechnology for Biofuels and Bioproducts, a research team led by Associated Professor WANG Peng from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, in collaboration with Dr. Rodrigo Ledesma-Amaro from Imperial College London, provided a comprehensive overview of ethanol as a renewable carbon source for producing various high-value products, offering new perspectives for the development of eco-friendly industrial biotechnology processes.
A research team has used a machine learning approach to investigate the evolution of shell structure for nuclei far from the stability valley, and reveals the double-magic nature of Tin-100 and the disappearance of the magic number 20 in Oxygen-28.
Recently, Prof. HUANG Qing’s group from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences discovered that a compound, ganoderic acid A (GAA), could help fight cancer by targeting glucose transporters, proteins that cancer cells use to take in sugar.
Researchers from the Changchun Institute of Optics, Fine Mechanics, and Physics of the Chinese Academy of Sciences recently developed a novel low-light image enhancement (LLIE) method, the Zero-Reference Camera Response Network (ZRCRN), which addresses limitations of existing LLIE methods.
Researchers from the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences have developed a novel autofocus method that harnesses the power of deep learning to dynamically select regions of interest in grayscale images.
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