Xiaomi Wang

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Environmental pollutants have received considerable attention due to their serious effects on human health. There are physical, chemical, and biological means to remediate pollution; among them, bioremediation has become increasingly popular. The nitrogen-fixing rhizobia are widely distributed in the soil and root ecosystems and can increase legume growth(More)
A bacterial strain ZY1 capable of utilizing PCBs as its carbon source was isolated from the root nodules of Chinese milk vetch (Astragalus sinicus L.). The strain was identified as Mesorhizobium sp. according to its physiological-biochemical properties and the analysis of its 16S rRNA gene sequence. When the initial OD600 was 0.15, 62.7% of 15 mg L(-1)(More)
BACKGROUND Cryptococcus neoformans infection usually presents as chronic meningitis and is increasingly being recognized in immunocompromised patients. Presentation with pleural effusion is rare in cryptococcal disease; in fact, only 4 cases of pleural effusion as the initial clinical presentation in cryptococcosis have been reported in English-language(More)
A rhizobial strain, Sinorhizobium meliloti NM, could use 3,3',4,4'-tetrachloro-biphenyl (PCB 77) as the sole carbon and energy source for growth in mineral salt medium. The degradation efficiency of PCB 77 by strain NM and the bacterial growth increased with a decrease in PCB 77 concentration (5-0.25mgL(-1)). The addition of secondary carbon sources,(More)
The role of symbiotic rhizobia in the alleviation of polychlorinated biphenyl (PCB)-induced phytotoxicity in alfalfa and the brassinosteroid (BR) hormone signaling involved were investigated during phytoremediation. The association between alfalfa and Sinorhizobium meliloti was adopted as a remediation model. Phytotoxicity due to PCB 77(More)
The visible and near-infrared (VNIR) spectroscopy prediction model is an effective tool for the prediction of soil organic matter (SOM) content. The predictive accuracy of the VNIR model is highly dependent on the selection of the calibration set. However, conventional methods for selecting the calibration set for constructing the VNIR prediction model(More)
Time series clustering algorithms have been widely used to mine the clustering distribution characteristics of real phenomena. However, these algorithms have several limitations. First, they depend heavily on prior knowledge. Second, the algorithms do not simultaneously consider the similarity of spatial locations, spatial-temporal attribute values, and(More)