Publications by authors named "Xiu Fu"

Article Synopsis
  • A comparison of total organic carbon, nitrogen, phosphorus, and soil microbial biomass between the rhizosphere of two plants, Paris polyphylla and Panax japonicus, reveals their differing effects on soil traits and nutrient cycles.
  • P. japonicus had the highest total organic carbon, total nitrogen, and microbial nitrogen, while P. polyphylla had the highest total phosphorus and microbial biomass phosphorus.
  • Despite changes in soil nutrient levels from monoculture planting, neither species created nutrient deficiencies, indicating different nitrogen and phosphorus demands, and raising questions about the ecological implications of their distinct soil influences.
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The defects and subsurface damages induced by crystal growth and micro/nano-machining have a significant impact on the functional performance of machined products. Raman spectroscopy is an efficient, powerful, and non-destructive testing method to characterize these defects and subsurface damages. This paper aims to review the fundamentals and applications of Raman spectroscopy on the characterization of defects and subsurface damages in micro/nano-machining.

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Oleanolic acid (OA), one of the bioactive ingredients in ginseng, has been reported to have neuroprotective activities. However, the effects and its mechanism on neural stem cell (NSC) induction are not entirely clear. In the present study, we investigated the effects of OA on promoting the migration, proliferation, and differentiation of neural stem cells (NSCs).

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Apigenin is a flavonoid belonging to the flavone structural class. It has been implicated as a chemopreventive agent against prostate and breast cancers. However, to the best of our knowledge, no published data are available regarding apigenin in colorectal cancer (CRC).

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Sequential minimal optimization (SMO) is one popular algorithm for training support vector machine (SVM), but it still requires a large amount of computation time for solving large size problems. This paper proposes one parallel implementation of SMO for training SVM. The parallel SMO is developed using message passing interface (MPI).

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