Yuejun Wang

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Due to their properties such as superparamagnetism, high surface area, large surface-to-volume ratio, easy separation under external magnetic fields, iron magnetic nanoparticles have attracted much attention in the past few decades. Various modification methods have been developed to produce biocompatible magnetic nanoparticles for protein immobilization.(More)
Polypeptide from Chlamys farreri (PCF) possesses strong antioxidant and photochemo-preventive properties. Our previous study has preliminarily demonstrated that PCF could reduce the intracellular reactive oxygen species (ROS) production and protect UVB-induced HaCaT cells apoptosis. But the anti-apoptotic effects of PCF on components of cell signaling(More)
The level of chemical weathering is strongly affected by climate. We presented magnetic properties associated with element ratios from the northern part of the South China Sea to denote links between chemical weathering intensity and monsoon changes in the previous 90,000 years. The magnetic parameter IRM AF80mT /SIRM, representing the variations of high(More)
Metalloproteases are emerging as useful agents in the treatment of many diseases including arthritis, cancer, cardiovascular diseases, and fibrosis. Studies that could shed light on the metalloprotease pharmaceutical applications require the pure enzyme. Here, we reported the structure-based design and synthesis of the affinity medium for the efficient(More)
MARTE (Modeling and Analysis of Real-Time and Embedded Systems) is a profile of UML (United Modeling Language). MARTE provides support for specification, design and verification of real-time and embedded systems. Even though MARTE time model offers a support to describe multiform clocks, it lacks the ability to model both discrete and continuous behaviors(More)
Modeling and Analysis of Real-Time and Embedded systems (MARTE) is a profile of United Modeling Language (UML), which provides support for specification, design and verification for Real-Time Embedded Systems (RTES). MARTE sequence diagram can deal with both discrete and dense time in which a clock can be either chronometric or logical. However it lacks the(More)
In fermentation process, fuzzy neural networks (FNN) is a novel machine learning method of soft sensor modeling, while the typical algorithm of FNN is inefficient because they can not optimize fuzzy rules and has long training time. Biological parameters can be measured online in real time which is helpful for the control of process optimization. So this(More)
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