Xuzhou Institute of Technology

About: Xuzhou Institute of Technology is a education organization based out in Xuzhou, China. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 1696 authors who have published 1521 publications receiving 13541 citations.

Preparation and Antioxidant Activity Evaluation of Flammulina velutipes Polysaccharide/Fe(II) Chelate

Abstract: In this study,the optimal conditions for the chelating reaction between Flammulina velutipes polysaccharide and Fe(Ⅱ) for achieving maximum chelating degree were investigated using single-factor method and response surface analysis,and evaluation of antioxidant activity of the obtained Flammulina velutipes polysaccharide/Fe(Ⅱ) chelate was performed. A maximum chelating degree of 86.21% was achieved when the reaction between Fe(Ⅱ) with an initial concentration of 6 mg/mL and Flammulina velutipes polysaccharide (3.54:1,mg/mg) was allowed to proceed for 6 h. Moreover,the antioxidant activity evaluation indicated that the abilities of Flammulina velutipes polysaccharide to scavenge hydroxyl and DPPH free radicals and the inhibitory effect against lecithin peroxidation were all improved after the chelation with Fe(Ⅱ).

Efficient framework for predicting MiRNA-disease associations based on improved hybrid collaborative filtering.

Abstract: Background Accumulating studies indicates that microRNAs (miRNAs) play vital roles in the process of development and progression of many human complex diseases. However, traditional biochemical experimental methods for identifying disease-related miRNAs cost large amount of time, manpower, material and financial resources. Methods In this study, we developed a framework named hybrid collaborative filtering for miRNA-disease association prediction (HCFMDA) by integrating heterogeneous data, e.g., miRNA functional similarity, disease semantic similarity, known miRNA-disease association networks, and Gaussian kernel similarity of miRNAs and diseases. To capture the intrinsic interaction patterns embedded in the sparse association matrix, we prioritized the predictive score by fusing three types of information: similar disease associations, similar miRNA associations, and similar disease-miRNA associations. Meanwhile, singular value decomposition was adopted to reduce the impact of noise and accelerate predictive speed. Results We then validated HCFMDA with leave-one-out cross-validation (LOOCV) and two types of case studies. In the LOOCV, we achieved 0.8379 of AUC (area under the curve). To evaluate the performance of HCFMDA on real diseases, we further implemented the first type of case validation over three important human diseases: Colon Neoplasms, Esophageal Neoplasms and Prostate Neoplasms. As a result, 44, 46 and 44 out of the top 50 predicted disease-related miRNAs were confirmed by experimental evidence. Moreover, the second type of case validation on Breast Neoplasms indicates that HCFMDA could also be applied to predict potential miRNAs towards those diseases without any known associated miRNA. Conclusions The satisfactory prediction performance demonstrates that our model could serve as a reliable tool to guide the following research for identifying candidate miRNAs associated with human diseases.

Preparation of a novel magnetorheological fluid for high temperatures

Abstract: Magnetorheological fluids, especially those in high-power magnetorheological devices, inevitably work at high temperatures because of the wall slip, energized coils and frictions between particles. In order to prepare a magnetorheological fluid for high temperatures, this work investigates the properties of three main components (soft magnetic particles, surfactants and base carrier fluids) for a magnetorheological fluid at high temperatures. On this basis, a novel magnetorheological fluid for high temperatures is prepared. Its sedimentation stability, viscosity and shear yield stress are investigated at high temperatures. The results show that the novel magnetorheological fluid has acceptable sedimentation, suitable viscosity and stable shear yield stress at high temperatures. The novel magnetorheological fluid for high temperatures can be applied to most magnetorheological devices, especially high-power magnetorheological devices.

Water Quality of Inflows to the Everglades National Park over Three Decades (1985⁻2014) Analyzed by Multivariate Statistical Methods

Abstract: The Everglades, a vast subtropical wetland, dominates the landscape of south Florida and is widely recognized as an ecosystem of great ecological importance Data from seven inflow sites to the Everglades National Park (ENP) were analyzed over three decades (1985⁻2014) for temporal trends by the STL (integrated seasonal-trend decomposition using LOESS) method A cluster analysis (CA) and principal component analysis (PCA) were applied for the evaluation of spatial variation The results indicate that the water quality change trend is closely associated with rainfall Increasing rainfall results in increasing flow and thus, decreasing concentrations of nitrogen and phosphorus Based on 10 variables, the seven sampling stations were classified by CA into four distinct clusters: A, B, C, and D The PCA analysis indicated that total nitrogen (TN) and total phosphorus (TP) are the main pollution factors, especially TN The results suggest that non-point sources are the main pollution sources and best management practices (BMPs) effectively reduce organic nitrogen However, TN and TP control is still the focus of future work in this area Increasing the transfer water quantity can improve the water quality temporarily and planting submersed macrophytes can absorb nitrogen and phosphorus and increase the dissolved oxygen (DO) concentration in water, continuously improving the water quality