Extraction and Analysis of Gully Head of Loess Plateau in China Based on Digital Elevation Model

In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.

Research on Online Reviews Impact on Commodity Sales in B2C E-commerce

The objective of this paper was to analyze the impact of online reviews on sales. Based on dual path model of commodity sales, an online reviews impact on the relationship between various factors, and then the theoretical hypothesis of each factor has been put forward in the model. As it is intuitive and strongly supported empirically, data including Chinese texts captured from Tmall.com was utilized, and then analyzed by SPSS and ROST CM6. Our empirical study on the reviews of Tmall.com indicated that the hypotheses are verified.

Accumulation and source of heavy metals in sediment of a reservoir near an industrial park of northwest China

The accumulation and source of heavy metals As, Ba, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn in the surface sediment of a reservoir near an industrial park of northwest China were determined by enrichment factor and multi- variate statistical analysis. Multivariate statistical analyses, i.e., factor analysis, cluster analysis, and correlation coefficient analysis, were used to identify the possible sources of the heavy metals. The results show that the mean concentrations of As, Ba, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn in the reservoir sediment are higher than their corresponding concentrations in the control sample, indicating all analyzed heavy metals accumulated in the surface sediments. The values of the mean concentrations of heavy metals in the surface sediment divided by their corresponding concentrations in the control sample increase in the order of Ba= Cr 〈 Co = Pb 〈 V 〈 Ni 〈 Cu = Zn 〈 As 〈 Mn. The enrichment factor values of Ba and Cr in the surface sediment samples are 〈 2, revealing minimal enrichment, while the enrichment factor values of As, Co, Cu, Mn, Ni, Pb, V, and Zn are in the range of 2-5, displaying moderate enrichment. Combining the results of correlation coefficient analysis, factor analysis, and cluster analysis, three main sources of these heavy metals were identified. As, Co, Cu, Mn, Ni, and V have mixed sources of natural and industrial sources and local consumption residues; Pb and Zn mainly originate from industrial activities, while Ba and Cr primarily originate from natural sources.