Spatial Variability of Soil Carbon to Nitrogen Ratio and Its Driving Factors in Ili River Valley,Xinjiang,Northwest China

Soil carbon to nitrogen(C/N) ratio is one of the most important variables reflecting soil quality and ecological function,and an indicator for assessing carbon and nitrogen nutrition balance of soils.Its variation reflects the carbon and nitrogen cycling of soils.In order to explore the spatial variability of soil C/N ratio and its controlling factors of the Ili River valley in Xinjiang Uygur Autonomous Region,Northwest China,the traditional statistical methods,including correlation analysis,geostatistic alanalys and multiple regression analysis were used.The statistical results showed that the soil C/N ratio varied from 7.00 to 23.11,with a mean value of 10.92,and the coefficient of variation was 31.3%.Correlation analysis showed that longitude,altitude,precipitation,soil water,organic carbon,and total nitrogen were positively correlated with the soil C/N ratio(P < 0.01),whereas negative correlations were found between the soil C/N ratio and latitude,temperature,soil bulk density and soil p H.Ordinary Cokriging interpolation showed that r and ME were 0.73 and 0.57,respectively,indicating that the prediction accuracy was high.The spatial autocorrelation of the soil C/N ratio was 6.4 km,and the nugget effect of the soil C/N ratio was 10% with a patchy distribution,in which the area with high value(12.00–20.41) accounted for 22.6% of the total area.Land uses changed the soil C/N ratio with the order of cultivated land > grass land > forest land > garden.Multiple regression analysis showed that geographical and climatic factors,and soil physical and chemical properties could independently explain 26.8%and 55.4% of the spatial features of soil C/N ratio,while human activities could independently explain 5.4% of the spatial features only.The spatial distribution of soil C/N ratio in the study has important reference value for managing soil carbon and nitrogen,and for improving ecological function to similar regions.

Empirical Study on Financial Failure Prediction of Listed Companies

Since it is a gradual process for listed companies to plunge into financial failure, it is desirable to discern tho potential risks in advance. This paper, with the adoption of multiple discriminant analyzing approach, tries to find out optimal variables and financial failure predicting model for Chinese listed companies based on audited accounting data.

A Low Complexity VCS Method for PAPR Reduction in Multicarrier Code Division Multiple Access

This paper investigates a peak to average power ratio （PAPR） reduction method in multicarrier code division multiple access （MC-CDMA） system. Variable code sets （VCS）, a spreading codes selection scheme, can improve the PAPR property of the MC-CDMA signals, but this technique requires an exhaustive search over the combinations of spreading code sets. It is observed that when the number of active users increases, the search complexity will increase exponentially. Based on this fact, we propose a low complexity VCS （LC-VCS） method to reduce the computational complexity. The basic idea of LC-VCS is to derive new signals using the relationship between candidature signals. Simulation results show that the proposed approach can reduce PAPR with lower comtational pucomplexity. In addition, it can be blindly received without any side information.

Behavior of reinforced concrete structural walls with various opening locations: experiments and macro model

Two experimental tests of three-storied reinforced concrete structural walls having large openings were performed.Based on an original macro model,a multiple modified macro-model was proposed to develop a simple method to design a reinforced concrete structural wall with large openings and various opening locations.The interaction between reinforcement ties and concrete struts formed along the perimeter of openings was neglected in the original model.However,the strut-and-tie node was proposed to take account of such interaction in the proposed model.The predicted behavior of two specimens using such a proposed model was compared with the experimental results.It is shown that the behavior of structural walls with large openings could be modeled well using the proposed model.Moreover,the study indicates that the proposed model is applicable even in cases of multi-story structural walls having large openings and various opening locations.