Dynamic Response of Earth Dam-Foundation System

A numerical procedure is proposed to analyze the seismic response of structure resting on layered medium. By this approach the effects of the dynamic soil-structure interaction (DSSI) upon the response of earth dam on multi-layered half space subjected to seismic ground motions are studied. The dynamic responses of earth dams on rigid base are also evaluated to compare with those on a flexible homogenous half space. It is noted that great differences may arise between the results of the two cases. To investigate the influence of the truncated size of foundation in horizontal direction on the dynamic response of the earth dam on a single layered foundation, the conventional finite element method (FEM) are employed, in which the dam together with a finite size of foundation is analyzed. It is shown that, for most cases, DSSI decreases the response amplitudes of the earth dam significantly

Short-term effects of forest gap size on soil enzyme activity in a Platycladus orientalis plantation

IntroductionSoil enzymes play a critical role in organic matter decomposition and nutrient cycling in forest ecosystems. However, the effects of forest gaps on soil enzyme activities remain uncertain.MethodsThis study aims to investigate the short-term effects of forest gap size on soil enzyme activities in Platycladus orientalis plantations. We conducted a study in a 50-year Platycladus orientalis plantation in Xuzhou, sampling soils from three levels of forest gap size (4 m radius, S; 8 m radius, M and 12 m radius, L) at different positions (within gap, edge, and outside the gap) and control plots (CK, no gaps) 2a after the creation of gaps. Soil peroxidase, dehydrogenase, urease, and invertase activities were measured.ResultsSpecifically, we found that M and S gaps had significantly (p < 0.05) higher soil peroxidase activity at the outside position in April and October, respectively, than CK. Additionally, L gaps had significantly (p < 0.05) higher soil dehydrogenase activity at the outside position in April than CK. Furthermore, L and S gaps had significantly (p < 0.05) higher soil urease activity at the outside position in October and July, respectively, than CK. Lastly, L and S gaps had significantly (p < 0.05) higher soil urease activity at the outside position in July than CK.ConclusionOur findings highlight the significant impact of canopy gaps on soil enzyme activities, which has important implications for forest management and conservation

An Outlier Detection Algorithm Based on Cross-Correlation Analysis for Time Series Dataset

Outlier detection is a very essential problem in a variety of application areas. Many detection methods are deficient for high-dimensional time series data sets containing both isolated and assembled outliers. In this paper, we propose an Outlier Detection method based on Cross-correlation Analysis (ODCA). ODCA consists of three key parts. They are data preprocessing, outlier analysis, and outlier rank. First, we investigate a linear interpolation method to convert assembled outliers into isolated ones. Second, a detection mechanism based on the cross-correlation analysis is proposed for translating the high-dimensional data sets into 1-D cross-correlation function, according to which the isolated outlier is determined. Finally, a multilevel Otsu\u27s method is adopted to help us select the rank thresholds adaptively and output the abnormal samples at different levels. To illustrate the effectiveness of the ODCA algorithm, four experiments are performed using several high-dimensional time series data sets, which include two smallscale sets and two large-scale sets. Furthermore, we compare the proposed algorithm with the detection methods based on wavelet analysis, bilateral filtering, particle swarm optimization, auto-regression, and extreme learning machine. In addition, we discuss the robustness of the ODCA algorithm. The statistical results show that the ODCA algorithm is much better than existing mainstream methods in both effectiveness and time complexity