Structural Analysis of Network Traffic Matrix via Relaxed Principal Component Pursuit

The network traffic matrix is widely used in network operation and management. It is therefore of crucial importance to analyze the components and the structure of the network traffic matrix, for which several mathematical approaches such as Principal Component Analysis (PCA) were proposed. In this paper, we first argue that PCA performs poorly for analyzing traffic matrix that is polluted by large volume anomalies, and then propose a new decomposition model for the network traffic matrix. According to this model, we carry out the structural analysis by decomposing the network traffic matrix into three sub-matrices, namely, the deterministic traffic, the anomaly traffic and the noise traffic matrix, which is similar to the Robust Principal Component Analysis (RPCA) problem previously studied in [13]. Based on the Relaxed Principal Component Pursuit (Relaxed PCP) method and the Accelerated Proximal Gradient (APG) algorithm, we present an iterative approach for decomposing a traffic matrix, and demonstrate its efficiency and flexibility by experimental results. Finally, we further discuss several features of the deterministic and noise traffic. Our study develops a novel method for the problem of structural analysis of the traffic matrix, which is robust against pollution of large volume anomalies.Comment: Accepted to Elsevier Computer Network

Last Glacial climate reconstruction by exploring glacier sensitivity to climate on the southeastern slope of the western Nyaiqentanglha Shan, Tibetan Plateau

Improvements in understanding glacial extents and chronologies for the southeastern slope of the western Nyaiqentanglha Shan on the Tibetan Plateau are required to understand regional climate changes during the Last Glacial cycle. A two-dimensional numerical model of mass balance, based on snow-ice melting factors, and of ice flow for mountain glaciers is used to assess the glacier sensitivity to climatic change in a catchment of the region. The model can reproduce valley glaciers, wide-tongued glaciers and a coalescing glacier within step temperature lowering and precipitation increasing experiments. The model sensitivity experiments also indicate that the dependence of glacier growth on temperature and/or precipitation is nonlinear. The model results suggest that the valley glaciers respond more sensitively to an imposed climate change than wide-tongued and coalescing glaciers. Guided by field geological evidence of former glacier extent and other independent paleoclimate reconstructions, the model is also used to constrain the most realistic multi-year mean temperatures to be 2.9-4.6 degrees C and 1.8-2.5 degrees C lower than present in the glacial stages of the Last Glacial Maximum and middle marine oxygen isotope stage 3, respectively

Dynamics of a Stage Structured Pest Control Model in a Polluted Environment with Pulse Pollution Input

By using pollution model and impulsive delay differential equation, we formulate a pest control model with stage structure for natural enemy in a polluted environment by introducing a constant periodic pollutant input and killing pest at different fixed moments and investigate the dynamics of such a system. We assume only that the natural enemies are affected by pollution, and we choose the method to kill the pest without harming natural enemies. Sufficient conditions for global attractivity of the natural enemy-extinction periodic solution and permanence of the system are obtained. Numerical simulations are presented to confirm our theoretical results

Estimation of Areal Mean Rainfall in Remote Areas Using B-SHADE Model

This study presented a method to estimate areal mean rainfall (AMR) using a Biased Sentinel Hospital Based Area Disease Estimation (B-SHADE) model, together with biased rain gauge observations and Tropical Rainfall Measuring Mission (TRMM) data, for remote areas with a sparse and uneven distribution of rain gauges. Based on the B-SHADE model, the best linear unbiased estimation of AMR could be obtained. A case study was conducted for the Three-River Headwaters region in the Tibetan Plateau of China, and its performance was compared with traditional methods. The results indicated that B-SHADE obtained the least estimation biases, with a mean error and root mean square error of −0.63 and 3.48 mm, respectively. For the traditional methods including arithmetic average, Thiessen polygon, and ordinary kriging, the mean errors were 7.11, −1.43, and 2.89 mm, which were up to 1027.1%, 127.0%, and 358.3%, respectively, greater than for the B-SHADE model. The root mean square errors were 10.31, 4.02, and 6.27 mm, which were up to 196.1%, 15.5%, and 80.0%, respectively, higher than for the B-SHADE model. The proposed technique can be used to extend the AMR record to the presatellite observation period, when only the gauge data are available

RCN1 induces sorafenib resistance and malignancy in hepatocellular carcinoma by activating c-MYC signaling via the IRE1α–XBP1s pathway

The increasing incidence of hepatocellular carcinoma (HCC) is of great concern globally, but the molecular pathogenesis of these tumors remains unclear. Sorafenib is a first-line drug for the treatment of advanced HCC. However, the efficacy of sorafenib in improving patient survival is limited, and most patients inevitably develop resistance to this drug. Recent studies have demonstrated that the activation of the IRE1α–XBP1s pathway might play a protective role in the response to sorafenib and contribute to malignancy in HCC. Here, we found that RCN1, an endoplasmic reticulum resident protein, is significantly upregulated in sorafenib-resistant HCC cells and promotes tumor progression. Our analysis showed that RCN1 may be an independent predictor of tumor recurrence and overall survival. Mechanistically, RCN1 promotes the dissociation of GRP78 from IRE1α in sorafenib-resistant cells by interacting with GRP78 through its EFh1/2 domain. Subsequently, the IRE1α–XBP1s pathway, a branch of the unfolded protein response, is sustainably activated. Interestingly, IRE1α–XBP1s pathway activity is required for c-MYC signaling, one of the most highly activated oncogenic pathways in HCC. These results suggest that RCN1-targeted therapy might be a feasible strategy for the treatment of HCC

Numerical simulation on the migration and permeable reaction barrier purification of groundwater contaminated by UCG

Underground coal gasification (UCG) is consistent with the development of low-carbon green transformation of energy in China. However, the groundwater pollution caused by it is the bottleneck preventing from the promotion and application of UCG. Permeable reaction barrier (PRB) is one of the research hotspots for in-situ groundwater remediation. In this paper, combined with the characteristics of UCG with shaft, the influence of PRB’s thickness and purification materials on the migration and dispersion of organic pollutants in groundwater, and purification and remediation were investigated by numerical simulation. On the foundation of the advection-diffusion equation (ADE), two hypotheses were introduced: ① The mass transfer involved in the adsorption and purification of pollutants in groundwater is related to: (i) the difference potential between the concentration of pollutants adsorbed in the liquid and solid phases, (ii) the difference potential between the current adsorption concentration of solid phase and the potential maximum adsorption concentration, and (iii) the process time; ② The strong adsorption ability of activated carbon may lead to the gradual accumulation of adsorption concentration in the solid phase and no longer easy desorption with the change of the external liquid phase concentration. Both the migration of pollutants and the adsorption and purification processes were simulated numerically and validated experimentally after that the finite element method and \begin{document}$\theta$\end{document}-format iteration were adapted and the corresponding program were coded in MATLAB. The results show that the remediation is enhanced with the increase of the thickness of PRB, but at a declining acceleration, and the marginal effect of the wall thickness increase on the purification shows the diminishing trend. The stronger the adsorption and purification rate of the wall material is, the better the purification of the PRB on pollutants will be, and the adsorption and purification rate also shows a diminishing trend of marginal effect on the purification. There is a synergistic influence between the thickness and the adsorption activity of the material, thus the thickness of PRB should be determined reasonably according to the adsorption and purification rate of the material when constructing PRB in order to obtain the best technical and economic consequence