Massive data delivery in unstructured peer-to-peer networks with network coding

With more and more multimedia applications on the Internet, such as IPTV, bandwidth becomes a vital bottleneck for the booming of large scale Internet based multimedia applications. Network coding is recently proposed to take advantage to use network bandwidth efficiently. In this paper, we focus on massive multimedia data, e.g. IPTV programs, transportation in peer-to-peer networks with network coding. By through study of networking coding, we pointed out that the prerequisites of bandwidth saving of network coding are: 1) one information source with a number of concurrent receivers, or 2) information pieces cached at intermediate nodes. We further proof that network coding can not gain bandwidth saving at immediate connections to a receiver end; As a result, we propose a novel model for IPTV data transportation in unstructured peer-to-peer networks with network coding. Our preliminary simulations show that the proposed architecture works very well.<br /

Performance optimization for energy-aware adaptive checkpointing in embedded real-time systems

Using additional store-checkpoinsts (SCPs) and compare-checkpoints (CCPs), we present an adaptive checkpointing for double modular redundancy (DMR) in this paper. The proposed approach can dynamically adjust the checkpoint intervals. We also design methods to calculate the optimal numbers of checkpoints, which can minimize the average execution time of tasks. Further, the adaptive checkpointing is combined with the DVS (dynamic voltage scaling) scheme to achieve energy reduction. Simulation results show that, compared with the previous methods, the proposed approach significantly increases the likelihood of timely task completion and reduces energy consumption in the presence of faults.<br /

Effect of ganoderic acid on diethylnitrosamine-induced liver cancer in mice

Purpose: To investigate the hepatoprotective role of ganoderic acid A (GAA) on liver cancer induced by diethylnitrosamine (DEN) via Nrf-2/HO-1/NF-κB signal pathway in mice. Methods: Sixty male C57BL/6J mice were randomly divided into 4 groups: (1) control group, (2) DEN (25 mg/kg) group, (3) GAA (20 mg/kg) + DEN group, (4) GAA (40 mg/kg) + DEN group. The protective effect of GAA on liver was evaluated by determining malondialdehyde (MDA), superoxide dismutase (SOD), inflammatory cytokines including interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and the expression of heme oxygenase-1 (HO-1), nuclear factor erythroid- 2-related factor-2 (Nrf-2), IκBα, p-IκBα, p65, p-p65, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in serum. Results: The results demonstrate that GAA treatment significantly suppressed the generation of MDA, proinflammatory cytokines, and restored the activity of SOD in the serum of DEN-induced liver cancer in mice. Western blots analysis revealed that GAA significantly restored Nrf-2/HO-1/NF-κB signal pathwayrelated protein levels in DEN-induced mice liver cancer model. Conclusion: This research reveals the anticancer activity of GAA in liver tissue, and suggests that GAA counters DEN-induced liver&nbsp; cancer through Nrf-2/HO-1/NF-κB signal pathway. Keywords: Ganoderic acid A, Nrf-2/HO-1/NF-κB pathway, Liver cancer, MDA, GAPDH, SO

Estimation of Semi-Varying Coefficient Models with Nonstationary Regressors

We study a semi-varying coefficient model where the regressors are generated by the multivariate unit root I(1) processes. The influence of the explanatory vectors on the response variable satisfies the semiparametric partially linear structure with the nonlinear component being functional coefficients. A semiparametric estimation methodology with the first-stage local polynomial smoothing is applied to estimate both the constant coefficients in the linear component and the functional coefficients in the nonlinear component. The asymptotic distribution theory for the proposed semiparametric estimators is established under some mild conditions, from which both the parametric and nonparametric estimators are shown to enjoy the well-known super-consistency property. Furthermore, a simulation study is conducted to investigate the finite sample performance of the developed methodology and results

Pushing the limit of earthquake detection with distributed acoustic sensing and template matching: a case study at the Brady geothermal field

Template matching has been widely applied in the detection of earthquakes and other seismic events due to its power in detecting weak signals. Recent studies using synthetics have shown that application of template matching to large-N arrays can potentially detect earthquakes substantially below the noise level. Here we apply template matching to the distributed acoustic sensing (DAS) data recorded in the Brady Hot Springs geothermal field, Nevada. Using 5 catalogued events, we detect 116 events and find 68 of them well below the noise level. We confirm 112 events are true earthquakes by examining the patterns of their sensor-to-sensor cross-correlation sections. This demonstrates that the combination of DAS and template matching has capability to detect microseismicity below the noise level, which is unusual for conventional seismic arrays and methods. With the updated catalogue, we observe a surge of earthquakes during the shutdown of a geothermal power plant nearby. In addition, the rapid increases in the downhole pressure record coincide with intense swarms of earthquakes. These observations show a strong correlation between the seismicity frequencies and the downhole pressure changes. Finally, we investigate several factors that may affect the detection performance and compare different strategies for spatial down-sampling, in order to provide helpful insights for future large-N design and data processing