Prevalence of Kaposi’s sarcoma-associated herpesvirus in Uygur and Han populations from the Urumqi and Kashgar regions of Xinjiang, China

Kaposi’s sarcoma-associated herpesvirus (KSHV) is the infectious etiologic agent associated with Kaposi’s sarcoma (KS), primary effusion lymphoma, and multicentric Castleman disease. It has been shown that high KSHV prevalence and high incidence of both classic KS and AIDSassociated KS are found mostly among people of Uygur ethnicity in Xinjiang, while people of Han ethnicity in Xinjiang have a higher KSHV seroprevalence than those of other Han populations in mainland China. However, it is still unclear why there is such geographical and population variation in KSHV distribution in China. In this work, we focused on the populations in the Kashgar region and Urumqi area, where a total of 1294 research subjects were randomly selected to investigate the potential correlation between KSHV prevalence and different ethnicities in endemic areas of Xinjiang, and to determine risk factors that may affect KSHV infection rates or KS incidence. We identified a high seroprevalence of KSHV and high peripheral blood DNA infection in the general Uygur and Han populations in both Urumqi and Kashgar regions of Xinjiang, and determined that advancing age, low education level, and stationary population status affect KSHV infection rates. Further, KSHV-positive Uygur participants were shown to have higher prevalence of neutralizing antibodies and neutralizing antibody titers than KSHV-positive Han participants

Feedback Linearization Control for Path Tracking of Articulated Dump Truck

The articulated dump truck is a widespread tansport vehicle for narrow rough terrain environment. To achieve the autonomous driving in the underground tunnel, this ariticle proporses a path following strategy of articulated vehicle based on feedback linearization algorithm. Fisrt of all, the articulated vehicle kinematics model, which reflects the relationship of the structure parameters and state variables, is established. Refering to the model, the nonlinear errors equation between real path and reference path, which are as the feedback from the path tracking process, is solved and linearized. After estimating the system controllable, according to the error equation, the path following controller with feedback linearization algorithm is designed through calaculating the parameters with the pole assignment. Finally, the hardware in the loop simulation on NI cRIO and PXI controller is lunched for verifying the control quality and real-time path tracking performance

Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory

In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G) technique, electric vehicles (EVs) can act as mobile energy storage units, which could be a solution for load frequency control (LFC) in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC) theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG) are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances

No association between XRCC1 gene Arg194Trp polymorphism and risk of lung cancer: evidence based on an updated cumulative meta-analysis

X-ray repair cross-complementing group 1 (XRCC1) gene Arg194Trp polymorphism has been reported to be associated with risk of lung cancer in many published studies. Nevertheless, the research results were inconclusive and conflicting. To reach conclusive results, several meta-analysis studies were conducted by combining results from literature reports through pooling analysis. However, these previous meta-analysis studies were still not consistent. Hence, we used an updated and cumulative meta-analysis to get a more comprehensive and precise result from 25 case–control studies searching through the PubMed database up to September 1, 2013. The meta-analysis was carried out by the Comprehensive Meta-Analysis software and the odds ratio (OR) with 95 % confidence interval (CI) was used to estimate the pooled effect. The result involving 8,876 lung cancer patients and 11,210 controls revealed that XRCC1 Arg194Trp polymorphism was not associated with lung cancer risk [(OR = 0.97, 95 %CI = 0.92–1.03) for Trp vs. Arg; (OR = 0.92, 95 % CI = 0.85–0.98) for ArgTrp vs. ArgArg; (OR = 1.07, 95 % CI = 0.92–1.23) for TrpTrp vs. ArgArg; (OR = 0.93, 95 % CI = 0.87–1.00) for (TrpTrp + ArgTrp) vs. ArgArg; and (OR = 1.08, 95 % CI = 0.94–1.25) for TrpTrp vs. (ArgTrp + ArgArg)]. The cumulative meta-analysis showed that the results maintained the same, while the ORs with 95 % CI were more stable with the accumulation of case–control studies. The sensitivity and subgroups analyses showed that the results were robust and not affected by any single study with no publication bias. Relevant studies might not be needed for supporting these results