Reliability Analysis of a Repairable C (2, 3; G ) System with Repair Priority and one is＂as good as new＂

In this paper, we discuss a repairable linear C (2, 3; G) system. One repairman carries out the maintenance of the system. It is assumed that the working time and the repair time of each component in the system are both exponentially distributed and only one component after repair is as good as new. Each component is classified as either a key component or an ordinary one according to its priority role to the system’s repair. We apply the geometric process, supplementary variable technique and generalized Markov process to study a repairable linear C (2, 3; G) system. We obtain Laplace transforms of some reliability indices such as availability and reliability.Key words: repairable system; generalized Markov process; key component; geometric proces

Globalization and pollution: tele-connecting local primary PM_(2.5) emissions to global consumption

Globalization pushes production and consumption to geographically diverse locations and generates a variety of sizeable opportunities and challenges. The distribution and associated effects of short-lived primary fine particulate matter (PM_(2.5)), a representative of local pollution, are significantly affected by the consumption through global supply chain. Tele-connection is used here to represent the link between production and consumption activity at large distances. In this study, we develop a global consumption-based primary PM_(2.5) emission inventory to track primary PM_(2.5) emissions embodied in the supply chain and evaluate the extent to which local PM2.5 emissions are triggered by international trade. We further adopt consumption-based accounting and identify the global original source that produced the emissions. We find that anthropogenic PM_(2.5) emissions from industrial sectors accounted for 24 Tg globally in 2007; approximately 30% (7.2 Tg) of these emissions were embodied in export of products principally from Brazil, South Africa, India and China (3.8 Tg) to developed countries. Large differences (up to 10 times) in the embodied emissions intensity between net importers and exporters greatly increased total global PM_(2.5) emissions. Tele-connecting production and consumption activity provides valuable insights with respect to mitigating long-range transboundary air pollution and prompts concerted efforts aiming at more environmentally conscious globalization

Effects of Vaccinium Berries on Serum Lipids: A Meta-Analysis of Randomized Controlled Trials

The beneficial effects of anthocyanins consumption on cardiovascular risk are supported by mechanistic and epidemiologic evidence. In order to explore the effects of Vaccinium berries rich in anthocyanins on serum lipids, we conducted a meta-analysis of relevant randomized controlled trials (RCTs). Sixteen studies with 1109 subjects were included in this meta-analysis. Significant heterogeneity confirmed differential effects between Vaccinium subclasses. The whortleberry group is significantly superior to placebo in lipids improvement. Besides, bilberry groups show significant differences in reducing LDL-C and increasing HDL-C in comparison with other treatments. For many of the other subgroups and comparison arms, there was insufficient evidence to draw conclusions about efficacy

Effects of Vaccinium

The beneficial effects of anthocyanins consumption on cardiovascular risk are supported by mechanistic and epidemiologic evidence. In order to explore the effects of Vaccinium berries rich in anthocyanins on serum lipids, we conducted a meta-analysis of relevant randomized controlled trials (RCTs). Sixteen studies with 1109 subjects were included in this meta-analysis. Significant heterogeneity confirmed differential effects between Vaccinium subclasses. The whortleberry group is significantly superior to placebo in lipids improvement. Besides, bilberry groups show significant differences in reducing LDL-C and increasing HDL-C in comparison with other treatments. For many of the other subgroups and comparison arms, there was insufficient evidence to draw conclusions about efficacy

Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method

The problem of course control for underactuated surface ship is addressed in this paper. Firstly, neural networks are adopted to determine the parameters of the unknown part of ideal virtual backstepping control, even the weight values of neural network are updated by adaptive technique. Then uniform stability for the convergence of course tracking errors has been proven through Lyapunov stability theory. Finally, simulation experiments are carried out to illustrate the effectiveness of proposed control method

Comparative analysis of the secretomes of Schizophyllum commune and other wood-decay basidiomycetes during solid-state fermentation reveals its unique lignocellulose-degrading enzyme system

Additional file 3: Table S2. Identified proteins in the secretomes of four fungi during SSF on Jerusalem artichoke stalk

Shen-Fu Injection Preconditioning Inhibits Myocardial Ischemia-Reperfusion Injury in Diabetic Rats: Activation of eNOS via the PI3K/Akt Pathway

The aim of this paper is to investigate whether Shen-fu injection (SFI), a traditional Chinese medicine, could attenuate myocardial ischemia-reperfusion (MI/R) injury in diabetes. Streptozotocin-induced diabetic rats were randomly assigned to the Sham, I/R, SFI preconditioning, and SFI plus wortmannin (a phosphatidylinositol 3-kinase inhibitor) groups. After the treatment, hearts were subjected to 30 min of coronary artery occlusion and 2 h reperfusion except the Sham group. Myocardial infarct size and cardiomyocytes apoptosis were increased significantly in MI/R group as compared with the Sham group. SFI preconditioning significantly decreased infarct size, apoptosis, caspase-3 protein expression, MDA level in myocardial tissues, and plasma level of CK and LDH but increased p-Akt, p-eNOS, bcl-2 protein expression, and SOD activity compared to I/R group. Moreover, SFI-induced cardioprotection was abolished by wortmannin. We conclude that SFI preconditioning protects diabetic hearts from I/R injury via PI3K/Akt-dependent pathway

Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder

Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited.Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier.Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%.Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis