Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method

Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. (C) 2015 Elsevier B.V. All rights reserved.

Influence of Anisotropy on Pavement Responses Using Adaptive Sparse Polynomial Chaos Expansion

Modeling the spatial variability that exists in pavement systems can be conveniently represented by means of random fields; in this study, a probabilistic analysis that considers the spatial variability, including the anisotropic nature of the pavement layer properties, is presented. The integration of the spatially varying log-normal random fields into a linear-elastic finite difference analysis has been achieved through the expansion optimal linear estimation method. For the estimation of the critical pavement responses, metamodels based on polynomial chaos expansion (PCE) are developed to replace the computationally expensive finite-difference model. The sparse polynomial chaos expansion based on an adaptive regression-based algorithm, and enhanced by the combined use of the global sensitivity analysis (GSA) is used, with significant savings in computational effort. The effect of anisotropy in each layer on the pavement responses was studied separately, and an effort is made to identify the pavement layer wherein the introduction of anisotropic characteristics results in the most significant impact on the critical strains. It is observed that the anisotropy in the base layer has a significant but diverse effect on both critical strains. While the compressive strain tends to be considerably higher than that observed for the isotropic section, the tensile strains show a decrease in the mean value with the introduction of base-layer anisotropy. Furthermore, asphalt-layer anisotropy also tends to decrease the critical tensile strain while having little effect on the critical compressive strain. (C) 2015 American Society of Civil Engineers.

Epigenetics and miRNA during bacteria-induced host immune responses

Various cellular processes including the pathogen-specific immune responses, host-pathogen interactions and the related evasion mechanisms rely on the ability of the immune cells to be reprogrammed accurately and in many cases instantaneously. In this context, the exact functions of epigenetic and miRNA-mediated regulation of genes, coupled with recent advent in techniques that aid such studies, make it an attractive field for research. Here, we review examples that involve the epigenetic and miRNA control of the host immune system during infection with bacteria. Interestingly, many pathogens utilize the epigenetic and miRNA machinery to modify and evade the host immune responses. Thus, we believe that global epigenetic and miRNA mapping of such host-pathogen interactions would provide key insights into their cellular functions and help to identify various determinants for therapeutic value.

Fast and slow climate responses to CO2 and solar forcing: A linear multivariate regression model characterizing transient climate change

Climate change in response to a change in external forcing can be understood in terms of fast response to the imposed forcing and slow feedback associated with surface temperature change. Previous studies have investigated the characteristics of fast response and slow feedback for different forcing agents. Here we examine to what extent that fast response and slow feedback derived from time-mean results of climate model simulations can be used to infer total climate change. To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, solar forcing, and change in global mean surface temperature. We derive the parameters of the regression model using time-mean results from a set of HadCM3L climate model step-forcing simulations, and then use the regression model to emulate HadCM3L-simulated transient climate change. Our results show that the regression model emulates well HadCM3L-simulated temporal evolution and spatial distribution of climate change, including surface temperature, precipitation, runoff, soil moisture, cloudiness, and radiative fluxes under transient CO2 and/or solar forcing scenarios. Our findings suggest that temporal and spatial patterns of total change for the climate variables considered here can be represented well by the sum of fast response and slow feedback. Furthermore, by using a simple 1-D heat-diffusion climate model, we show that the temporal and spatial characteristics of climate change under transient forcing scenarios can be emulated well using information from step-forcing simulations alone.

Immune responses against hepatitis C virus genotype 3a virus-like particles in mice: A novel VLP prime-adenovirus boost strategy

Chronic hepatitis C virus (HCV) infection represents a major health threat to global population. In India, approximately 15-20% of cases of chronic liver diseases are caused by HCV infection. Although, new drug treatments hold great promise for HCV eradication in infected individuals, the treatments are highly expensive. A vaccine for preventing or treating HCV infection would be of great value, particularly in developing countries. Several preclinical trials of virus-like particle (VLP) based vaccine strategies are in progress throughout the world. Previously, using baculovirus based system, we have reported the production of hepatitis C virus-like particles (HCV-LPs) encoding structural proteins for genotype 3a, which is prevalent in India. In the present study, we have generated HCV-LPs using adenovirus based system and tried different immunization strategies by using combinations of both kinds of HCV-LPs with other genotype 3a-based immunogens. HCV-LPs and peptides based ELISAs were used to evaluate antibody responses generated by these combinations. Cell-mediated immune responses were measured by using T-cell proliferation assay and intracellular cytokine staining. We observed that administration of recombinant adenoviruses expressing HCV structural proteins as final booster enhances both antibody as well as T-cell responses. Additionally, reduction of binding of VLP and JFH1 virus to human hepatocellular carcinoma cells demonstrated the presence of neutralizing antibodies in immunized sera. Taken together, our results suggest that the combined regimen of VLP followed by recombinant adenovirus could more effectively inhibit HCV infection, endorsing the novel vaccine strategy. (C) 2015 Elsevier Ltd. All rights reserved.

Dual role of arginine metabolism in establishing pathogenesis

Arginine is an integral part of host defense when invading pathogens are encountered. The arginine metabolite nitric oxide (NO) confers antimicrobial properties, whereas the metabolite ornithine is utilized for polyamine synthesis. Polyamines are crucial to tissue repair and anti-inflammatory responses. iNOS/arginase balance can determine Th1/Th2 response. Furthermore, the host arginine pool and its metabolites are utilized as energy sources by various pathogens. Apart from its role as an immune modulator, recent studies have also highlighted the therapeutic effects of arginine. This article sheds light upon the roles of arginine metabolism during pathological conditions and its therapeutic potential.