169 research outputs found

    Optimization and investigation of process parameters in single point incremental forming

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    246-255Single point incremental forming (SPIF) process is an innovative and dies-less forming technique to produce various useful shapes for small batch size economically. This process exempts expensive and complex tooling which is used in traditional sheet forming processes. Study of forming force and thickness reduction of the components formed by SPIF process would help the process engineers to provide some guidelines regarding the implementations of this process to mainstream of manufacturing industries. In this work, seven impact factors of this process have been exploited to optimize SPIF process using Taguchi method as a design of experiment (DoE) technique. The objective of current work is to optimize the forming forces and thickness reduction of the formed conical frustums for a given set of factors for operation sustainability. The predictive models have also been generated for estimating optimal characteristics of the process. The predictive model estimated the response characteristics of the SPIF process effectively and accurately

    Optimization and investigation of process parameters in single point incremental forming

    Get PDF
    Single point incremental forming (SPIF) process is an innovative and dies-less forming technique to produce various useful shapes for small batch size economically. This process exempts expensive and complex tooling which is used in traditional sheet forming processes. Study of forming force and thickness reduction of the components formed by SPIF process would help the process engineers to provide some guidelines regarding the implementations of this process to mainstream of manufacturing industries. In this work, seven impact factors of this process have been exploited to optimize SPIF process using Taguchi method as a design of experiment (DoE) technique. The objective of current work is to optimize the forming forces and thickness reduction of the formed conical frustums for a given set of factors for operation sustainability. The predictive models have also been generated for estimating optimal characteristics of the process. The predictive model estimated the response characteristics of the SPIF process effectively and accurately

    The role of mucosal immunity and host genetics in defining intestinal commensal bacteria

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    Dramatic advances in molecular characterization of the largely noncultivable enteric microbiota have facilitated better understanding of the composition of this complex ecosystem at broad phylogenetic levels. This review outlines current understanding of mechanisms by which commensal bacteria are controlled and shaped into functional communities by innate and adaptive immune responses, antimicrobial peptides produced by epithelial cells and host genetic factors

    Revenue Driven Resource Allocation for Virtualized Data Centers

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    Abstract—The increasing VM density in cloud hosting services makes careful management of physical resources such as CPU, memory, and I/O bandwidth within individual virtualized servers a priority. To maximize cost-efficiency, resource management needs to be coupled with the revenue generating mechanisms of cloud hosting: the service level agreements (SLAs) of hosted client applications. In this paper, we develop a server resource man-agement framework that reduces data center resource manage-ment complexity substantially. Our solution implements revenue-driven dynamic resource allocation which continuously steers the resource distribution across hosted VMs within a server such as to maximize the SLA-generated revenue from the server. Our experimental evaluation for a VMware ESX hypervisor highlights the importance of both resource isolation and resource sharing across VMs. The empirical data shows a 7%-54 % increase in total revenue generated for a mix of 10-25 VMs hosting either similar or diverse workloads when compared to using the currently available resource distribution mechanisms in ESX. I

    A causal association between Accutane and IBD has yet to be established

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    A number of case reports have been published describing a possible association between isotretinoin (Accutane) and inflammatory bowel disease (IBD). We critically appraised the published literature on this association to assess whether the current literature supports a causal relationship between isotretinoin and IBD

    Comparative analysis of microbiome measurement platforms using latent variable structural equation modeling

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    Abstract Background Culture-independent phylogenetic analysis of 16S ribosomal RNA (rRNA) gene sequences has emerged as an incisive method of profiling bacteria present in a specimen. Currently, multiple techniques are available to enumerate the abundance of bacterial taxa in specimens, including the Sanger sequencing, the ‘next generation’ pyrosequencing, microarrays, quantitative PCR, and the rapidly emerging, third generation sequencing, and fourth generation sequencing methods. An efficient statistical tool is in urgent need for the followings tasks: (1) to compare the agreement between these measurement platforms, (2) to select the most reliable platform(s), and (3) to combine different platforms of complementary strengths, for a unified analysis. Results We present the latent variable structural equation modeling (SEM) as a novel statistical application for the comparative analysis of measurement platforms. The latent variable SEM model treats the true (unknown) relative frequency of a given bacterial taxon in a specimen as the latent (unobserved) variable and estimates the reliabilities of, and similarities between, different measurement platforms, and subsequently weighs those measurements optimally for a unified analysis of the microbiome composition. The latent variable SEM contains the repeated measures ANOVA (both the univariate and the multivariate models) as special cases and, as a more general and realistic modeling approach, yields superior goodness-of-fit and more reliable analysis results, as demonstrated by a microbiome study of the human inflammatory bowel diseases. Conclusions Given the rapid evolution of modern biotechnologies, the measurement platform comparison, selection and combination tasks are here to stay and to grow – and the latent variable SEM method is readily applicable to any other biological settings, aside from the microbiome study presented here

    Inflammation-Induced Acid Tolerance Genes gadAB in Luminal Commensal Escherichia coli Attenuate Experimental Colitis

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    ABSTRACT Dysregulated immune responses to commensal intestinal bacteria, including Escherichia coli , contribute to the development of inflammatory bowel diseases (IBDs) and experimental colitis. Reciprocally, E. coli responds to chronic intestinal inflammation by upregulating expression of stress response genes, including gadA and gadB . GadAB encode glutamate decarboxylase and protect E. coli from the toxic effects of low pH and fermentation acids, factors present in the intestinal lumen in patients with active IBDs. We hypothesized that E. coli upregulates gadAB during inflammation to enhance its survival and virulence. Using real-time PCR, we determined gadAB expression in luminal E. coli from ex-germfree wild-type (WT) and interleukin-10 (IL-10) knockout (KO) (IL-10 −/− ) mice selectively colonized with a commensal E. coli isolate (NC101) that causes colitis in KO mice in isolation or in combination with 7 other commensal intestinal bacterial strains. E. coli survival and host inflammatory responses were measured in WT and KO mice colonized with NC101 or a mutant lacking the gadAB genes (NC101Δ gadAB ). The susceptibility of NC101 and NC101Δ gadAB to killing by host antimicrobial peptides and their translocation across intestinal epithelial cells were evaluated using bacterial killing assays and transwell experiments, respectively. We show that expression of gadAB in luminal E. coli increases proportionately with intestinal inflammation in KO mice and enhances the susceptibility of NC101 to killing by the host antimicrobial peptide cryptdin-4 but decreases bacterial transmigration across intestinal epithelial cells, colonic inflammation, and mucosal immune responses. Chronic intestinal inflammation upregulates acid tolerance pathways in commensal E. coli isolates, which, contrary to our original hypothesis, limits their survival and colitogenic potential. Further investigation of microbial adaptation to immune-mediated inflammation may provide novel insights into the pathogenesis and treatment of IBDs

    Intestinal Interleukin-17 Receptor Signaling Mediates Reciprocal Control of the Gut Microbiota and Autoimmune Inflammation

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    Interleukin-17 (IL-17) and IL-17 receptor (IL-17R) signaling are essential for regulating mucosal host defense against many invading pathogens. Commensal bacteria, especially segmented filamentous bacteria (SFB), are a crucial factor that drives T helper 17 (Th17) cell development in the gastrointestinal tract. In this study, we demonstrate that Th17 cells controlled SFB burden. Disruption of IL-17R signaling in the enteric epithelium resulted in SFB dysbiosis due to reduced expression of α-defensins, Pigr and Nox1. When subjected to experimental autoimmune encephalomyelitis, IL-17R signaling deficient mice demonstrated earlier disease onset and worsened severity that was associated with increased intestinal Csf2 expression and elevated systemic GM-CSF cytokine concentrations. Conditional deletion of IL-17R in the enteric epithelium demonstrated that there was a reciprocal relationship between the gut microbiota and enteric IL-17R signaling that controlled dysbiosis, constrained Th17 development, and regulated the susceptibility to autoimmune inflammation
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