85 research outputs found

    Synthesis and Characterisation of Nanomaterials

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    Development of synthesis protocols for realising nanomaterials over a range of sizes, shapes,and chemical compositions is an important aspect of nanotechnology. The remarkable size-dependent physico-chemical properties of nanoparticles have fascinated and inspired researchactivity in this direction. This paper describes some aspects on synthesis and characterisationof nanoparticles of metals, metal alloys, and oxides, either in the form of thin films or bulk shapes.A brief discussion on processing of two-phase nanocomposite magnets is also presented.Defence Science Journal, 2008, 58(4), pp.504-516, DOI:http://dx.doi.org/10.14429/dsj.58.167

    Efficient Web Service Discovery and Selection Model

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    Selection of an optimal web service is a challenging task due to the uncertainty of Quality of Service, which is the deciding factor to identify the accurate web service. Several discovery mechanisms have proposed but most of the research work does not consider the non-functional characteristics called Quality of service. The proposed model for web service selection combines two techniques. First, with Skyline method reduce the search space by filtering the redundant service and secondly to calculate the Relevancy function to normalize the skyline services. The experimental results show that the proposed technique outperforms the existing method

    Impact of Vetiveria zizanioides rhizosphere bacterial isolates on PGPR traits and cadmium resistance

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    In our study we have proved that most vetiver rhizosphere bacterial isolates are potent biomolecule synthesizers. We isolated culturable bacterium associated with vetiver rhizosphere using three carbon sources and phenotypic characterizations were performed. The medium and cultural conditions of the isolates were optimized under shake flask conditions. Further, the isolates were assessed for their ability to synthesize biomolecules and plant growth promoting rhizobacterial (PGPR) traits. Siderophore production was determined in all the tested isolates; Phosphate solubilization was performed and seven isolates were shown to solubilize phosphate. Indole 3-acetic acid (IAA) was produced by all isolates when grown on MS medium supplemented with tryptophan and the amount of IAA produced were quantified with standards. Metal tolerance concentration (MTC) was performed and it was observed that most isolates were able to survive till 300mg L-1 on cadmium amended minimal medium. The isolate (VITJCSKK14) was able to show resistance till 500mg L-1. Solubilization of zinc metal (0.1%) was analysed using LGI medium; halos were observed and quantified by checking the growth, pH and optical density. The soluble Zn present in the culture broth was determined using an atomic absorption spectrophotometer (AAS-Model Varian C) at different periods of growth and the maximum solubilization was recorded after 120 h with a 0.1% Zn metal amendment was 634mgl-1. Further the intracellular proteins were separated to observe the whole cell protein and stress tolerant proteins from VITJCSKK14. The intracellular proteins were extracted from the cultures grown in Tris minimal media supplemented with cadmium and quantification was performed using Bradford’s method. The proteins were separated on SDS-PAGE and the stress protein bands were observed. It was found that high molecular weight protein was appeared in the test sample. The molecular taxonomy of the active isolate VITJCSKK14 was carried out by 16S rRNA analysis and phylogenetic tree was constructed using CLUSTALV software. Based on the phenotypic and phylogenetic analysis, the isolate VITJCSKK14 was identified as Acinetobacter Sp. This study also gives a hypothesis that Vetiveria zizanioides rhizosphere bacterium may aid in plant growth promotion and their survivability in adverse conditions

    Towards an Effective QoS Prediction of Web Services using Context-Aware Dynamic Bayesian Network Model

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    The functionally equivalent web services (WSs) with different quality of service (QoS) leads to WS discovery models to identify the optimal WS. Due to the unpredictable network connections and user environment, the predicted values of the QoS are likely to fluctuate. The proposed Context-Aware Bayesian Network (CABN) system overcomes these limitations by incorporating the contextual factors in user, server, and environmental perspective. In this paper, three components are introduced for personalized QoS prediction. First, the CABN incorporates the pre-clustering model and reduces the searching space for QoS prediction. Second, the CABN confronts with the multi-constraint problem while considering the multi-dimensional QoS parameters of similar QoS data in WS discovery. Third, the CABN sends the normalized QoS value of records in similar as well as neighbor clusters as inputs to the Dynamic Bayesian Network and improves the prediction accuracy. The experimental results prove that the proposed CABN achieves better WS-Discovery than the existing work within a reasonable time

    Preparation of printable and biodegradable cellulose-laponite composite for electronic device application

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    Printable and biodegradable printed circuit boards (PCBs) prepared by using cellulose as the continuous matrix, laponite as flame retardant filler with various weight ratio (0, 5, 10 and 20 wt% with respect to the α-cellulose quantity used to prepare the composites) and 1-ethyl-3-methylimidazolium acetate ([emim][OAc]) as the recoverable dissolution medium. Prepared cellulose-composites were subjected into physical, chemical, thermal, mechanical and biodegradation analyses to check the suitability of the cellulose-laponite composite for biodegradable electronic application. The addition of laponite into cellulose increased the degradation temperature, flame retardancy and decreased the mechanical properties of the cellulose-laponite composites. The surface nature of the cellulose composite converted from hydrophilic to hydrophobic (contact angle value increased in the range from 50° to 112°) by treating with relatively small amount of hydrophobizing agent (< 1 wt%). The conductive ink printing experiments on the composites explaining the role of hydrophobizing agent and laponite in the composites. Biodegradability of the cellulose was evaluated by enzyme treatments and derived the effect of laponite, hydrophobic agent and conductive ink

    Latent tuberculosis co-infection is associated with heightened levels of humoral, cytokine and acute phase responses in seropositive SARS-CoV-2 infection

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    OBJECTIVES: : Latent Tuberculosis infection (LTBI) is postulated to modulate immune responses and alter disease severity in SARS-CoV-2 co-infection. However, no data exist on the effect of LTBI on the immune responses in SARS-CoV-2 co-infected individuals. METHODS: : We examined the SARS-CoV-2 specific antibody responses, plasma cytokines, chemokines, acute phase proteins and growth factor levels in LTBI positive and negative individuals with SARS-CoV-2 infection. RESULTS: : Our results demonstrated that individuals with LTBI (LTBI+) and seropositive for SARS-CoV-2 infection were associated with elevated SARS-CoV-2 specific IgM, IgG and IgA antibodies, as well as enhanced neutralization activity compared to those negative for LTBI (LTBI-) individuals. Our results also demonstrate that LTBI+ individuals exhibited significantly higher plasma levels of IFNγ, IL-2, TNFα, IL-1α, IL-1β, IL-6, IL-12, IL-15, IL-17, IL-3, GM-CSF, IL-10, IL-25, IL-33, CCL3 and CXCL10 compared to LTBI- individuals. Finally, our results show that LTBI+ individuals exhibit significantly higher levels of C-reactive protein, alpha-2 macroglobulin, VEGF and TGFα compared to LTBI- individuals. CONCLUSIONS: : Thus, our data clearly demonstrates that LTBI+ individuals seropositive for SARS-CoV2 infection exhibit heightened levels of humoral, cytokine and acute phase responses compared to LTBI- individuals. Thus, LTBI is associated with modulation of antibody and cytokine responses as well as systemic inflammation in individuals seropositive for SARS-CoV2 infection

    Bedaquiline, Delamanid, Linezolid and Clofazimine for Treatment of Pre-extensively Drug-Resistant Tuberculosis.

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    BACKGROUND Treatment success rates for multidrug-resistant tuberculosis (MDR-TB) remain low globally. Availability of newer drugs has given scope to develop regimens that can be patient-friendly, less toxic, with improved outcomes. We proposed to determine the effectiveness of an entirely oral, short-course regimen with Bedaquiline and Delamanid in treating MDR-TB with additional resistance to fluoroquinolones (MDR-TBFQ+) or second-line injectable (MDR-TBSLI+). METHODS We prospectively determined the effectiveness and safety of combining two new drugs with two repurposed drugs - Bedaquiline, Delamanid, Linezolid, and Clofazimine for 24-36 weeks in adults with pulmonary MDR-TBFQ+ or/and MDR-TBSLI+. The primary outcome was a favorable response at end of treatment, defined as two consecutive negative cultures taken four weeks apart. The unfavorable outcomes included bacteriologic or clinical failure during treatment period. RESULTS Of the 165 participants enrolled, 158 had MDR-TBFQ+. At the end of treatment, after excluding 12 patients due to baseline drug susceptibility and culture negatives, 139 of 153 patients (91%) had a favorable outcome. Fourteen patients (9%) had unfavorable outcomes: four deaths, seven treatment changes, two bacteriological failures, and one withdrawal. During treatment, 85 patients (52%) developed myelosuppression, 69 (42%) reported peripheral neuropathy, and none had QTc(F) prolongation >500msec. At 48 weeks of follow-up, 131 patients showed sustained treatment success with the resolution of adverse events in the majority. CONCLUSION After 24-36 weeks of treatment, this regimen resulted in a satisfactory favorable outcome in pulmonary MDR-TB patients with additional drug resistance. Cardiotoxicity was minimal, and myelosuppression, while common, was detected early and treated successfully

    Host lipidome and tuberculosis treatment failure

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    INTRODUCTION: Host lipids play important roles in tuberculosis (TB) pathogenesis. Whether host lipids at TB treatment initiation (baseline) affect subsequent treatment outcomes has not been well characterised. We used unbiased lipidomics to study the prospective association of host lipids with TB treatment failure. METHODS: A case–control study (n=192), nested within a prospective cohort study, was used to investigate the association of baseline plasma lipids with TB treatment failure among adults with pulmonary TB. Cases (n=46) were defined as TB treatment failure, while controls (n=146) were those without failure. Complex lipids and inflammatory lipid mediators were measured using liquid chromatography mass spectrometry techniques. Adjusted least-square regression was used to assess differences in groups. In addition, machine learning identified lipids with highest area under the curve (AUC) to classify cases and controls. RESULTS: Baseline levels of 32 lipids differed between controls and those with treatment failure after false discovery rate adjustment. Treatment failure was associated with lower baseline levels of cholesteryl esters and oxylipin, and higher baseline levels of ceramides and triglycerides compared to controls. Two cholesteryl ester lipids combined in a unique classifier model provided an AUC of 0.79 (95% CI 0.65–0.93) in the test dataset for prediction of TB treatment failure. CONCLUSIONS: We identified lipids, some with known roles in TB pathogenesis, associated with TB treatment failure. In addition, a lipid signature with prognostic accuracy for TB treatment failure was identified. These lipids could be potential targets for risk-stratification, adjunct therapy and treatment monitoring

    Large-scale unit commitment under uncertainty: an updated literature survey

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    The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject
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