Thermal Decomposition of Ba(II) & Sr(II) Bis(oxalato)-oxovanadates(IV)

863-86

A Circular Economy Framework based on Organic Wastes Upcycling for Biodiesel Production from Hermetia illucens

The present waste management practices have adverse environmental impacts at the same time costly. Approximately, 80 % of the Malaysian municipal wastes including organic wastes are usual disposed into landfills. Hence, transformation organic wastes not only providing economic and environmental benefits but has given waste a value. This study focused on synthesis of biodiesel from H. illucens pre-pupae fed with fruit waste and food waste. The objective was to evaluate interactions between the variables including catalyst loading, reaction time versus fatty acid methyl esters (FAME) yield (wt %), temperature and methanol to sample mass ratio. The response surface methodology (RSM) was used to investigate the bioconversion optimization process. Optimal biodiesel yield based on fruit waste achieved was 96.15 % at 51ºC; 8.3:1 methanol: mass ratio; 253 min and 15.1 % catalyst. Furthermore, the optimal yield obtained from the second set of optimization using lipids of pre-pupae derived from food waste was achieved at 94.63 %.  The optimum conditions for reaction temperature was 71°C, with methanol to mass ratio of 6.8:1, at reaction time of 254 min and catalyst loading of 7.0 v/v%. The properties of FAME produced were in accordance with EN 14214 and ASTM 6751 biodiesel standards

Optimization of polyurethane foam cube in enhancing the attachment of microalgae biomass

Attachment of microalgae biomass to polyurethane foam material is believed could reduce the cost and time needed for harvesting process in making it reliable to be used in industry for biodiesel production. This paper aim to optimize the usage of polyurethane for higher attachment of microalgae biomass yield in term of it sizes and packing volume. The investigation revealed that 1.0 cm3 polyurethane foam yield highest attached biomass (0.812 g) and it has best performance compared to 0.125 cm3, 8 cm3 and 27 cm3 with attached biomass yield 0.666 g, 0.546 g, and 0.368 g respectively. For packing volume, 6% is the best since has highest attached microalgae biomass with yield 0.753 g, compared with 2%, 4%, 8% and 10% with yield 0.426 g, 0.577 g, 0.687 g and 0.644 g attached biomass respectively.Keywords: microalgae; chlorella vulgaris, polyurethane; attached biomass.

Echocardiographic Parameters for Risk Prediction in Borderline Right Ventricle: Review with Special Emphasis on Pulmonary Atresia with Intact Ventricular Septum and Critical Pulmonary Stenosis

The aim of the present review is to highlight the strengths and limitations of echocardiographic parameters and scores employed to predict favorable outcome in complex congenital heart diseases (CHDs) with borderline right ventricle (RV), with a focus on pulmonary atresia with intact ventricular septum and critical pulmonary stenosis (PAIVS/CPS). A systematic search in the National Library of Medicine using Medical Subject Headings and free-text terms including echocardiography, CHD, and scores, was performed. The search was refined by adding keywords “PAIVS/CPS”, Ebstein’s anomaly, and unbalanced atrioventricular septal defect with left dominance. A total of 22 studies were selected for final analysis; 12 of them were focused on parameters to predict biventricular repair (BVR)/pulmonary blood flow augmentation in PAIVS/CPS. All of these studies presented numerical (the limited sample size) and methodological limitations (retrospective design, poor definition of inclusion/exclusion criteria, variability in the definition of outcomes, differences in adopted surgical and interventional strategies). There was heterogeneity in the echocardiographic parameters employed and cut-off values proposed, with difficultly in establishing which one should be recommended. Easy scores such as TV/MV (tricuspid/mitral valve) and RV/LV (right/left ventricle) ratios were proven to have a good prognostic accuracy; however, the data were very limited (only two studies with <40 subjects). In larger studies, RV end-diastolic area and a higher degree of tricuspid regurgitation were also proven as accurate predictors of successful BVR. These measures, however, may be either operator and/or load/pressure dependent. TV Z-scores have been proposed by several authors, but old and heterogenous nomograms sources have been employed, thus producing discordant results. In summary, we provide a review of the currently available echocardiographic parameters for risk prediction in CHDs with a diminutive RV that may serve as a guide for use in clinical practice

Application of Boruta algorithms as a robust methodology for performance evaluation of CMIP6 general circulation models for hydro- climatic studies

Regional climate models are essential for climate change projections and hydrologic modelling studies, especially in watersheds that are overly sensitive to changes in climate. Accurate hydrologic model development is a daunting task in data-sparse regions where climate change’s impact on hydrologic and water quality processes is necessary for a well-informed policy decision on adaptation and hazard mitigation strategies. Novel approaches have been evolving that evaluated GCMs with the objective of improved parameterization to limit uncertainty and improve hydrologic model development. However, conclusions drawn should be purpose-driven based on intended usage. This study provides an overview of the state-of-the-art Boruta random forest as a robust methodology in the performance evaluation of GCMs models for hydroclimatic study. Highlights from the assessment indicate that: (1) there is consistency in replicating the three observed climate variables of daily precipitation, maximum and minimum temperature respectively, (2) better temporal correlation (R2 = 0.95) in annual precipitation with a mean bias of 0.638mm/yr.; when compared to symmetrical uncertainty (SU) (R2 = 0.82), and all models ensembles (AME) (R2 = 0.88) with associated biases of 68.19mm/yr. and 10.57mm/yr. respectively. Evaluation of the multi-year climate extreme indices, trends and magnitude reveal that there is a fair representation of basin-scale observed climate extreme events. However, the Boruta random forest approach exhibited a better statistical trend and magnitude of the extreme event in the basin. The findings of the study revealed enhanced GCM dataset evaluation and present a simple and efficient methodology to examine the limitations associated with the selected GCM ensemble for impact study in hydrology

Association between proton pump inhibitor therapy and clostridium difficile infection: a contemporary systematic review and meta-analysis.

Abstract Introduction Emerging epidemiological evidence suggests that proton pump inhibitor (PPI) acid-suppression therapy is associated with an increased risk of Clostridium difficile infection (CDI). Methods Ovid MEDLINE, EMBASE, ISI Web of Science, and Scopus were searched from 1990 to January 2012 for analytical studies that reported an adjusted effect estimate of the association between PPI use and CDI. We performed random-effect meta-analyses. We used the GRADE framework to interpret the findings. Results We identified 47 eligible citations (37 case-control and 14 cohort studies) with corresponding 51 effect estimates. The pooled OR was 1.65, 95% CI (1.47, 1.85), I2 = 89.9%, with evidence of publication bias suggested by a contour funnel plot. A novel regression based method was used to adjust for publication bias and resulted in an adjusted pooled OR of 1.51 (95% CI, 1.26–1.83). In a speculative analysis that assumes that this association is based on causality, and based on published baseline CDI incidence, the risk of CDI would be very low in the general population taking PPIs with an estimated NNH of 3925 at 1 year. Conclusions In this rigorously conducted systemic review and meta-analysis, we found very low quality evidence (GRADE class) for an association between PPI use and CDI that does not support a cause-effect relationship