180 research outputs found

    STUDIES OF THE BENTHIC MACROINVERTEBRATE FOR WATER QUALITY MONITORING IN CAN GIO-HCMC

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    Joint Research on Environmental Science and Technology for the Eart

    CeO2 based catalysts for the treatment of propylene in motorcycle's exhaust gases

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    In this work, the catalytic activities of several single metallic oxides were studied for the treatment of propylene, a component in motorcycles' exhaust gases, under oxygen deficient conditions. Amongst them, CeO2 is one of the materials that exhibit the highest activity for the oxidation of C3H6. Therefore, several mixtures of CeO2 with other oxides (SnO2, ZrO2, Co3O4) were tested to investigate the changes in catalytic activity (both propylene conversion and CO2 selectivity). Ce0.9Zr0.1O2, Ce0.8Zr0.2O2 solid solutions and the mixtures of CeO2 and Co3O4 was shown to exhibit the highest propylene conversion and CO2 selectivity. They also exhibited good activities when tested under oxygen sufficient and excess conditions and with the presence of co-existing gases (CO, H2O)

    Vietnamese Version of Cornell Scale for Depression in Dementia at an Outpatient Memory Clinic: A Reliability and Validity Study

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    Background: In Vietnam, there has been, currently, no standardized tool for depression assessment for people with dementia (PWD). Cornell Scale for Depression in Dementia (CSDD) is a widely studied and used scale for PWD worldwide. Objectives: The aim of this study was to standardize the Vietnamese version of the CSDD (V-CSDD) in depression assessment in PWD through reliability and validity examination. Methods: V-CSDD was rated in terms of reliability and validity with gold standard regarding "major depressive episode"and "major depressive-like episode"of DSM-5. Cronbach's α, ICC, exploratory factor analysis (EFA), and receiver operating characteristic analysis were performed. Results: V-CSDD was found to have a high internal consistency reliability (Cronbach's α = 0.80), inter-rater reliability at sound ranking (ICC = 0.89; 95% CI = 0.81-0.94), maximum cut-off mark of 13 (sensitivity = 70%, specificity = 92%), and EFA, which suggested that V-CSDD may comprise 5 factors. Conclusions: Results indicate the V-CSDD to be a reliable and valid assessment and to be beneficial in classifying and diagnosing depression in dementia outpatients in clinical contexts

    AMMONIA REMOVAL FROM SWINE WASTEWATER USING AN AEROBIC, ANOXIC FILTER AT A PILOT-SCALE IN THANH LOC BIOSTATION

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    Joint Research on Environmental Science and Technology for the Eart

    Model Updating for Large-Scale Railway Bridge Using Grey Wolf Algorithm and Genetic Alghorithms

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    This paper proposes a novel hybrid algorithm to deal with an inverse problem of a large-scale truss bridge. Grey Wolf Optimization (GWO) Algorithm is a well-known and widely applied metaheuristic algorithm. Nevertheless, GWO has two major drawbacks. First, this algorithm depends crucially on the positions of the leading Wolf. If the position of the leaderis far from the best solution, the obtained results are poor. On the other hand, GWO does not own capacities to improve the quality of new generations if elements are trapped into local minima. To remedy the shortcomings of GWO, we propose a hybrid algorithm combining GWO with Genetic Algorithm (GA), termed HGWO-GA. This proposed method contains two key features (1) based on crossover and mutation capacities, GA is first utilized to generate the high-quality elements (2) after that, the optimization capacity of GWO is employed to seek the optimal solutions. To assess the effectiveness of the proposed approach, a large-scale truss bridge is employed for model updating. The obtained results show that HGWO-GA not only provides a good agreement between numerical and experimental results but also outperforms traditional GWO in terms of accuracy

    Model Updating for Large-Scale Railway Bridge Using Grey Wolf Algorithm and Genetic Alghorithms

    Get PDF
    This paper proposes a novel hybrid algorithm to deal with an inverse problem of a large-scale truss bridge. Grey Wolf Optimization (GWO) Algorithm is a well-known and widely applied metaheuristic algorithm. Nevertheless, GWO has two major drawbacks. First, this algorithm depends crucially on the positions of the leading Wolf. If the position of the leaderis far from the best solution, the obtained results are poor. On the other hand, GWO does not own capacities to improve the quality of new generations if elements are trapped into local minima. To remedy the shortcomings of GWO, we propose a hybrid algorithm combining GWO with Genetic Algorithm (GA), termed HGWO-GA. This proposed method contains two key features (1) based on crossover and mutation capacities, GA is first utilized to generate the high-quality elements (2) after that, the optimization capacity of GWO is employed to seek the optimal solutions. To assess the effectiveness of the proposed approach, a large-scale truss bridge is employed for model updating. The obtained results show that HGWO-GA not only provides a good agreement between numerical and experimental results but also outperforms traditional GWO in terms of accuracy

    Co3O4 catalysts on CeO2-ZrO2 supports and Co3O4-CeO2 catalysts on Al2O3/SiO2 supports for the oxidation of propylene

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    Different compositions of Co3O4 catalysts on CeO2-ZrO2 solid solution (Ce0.9Zr0.1O2 and Ce0.8Zr0.2O2) have been studied for the oxidation of propylene. The optional amount of Co3O4 active phase on CeO2-ZrO2 support of 30 wt% was found. The mixed Co3O4-CeO2-ZrO2 with the same composition of the optimal supported ones showed approximately the same activity, which was not higher than the activity of the mixed Co3O4-CeO2 catalyst. Catalytic activities of mixed Co3O4-CeO2 with different loading contents supported on high surface area supports (Al2O3, SiO2) were then measured. The optimal composition of active phase was still 30 wt% but the minimum temperature of the highest activity increased to above 300 degrees C due to the inert nature influence of the support
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