Magnesium oxide nanoparticles (MgO NPs) were synthesized by a green method using the peels of Persimmon extract as the reducing agent , magnesium nitrate, and NaOH. This method is eco-friendly and non-toxic. In this study, an ultrasound device was used to reduce the particle size, with the impact on the energy gap was set at the beginning at 5.39 eV and then turned to 4.10 eV. The morphological analysis using atomic force microscopy (AFM) showed that the grain size for MgO NPs was 67.70 nm which became 42.33 nm after the use of the ultrasound. The shape of the particles was almost spherical and became cylindrical. In addition the Field-Emission Scanning Electron Microscopy (FESEM) analysis showed that the average particle size was reduced and the spherical shape was changed into cylindrical flakes. The antibacterial activity of MgO Nps was measured against both gram positive and negative bacteria (Staphylococcus aureus and Escherichia coli, respectively) for both the synthesized and the scaled-down particles by the ultrasonic. MgO NPs showed an efficacy at a minimum inhibitory concentration (MIC) of 500 μg/ml, with the better effect being observed after the ultrasonic treatment of the MgO NPs.
The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin
... Show MoreIn this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for
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