Nowadays nanoparticles are used in many fields of life all over the world, and there are numerous ways to obtain them: chemical, physical and biological processes. In recent times, the biological method for the synthesis of nanoparticles associated with using plant extract is widely spread. Optimal conditions for synthesis of silver nanoparticles using aqueous seeds extract of Myristica fragrance were highlighted in this research, such as type of plant extract, weight of extracted plant material, volume ratio of plant extract to AgNO3 and temperature of reaction. The study proved that the optimal status for AgNPs synthesis by using 10 g of M. fragrance seeds powder were added to 100 mL boiled distilled water, then homogenized and filtered after 24 hours. Aliquot of 5 mL of hot aqueous extract were added to 45 mL of 1*10-3 M AgNO3 solution in the water bath with a magnetic stirrer for the bio-reduction process at 60 °C. The biological activity of AgNPs nanoparticles was evaluated by using well diffusion method and biofilm formation for G+ and G- bacteria including Escherichia coli, Staphylococcus aureus, Staphylococcus epidermidis and Klebsiella pneumonia, while the effect of AgNPs nanoparticles on plasmid curing was investigated for Escherichia coli and Staphylococcus aureus only. Atomic Force Microscopy (AFM) images proved that Ag particles are in nanometer- size and have granular shape, the size of silver nanoparticle is (74.55 nm) for the sample taken after 16 min of the reaction. Nanoparticles of various concentrations have proven effective in inhibiting bacterial growth after antimicrobial activity test, biofilm formation and plasmid curing as they exhibited a remarkable effect in inhibiting the growth of both Gram-positive and negative bacteria
In this study, different methods were used for estimating location parameter and scale parameter for extreme value distribution, such as maximum likelihood estimation (MLE) , method of moment estimation (ME),and approximation estimators based on percentiles which is called white method in estimation, as the extreme value distribution is one of exponential distributions. Least squares estimation (OLS) was used, weighted least squares estimation (WLS), ridge regression estimation (Rig), and adjusted ridge regression estimation (ARig) were used. Two parameters for expected value to the percentile as estimation for distribution f
... Show MoreThe 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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