The approach of green synthesis of bio-sorbent has become simple alternatives to chemical synths as they use for example plant extracts, plus green synthesis outperforms chemical methods because it is environmentally friendly besides has wide applications in environmental remediation. This paper investigates the removal of ciprofloxacin (CIP) using green tea nano zero-valent iron (GT-NZVI) in an aqueous solution. The synthesized GT-NZVI was categorized using SEM, AFM, BET, FTIR, and Zeta potentials techniques. The spherical nanoparticles were found to be nano zero-valent, with an average size of 85 nm and a surface area of 2.19m2/g. The results showed that the removal efficiency of ciprofloxacin depends on the initial pH (2.5-10),

This study was aimed to investigate the response surface methodology (RSM) to evaluate the effects of various experimental conditions on the removal of levofloxacin (LVX) from the aqueous solution by means of electrocoagulation (EC) technique with stainless steel electrodes. The EC process was achieved successfully with the efficiency of LVX removal of 90%. The results obtained from the regression analysis, showed that the data of experiential are better fitted to the polynomial model of second-order with the predicted correlation coefficient (pred. R2) of 0.723, adjusted correlation coefficient (Adj. R2) of 0.907 and correlation coefficient values (R2) of 0.952. This shows that the predicted models and experimental values are in go

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

United nation determined many basic climatic effects which affect the crust of Earth.
And the most important one is the climatic change and its effect on environmental, economic,
social, and political effects. So, the amount of rain which is considered as one of climatic
changes in Iraq should be studied.So, this research explains the factors which affect rain, its
overall average, the variation in the amounts of rain, the amount of yearly rain and variation
in both yearly and monthly rains by using standard variation and yearly fluctuation.As a
result, it is concluded that the number of rainy days doesn't mean an increase in rains amount.
And there's variation in rains amount in all study areas which is contrastive

Abstract                                                                                              

The methods of the Principal Components and Partial Least Squares can be regard very important methods  in the regression analysis, whe

Although its wide utilization in microbial cultures, the one factor-at-a-time method, failed to find the true optimum, this is due to the interaction between optimized parameters which is not taken into account. Therefore, in order to find the true optimum conditions, it is necessary to repeat the one factor-at-a-time method in many sequential experimental runs, which is extremely time-consuming and expensive for many variables. This work is an attempt to enhance bioactive yellow pigment production by Streptomyces thinghirensis based on a statistical design. The yellow pigment demonstrated inhibitory effects against Escherichia coli and Staphylococcus aureus and was characterized by UV-vis spectroscopy which showed lambda maximum of

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

Four rapid, accurate and very simple derivative spectrophotometric techniques were developed for the quantitative determination of binary mixtures of estradiol (E2) and progesterone (PRG) formulated as a capsule. Method I is the first derivative zero-crossing technique, derivative amplitudes were detected at the zero-crossing wavelength of 239.27 and 292.51 nm for the quantification of estradiol and 249.19 nm for Progesterone. Method II is ratio subtraction, progesterone was determined at λmax 240 nm after subtraction of interference exerted by estradiol. Method III is modified amplitude subtraction, which was established using derivative spectroscopy and mathematical manipulations. Method IIII is the absorbance ratio technique, absorba

 ملخص البحث

      يعد البيت المكان الاجتماعي الأول الذي تبنى فيه الصحة النفسية لدى الفرد منذ بداية حياته كطفل  في ظل أسرته ، إلا أن الروضة تمتلك على الرغم من ذلك أثراً تكوينياً مهماٌ في حياة الطفل وعلى شخصيته ، والتي لا يمكن ان يقلُّ عن أثر الايجابي للبيت ؛ ذلك أن المفهوم الجديد لدور الروضة لا يقتصر بمجرد كونها مكانًا تقوم فيها المعلمة بتزويد الاطفال بالمعر

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and