Aim: The study designed to evaluate the Geno-protective effect of green tea extract against genotoxicity induced by metronidazole and tinidazole. Methods: Thirty-six mice were used, For each experiment, The animals divided into 6 groups: Group I- Negative control administered distilled water; Group II-Healthy mice treated with metronidazole alone, Group III- Healthy mice treated with tinidazole alone; Group IV- Healthy mice administered green tea extract alone Group V- Healthy mice treated with metronidazole, followed by green tea extract administration, Group VI- Healthy mice treated with tinidazole, followed by administration of green tea extract. Results: treatment with Tinidazole significantly increase total chromosomal aberration (0.18

Electrochemical oxidation in the presence of sodium chloride used for removal of phenol and any other organic by products formed during the electrolysis by using MnO2/graphite electrode. The performance of the electrode was evaluated in terms fraction of phenol and the formed organic by products removed during the electrolysis process. The results showed that the electrochemical oxidation process was very effective in the removal of phenol and the other organics, where the removal percentage of phenol was 97.33%, and the final value of TOC was 6.985 ppm after 4 hours and by using a speed of rotation of the MnO2 electrode equal to 200 rpm.

The method of operational matrices based on different types of polynomials such as Bernstein, shifted Legendre and Bernoulli polynomials will be presented and implemented to solve the nonlinear Blasius equations approximately. The nonlinear differential equation will be converted into a system of nonlinear algebraic equations that can be solved using Mathematica^®12. The efficiency of these methods has been studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as the polynomial degree (n) increases, since the errors decrease. Moreover, the approximate solutions obtained by the proposed methods are compared with the solution of the 4^th order Runge-Kutta meth

A new class of thiadiazole /silica nanocomposites with chemical bonds between thiadiazole monomers and modified nanosilica surface were synthesized by free radical polymerization. Presence silica nanoparticles in the structure of  nanocomposite showed effectively improve the physical and chemical properties of Producing polymers. A nanocomposite material with feature properties comparison with their polymers, The structure and morphology of the synthesis materials were investigated by FT-IR spectrum which display preparation new thiadiazole compounds and polymerization monomers. FT-IR showed disappeared double bond (C=C) of monomers, due to produce long chains of thiadiazole polymers and nanocomposite. X-ray diffraction gave idea ab

RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2

In the recent years the research on the activated carbon preparation from agro-waste and byproducts have been increased due to their potency for agro-waste elimination. This paper presents a literature review on the synthesis of activated carbon from agro-waste using microwave irradiation method for heating. The applicable approach is highlighted, as well as the effects of activation conditions including carbonization temperature, retention period, and impregnation ratio. The review reveals that the agricultural wastes heated using a chemical process and microwave energy can produce activated carbon with a surface area that is significantly higher than that using the conventional heating method.

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv