In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For

Fusidic acid (FA) is a well-known pharmaceutical antibiotic used to treat dermal infections. This experiment aimed for developing a standardized HPLC protocol to determine the accurate concentration of fusidic acid in both non-ionic and cationic nano-emulsion based gels. For this purpose, a simple, precise, accurate approach was developed. A column with reversed-phase C18 (250 mm x 4.6 mm ID x 5 m) was utilized for the separation process. The main constituents of the HPLC mobile phase were composed of water: acetonitrile (1: 4); adjusted at pH 3.3. The flow rate was 1.0 mL/minute. The optimized wavelength was selected at 235 nm. This approach achieved strong linearity for alcoholic solutions of FA when loaded at a serial concentrati

Background: Ulcerative colitis (UC) is a chronic inflammatory disorder of the colon that often extends to involve the remainder of the large intestine in a continuous manner. Intestinal amoebiasis can present as a chronic, dysenteric syndrome of diarrhea, weight loss, and abdominal pain that can last for years and mimic ulcerative colitis.
Objective: Studying the prevalence of E..histolytica by using serological method ELISA for their detection, Investigate the possible role of E.histolytica as a cause of blood, diarrhea in non-ulcerative colitis group &Comparison between serological detection of E.histolytica and stool examination.
Patients and Methods: Retrospective and prospective study was conducted

In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms
(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency i

Background: obesity is an important cause of adverse health problems, including male infertility. Testosterone is essential for spermatogenesis and permits the release of mature sperms. In the absence of testosterone stimulation, spermatogenesis does not proceed beyond the meiosis stage. Aromatase expression is directly related to the degree of adiposity; it is dependent on cytokine stimulation and requires the presence of glucocorticoids, 17β-estradiol in the plasma of adult men is formed by aromatization convert testosterone and androstinedione to 17β-estradiol Apoptosis is an important process in the context of germ cells since they undergo both mitosis and meiosis, and this process is affected by

  The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.

      And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)