The Co(II), Ni(II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II) complexes of mixed of amino acid (L-Proline ) and Trimethoprim antibiotic were synthesized. The complexes were characterized using solubility, melting point, conductivity measurement ,. and determination the percentage of the metal in the complexes by flame(AAS).Magnetic susceptibility, Spectroscopic Method [FT-IR and UV-Vis]. Draw the proposed structure of the complexes using program , Chem. office 3D(2006). The ligands and there metal complexes were screened for their antimicrobial activity against four bacteria (gram + ve) and (gram -ve){Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Bacillus}.The proposed structure of the complexes using program , Chem office 3D(

Flow-injection (FI) spectrophotometric method has been developed for the analysis of thymol in pharmaceutical preparations. The method is based on organic coupling reaction between thymol and 4-amino antipyrine in the presence of alkaline medium to form an intense stable red color complex with copper nitrate that has a maximum absorption at 490 nm. Optimum conditions for determination of the drug was investigated .The calibration graph was linear over the range of 5-500 µg.ml-1 of thymol . The limit of detection (LOD) and limit of quantification (LOQ) were 1.81 ?g mL-1 and 3.60 ?g mL-1 respectively .The proposed method was applied satisfactorily to the determination of thymol in mouth wash preparations. The procedure is characterized by

Necessary and sufficient conditions for the operator equation I AXAX n*, to have a real positive definite solution X are given. Based on these conditions, some properties of the operator A as well as relation between the solutions X andAare given.

The study was conducted from November 2021 to May 2022 at the three study sites within the Baghdad governorate. The study aims to identify the impact of human activities on the Tigris River, so an area free of human activities was chosen and represented the first site. A total of 48 types were diagnosed, 6204 ind/m3 spread over three sites. The following environmental indicators were evaluated: Constancy Index (S), Relative abundance index (Ra), Richness Index (between 17.995 and 23.251), Shannon Weiner Index (0.48-1.25 bit/ind.), Uniformity Index (0.124 -0.323). The study showed that the highest percentage recorded was for the phylum Annileda 34%; and the stability index shows that taxes (Stylaria sp., Aoelosoma sp., Branchinra sowerby, Ch

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Cloud computing represents the most important shift in computing and information technology (IT). However, security and privacy remain the main obstacles to its widespread adoption. In this research we will review the security and privacy challenges that affect critical data in cloud computing and identify solutions that are used to address these challenges. Some questions that need answers are: (a) User access management, (b) Protect privacy of sensitive data, (c) Identity anonymity to protect the Identity of user and data file. To answer these questions, a systematic literature review was conducted and structured interview with several security experts working on cloud computing security to investigate the main objectives of propo

Bac kground:: Septal deviation is one of the commonest anatomical deformities of the nasal skeleton, this deviation is usually accompanied by compensatory hypertrophy of the inferior turbinate on the concave side that will accentuate the severity of nasal obstruction.
Objectives: To evaluate the effect of septoplasty on the size of the inferior turbinate in patients with nasal septum deviation.
Methods: This is a prospective study of 25 patients attending the otolaryngological department at Al-Jirahat teaching hospital from September 2011 to November 2013, complaining mainly of nasal obstruction. Otolaryngological examination had shown nasal septum deviation. The cross sectional areas of inferior turbinates were measured with compu

    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne