ABSTRACT : The restoration of bone continuity and bone union are complex processes and their success is determined by the effectiveness of osteosynthesis. The use of plants for healing purposes predates human history and forms the source of current modern medicine. This research was planned to study the histological and immunohisto-chemistry of osteocalcin to evaluate of effect of local application of lepidium sativum oilon healing of induced bone defect in rat tibia. In this study, fourty albino male rats, weighting (300-400) gram, aged (6-8) months, will be used under control conditions of temperature, drinking and food consumption. The animals will subject for a surgical operation of medial side of tibiae bone, in control group the bone

     Aeromonas hydrophila is widely distributed throughout the world and causes diseases to animals and human exposed to contaminated environments such as water and soil. This study aimed to compare between isolates of A. hydrophila collected from clinical and environmental samples, through investigating the phenotype of some virulence factors in vitro, including hemolysin, protease, lipase, nuclease and biofilm formation ability. Also, the antimicrobial susceptibility for different antibiotics was determined using disc diffusion method. For genotypic identification of isolates and phylogenetic tree construction, 16S rDNA target gene was amplified and sequenced. The phenoty

The petrophysical analysis is very important to understand the factors controlling the reservoir quality and production wells. In the current study, the petrophysical evaluation was accomplished to hydrocarbon assessment based on well log data of four wells of Early Cretaceous carbonate reservoir Yamama Formation in Abu-Amood oil field in the southern part of Iraq. The available well logs such as sonic, density, neutron, gamma ray, SP, and resistivity logs for wells AAm-1, AAm-2, AAm-3, and AAm-5 were used to delineate the reservoir characteristics of the Yamama Formation. Lithologic and mineralogic studies were performed using porosity logs combination cross plots such as density vs. neutron cross plot and M-N mineralogy plot. Thes

During the last decade, there has been a concern about the relation between aluminum residuals in treated water and Alzheimer disease, and more interest has been considered on the development of natural coagulants. The present study aimed to investigate the efficiency of alum as a primary coagulant in conjunction with mallow, Arabic gum and okra as coagulant aids for the treatment of water samples containing synthetic turbidity of kaolin. Jar test experiments were carried out for initial raw water turbidities 100, 200 and 500 (NTU). The optimum doses of alum, mallow, Arabic gum and okra were 20, 2, 1 and 1 mg/L for100 NTU turbidity level, 35, 4, 2 and 3 mg/L , for 200NTU turbidity level and 50, 8, 10 and 8 mg/L for 500 NTU turbidity leve

Water samples were collected from output of water for Al-Wahda plant where located in al-karrada area in Baghdad city to study water contamination with bacteria, fungi and Algae. The study lasted one year started on August, 2016 to July,2017.Results were acquired according to two tests performed, the first is biological test included total coliform,E.coli, pseudomonas aeruginosa, total fungi, Diatom and non Diatom Algae and the second is physiochemical test included temperature, turbidity and residual chlorine. The results of bacteria were within the permitted specification in the Iraqi standards no. 14/2270 for the year 2015 except August was exceeded the permitted standard for total coliform, it was 1.1< cell/100 ml.Total Fungi, Dia

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.