The Reversed Phase High Performance Liquid Chromatography (RP-HPLC) has been used for the separation of Poly aromatic hydrocarbons(PAHs) by using column Reprosil 100 C 18 which was found to be a suitable one for this purpose. The result showed that using mobile phase of (Acetonitrile-water) Reversed Phase HPLC , flow rate of (1.2 ml/min) , column temperature (30CËš) and wave length of (254nm), give a complete separation with a good resolution . The total separation time was less than 20 min. The result of the study showed that the vegetables of Baghdad city were polluted by poly aromatic hydrocarbons(PAHs) in different places where samples taken because of drainage of the heavy water ,industrial trash and trash of oil colanders. -

Determining risk indicators for dental implants is an essential strategy for preventing peri-implant diseases and effective diagnosis of dental implant success. To investigate the impact of certain potential factors on the osseointegrated dental implant. Eighty-four individuals were included in our study, 50 cases as a patient’s group and 34 participants as a control group. All cases were diagnosed based on certain criteria, 30 (60%) of patients had peri-implantitis, 20 (40%) with severe periimplantitis, 36(72%) were generalized, and 15 (30%) as localized peri-implantitis cases. The study has indicated that 44.7% of dental implants were in the anterior maxilla, followed by (27.3%) posterior maxilla, (17.4%) posterior mandible, and (10.4%)

The interest in pre-service teacher training has become influential in teaching English as a foreign language, and the purpose of this training course is to prepare qualified teachers to teach effectively through the application of this technique by undergraduate students. This research aims to find out the effect of using the seven principles of good practice as a teaching technique on the fourth stage student-teachers’ performance at the College of Education for Women/University of Baghdad, during the academic year 2017-2018. The sample includes (60) students selected according to the stratified sampling method. The observational checklist used by the department to assess the student teachers’ performance during the practicum perio

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Abstract Twenty Bacillus isolated were obtained from different sample food and water. Bacillus B1 isolated was the highest asparaginase producer, it was identified as a strain of B. subtilis. The highest production of asparaginase was observed when mineral salt medium containing 0.3% asparagen, pH 8 and incubated at 40°c for 24 hrs. B. subtilis B1 cells were immobilized by entrapment methods (calcium alginate and agar), and by adsorption on solid surface such as sawdust and cotton. The result showed that the immobilized cells by adsorption on sawdust was the best, the immobilized cell retained 88% of asparginase activity after 48h while free cell retained 65%. Cells immobilized by adsorption on sawdust was incubated at different temperatu

   In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the  traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit

The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

n this study, 25 clinical isolates of Proteus spp. were collected from urine, wounds and burns specimens from different hospitals in Baghdad city, all isolates were identified by using different bacteriological media, biochemical assays and Vitek-2 system. It was found that 15 (60%) isolates were identifies as Proteus mirabilis and 10 (40 %) isolates were Proteus vulgaris. The susceptibility of P. mirabilis and P. vulgaris isolates towards cefotaxime was (66.6 %) and (44.4 %) respectively; while the susceptibility of P. mirabilis and P. vulgaris isolates towards ceftazidime was (20%). Extended spectrum β-lactamses producing Proteus was (30.7 %). DNA of 10 isolates of P. mirabilis and 4 isolates of P. vulgaris were extracted and de