In the present work advanced oxidation process, photo-Fenton (UV/H2O2/Fe+2) system, for the treatment of wastewater contaminated with oil was investigated. The reaction was influenced by the input concentration of hydrogen peroxide H2O2, the initial amount of the iron catalyst Fe+2, pH, temperature and the concentration of oil in the wastewater. The removal efficiency for the system UV/ H2O2/Fe+2 at the optimal conditions and dosage (H2O2 = 400mg/L, Fe+2 = 40mg/L, pH=3, temperature =30o C) for 1000mg/L load was found to be 72%.

Research was: 1- known as self-efficacy when students perceived the university. 2- know the significance of statistical differences in perceived self-efficacy according to gender and specialty. Formed the research sample of (300) students were chosen from the original research community by way of random (150) male specialization and scientific and humanitarian (150) females specialized scientific and humanitarian. The search tool to prepare the yard tool to measure perceived self-efficacy based on measurements and previous literature on the subject of perceived self-efficacy. The researcher using a number of means, statistical, including test Altaúa and analysis of variance of bilateral and results showed the enjoyment of the research s

Objective: The aim of this study is to determine the role of spiral Computerized Tomography in the diagnosis and
detection the types of stroke.
Methodology: One hundred sixty two patients (162) (99 males and 63 females) their ages ranging from (13 – 80)
year, all of them are suffering from stroke. They were collected randomly from spiral Computerized Tomography
unit in Baquba Teaching hospital during the period from November / 2010 to December / 2011 .All the patients
were examined clinically and then done spiral Computerized Tomography examination.
Results : The results of this study showed that the stroke effected different age groups and both sex but males is
more affected than the females .The results of spiral

Background: We aimed to investigate the accuracy of salivary matrix metalloproteinases (MMP)-8 and -9, and tissue inhibitor of metalloproteinase (TIMP)-1 in diagnosing periodontitis and in distinguishing periodontitis stages (S)1 to S3. Methods: This study was a case–control study that included patients with periodontitis S1 to S3 and subjects with healthy periodontia (controls). Saliva was collected, and then, clinical parameters were recorded, including plaque index, bleeding on probing, probing pocket depth, and clinical attachment level. Diagnosis was confirmed by assessing the alveolar bone level using radiography. Salivary biomarkers were assayed using an enzyme-linked immunosorbent assay. Results: A total of 45 patients (15

In this work Different weight of pure Zinc powder suspended particles in 4ml base engine Oil were used.
Intensity of Kα Line was measured for the suspended particles ,also for mixture which consist from Zinc particle blended with Engine base Oil. Calibration Curve was drawn between Ikα line Intensity and Zinc concentration at different operation condition. The Lower Limit detection (LLD) and Sensitivity (m) of Spectrometer were determined for different Zinc Concentration (Wt%). The results of LLD and m for Samples were analyzed at Operation Condition of 30KV,17mA is best from Samples were analyzed at Operation Condition of 25KV,15mA

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Urinary tract infections (UTIs) mean microbial pathogens in the urethra or bladder (lower urinary tract). Important risk factors for recurrent UTI include obstruction of the urinary tract, use of a bladder catheter or a suppressed immune system. This study aims to isolate and identify bacteria from patients with TCC-bladder cancer or patients with a negative cystoscope and estimate antibiotic susceptibility patterns and evaluate some of the virulence factors. From a total of 62 patients with TCC-BC or negative cystoscope, only 35 favorable bacterial growths were obtained, including Escherichia coli (UPEC), a significant bacterial isolate, and Stenotrophomonas maltophilia. The percentage of multi drug-resistance bacteria

This paper presents an enhancement technique for tracking and regulating the blood glucose level for diabetic patients using an intelligent auto-tuning Proportional-Integral-Derivative PID controller. The proposed controller aims to generate the best insulin control action responsible for regulating the blood glucose level precisely, accurately, and quickly. The tuning control algorithm used the Dolphin Echolocation Optimization (DEO) algorithm for obtaining the near-optimal PID controller parameters with a proposed time domain specification performance index. The MATLAB simulation results for three different patients showed that the effectiveness and the robustness of the proposed control algorithm in terms of fast gene