The electrical and thermal performance of a typical single pass hybrid photovoltaic/thermal (PV/T) air collector is modeled, simulated and analyzed for two selected case studies in Iraq. An improved mathematical thermo-electrical model is derived in terms of design, operating and climatic parameters of the hybrid solar collector to evaluate its important characteristics: collector flow and heat removal factors, PV maximum power point and its temperature coefficient, and overall power and efficiency. Unlike previous PV/T thermal models, the present model is obtained with some additions and corrections in radiation and convection heat coefficients for the top loss and for the air duct with more applicable sky temperature correlation. The well

A total of 400 hard tick specimens (250 ♂♂, 150 ♀♀) were collected from 160 sheep Ovis aries Linnaeus, 1758 out of 200 samples examined in the different localities of Iraq, representing an infestation rate of 80% of the sheep. The results of the current research identified eight species of hard ticks belonging to two genera, Hyalomma C. L. Koch, 1844 and Rhipicephalus Koch,1844 and belonging to the Ixodidae family, as follows: Hyalomma anatolicum Koch, 1844, H. excavatum Koch, 1844, H. impeltatum Schulze & Schlottke, 1930, H. scupense Schulze, 1919, Rhipicephalus bursa Canastrini & Fanzago, 1878, R. camicasi Morel, Mouchet & Rodhain, 1976, R. sanguineus Latreille, 1806, and R. turanicus Pomerantsev, 1936. Molec

The objective of present study was to investigate the effect of using duplex volaticle oil of Rosmarinusoficinolis and Nigella sativain microbial quality, sensing and extending storage time of minced cold poultry meat. Duplex volaticle oil was added at 25, 50 and 75 mg/kg to minced poultry meat , these treatments were stored individually for (0 ,4 and 7) days at( 4-7) C0 . After making several microbial and sensing test. The following results were obtained:- The process of adding duplex volaticle oil of Rosmarinus officinolis and Nigella sativa to minced poultry meat led to significant reduced (P<0.01) in total arobic count, psychrophilic count and coliform bacteria during refrigerated storage periods. The results showed asignificant sens

KE Sharquie, JR Al-Rawi, AA Noaimi, MM Jabir, Iraqi Postgraduate Medical Journal, 2009

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

S Khalifa E, AR Jamal R, N Adil A, J Munqithe M…, 2009