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The Association of Prothrombin Gene Mutations and Cytomegalovirus Infection with Abortion Among Iraqi Women
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Abortion is categorized as the termination of conception caused by the failure or removal of the embryo from the uterus before the conclusion of pregnancy. Microorganisms and genetic factors are two of the many factors associated with abortion. Cytomegalovirus is a widespread congenital virus infection pathogen that affects a wide variety of people. The prothrombin gene is one of the essential causes that trigger blood clotting and the function of abortion women, therefore the aim of the study is to detect and associate Cytomegalovirus and prothrombin gene mutation (Gene ID: 14061 in NCBI) with abortion through genetic and immunological methods. Five ml of whole blood was collected from an intravenous puncture and divided into two tubes, one with EDTA and one without (plain tube) from 74 women with an abortion history as a patient group and 74 women without an abortion record who had at least one successful fertility as a control group. Allele-specific PCRs are used to amplify gene regions with genetic primers containing prothrombin gene polymorphisms. Current results have shown the greatest risk of abortion was observed in women patients with IgG seropositivity in 65 women with frequency (87.8%) and the lowest rate of abortion was in IgM seropositivity in 3 women with frequency (4.1%) and 6 (8.1%) were positive for IgM-and IgG indicating they have both an old and recent infections. Furthermore, allele-specific PCRs are used to amplify prothrombin G20201A polymorphism. The result of this study demonstrated there is no association between prothrombin genotype level frequency and abortion in CMV-infected women. While, there is a highly significant association between A and G Alleles combinations and abortion in CMV-infected women.

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Publication Date
Mon Oct 01 2018
Journal Name
Materials Research Bulletin
Fabrication of CdSe nanoparticles sensitized TiO 2 nanotube arrays via pulse electrodeposition for photoelectrochemical application
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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Petroleum Science And Engineering
Effect of wettability on particle settlement behavior within Mono-Ethylene Glycol regeneration pre-treatment systems
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This study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su

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Publication Date
Mon Jan 01 2018
Journal Name
Ndt &amp; E International
Porosity evaluation of in-service thermal barrier coated turbine blades using a microwave nondestructive technique
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Publication Date
Wed Nov 05 2014
Journal Name
International Journal Of Applied Mathematical Research
Approximate solution of a model describing biological species living together using a new iterative method
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Publication Date
Fri Jan 01 2021
Journal Name
2nd International Conference On Engineering &amp; Science
Comparative on-grid solar systems winter performance analyses of different PV technologies in Baghdad weather
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Publication Date
Tue Mar 17 2020
Journal Name
Optical And Quantum Electronics
Photocatalytic activity of Ag-doped TiO2 nanostructures synthesized by DC reactive magnetron co-sputtering technique
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
Rapid Detection of Aspergillus flavus isolates producing aflatoxin using UV light on different culture media
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This study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able

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Publication Date
Sat Oct 10 2026
Journal Name
Al-khwarizmi Engineering Journal
Numerical Analysis of Double Diffusive Laminar Natural Convection in a Right Angle Triangular Solar Collector
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Publication Date
Fri Dec 25 2015
Journal Name
مجلة اتحاد الجامعات العربية للدراسات والبحوث الهندسية
Smart Sensing for Variable Pressure of Oil Well Safety Valve Using Proportional Pressure Control valve
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Protection of the oil pipelineswhich extracted from the wells was found to shut the well and prevent the leakage of oil when broken using safety valve. This valve is automatically activated by loss of pressure between the well and pipelines, which take the pressure, signal from hydraulic pressure sensor through pressure control valve which has constant or variable value but it is regulated manually. The manual regulatory process requires the presence of monitoring workers continuously near the wells which are always found in remote areas. In this paper, a smart system has been proposed that work with proportional pressure control valve and also electronic pressure sensor through Arduino controller, which is programmed in a way that satisfie

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