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Molecular screening of the entA gene of Enterococcus faecium isolated from Food and clinical sources
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Background: The microbial production of substances that have the potency to suppress the growth of other microorganisms is probably one of the prevalent defense strategy developed in nature, microorganisms produce a variable bunch of microbial defense systems, which include antibiotics, metabolic by-products, lytic agents, bacteriocins and others. Objective: The purpose of the present study was to isolate and identify Enterococcus faecium isolates then detecting its ability of carrying the gene responsible for enterocin production in this species. Materials and methods: Out of 50 samples from different sources (food and clinical sources) were collected for the Enterococcus faecium isolation, and the isolated bacteria Enterococcus faecium (37) isolates were detected for their harboring of Enterocin A gene (entA), using conventional PCR technique. Results: The identification revealed that 37(74%) isolates were considered as Enterococcus faecium, 20 isolates (54.05%) out of food samples (10 samples were collected from dairies, 7 from vegetables and 3 from fish samples), and 17 isolates 45.9% out of clinical samples (11 from stool and 6 from urine source). Genotypic Detection done by the amplification of the enterocin coding gene (ent A),  and the results revealed that all the isolates were harboring that gene despite of the phonotypical differences, that they amplified entA gene and the PCR product size (362 bp) was detected using agarose gel electrophoresis. Conclusions: This study indicates the presence of Enterococcus spp. in food and clinical sources and the ability of these bacteria to produce antibacterial substances which is active against closely related clinical isolates.

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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
Fri Jan 01 2021
Journal Name
Ieee Access
Multichannel Optimization With Hybrid Spectral- Entropy Markers for Gender Identification Enhancement of Emotional-Based EEGs
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Publication Date
Mon Oct 19 2026
Journal Name
Journal Of Baghdad College Of Dentistry
An Assessment of Oral Health in Hypertensive Patients Treated with HMG-CoA Reductase Inhibitors (Statins)
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Background: Hypertension is a chronic medical condition in which the blood pressure in the arteries is elevated, it's classified as either primary (essential) hypertension or secondary hypertension, and it increases the risk of ischemic heart disease, peripheral vascular disease and other cardiovascular diseases. Several classes of medications collectively referred to as antihypertensive drugs like beta blockers, calcium channel blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers, renin inhibitors and statins (HMG-CoA) reductase inhibitor. Statin medication may have some beneficial effects when subjects have dental plaque or signs of periodontitis as gingival bleeding. The purpose of this study were to as

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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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