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Molecular detection and the frequency of a pore-forming toxin in Enterococcus faecalis isolated from urinary tract infections
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Background: Enterococcus faecalis is a causative agent for urinary tract infections (UTIs) in Iraq and worldwide, even though it is a commensal bacterium in human and animal intestines. It can cause different illnesses due to its ability to produce various virulence factors. A pore-forming toxin (cytolysin) is the most virulence factor in this bacterium. Objective: This study aims to molecularly investigate the frequency of cytolysin toxin among E. faecalis isolated from UTIs. Methods: A hundred and eighty urine specimens were collected from females diagnosed with UTIs. Traditional laboratory and molecular methods were used for bacterial identification and toxin detection using a modified DNA extraction method. Results: The findings revealed that 27.7% (50\180) of causative agents in UTIs were E. faecalis based on the molecular technique that targeted a housekeeping gene (ddI) with specific primers using polymerase chain reaction (PCR). Most of the isolates harboured the cytolysin toxin gene (cylLL) with a frequency rate of 92% (46\50). Conclusions: A considerable prevalence of cytolysin-positive isolates in UTIs, which is a worrying indicates of the extensive spreading of a toxic strain in UTIs. The modified method for DNA extraction in gene detection was successfully used to amplify a housekeeping gene (ddI) and a virulence gene (cylLL) for cytolysin toxin detection, and this approach can be utilised for rapid bacterial identification and gene detection in medical and research purposes with a large sample size in an inexpensive manner within a short time.

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Thu Jan 16 2025
Journal Name
Al–bahith Al–a'alami
Foreign Propaganda in the Electronic Press about the Syrian Crisis A Comparative Study of the Sites of Russia Today and Alhurra - A research drawn from a Master Degree thesis
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The research problem lies in the ambiguity of the usage of propaganda contents by two main media outlets (the Russian RT and American Alhurra) in their news coverage of the Syrian crisis through their websites and the methods used by them to convince users taking into account the mutual propaganda conflict between the United States and Russia in the war against Syria. The objectives of the research can be represented by the following: investigating the contents of American and Russian electronic propaganda towards Syrian crisis.
• Identifying the contents that received most of the coverage in the Syrian crisis by the two news outlets.
• Identifying the terms and phrases that have been most used by the websites of RT and Alhurr

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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
Detection of Bacterial Resistance Genes from Neonatal’s Incubators Environment at Selected Sites of Baghdad Hospitals
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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
A Review on Face Detection Based on Convolution Neural Network Techniques
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     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Effect of Ferocene Concentration on the Percent Conversion and Molecular Weight of Poly(Methyl Methacrylate) Homopolymers
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This research is addressing the effect of different ferrocene concentration (0.00, 2.15x10-3, 4.30x10-3, 8.60x10-3, and 12.9x10-3) on the bulk free radical polymerization of methyl methacrylate monomer in benzene using benzoyl peroxide as initiator. The polymerization was conducted at 60º C under free oxygen atmosphere. The resulting polymers were characterized by FTIR. The results were compared with the presence and absence of ferrocene at 10% conversion. The %conversion was 3.04% with no ferrocene present in the polymerization medium and its increase to 9.06 with a first lowest ferrocene concentration added, i.e. 2.15 x10-3mol/l. This was positively reflected on the poly(methyl methacrylate) molecular weight measured by viscosity techniq

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Scientific & Engineering Research
Horizontal Fragmentation for Most Frequency Frequent Pattern Growth Algorithm
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Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Block-Iterative Frequency-Domain Equalizations for SC-IDMA Systems
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In wireless broadband communications using single-carrier interleave division multiple access (SC-IDMA) systems, efficient multiuser detection (MUD) classes that make use of joint hybrid decision feedback equalization (HDFE)/ frequency decision-feedback equalization (FDFE) and interference cancellation (IC) techniques, are proposed in conjunction with channel coding to deal with several users accessing the multipath fading channels. In FDFE-IDMA, the feedforward (FF) and feedback (FB) filtering operations of FDFE, which use to remove intersymbol interference (ISI), are implemented by Fast Fourier Transforms (FFTs), while in HDFE-IDMA the only FF filter is implemented by FFTs. Further, the parameters involved in the FDFE/

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Detection of Pollution by Antibiotics and the Level of Some Hormones in Some Canned Meats
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  The study aimed to identify the extent of contamination of some imported canned meat to Iraq through the assessment of the level of certain hormones, antibiotics and parasites which included canned food samples and different types of canned beef and luncheon meat beef and canned luncheon and canned chicken.  The results showed for the level of certain hormones progesterone hormone that has a high level of these models in terms of its value ranged from (21.7-34.5) ng/ml and either hormone testosterone was within allowable level where its value ranged from (1.4-4.4) ng/ml  As for antibiotics , there has been effective inhibitory in all canning toward the bacterium Staphylococcus aureus and Pseudomonas aeruginosa and E.Coli

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Biological Effect of Different Concentrations of Bacillus Thurngensis Isolated From The Soils of Sawa Lake, Al Muthanna Governorate on The of Hypera postica at Different Time Periods
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Abstract<p>This study conduct in Al-Muthanna governorate to assess five concentrations of <italic>Bacillus</italic> thurngensisagonist <italic>Hyperapostica</italic>. The results showed the presence of <italic>Bacillus thurngensisin</italic> all the studied sites of Lake Sawa in Muthanna Governorate, and the rates of its presence were close to the same sites, and the rate of its presence in those sites was 35%, and its highest rate was recorded in the north and east of the lake, as it reached 40% and the lowest amounted to 30% in the two sites south and west site. The results of the study showed that five concentrations were taken from bacterial isolates of <it></it></p> ... Show More
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Publication Date
Sun Jan 16 2022
Journal Name
Iraqi Journal Of Science
A Multi-Objective Evolutionary Algorithm based Feature Selection for Intrusion Detection
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Nowad ays, with the development of internet communication that provides many facilities to the user leads in turn to growing unauthorized access. As a result, intrusion detection system (IDS) becomes necessary to provide a high level of security for huge amount of information transferred in the network to protect them from threats. One of the main challenges for IDS is the high dimensionality of the feature space and how the relevant features to distinguish the normal network traffic from attack network are selected. In this paper, multi-objective evolutionary algorithm with decomposition (MOEA/D) and MOEA/D with the injection of a proposed local search operator are adopted to solve the Multi-objective optimization (MOO) followed by Naï

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