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bsj-5706
Colistin as A Good Monotherapy to Restrain the Pathogenicity of Acinetobacter baumannii In vivo and In vitro
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        Acinetobacter baumannii  (A. baumannii) is a major opportunistic nosocomial pathogen, mostly resistant to several groups of antibiotics. Colistin is now used as a last-line treatment for isolates that are highly resistant. The purpose of this study is to identify the importance of LptD; which is involved in the translocation of LPS from the inner membrane to the outer membrane in compartment with LptA and LptC of A. baumannii and its indispensable role as a virulence factor, and the efficiency of colistin as a monotherapy. In the current research, two isolates of A.baumannii were used, the local isolate HHR1 isolated from urine sample and the global strain ATCC 17904, and three antibiotics (colistin, rifampicin and Fosfomycin) were used as a monotherapy and synergic therapy in vivo and ex vivo. The results demonstrated that A. baumannii HHR1 was more resistant to Antimicrobial peptides (AMPs) than the standard strains. The effect of AMPs  on A. baumannii was increased by increasing the concentration and the time of incubation, and also AMPs were shown to be lethal on A. baumannii growth spatially at high concentration (2 µg ml-1) in  monotherapy and (1.5, 2 µg ml-1) in synergic. The susceptibility of isolates towards antibiotics was variable, where colistin exerts significant growth had defect as a monotherapy and in combination with others. The results showed that the expression of lptD, lptA genes of A.baumannii HHR1 were  higher than of  the same genes in A.baumannii ATCC 17904 in the presence of 2 µg ml-1  colistin, while lptE gene of the A.baumannii ATCC 17904 showed an upregulation pattern  than in A.baumannii HHR1. Furthermore, colistin influences the adhesion ability of A. baumannii on epithelial cells (A-549 lung cancer cell) by reducing the number of cells, and thus could colistin be a good candidate for A. baunmannii treatment.

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Publication Date
Thu Jun 01 2023
Journal Name
2023 Ieee 36th International Symposium On Computer-based Medical Systems (cbms)
Toward a Minimal sEMG Setup for Knee and Ankle Kinematic Estimation during Gait
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Publication Date
Tue Dec 29 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Personal tax exemptions "a comparative study with some Arab and European system legislations
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This research aims primarily to highlight personal tax exemptions A comparative study with some Arab and European regulations. And by conducting both theoretical comparative analyses. Most important findings of the study is the need to grant personal and family exemptions that differ according to the civil status of the taxpayer (single or married). In other words, the exemption increases as the number of family members depend on its social sense. Also taking into account some incomes that require a certain effort and looking at the tax rates, it is unreasonable for wages to be subject to the same rates applied to commercial profits.      

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Activity, Profitability Indictors Analysis: A Comparsion Study among Nationality and Iraqi Insurance Company
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Reseach target the most important topic, is Activity and ProfitabilityIndictors Analysis for
Nationality and Iraqi Insurance Company, In order to stand on them ability to cover its risks
and explore the efficiency asset and its avialible resources using to determine them abilities to
profit generation from its insurance activity. The analysis was focus to examine their profit
and activity power, and test the significant differences aming them performance. Test 2
hypothese that is related and result it sign that the 2 company no has significant differences at
profitability and activity level. The research depend on coneclusion, recommended two
company to work at efficiency with cost element of insurance activity in or

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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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
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
Mon Apr 07 2025
Journal Name
The Peerian Journal
Plant-Bacterial Interactions: A latent Alliance for Growth promotion and Environmental Stress Tolerance
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This encapsulates the general relationship between plant and bacteria in the natural and agricultural ecosystem. It is based on the activities of useful bacteria, such as plant growth-promoting bacteria (PGPRs) and nitrogen-fixing bacteria, in promoting plant growth and plant tolerance to stressful situations regarding pollution, salinity, and drought. The article also mentions that the bacteria maintain plant health by secretion of phytohormones, nitrogen fixation, solubilization of phosphate, and production of antibiotics against pathogenic bacteria. The article also mentions the existing applications of the interaction in sustainable agriculture and bioremediation of contaminated soils.

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Publication Date
Fri Jun 30 2023
Journal Name
Pakistan Heart Journal
Workplace Violence and Nursing Job Performance at Pediatric Emergency Departments: A Comparative Study
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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Industrial And Engineering Chemistry
Petroleum refinery wastewater treatment using a novel combined electro-Fenton and photocatalytic process
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