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Genetic Detection of IMP-1 Gene and its Relationship with Biofilm Formation in Klebsiella pneumonia
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Background: Klebsiella pneumoniae were considered as normal flora of skin, and intestine. It can cause damage to human lungs; the danger of this bacterium is related to exposure to the hospital surroundings. materials and methods: the detection of Klebsiella pneumoniae on morphological and biochemical tests and then assured with VITEK 2 system. Resistance to antibiotics was determined by Kirby-Baeur method. And genotyping of IMP-1 in isolates was done by PCR technique, then biofilm formation was identified by Micro titer plate method. Results: The present study included a collecting of 50 specimens from different clinical specimens, (blood 40%, urine 30%, sputum 20%, wound infection 10%); 10 isolates were identified as Klebsiella pneumoniae . All isolates, under study, developed high resistance toward Cefitrixon, Ampicillin, Amoxicillin, Ticarcillin, Ticarcillin+Clavulanic acid, and Ceftazidim estimated by disc diffusion method. All isolates characterized by harboring the highest resistant in a percentage reached 100% against antibiotics, under study. This study determined the Minimal Inhibitory Concentration were detected by eight E-test strips for isolates. As well as the isolates were strong biofilm production for three isolates, while three were moderate of biofilm formation and other isolates were weak former; at the value of (P≤0.05) was considered as a significant. Genotype detection of Metalo-beta lactamase (IMP-1) by PCR technique in Klebsiella pneumoniae . Upon using PCR technique exposed only three isolates;30% of isolates (two from urine, one from blood) samples harbored IMP-1 gene. The study was also found relationship between IMP-1 and biofilm formation in isolates which were harboring these genes, when (P ≤ 0.05). Conclusions: K. pneumoniae were isolated from different sources. All isolates were resistant to most antibiotics used in this study. The isolates have Metallo-beta lactamse. PCR was showed K. pneumoniae have IMP-1 gene,.This study also found there was relationship between biofilm formation and IMP-1 gene in K. pneumoniae (P≤0.05).  

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Servant Leadership and its Impact on the Effectiveness of Teamwork
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   The research problem stems from the suffering of organizations from the weakness of their organizing aspect and the weak influence of the leadership on the subordinates and their dispersion. Organizations today are in rapid development and therefore work relations are not dominated by the humanitarian aspect and the first goal has become productivity. The research aims to identify the influence of servant leadership and its dimensions as an independent variable on the effectiveness of work teams as an approved variable and their importance increases when these organizations are service organizations, and how their influence increases when this leadership is the servant leadership and its dimensions in the Health Depa

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Publication Date
Thu Aug 01 2013
Journal Name
International Journal Of Physics And Research
THE MECHANISM OF SN1987A EXPLOSION AND ITS EJECTA MASS ENVELOPE
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Optical spectrum of SN1987A at days 4 from the explosion and its light curve through the first 1444 days after the explosion have been studied. The hydrogen lines present in the spectrum confirms the general characteristics of Type II SN that occur due to core collapse of massive star. Each of the total mass ejected from the explosion and the amount of the total mass of Nickel radioactive isotopes that produced during the explosion as well as the initial velocity of the ejecta and the explosion energy have been determined and compared with different observed and calculated models obtained by different researchers and it’s found that, about 8.8 Mʘ of the progenitor envelope mass had been ejected during the explosion and it’s mixed with

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Publication Date
Fri Oct 23 2020
Journal Name
Biomed Research International
A Computational Model of the Brain Cortex and Its Synchronization
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Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to mea

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Materials Research And Technology
The effect of laser pulse energy on ZnO nanoparticles formation by liquid phase pulsed laser ablation
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Zinc Oxide nanoparticles were prepared using pulsed laser ablation process from a pure zinc metal placed inside a liquid environment. The latter is composed of acetyltrimethylammonium bromide (CTAB) of 10−3 molarity and distilled water. A Ti:Sapphire laser of 800 nm wavelength, 1 kHz pulse repetition rate, 130 fs pulse duration is used at three values of pulse energies of 0.05 mJ, 1.11 mJ and 1.15 mJ. The evaluation of the optical properties for the obtained suspension was applied through ultraviolet–visible absorption spectroscopy test (UV/VIS). The result showed peak wavelengths at 210 nm, 211 nm and 213 nm for the three used pulse energies 0.05 mJ, 1.11 mJ and 1.15 mJ respectively. This indicates a blue shift,

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Publication Date
Fri Jan 31 2020
Journal Name
Iraqi Geological Journal
ESTIMATION OF SHEAR WAVE VELOCITY FROM WIRELINE LOGS DATA FOR AMARA OILFIELD, MISHRIF FORMATION, SOUTHERN IRAQ
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Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Metal Complexes of Multidentate N<sub>2</sub>S<sub>2</sub> Heterocyclic Schiff-base Ligands;Formation, Structural Characterisation and Biological Activity
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Abstract<p>The synthesis of ligands with N<sub>2</sub>S<sub>2</sub> donor sets that include imine, an amide, thioether, thiolate moieties and their metal complexes were achieved. The new Schiff-base ligands; N-(2-((2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio)-acetamide (H<sub>2</sub>L<sup>1</sup>) and N-(2-((2,4-di-p-tolyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio) acetamide (H2L<sup>2</sup>) were obtained from the reaction of amine precursors with 1,4-dithian-2-one in the presence of triethylamine as a base in the CHCl3 medium. Complexes of the general formula K<sub>2<</sub></p> ... Show More
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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Early detection of first degree relatives to type-II diabetes mellitus
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Hypertension among Cardiac Diseases Inpatients at Kirkuk City Hospitals
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Objectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Dise

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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