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ANALYSIS OF BLOOD CULTURE RESULTS OF BURN SEPTICAEMIA PATIENTS OVER A PERIOD OF NINE YEARS IN THE BAGHDAD BURN MEDICAL CENTRE
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Burn is one of the most devastating traumas that someone can encounter in their life. Burn wound sepsis is still the leading cause of death in burned patients. Appropriate knowledge of the causative pathogen in burn sepsis is important for successful patient management and for the reduction of the incidence of antibiotic resistance. A retrospective study was conducted between 2010 and 2018 at the Burn Specialty Hospital in Baghdad.Atotal of 320 blood culture samples were obtained from patients with sepsis orsuspected of having sepsis. Patient age ranged between 9 months to 70 years old, with a mean total burn surface area of 45.26%. The most common microorganisms isolated from those patients who had sepsis or suspicion of sepsis were Klebsiella (48 cases) followed by Pseudomonas (36 cases), Staphylococcus species (26 cases), Enterococcus (8 cases), Acinetobacter (11 cases), E-Coli (11 cases), Candida (4 cases), Proteus (2 cases), and Salmonella, Streptococcus pneumonia, Monilia, and Seriata one case for each. The most commonly isolated organism was Klebsiella: it was sensitive to Imipenem followed by Amikacin, Nitrofurantoin, Piperacillin, Ciprofloxacin, Co-trimoxazole, Chloramphenicol, Tetracycline, Azithromycin and Cefotaxime. Microbio- logical surveillance of burn patients with sepsis or suspicion of having sepsis over a period of 9 years in our hospital has shown that the most common microorganism isolated from blood cultures was Klebsiella. Kleb- siella was sensitive to Imipenem mainly according to sensitivity testing using the disk diffusion method.

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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials & Continua
A Technical Framework for Selection of Autonomous UAV Navigation Technologies and Sensors
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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation of Alpha Tocopherol Acetate as a Powder Dosage Form by Adsorption
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Alpha-tocopherol acetate is one of the most important vitamin E derivatives,that were used  as antioxidants. Adsorbents like kaolin, magnesium carbonate, and microcrystalline cellulose were used successfully to incorporate oily alpha-tocopherol acetate into an acceptable powder dosage form. The results revealed that microcrystalline cellulose as an adsorbents gave the best results with 50% loading capacity at time, 8 minutes before and after incubation period (3 months at 30C°), while kaolin and magnesium carbonate have been shown a significant difference before and after incubation. Addition of 1% w/w magnesium carbonate to the kaolin enhanced the loading capacity by decreasing the time of adsorption from 20 to 6 minutes and 47

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Publication Date
Sun Nov 01 2015
Journal Name
Iosr Journal Of Dental And Medical Sciences (iosr-jdms)
Acanthosis Nigricans as a Cause of Facial M Elanosis (Clinical Andhistopathological Study
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PKE Sharquie MD, PDPAA Noaimi MD, DDV, FDSM Al-Ogaily MD, IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2015

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Publication Date
Mon May 25 2020
Journal Name
Journal Of Xi'an University Of Architecture & Technology
Iraqi Virtual Science Library (IVSL)): A field study of Iraqi researcher’s viewpoint
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The aim of the research is to shed light on the stages of developing the Iraqi virtual science Library(IVSL) project, and to define its distinctive role in providing all kinds of electronic resources to researchers from professors and graduate students, to identify its contents , the entry interfaces and applications of use, and provide them through electronic portals to publishing houses, research institutions and international universities, The research sample included the teaching staff and researchers participating in educational qualification courses at the Continuing Education Center at the University of Baghdad, The research population and its sample consisted of the category of (IVSL) users, and its sample (387) users. Analysis meth

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Publication Date
Sat Sep 01 2018
Journal Name
King's College London
A novel sol-gel silica formulation for management of methadone hydrochloride abuse
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Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc

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Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
On Fully (m,n)-stable modules relative to an ideal A of
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Let R be a commutative ring with non-zero identity element. For two fixed positive integers m and n. A right R-module M is called fully (m,n) -stable relative to ideal A of , if for each n-generated submodule of Mm and R-homomorphism . In this paper we give some characterization theorems and properties of fully (m,n) -stable modules relative to an ideal A of . which generalize the results of fully stable modules relative to an ideal A of R.

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Publication Date
Fri Oct 20 2023
Journal Name
Al-ameed Journal For Medical Research And Health Sciences
Perceptions of Nursing Students about COVID-19 Transmission: A Multi University Study
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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Sun Feb 20 2022
Journal Name
Papers In Physics
Electronic and optical properties of nickel-doped ceria: A computational modelling study
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Cerium oxide (CeO2), or ceria, has gained increasing interest owing to its excellent catalytic applications. Under the framework of density functional theory (DFT), this contribution demonstrates the eect that introducing the element nickel (Ni) into the ceria lattice has on its electronic, structural, and optical characteristics. Electronic density of states (DOSs) analysis shows that Ni integration leads to a shrinkage of Ce 4f states and improvement of Ni 3d states in the bottom of the conduction band. Furthermore, the calculated optical absorption spectra of an Ni-doped CeO2 system shifts towards longer visible light and infrared regions. Results indicate that Ni-doping a CeO2 system would result in a decrease of the band gap. Finally,

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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