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Identification of microflora associated with dust falling on Karbala province and seasonal distribution
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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Meiobenthic Invertebrates Community Associated with Aquatic plant Ceratophyllum demersum Salamiyat irrigation canal / north Baghdad
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The aim of the present study is to study the meiobenthic invertebrate's community associated with the aquatic plant Ceratophyllum demersum in Al-Salamiyat irrigation canal / north Baghdad, with the chemical and physical parameters of the canal water, during the study period from September 2015 to May 2016. Two sites were chosen for sample collection, the first site (S1) at the beginning of the canal near it's connection with Tigris river, and the second site (S2) after 10 km from the first site. The chemico-physical analysis results revealed that the water temperature ranged from 10-30oC, and pH values ranged between 6.9-7.8, and the dissolved oxygen concentration and the BOD values from 7.2-9.2 mg/l, and 1.2-5.4 mg/l, respectively. The sal

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Ecological Engineering
Contaminants Removal from Real Refinery Wastewater Associated with Energy Generation in Microbial Fuel Cell
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Publication Date
Mon Jul 14 2025
Journal Name
European Journal Of Clinical Microbiology & Infectious Diseases
Vibriosis-Associated Acute Kidney Injury: Incidence and Outcome
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Abstract<p><bold>Purpose: </bold>Vibriosis, caused by <italic>Vibrio cholerae</italic>, is an intestinal infection characterized by profuse watery diarrhea, leading to significant fluid loss. This study aimed to assess the clinical features, outcomes, and severity of cholera among hospitalized patients and its association with acute kidney injury (AKI). <bold>Methods</bold>: A prospective cohort study was conducted on 70 patients with confirmed <italic>V. cholerae</italic> infection at Baghdad Teaching Hospital, Medical City, during the cholera outbreak in Iraq (June–October 2022). Patients were recruited from the emergency department and medical quarantine ward. Diagnosis was based on clinical features and confir</p> ... Show More
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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Isolation and Identification of Salmosamonella typhi from clinical samples with molecular detection of O-antigen encoded genes
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Abstract

Antibiotic treatment of  S.typhi is difficult as compared to treatment of acute infection. Antibiotic resistance carried against S.typhi  by using 6 kinds of antibiotics from  different classes, their results  showed that all isolates were  high resistance to Ampicillin (99%), Gentamicin (98%), Amikacin (79%) and   less  resistances  Trimethoprim (55%) ,  Imipenem (60%)  and Ceftriaxone(66%)  .

The present study focused on the molecular detection of Wzx flippase, Wzy polymerase genes in some Salmonella typhi isolates, Samples were collected from typhoid patients by classical lab work. Antibiotics susceptibilit

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Publication Date
Tue Dec 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Constructing a new mixed probability distribution with fuzzy reliability estimation
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This paper deals with constructing mixed probability distribution from mixing exponential

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Publication Date
Mon Jul 01 2024
Journal Name
International Journal Of Engineering In Computer Science
Human biometric identification: Application and evaluation
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Publication Date
Thu Oct 01 2009
Journal Name
Journal Of The College Of Languages (jcl)
Lexical Bundles: Identification and Distinguishing Features
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It is not often  easy to identify a certain group of words as a lexical bundle, since the same set of words can be, in different situations, recognized as idiom,  a collocation, a lexical phrase or a lexical bundle. That is, there are many cases where the overlap among the four types is plausible. Thus, it is important to extract the most identifiable and distinguishable characteristics with which a certain group of words, under certain conditions, can be recognized as a lexical bundle, and this is the task of this paper.

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Publication Date
Mon Oct 21 2024
Journal Name
Iraqi Statisticians Journal
On Inference of Finite Mixture of Rayleigh Distribution by Gibbs Sampler and Metropolis-Hastings
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Inferential methods of statistical distributions have reached a high level of interest in recent years. However, in real life, data can follow more than one distribution, and then mixture models must be fitted to such data. One of which is a finite mixture of Rayleigh distribution that is widely used in modelling lifetime data in many fields, such as medicine, agriculture and engineering. In this paper, we proposed a new Bayesian frameworks by assuming conjugate priors for the square of the component parameters. We used this prior distribution in the classical Bayesian, Metropolis-hasting (MH) and Gibbs sampler methods. The performance of these techniques were assessed by conducting data which was generated from two and three-component mixt

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Publication Date
Fri Nov 15 2024
Journal Name
Iraqi Journal Of Science
Comparative Analysis for the Seasonal Variations of the IF2 and T Ionospheric Indices during Solar Cycles 23 and 24
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In this work, a comparative analysis for the behavior and pattern of the variations of the IF2 and T Ionospheric indices was conducted for the minimum and maximum years of solar cycles 23 and 24. Also, the correlative relationship between the two ionospheric indices was examined for the seasonal periods spanning from August 1996 to November 2008 for solar cycle 23 and from December 2008 to November 2019 for solar cycle 24. Statistical calculations were performed to compare predicted values with observed values for the selected indices during the tested timeframes. The study's findings revealed that the behavior of the examined indices exhibited almost similar variations throughout the studied timeframe. The seasonal variations were

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Publication Date
Thu Oct 30 2025
Journal Name
Iraqi Journal Of Science
Postmortem Panoramic Dental Radiography: Human Identification Based on Convolution Neural Network and Contourlet Transform
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Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted

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