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Detection Of Candida Albicans Responsible For Vulvovaginitis In Women
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Background: The vaginal microbial ecosystem stability preclude many other organisms but sometimes the vaginal micro biota is disturbed and this cause change in the normal

balance causing symptoms of vulvuvaginitis like abnormal or increased vaginal discharge, redness and itching.

Objective: To prove C. albicans presence in their vagina clinically and laboratory by culture of vaginal swab on two media.

Type of the study: This study is a case control study

Methods: This study is a case control study in which 100 clinically patient women admitted to maternity hospital in kalar city and khanaqin hospital during the period from 1st August– 30th of October 2016 who were examined to prove C. albicans presence in their vagina clinically and laboratory by culture of vaginal swab on two media, the first media was used for primary isolation which was Sabouraud´s dextrose agar media and the second was to differentiate Candida spp. according to their color .

Results: Results of this study presented that the highest invasion of the vagina of Candida spp was accounted for C. albicans (39.6%)from the (53) positive cultures , while other species were as follows: C. glabrata (26.4%), C. tropicalis (20.8%) ,C. krusi(13.2 %).  

Conclusions: this study presented that the highest invasion of the vagina of Candida spp was accounted for C. albicans

 

 

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Publication Date
Sun Jul 01 2018
Journal Name
Computers And Electronics In Agriculture
Detection of charcoal rot (Macrophomina phaseolina) toxin effects in soybean (Glycine max) seedlings using hyperspectral spectroscopy
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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Automated Detection of Dubas Bug Infestation in Palm Trees Using Deep Learning with Residual Neural Networks
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Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health

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Publication Date
Mon Dec 01 2014
Journal Name
Iraqi Journal Of Science
Detection of human leukocyte antigen and celiac disease auto antibodies in serum of patients with multiple sclerosis
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To determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos

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Publication Date
Mon Dec 01 2014
Journal Name
Iraqi Journal Of Science,
Detection of human leukocyte antigen and celiac disease auto antibodies in serum of patients with multiple sclerosis
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To determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos

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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Detection of early occlusal caries of the first permanent molar using different techniques (An in vivo study)
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Background: Molars and premolars are considered as the most vulnerable teeth of caries attack, which is related to the morphology of their occlusal surfaces along with the difficulty of plaque removal. different methods were used for early caries detection that provide sensitive, accurate preoperative diagnosis of caries depths to establish adequate preventive measures and avoid premature tooth treatment by restoration. The aim of the present study was to evaluate the clinical sensitivity and specificity rates of DIAGNOdent and visual inspection as opposed to the ICDAS for the detection of initial occlusal caries in noncavitated first permanent molars. Materials and Methods: This study examined 139 occlusal surface of the first permanent

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Publication Date
Sat Feb 01 2014
Journal Name
World Journal Of Pharmaceutical Sciences
Detection of JAK2V617F Mutation and Serum Levels of Alkaline Phosphatase and Lactate Dehydrogenase in Chronic Myelogenous Leukemia.
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Chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm arises from Bcr-Abl gene translocation (called Ph chromosome) in hematopoietic stem cells (HSCs). This genetic abnormality results in constitutive activation of tyrosine kinase and subsequent uncontrol growth and multiplication of granulocytes. The cornerstone in treatment of CML are tyrosine kinase inhibitors, of which imatinib is the most effectively used. JAK2V617F mutation is an acquired single nucleotide polymorphism (SNP) occurs in JAK2 gene and is associated with many hematological malignancy other than CML. It was thought that the two genetic abnormalities (Bcr-Abl and JAK2V617F) occur mutually; however, growing body of evidences suggested the reverse. This study a

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Publication Date
Fri Dec 01 2017
Journal Name
Rawaa Emad Jaloud And Fadia Falahfadia Falah
Isolation and Identification of Fungal Propagation in Iraqi Meat and Detection of Aflatoxin B1 Using ELISA Technique
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Publication Date
Wed Jan 01 2025
Journal Name
Kuwait Journal Of Science
Detection of the most frequent sources of dust storms in Iraq during 2020–2023 using space tools
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Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so

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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques
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This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

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