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Phylogenetic Analysis and Detection of Drug Resistance Gene in Theileria annulata Isolated from Buffaloes
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Bovine theileriosis, caused by Theileria annulate, is disease affecting cattle and buffaloes worldwide. The current study aimed to screen the blood samples of 30 naturally suspected local buffaloes infected with Theileria species. The blood samples were initially examined by light microscopic and then the positive samples were subjected to PCR reactions. All 30 animals indicated clinical symptoms, such as high fever, loss of appetite, the presence of the hard tick, and enlargement of lymph nodes. The amplified products of 18S rRNA were analyzed, along with molecular detection of the drug-binding site alterations and interrelated changes in the cytochrome b (cyto b) gene. Blood smears revealed the presence of infected erythrocytes with Theileria spp. The PCR results confirmed infection in samples when DNA amplified with partial 18S rRNA and cyto b genes. The sequencing data were obtained from GeneBank using the accession numbers OM937770.1, ON207523.1, ON207525.1, ON207524.1, ON207526.1, and ON207527.1 Following BLAST analysis (Basic Local Alignment Search Tool), genetic differences were observed between the Iraqi isolate OM937770.1 and strains from India, Iran, and Turkey. The data obtained from the current study may reveal the genetic alteration of the local strain in the drug-target codons, which are found in one isolate and are different from the GenBank isolates. The results suggest that the failure of buparvaquone therapy might be due to the resistance to cyto b gene.

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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
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Practical Study for the Properties of Hueckel Edge Detection Operator
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Publication Date
Thu Jan 12 2017
Journal Name
Journal Of Agricultural And Food Chemistry
Using Standing Gold Nanorod Arrays as Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Detection of Carbaryl Residues in Fruit Juice and Milk
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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Tue Sep 15 2015
Journal Name
Asian Journal Of Poultry Science
Association of Insulin-Like Growth Factor-1 Gene Polymorphism at 279 Position of the 5’UTR Region with Body Weight Traits in Broiler Chicken
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insulin-like Growth Factor 1 (IGF-1) gene has been described in several studies as a candidate gene for growth. The present study attempts to identify associations between body weight traits and polymorphisms at 279 position of 5'UTR flanking region of IGF-1 gene in broiler chickens. Three hundred broiler chickens from two breeds (Cobb 500 and Hubbard F-15) were used in this study. A single nucleotide polymorphism (SNP) at 279 position of 5'UTR region of the IGF-1 gene was identified in 20.6 and 60.3% of Cobb 500 and Hubbard F-15, respectively, using the PCR-RFLP technique. Allele frequencies were 83.87 and 42.80% for the T allele and 16.13 and 57.20% for the C allele in Cobb500 and Hubbard-15 breeds, respectively. Genotype frequencies were

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Entomology And Zoology Studies
Isolation and identification of Enterococcus fecalis from cow milk samples and vaginal swab from
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The aim of the present study was to isolated the Enterococcus spp. from milk samples of cow and vaginal swabs from aborted women and patient women in Baghdad during September 2016 to april 2017. All 100 milk sample collecting was carried out on California Mastitis Test (CMT) and the positive Percentage of CMT reactions was 5% and the percentage of Enterococcus isolates from mastitic milk was 60% and 30% from nonmasitic milk. The prevalence of Enterococcus spp was 31% of milk samples and the prevalence of Enterococcus spp. Isolates were 67.74% of the isolates of cow milk samples were Enterococcus faecalis, 25.80% was Group D and 6.45% was non groupable while Enterococcus spp. isolates from aborted women samples were 20% and all isolated was

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Publication Date
Thu Dec 01 2016
Journal Name
Karbala Journal Of Medicine
Assessment Of Her-2/Neu Gene Amplification Status by Chromogenic in Situ Hybridization in Breast Cancer Patients with Equivocal 2+ Her-2/Neu Immunostaining and Its Relation to The Clinic Pathological Parameters
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background: human epidermal growth factor receptor-2 (her2/neu) is related to growth factor receptors with alkaline kinase activity and it is regarded as important prognostic and therapeutic factor that can depended on in breast cancer therapy. HER2/neu expression by immunohistochemistry (IHC) is submitted to a great in terob server inconsistency. Subsequently additional confirmatory tests for assessment of gene alterations and amplification status are needed for patients with early or metastatic breast cancer. In situ hybridization techniques and specifically Chromogenic in situ hybridization (CISH) was arise as a practical, cost-effective, and alternative to fluorescent in situ hybridization in testing for gene alterationAims of the study

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