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Molecular Identification of Methylorubrum extorquens using PCR-Amplified MxaF Gene Fragments as A Molecular Marker
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  Methylotrophs bacteria are ubiquitous, and they have the ability to consume single carbon (C1) which makes them biological conversion machines. It is the first study to find facultative methylotrophic bacteria in contaminated soils in Iraq. Conventional PCR was employed to amplify MxaF that encodes methanol dehydrogenase enzyme. DNA templates were extracted from bacteria isolated from five contaminated sites in Basra. The gene specific PCR detected Methylorubrum extorquens as the most dominant species in these environments. The ability of M. extorquens to degrade aliphatic hydrocarbons compound was tested at the laboratory. Within 7 days, gas chromatographic (GC) studies of remaining utilized crude oil revealed that 61.14 % of the initial content had been degraded, and GC fingerprinting of the utilized aliphatic compounds revealed significant reductions in C12, C13, C14, and C15. Globally this is the first time found a new strain of   M. extorquens has the ability to degrade aliphatic hydrocarbons compound. Conventional PCR and gene sequencing revealed the presence of the facilitative methylotrophic bacteria in polluted areas in Basra. M. extorquens was dominant and showed a substantial ability to degrade crude oil which makes them an important tool to be employed in bioremediation.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Sun Aug 05 2018
Journal Name
Journal Of Entomology And Zoology Studies
Some biochemical traits in broiler chicken as affected by insulin-like growth factor-1 (IGF-1) gene polymorphisms
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This study was conducted during the period 1/9/2014 – 1/2/2015 and aimed to identify the polymorphisms of IGF-1 gene in broiler chickens and their effects on some biochemical traits. A total of 300 one-day-old broiler chicks (Cobb500, n=150; Hubbard F-15, n=150) were evaluated in this study. Blood samples were individually collected from all birds for DNA extraction. PCR-RFLP method being used for determination the genotypes of IGF-1 gene which then correlated with biochemical traits studied. Cobb500 broilers with TT genotype had significantly (p˂0.05) higher serum triglycerides values than those of TC and CC genotypes. Low density lipoprotein (LDL) were significantly (p˂0.05) higher in Hubbard F-15 broilers with TT genotype than those

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
CA 27-29: A Valuable Marker for Breast Cancer Management in Correlation with CA 15-3
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Publication Date
Sun Jul 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using a 3D Chaotic Dynamic System as a Random Key Generator for Image Steganography
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In today's digital era, the importance of securing information has reached critical levels. Steganography is one of the methods used for this purpose by hiding sensitive data within other files. This study introduces an approach utilizing a chaotic dynamic system as a random key generator, governing both the selection of hiding locations within an image and the amount of data concealed in each location. The security of the steganography approach is considerably improved by using this random procedure. A 3D dynamic system with nine parameters influencing its behavior was carefully chosen. For each parameter, suitable interval values were determined to guarantee the system's chaotic behavior. Analysis of chaotic performance is given using the

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Publication Date
Wed Feb 20 2019
Journal Name
Iraqi Journal Of Physics
Preparation of polyaniline polymer and using it as a Vapor sensor of acids
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 Polyaniline organic Semiconductor polymer was prepared by oxidation polymerization by adding hydrochloric acid concentration of 0.1M and potassium per sulfate concentration of 0.2M to 0.1M of aniline at room temperature, the polymer was deposited at glass substrate, the structural and optical properties were studies through UV-VIS, IR, XRD measurements, films have been operated as a sensor of vapor  H2SO4 and HCl  acids.

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Publication Date
Sat Nov 01 2014
Journal Name
Pigmentary Disorders
Vitiligo: Skin Malignancies and Tumor Suppressive Marker P53
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KE Sharquie, AA Noaimi, AR Bandar, SY Mohsin, Pigmentary Disorders, 2014 - Cited by 5

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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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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Detection of resistance genes (gyrA,qepA,drf1,drf17) for E.coli in Iraqi aquatic environment
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The control of water represents the safe key for fair and optimal use to protect water resources due to human activities, including untreated wastewater, which is considered a carrier of a large number of antibiotic-resistant bacterial species. This study aimed to investigate the prevalence of antibiotic-resistance to E. coli in Tigris River by the presence of resistance genes for aminoglycoside(qepA( ,quinolone (gyrA), and sulfa drugs( dfr1 ,dfr17) due to the frequent use of antibiotics and their release into wastewater of hospitals. Samples were collected from three sites on Tigris River: S1( station wastewater in Adhamiya), S2 (station wastewater in Baghdad Medical city hospital), S3 (station wastew

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Constructing a Sustainable Roller Compacted Concrete Using Waste Demolished Material as Replacement of Cement: A Review
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Roller Compacted Concrete is a type of concrete that is environmentally friendly and more economical than traditional concrete. Roller Compacted Concrete is typically used for heavy-duty and specialist constructions, such as hydraulic structures and pavements, because of its coarse surface. The main difference between RCC and conventional concrete mixtures is that RCC has a more significant proportion of fine aggregates that allow compaction and tight packing. In recent years, it has been estimated that several million tons of waste demolished material (WDM) produced each year are directed to landfills worldwide without being recycled for disposal. This review aimed to study the literature about creating a Roller-Comp

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