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Serum HCV-RNA levels in patients with chronic hepatitis C: correlation with histological features.
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Publication Date
Mon Mar 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Depression status in relation to dental caries and salivary C-Reactive Protein among 17 years old secondary school female in Baghdad City/Iraq.
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Background: Depression is a state of low mood and aversion to activity, it can affect a person's thoughts, behavior and sense of well-being. It can affect oral health and lead to an increased risk of dental caries. Dental caries is the most common oral infectious diseases that stresses the immune system and causes changes in cellular and molecular components of peripheral blood and C-Reactive Protein is one of these components, considered a key biomarker of inflammation. This study was conducted to assess the effect of depression status on dental caries among 17 years old secondary school female students in relation to salivary C-Reactive Protein. Materials and Methods: A cross sectional study was carried and the whole sample composed of

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Scopus (11)
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Publication Date
Thu Jun 01 2023
Journal Name
Iraqi Journal Of Physics
Assessment of the Natural Radioactivity Levels of Soil Samples in IT1 Oil Reservoirs in Kirkuk City, Northeast Iraq
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In this study, gamma-ray spectrometry with an HPGe detector was used to measure the specific activity concentrations of 226Ra, 232Th, and 40K in soil samples collected from IT1 oil reservoirs in Kirkuk city, northeast Iraq. The “spectral line Gp” gamma analysis software package was used to analyze the spectral data. 226Ra specific activity varies from 9  0.34 Bq.kg-1 to 17  0.47 Bq.kg-1. 232Th specific activity varies from 6.2  0.08 Bq.kg-1 to 18  0.2 Bq.kg-1. 40K specific activity varies from 25  0.19 Bq.kg-1 to 118  0.41 Bq.kg-1. The radiological hazard due to the radiation emitted from natural r

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Publication Date
Fri Oct 01 2021
Journal Name
International Journal Of Mechanical Engineering And Robotics Research
Proportional-Derivative PD Vibration Control with Adaptive Approximation Compensator for a Nonlinear Smart Thin Beam Interacting with Fluid
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This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads

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Publication Date
Tue Mar 31 2020
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Experimental and Theoretical Analysis of a Mono PV Cell with Five Parameters, Simulation Model Compatible with Iraqi Climate
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The present work included study of the effects of weather conditions such as solar radiation and  ambient temperature on solar panels (monocrystalline 30 Watts) via proposed mathematical model, MATLAB_Simulation was used by scripts file to create a special code to solve the mathematical model , The latter is single –diode model (Five parameter) ,Where the effect of ambient temperature and solar radiation on the output of the solar panel was studied, the Newton Raphson method was used to find the  output current of the solar panel and plot P-V ,I-V curves, the performance of the PV was determined at Standard Test Condition (STC) (1000W/m2)and a comparison between theoretical and experimental results were done .The best efficiency

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Branch and Bound Algorithm with Penalty Function Method for solving Non-linear Bi-level programming with application
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The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

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Publication Date
Sun Oct 01 2023
Journal Name
Rawal Medical Journal
Fixation of unstable intertrochanteric fractures with proximal femoral nailing: Supine position with traction table versus lateral decubitus position
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Objective: To compare two positioning approaches in the surgical treatment of unstable intertrochanteric femoral fractures fixed by proximal femoral nailing, the supine versus lateral decubitus position Methodology: This randomized prospective comparative study on 26 patients with unstable intertrochanteric fractures was carried out from January 2020 and June 2022. We randomly divided patients into two groups: group A (13 patients) were operated using the traction table in the supine position for implant insertion, and group B (13 patients) were operated using the lateral decubitus position. We compared both groups regarding the setup time, operative time, tip-to-apex distance, collodiaphyseal angle, time for fluoroscopic time expo

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Publication Date
Wed Apr 15 2026
Journal Name
Experimental And Theoretical Nanotechnology
Antibacterial and antioxidant activity of gamma star-like MnO2 nanostructure with and without coating with iron oxide nanoparticles
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Bacterial resistance caused by antibiotic misuse has garnered substantial attention, prompting numerous researchers to develop materials that can combat these resistant pathogens. The hydrothermal method is employed to produce γ-MnO2 nanostars and to coat them with Fe2O3 nanoparticles. The materials are characterized using XRD, FE-SEM, EDX, and UV-vis spectrophotometry, as well as antioxidant and antibacterial activities. The nano γ-MnO2 star shapes are coated with tiny spherical Fe2O3 nanoparticles with diameters of 35-47 nm. The peaks located at the crystal planes (120), (031), (131), (230), (300), (160), (421), and (003) are represented by the values of 2θ = 22.36º, 34.36º, 37.22º, 38.78º, 42.56º, 56.14º, 65.48º and 68.

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
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Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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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 Jan 01 2026
Journal Name
Ieee Transactions On Human-machine Systems
Deep Learning-Driven Decision Fusion: Spatio-Spectrogram Features for Inner Speech Recognition From Electroencephalogram Signals
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