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Detection of anti-Helicobacter pylori in patients with Multiple Sclerosis
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To determine the relationship between Helicobacter pylori infection and Multiple Sclerosis (MS) disorder, 20 patients with MS aged (25-60) years have been investigated from the period of 2016/12/1 to 2017/3/1 and compared to 15 apparently healthy individuals. All study groups were carried out to measure anti H.pylori IgA and H.pylori IgG antibodies by enzyme linked immunosorbent assay (ELISA) technique. There was a significant elevation (p<0.05) in the concentration of anti H.pylori IgG and IgA antibodies (Abs) compared to control group, and there was no significant difference (p>0.05) in the concentration of IgA and IgG (Abs) of H.pylori according to gender, and there was no significant difference (p>0.05) in the concentration of IgA and IgG (Abs) of H.pylori according to gender and age. This result indicates that infection with H.pylori may play a role in the pathogenesis of MS.

Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
The role of relaxation program for reducing anxiety of patients in dental clinic
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The role of relaxation program for reducing anxiety of patients in dental clinic  

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Publication Date
Sat Jan 01 2022
Journal Name
Malaysian Journal Of Medicine And Health Sciences
Severity of Coronavirus Disease 19: A Profile of Inflammatory Markers in Iraqi Patients
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Publication Date
Tue Sep 23 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Salivary IgA in chronic kidney disease patients undergoing hemodialysis in Missan governorate
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Background: Chronic kidney disease is a worldwide health problem, with adverse outcomes of cardiovascular disease and premature death, can be divided into five stages, depending on how severe the damage is to the kidneys, or the level of decrease in kidney function, the final stage of chronic kidney disease is called end-stage renal disease, salivary immunoglobulin A is the main immunoglobulin found in mucous secretions, including tears, saliva, colostrum and secretions from the genitourinary tract gastrointestinal tract, prostate and respiratory epithelium . It is also found in small amounts in blood.This study aimedto measuresalivary flow rate and salivaryimmunoglobulin Alevels in chronic kidney disease patients on hemodialysis treatment

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
DC-SIGN Receptor Level in Rheumatoid Arthritis Patients in Baghdad; Serological study
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Rheumatoid arthritis (RA), is an autoimmune, and inflammatory disease that is closely related to the destruction of cartilage and bone. DC-SIGN are important types of C-type lectin receptors (CLRs), expressed on dendritic cells and macrophages, and have a central role in regulating innate and adaptive immunity, function as pattern recognition receptors, and as cell adhesion molecules. Recent evidence has demonstrated that DC-SIGN is involved in the pathophysiological of chronic inflammation, so DC-SIGN has been linked to several autoimmune and may play an essential indicator in the pathogenesis and progression of RA. Therefore, the purpose of this study is to determine the serum level of DC-SIGN in RA patients, as well as the level of DC

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
COMPARATIVE STUDY FOR EDGE DETECTION OF NOISY IMAGE USING SOBEL AND LAPLACE OPERATORS
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Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Sat Mar 21 2020
Journal Name
Journal Of Engineering
Development of Iraqi license plate recognition system based on Canny edge detection method
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny Edge detection algo

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Publication Date
Thu Jul 01 2004
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
DETECTION OF SUBSURFACE CAVITIES BY THE ELECTROMAGNETIC METHOD (Case Study at Haditha Area)
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Two EM techniques, terrain conductivity and VLF-Radiohm resistivity (using two
different instruments of Geonics EM 34-3 and EMI6R respectively) have been applied to
evaluate their ability in delineation and measuring the depth of shallow subsurface cavities
near Haditha city.
Thirty one survey traverses were achieved to distinguish the subsurface cavities in the
investigated area. Both EM techniques are found to be successfiul tools in study area.

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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