Background: Helicobacter pylori are important gastrointestinal pathogen associated with gastritis, peptic ulcers, and an increased risk of gastric carcinoma. There are several popular methods for detection of H. pylori (invasive and non-invasive methods) each having its own advantages, disadvantages, and limitations, and by using PCR technique the ability to detect H. pylori in saliva samples offers a potential for an alternative test for detection of this microorganism. Materials and methods: The study sample consists of fifty participants of both genders, who undergo Oesophageo-gastrodudenoscopy at the Gastroenterology Department of Al-Kindy Teaching Hospital Baghdad/ Iraq, during five months period from January 2014 to May 2014. They were grouped into 32 participants with PUD (case group) and 18 healthy participants (control group). A full-mouth examination was performed for every patient; saliva and gastric samples from both groups were obtained. Helicobacter pylori were detected in gastric biopsies by histological examination by using H & E stain, and Polymerase Chain Reaction (PCR) was carried out on the oral samples. Results: Helicobacter pylori DNAwas determined by PCR in oral samples in 88% patients and in gastric biopsies by histology in 86% patients, and in both samples in 84% patients.It was highly significant to find simultaneous presence for those have H. pylori in stomach also have such microorganism in the mouth P < 0.05 and there was an excellent correlation between detecting H. pylori simultaneously in both stomach and mouth. If we screen for stomach H. pylori through detecting this microorganism in the mouth; saliva samples is highly sensitive (98%) but not very specific. Conclusion: Helicobacter pylori saliva test has high sensitivity, specificity, and accuracy for the diagnosis of H. pylori infection in Iraqi population. The test can be clinically applied as a routine diagnostic tool for H. pylori infection this could permit not only a target for therapeutic procedures but also a monitoring tool for the efficacy of therapy. It seems to overcome some limitations of the conventional invasive techniques.
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In this article, a continuous terminal sliding mode control algorithm is proposed for servo motor systems. A novel full-order terminal sliding mode surface is proposed based on the bilimit homogeneous property, such that the sliding motion is finite-time stable independent of the system’s initial condition. A new continuous terminal sliding mode control algorithm is proposed to guarantee that the system states reach the sliding surface in finitetime. Not only the robustness is guaranteed by the proposed controller but also the continuity makes the control algorithm more suitable for the servo mechanical systems. Finally, a numerical example is presented to depict the advantages of the proposed control algorithm. An application in the rota
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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Cystic fibrosis (CF) is an autosomal recessive multisystem disease that results from mutation(s) of the cystic fibrosis transmembrane conductance regulator (
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In this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A comparison between numerical and experimental data, illustrated
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