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 we

To assess the effect of Nigella sativa oil as a topical preparation for treatment of oro- genital ulceration of Behcet's disease. This is a double blinded therapeutic trial in which 40 patients with Behcet's disease manifested as recurrent episodes of oral and genital ulceration were enrolled into 2 groups; Nigella sativa oil was applied as 10% in glycerin topically 3 times / daily to the first 20 patients. The other 20 were given glycerin only. Assessment was done 4 days then 8 days after treatment.Results were recorded as they appeared in clinical examination and those records were arranged in tables for both groups concerning oral and genital ulceration cases.Nigella sativa oil is a new topical agent for promotion of healing of o

The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Ever

Researchers have recently increased their focus on the link between autoimmune diseases and infections. Most of the recent research indicates that silent human cytomegalovirus (HCMV), may have diverse roles in the initiation, development, and exacerbation of autoimmune diseases, such as coeliac Disease (CD) and inflammatory bowel disease. The aim of this study is to evaluate the role of HCMV infection in Iraqi patients with CD. Serum samples were obtained from 60 patients with CD, and from 60 healthy subjects. Enzyme-linked immunosorbent assay was used to determine the Anti-Transglutaminase IgG/IgA, Anti-gliadin IgA/ IgG, as well as the HCMV IgM/ IgG levels in the serum samples. Significantly higher percentage of positivity for seru

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

The Frequency-hopping Spread Spectrum (FHSS) systems and techniques are using in military and civilianradar recently and in the communication system for securing the information on wireless communications link channels, for example in the Wi-Fi 8.02.X IEEE using multiple number bandwidth and frequencies in the wireless channel in order to hopping on them for increasing the security level during the broadcast, but nowadays FHSS problem, which is, any Smart Software Defined Radio (S-SDR) can easily detect a wireless signal at the transmitter and the receiver for the hopping sequence in both of these, then duplicate this sequence in order to hack the signal on both transmitter and receiver messages using the order of the se

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte