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 I

Reactive arthritis (ReA) is an incendiary joint inflammation that occurs few days to weeks after a gastrointestinal or genitourinary infection. The etiology of the disease is not well-known. Therefore, the present study included 80 females and 25 males, divided into 51 patients with reactive arthritis and 54 healthy individuals as control group.  The study involved the detection of serum levels of anti-rheumatoid factor and anti-cyclic citrullinated peptide antibodies (anti-CCP) as well as those of CRP and C3 in all subjects. In addition, EBV levels were detected by Real Time-PCR technique. The results showed significantly increased levels (P < 0.05) of CRP, C3 and anti-CCP Ab in ReA patients’ group compared to th

Psoriasis is a common, chronic, immune-mediated skin disease with systemic pro-inflammatory activation.  This study was designed to estimate the level of two cytokines, Interleukin-36 (IL-36) and Interleukin-10 (IL-10), in psoriasis female patients. The study was accomplished on 50 Iraqi patients with psoriasis who were referred to the consulting clinic at Al-Yarmouk Teaching Hospital during the period from November 2018 to March 2019. These patients were diagnosed under the supervision of dermatologists. For the purpose of comparison, the study included 30 healthy women as a healthy control group. The serum levels of cytokines  were measured using the enzyme-linked immunosorbent technique (ELISA).The results of this study show

Detection of pathogenic bacteria, such as Listeria  monocytogenes, in food is crucial for safeguarding public health in Iraq.  Forty five samples of frozen meat (15 samples of each of minced red meat, chicken, and fish) were collected from different markets in Baghdad city. Molecular (RT-PCR) and culturing (conventional microbiological examination) methods were used to determine the level of contamination of L. monocytogenes in these types of meat.

For the culturing method, TSYEB broth was used as an enrichment medium, whereas BALCAM medium (HiMedia) with the listeria selective supplement FD061 was used as a selective medium, for the isolation and identification of this bacterium. The isolates were con

Objective: Evaluation of women's knowledge about risk factors and early detection of breast cancer at
Ibn Rushd college of education in Baghdad University.
Methodology: The study sample included (184) women in the Ibn Rushd College / University of
Baghdad, whose age ranged between (17-58) years. Data were collected through a structured
questionnaire prepared by the National Cancer Research Center which were answered during a scientific
symposium about breast cancer. The score was calculated by correcting the results of the answer, giving
one score for each correct answer and then estimating the level of knowledge and inputting all data in a
statistical program.
Results: The results showed limited level of women's

An Auto Crop method is used for detection and extraction signature, logo and stamp from the document image. This method improves the performance of security system based on signature, logo and stamp images as well as it is extracted images from the original document image and keeping the content information of cropped images. An Auto Crop method reduces the time cost associated with document contents recognition. This method consists of preprocessing, feature extraction and classification. The HSL color space is used to extract color features from cropped image. The k-Nearest Neighbors (KNN) classifier is used for classification. 

The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

     With the growth of the use mobile phones, people have become increasingly interested in using Short Message Services (SMS) as the most suitable communications service. The popularity of SMS has also given rise to SMS spam, which refers to any unwanted message sent to a mobile phone as a text. Spam may cause many problems, such as traffic bottlenecks or stealing important users' information. This paper,  presents a new model that extracts seven features from each message before applying a Multiple Linear Regression (MLR) to assign a weight to each of the extracted features. The message features are fed into the Extreme Learning Machine (ELM) to determine whether they are spam or ham. To evaluate the proposed model, the UCI bench

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect