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

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.

     Epilepsy is one of the most common diseases of the nervous system around the world, affecting all age groups and causing seizures leading to loss of control for a period of time. This study presents a seizure detection algorithm that uses Discrete Cosine Transformation (DCT) type II to transform the signal into frequency-domain and extracts energy features from 16 sub-bands. Also, an automatic channel selection method is proposed to select the best subset among 23 channels based on the maximum variance. Data are segmented into frames of  one Second length without overlapping between successive frames. K-Nearest Neighbour (KNN) model is used to detect those frames either to ictal (seizure) or interictal (non-

The energy density state are the powerful factor for evaluate the validity of a material in any application. This research focused on examining the electrical properties of the Se6Te4- xSbx glass semiconductor with x=1, 2 and 3, using the thermal evaporation technique. D.C electrical conductivity was used by determine the current, voltage and temperatures, where the electrical conductivity was studied as a function of temperature and the mechanical electrical conduction were determined in the different conduction regions (the extended and localized area and at the Fermi level). In addition, the density of the energy states in these regions is calculated using the mathematical equations. The constants of energy density states are det