Multiple sclerosis (MS) is a chronic disorder of the central nervous system (CNS) characterized by autoimmune inflammation, demyelination, and axonal damage. The present study aimed to shed a light on the contribution of interlukin-35 and its relation to some sex hormones in the pathogenesis of multiple sclerosis. Sixty six female patients with age range (20-40) years were taken from Baghdad Teaching Hospital through the period from Nov. 2012 to –April 2013 and 20 apparently healthy subject as control group matched age as group G1. The patients were divided into three groups depending on duration of MS diseases G2 from 3 months to 2 years, G3 from 2 years to 4 years, G4 from 4 years to 10 years and more. Investi

Alhagi maurorum (camel thorn) is a grayish, evergreen, deeply rooting plant that has spiny needle -like branches. In our study, the phytochemical contents of the root ethanoloic extract of A. maurorum were determined by using gas chromatography-mass spectroscopy (GC-MS). Thirty two chemical constituents were identified. We revealed the existence of oxalic acid, anti-2 acetoxyacetaldoxime, sulfone, butyl isopropyl, 2,3-pentanedione, 2-butanone, n,n,o triacetylhydroxylamine. di(1,2,5-oxadiazole)[3,4-b;3,4-e]pyrazine, isobutane,3,4-hexanedione,3-hexanone, pentane, 3-pentanone, 3-butene, 2-thiopheneacetic acid, 2-pyrazoline, 4-hepten-3-onemethylphosphonic acid, butane, propanoic acid, methane, azetidine, heptane, butanoic a

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Intrusion-detection systems (IDSs) aim at detecting attacks against computer systems and networks or, in general, against information systems. Most of the diseases in human body are discovered through Deoxyribonucleic Acid (DNA) investigations. In this paper, the DNA sequence is utilized for intrusion detection by proposing an approach to detect attacks in network. The proposed approach is a misuse intrusion detection that consists of three stages. First, a DNA sequence for a network traffic taken from Knowledge Discovery and Data mining (KDD Cup 99) is generated. Then, Teiresias algorithm, which is used to detect sequences in human DNA and assist researchers in decoding the human genome, is used to discover the Shortest Tandem Repeat (S