Multiple Sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS). Up to 10 % of MS patients have onset in paediatric age group. Although the clinical profile of MS appears similar to that seen in adults, several features may differ and specific issues arise in children. Here, we reported a 12-year old girl who presented with 3-year history of episodes of seizures and facial nerve palsy and finally fatigue and cognitive impairment were noted and interfered with her academic performance. Because of the presumed atypical clinical presentations, the diagnosis was missed then dismissed despite neuroimaging features and CSF immunological findings that were highly suggestive of MS. Later, evolution of the

The use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models                  

          In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear

Cytokines are signaling molecules between inflammatory cells that play a significant role in the pathogenesis of a disease. Among these cytokines are interleukins (ILs) 17A and 33, and accordingly, the current case-control study sought to investigate the role of each of the two cytokines in the risk of developing multiple sclerosis (MS). Sixty-eight relapsing-remitting MS (RRMS) Iraqi patients and twenty healthy individuals (control group) were enrolled. Enzyme linked immunosorbent assay (ELISA) kits were used to determine serum levels of IL-17A and IL-33. Results revealed that IL-17A and IL-33 levels were significantly higher in MS patients than in controls (14.1 ± 4.5 vs. 7.5 ± 3.8 pg/mL; p < 0.001 and 65.3 ± 16

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

           The plants of genus Heliotropium L. (Boraginaceae) are well-known for containing the toxic metabolites called pyrrolizidine alkaloids (PAs) in addition to the other secondary metabolites. Its spread in the Mediterranean area northwards to central and southern Europe, Asia, South Russia, Caucasia, Afghanistan, Iran, Pakistan, and India, Saudi Arabia, Turkey, and over lower Iraq, Western desert. The present study includes the preparation of various extracts from aerial parts of the Iraqi plant. Fractionation, screening the active constituent, and identification by chromatographic techniques were carried out.Heliotropium  europaeum

Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

One hundred thirty - five clinical specimens of urine, blood, teeth root canal and burns were obtained from patients in hospitals of Baghdad. The specimens were cultured on Pfizer Selective Enterococcus agar to purify Enterococci isolates. 20 E. faecalis isolates were identified biochemically by growing in 10Cº, 45Cº, 6.5% NaCl, at pH 9.6 and confirmed by VITEK. Determination of Vancomycin-Resistant E. faecalis isolates were done by the minimum inhibitory concentrations [MICs] using agar dilution method. Seventeen E. faecalis isolates were determined as Vancomycin-Resistant and Intermediate Resistant.