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. Investigations included estimation of serum levels of Interlukin-35 (IL-35), Testosterone (TEST), Progesterone (PROG), follicle stimulating hormone (FSH), luteinizing hormone (LH) and Prolactin (PRL). Serum IL-35 levels were significantly higher in MS patients as compared with control subject, also significant increase appeared in TEST levels in G3 compared to control in for MS female patients. No significant differences were found between PROG and FSH with duration also non-significant difference levels G2 compared to G1 in LH, on the other hand a significant increase levels for LH in G3 and G4 compared to control subject , a significant difference in prolactin levels for G2 and G4, but non-significant difference for G3. From this study a conclusion was drawn, that evaluation of concentration of a new super family cytokines IL-35 can be considered as a clinical biomarker in multiple sclerosis female patients. This finding may indicate that MS might influence cytokine e.g. interleukin-35 production in these patients.
<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver & kroeber, overlap, and pearson correlation
... Show MoreThe ability of beans (Phaseolus vulgaris L.) to uptake three pharmaceuticals (diclofenac, mefenamic acid and metronidazole) from two types of soil (clay and sandy soil) was investigated in this study to explore the human exposure to these pharmaceuticals via the consumption of beans. A pot experiment was conducted with beans plants which were grown in two types of soil for six weeks under controlled conditions. During the experiment period, the soil pore water was collected weekly and the concentrations of the test compounds in soil pore water as well as in plant organs (roots, stems and leaves) were weekly determined.
The results showed that the studied pharmaceuticals were detected in all plant tissues; their concentration
NH3 gas sensor was fabricated based on deposited of Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) suspension on filter paper substrates using suspension filtration method. The structural, morphological and optical properties of the MWCNTs film were characterized by XRD, AFM and FTIR techniques. XRD measurement confirmed that the structure of MWCNTs is not affected by the preparation method. The AFM images reflected highly ordered network in the form of a mat. The functional groups and types of bonding have appeared in the FTIR spectra. The fingerprint (C-C stretch) of MWCNTs appears in 1365 cm-1, and the backbone of CNTs observed at 1645 cm-1. A homemade sensi
... Show MoreErratum for Organic acid concentration thresholds for ageing of carbonate minerals: Implications for CO2 trapping/storage.
In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we
... Show MoreA new, simple, sensitive and fast developed method was used for the determination of methyldopa in pure and pharmaceutical formulations by using continuous flow injection analysis. This method is based on formation a burgundy color complex between methyldopa andammonium ceric (IV) nitrate in aqueous medium using long distance chasing photometer NAG-ADF-300-2. The linear range for calibration graph was 0.05-8.3 mmol/L for cell A and 0.1-8.5 mmol/L for cell B, and LOD 952.8000 ng /200 µL for cell A and 3.3348 µg /200 µL for cell B respectively with correlation coefficient (r) 0.9994 for cell A and 0.9991 for cell B, RSD % was lower than 1 % for n=8. The results were compared with classical method UV-Spectrophotometric at λ max=280 n
... Show MoreActivity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif
... Show MoreIn this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better