Anodic electrodeposition was used to synthesize a composite electrode of nanostructured manganese dioxide/carbon fiber (CF) galvanostatically. Different characterization results of the nanostructured MnO2 were obtained by varying the H2SO4 concentration and the current density. Field emission scanning electron microscopy, X‐ray diffraction, and atomic force microscopy were utilized to characterize the prepared composite electrodes. The best conditions were: 0.3 mA cm−2 current density and 0.64 M H2SO4 concentration. The electrosorption performance of the MnO2/CF electrode prepared under the best conditions was tested by way of its chromium(VI) ion adsorption from a simulated solution. The applied voltage, pH, and ionic strength affect the efficiency of Cr(VI) ion removal. The highest chromium removal efficiency was 99.98 %, achieved at pH 2, a cell voltage of 4.6 V, and a NaCl concentration of 1 g L−1.
For the design of a deep foundation, piles are presumed to transfer the axial and lateral loads into the ground. However, the effects of the combined loads are generally ignored in engineering practice since there are uncertainties to the precise definition of soil–pile interactions. Hence, for technical discussions of the soil–pile interactions due to dynamic loads, a three-dimensional finite element model was developed to evaluate the soil pile performance based on the 1 g shaking table test. The static loads consisted of 50% of the allowable vertical pile capacity and 50% of the allowable lateral pile capacity. The dynamic loads were taken from the recorded data of the Kobe e
Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq
... Show MoreThe recurrent somatic variations in
The aim of the study was to detect the frequency of R132 mutations in the
Type 2 diabetes mellitus (T2DM) is the most frequent endocrinal disease commonly associated with thyroid disorders .The study is conducted at the Specialized Center for Endocrinology and Diabetes in Baghdad ,during December 2014 up to October 2015.This study was done to investigate the prevalence of anti- thyroid peroxidase (Anti-TPO) antibody in patients suffered from type 2 diabetes with thyroid disorders .The study groups included a total number of 80 subjects consisting of 60 type 2 diabetic patients divided into 20 hyperthyroidism subjects (group 1) ,20 hypothyroidism subjects (group 2), 20 euthyroidism subjects (group 3) and 20 healthy controls (group 4) . The fasting blood samples were analyzed for (T3,T4,TSH) by using Vitek Immuno d
... Show MoreIn the present study, cytogenetic and molecular techniques were conducted to detect the chromosomal aneuploidy and the involvement of N and H genes in squamous larynx carcinoma cell line Hep-2.Our results showed that numerical and structural abnormalities were involved in larynx cancer Hep-2.The total number of chromosomes ranging from tripolyploidy in passage187to more than that in passage207.The more frequent chromosomes involved in numerical aberrations were chromosomes1,7,16,17 and 18. Structural chromosomal aberrations were also detected.Deletion of short arm was detected in chromosome 1(del 1p) and the long arm of chromosome 1(del 1q)and 6(del 6q).Gaining on short arms were also recorded in chromosomes 3(3p+) and 12(12p+).At the mole
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
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