New series of 4,4'-((2-(Aryl)-1H-benzo[d]imidazole-1,3(2H)-diyl)bis(methylene))Diphenol(3a-g) was successfully synthesized from cyclization of the reduction product of bis Schiff bases (2) with aryl aldehydes bearing phenolic hydroxyl in the presence of acetic acid. The structure of these compounds was identified from FT-IR, 1H NMR, 13C NMR and EIMs. The Antioxidant capability was screened by DPPH and FRAP assays. Both assays showed antioxidant capability more than BHT as well. Compounds 3b and 3c showed antioxidant capacity slightly less than ascorbic acid. The docking study for theses compound was carried out as III DNA polymerase inhibitor. The results of docking demonstrated that the increase in hinderances around phenolic hydr

A theoretical and protection study was conducted of the corrosion behavior of carbon steel surface with different concentrations of the derivative (Quinolin-2-one), namly (1-Amino-4,7-dimethyl-6-nitro-1H-quinolin-2-one (ADNQ2O)). Theoretically, Density Functional Theory (DFT) of B3LYP/ 6-311++G (2d, 2p) level was used to calculate the optimized geometry, physical properties and chemical inhibition parameters, with the local reactivity to predict both the reactive centers and to locate the possible sites of nucleophilic and electrophilic attacks, in vacuum, and in two solvents (DMSO and H₂O), all at the equilibrium geometry. Experimentally, the inhibition efficiencies (%IE) in the saline solution (of 3.5%) NaCl were st

Recording two species of larval cestodes Callitetrarhynchus gracilis and Callitetrarhynchus sp. (Cestoda: Trypanorhyncha) parasitic in body cavity of two carangid fishes (Carangoides malabaricus and Megalaspis cordyla) from north west Arab Gulf, Iraq, is described. The species Callitetrarhynchus sp. was recorded for the first time in Iraq in carangid fishes. Also, two fish species (C. malabaricus and M. cordyla) are considered as new hosts for C. gracilis and Callitetrarhynchus sp. in the Arab Gulf. The cestodes were sent to Prof. Dr. Harry W. Palm, Department of Fisheries Biology, Institute Zoo Morphology, Germany for confirmation of the identification.

Background: With the increasing demands for adult orthodontics, a growing need arises to bond attachments to porcelain surfaces. Optimal adhesion to porcelain surface should allow orthodontic treatment without bond failure but not jeopardize porcelain integrity after debonding.The present study was carried out to compare the shear bond strength of metal bracket bonded to porcelain surface prepared by two mechanical treatments and by using different etching systems (Hydrofluoric acid 9% and acidulated phosphate fluoride 1.23%). Materials and Methods: The samples were comprised of 60 models (28mm *15mm*28mm) of metal fused to porcelain (feldspathic porcelain). They were divided as the following: group I (control): the porcelain surface left u

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu