In this study, Zinc oxide nanostructures were synthesized via a hydrothermal method by using zinc nitrate hexahydrate and sodium hydroxide as a precursor. Three different annealing temperatures were used to study their effect on ZnO NSs properties. The synthesized nanostructure was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Atomic force microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). Their optical properties were studied by using UV -visible spectroscopy. The XRD analysis confirms that all ZnO nanostructures have the hexagonal wurtzite structure with average crystallite size within the range of (30.59 - 34.52) nm. The crystallite size increased due to the incensement of annealing temperature. FESEM analysis indicates that ZnO has hexagonal shape of cylindrical pores, plate-like nanocrystals and Nanorods. AFM analysis shows that the average surface roughness of ZnO Nanostructures increases from 3.96 to 19.1 nm with the increase of annealing temperature. The FTIR peaks indicate successful preparation of ZnO Nanostructures. The FTIR method was used to analyses the chemical bonds which conformed the present of the Zn-O group in the region between (400-500) cm-1. The UV-visible showed a red shift in the absorption spectra related to the shift in the energy gap related to increase in the particle size. the band gap energy has been calculated from the optical absorption spectra. The annealing process has been fond more effective on the value of energy gap. As the annealing temperature increases, the value of energy gap, increases as well; from (3.12to 3.22) eV. The prepared Nanostructure is used for antibacterial property. It shows strong antibacterial activity against S. aureus and P.aeuruginosa bacteria by the agar disc diffusion method. The white precipitate of ZnO NSs has superior antibacterial activity on gram-positive (S. aureus) than the gram-negative (P.aeuruginosa) bacteria.
Objective(s): The present study aims at studying the relationship between immunoglobulin IgG, IgA,
IgM , as well as to C-3 and C-4 in brain tumours patients immunity (meningioms and gliomas).
Methodology: Forty sera of brain tumour patients were included 20 glioma and 20 meningioma was
tested to determine the levels of IgM, IgG IgA, C-3 and C-4 by using single radial immune-diffusion
technique and compared with 20 apparently healthy blood donors.
Results: The study revealed a significant decreasing in IgG levels in glioma as compare to meningioma
and control. The concentration of two other serum immunoglobulins and complement in both
meningioma and glioma show no significant differences with those in control group.
The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi
... Show MoreIn this study, a different design of passive air Solar Chimney(SC)was tested by installing it in the south wall of insulated test room in Baghdad city. The SC was designed from vertical and inclined parts connected serially together, the vertical SC (first part) has a single pass and Thermal Energy Storage Box Collector (TESB (refined paraffin wax as Phase Change Material(PCM)-Copper Foam Matrix(CFM))), while the inclined SC was designed in single pass, double passes and double pass with TESB (semi refined paraffin wax with copper foam matrix) with selective working angle ((30o, 45o and 60o). A computational model was employed and solved by Finite Volume Method (FVM) to simulate the air i
... Show MoreThe support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample
... Show MoreThe alterations in glyoxylate reductase and hydroxy-pyruvate reductase concentrations in the sera and the genetic alterations associated with calcium oxalate kidney stones in Iraqi patients were not studied previously so this study aimed to focus on these points. This study included 80 subjects; they were 50 patients with calcium oxalate stones compared to 30 apparently healthy controls. Biochemical investigations for kidney functions (creatinine, urea, and uric acid), were performed on the sera of both groups. Also, complete blood count, random blood sugar, and blood group tests. Furthermore, urine had been collected for General Urine Examination to visualize oxalate crystals in the urine of the patient. Also, the GRHPR
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