Electrodeposition of metal oxides on graphite electrodes can improve their ability to remove organic substances. In this work, multicomponent oxides of Mn, Co, and Ni were electrochemically deposited on both the anode and cathode of graphite electrodes to enhance their performance in removing phenol. Formation of the deposit was achieved within 2 h in current densities of 20, 25, 30, and 35 mA/cm2 for better composite properties. The deposited layer was characterized by testing the surface structure, morphology, composition, and roughness. X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and Atomic force microscopy (AFM) techniques facilitated these tests. The composite electrodes have synthesized

A new simple and sensitive spectrophotometric method for the determination of trace amount of Co(II) in the ethanol absolute solution have been developed. The method is based on the reaction of Co(II) with ethyl cyano(2-methyl carboxylate phenyl azo acetate) (ECA) in acid medium of hydrochloric acid (0.1 M) givining maximum absorbance at ((λmax = 656 nm). Beer's law is obeyed over the concentration range (5-60) (μg / ml) with molar absorptivity of (1.5263 × 103 L mol-1 cm-1) and correlation coefficient (0.9995). The precision (RSD% ˂ 1%). The stoichiometry of complex was confirmed by Job's method which indicated the ratio of metal to reagent is (2:1). The studied effect of interference elements Zn(II), Cu(II), Na(I), K(I), Ca(II) and Mg

Background: In December 2019, an episode of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV2) was reported in Wuhan, China and has spread around the world, increasing the number of contagions. Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are common herpesviruses that can cause persistent latent infections and affect the developing immune system.The study was conducted to explore the prevalence and reactivation of CMV and EBV antibodies in COVID-19 patients group in comparison to healthy group and to investigate the association between the presence of these viruses with each of severity of disease and oral hygiene. Materials and Methods: Eighty Five subjects were participated in this case control study (5

  This paper deals  the prediction of the process of  random spatial data of two properties, the first is called  Primary variables  and the second is called secondary  variables ,   the method  that were used in the  prediction process for this type  of data is technique Co-kriging  , the method is usually used when the number of primary variables  meant to predict for one of its elements is measured in a particular location a few (because of the cost or difficulty of obtaining them) compare with secondary variable which is the number of elements  are available and  highly correlated with primary variables, as was the&nbs

    The behaviour of Np-239 during the Continuous extraction and stripping  was followed . Three Continuous extraction experiments were carried out . In the first experiment the extraction and stripping were carried out by using Tributyl Phosphate / treated odorless kerosene as the organic phase , while the aqueous phase was uranium and neptunium-239 dissolved in 3M HNO3 . In the second experiment irradiation of organic phase up to 30 M rad were carried out , while keeping the aqueous phase as it is in the first experiment. In the third experiment , the acidity of the aqueous phase was 1.5M instead of 3M and keeping the organic phase as it is in experiment 1. The results obtained in tables 1-3 show the possibility of

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between ev

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every