Rate of zinc consumption during the cathodic protection of copper pipeline which carries saline water was measured by weight loss technique in the absence and presence of bacteria. Variables studied were solution flow rate, temperature, time and NaCl concentration. It was found that within the present range of variables; the rate of zinc consumption increases with the increase of all operating conditions. The presence of bacteria increases the zinc consumption. Fourth order multi-term model and one-term model were suggested to represent the consumption data. Nonlinear regression analysis was used to estimate the coefficients of these models, while statistical analysis was used to determine the effect of each coefficient. Both models were re

A simple technique is proposed in this paper for estimating the coefficient of permeability of an unsaturated soil based on physical properties of soils that include grain size analysis, degree of saturation or water content, and porosity of the soil. The proposed method requires the soil-water characteristic curve for the prediction of the coefficient of permeability as most of the conventional methods. A procedure is proposed to define the hydraulic conductivity function from the soil water characteristic curve which is measured by the filter paper method. Fitting methods are applied through the program (SoilVision), after indentifying the basic properties of the soil such as Attereberg limits, specific gravity, void ratio, porosity, d

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

The effect of different doses (75,100,150 ppm) and periods of

treatment (3,6,9 days) on the spermatognic cells in white mice was studied. It was found that there was a significant decrease (P<0.05) in the percentage of spermatogonia specially in concentration 1 00 and

150 ppm lasted six and nine days and of primary spermatocytes at period of nine days. A significant decrease (P<0.05) was noticed in the percentages of secondary spermatoytes and spermatids, while the percentage of sperms illustrated a significant increase for all concentrations and treatment periods.

 The adsorption behavior of methyl orange from aqueous solution on Iraqi bentonite was investigated. The effects of various parameters such as initial concentration of methyl orange, amount of adsorbent, ionic strength and temperature on the adsorption capacity has been studied. The percentage removal of methyl orange increased with the decrease of initial concentration of methyl orange and it increased with the increase of dose of adsorbent. The adsorbed amount of methyl orange decrease with increasing ionic strength and an increase in temperature. The equilibrium adsorption isotherms have been analysed by the linear, Langmuir and Temkin models. The Langmuir isotherms have the highest correlation coefficients. Thermodynamic paramet

Pharmaceuticals are widely distributed in different applications and also released into the environment. Adsorption of Ciprofloxacin HCl (CIPH) on Porcelinaite was studied at ambient conditions. The adsorption isotherms can be well described using the Freundlich and Temkin equations. The pH of the solution influences significantly the adsorption capacity of Porcelinaite, the adsorption of CIPH increased from the initial pH 1.3 and then decreased over the pH rang of 3.8-9. The adsorption is sensitive to the change in ionic Strength, which indicate that electrostatic attraction is a significant mechanism for sorption process. The enthalpy change (ΔH) for the adsorption of CIPH onto Porcelinaite signifies an endothermic adsorption. The ΔG va