The corrosion inhibition of low carbon steel in1N HCl solution in the presence of peach juice at temperature (30,40,50,and 60)°C at concentration ( 5, 10, 20, 30, 40and 50 cm3/L)were studied using weight loss and polarization techniques. Results show that the inhibition efficiency was increased with the increase of inhibitor concentration and increased with the increase of temperature up to 50ºC ,above 50ºC (i.e. at 60 ºC) the values of efficiency decreases. Activation parameters of the corrosion process such as activation energies, Ea, activation enthalpies, ΔH, and activation entropies, ΔS, were calculated. The adsorption of inhibitor follows Langmuir isotherm. Maximum inhibition efficiency obtained was a bout 91% at 50ºC in the

    The objective of this work was to determine and compare the physiological changes in some: blood components (packed cell volume and hemoglobin) and plasma biochemical parameters (glucose, total protein, albumin, cholesterol and triglycerides) under 3 day of different types of stress: water deprivation, starvation, overcrowding and handling stress. Twenty five male Wister rats weighted 100-120 gm, were divided randomly into five groups: control, water deprivation, starvation, overcrowding and handling stress. On the third day of stress the animals anesthetized for blood collection; the results of blood component revealed a significant increase in PCV and a significant decrease in Hb of water deprivation group and starva

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

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

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

The purpose of this work is to study the classification and construction of (k,3)-arcs in the projective plane PG(2,7). We found that there are two (5,3)-arcs, four (6,3)-arcs, six (7,3)arcs, six (8,3)-arcs, seven (9,3)-arcs, six (10,3)-arcs and six (11,3)-arcs. All of these arcs are incomplete. The number of distinct (12,3)-arcs are six, two of them are complete. There are four distinct (13,3)-arcs, two of them are complete and one (14,3)-arc which is incomplete. There exists one complete (15,3)-arc.

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

         Melatonin is a potent scavenger of reactive oxygen species or free radicals like superoxide and hydroxyl radicals. The oxidation of hemoglobin to methemoglobin (meth-Hb) by oxidizing compounds has been widely studied. The present work was designed to evaluate the ability of different concentrations of melatonin to inhibit nitrite–induced oxidation of hemoglobin. Blood samples were obtained from apparently healthy individuals from which erythrocyte hemolysate was prepared. Different concentrations of melatonin (10^-9-1.0 mg/ml) were incubated for 10 min with the hemolysate, then to the resultant mixture 1 ml of sodium nitrite (final concentration 0.6 mM) was added, and the