This study is concerned with the effect of Deep Cryogenic Treatment (DCT) at liquid nitrogen temperature (-196 o C) on the mechanical properties and performance of low carbon steel (A858). The tests specimens were divided in to two groups, the first group was subjected to the conventional heat treatment of normalizing, and the second group was also normalized then subjected to (DCT). The results have shown that after (DCT), the Hardness, Tensile properties and the impact energy absorbed were all slightly increased. However the fatigue test showed some positive improvement in fatigue limit by 20(N/mm2 ), and the volume wear rates at different loads were significantly decreased after (DCT). The changes in microstructure due to (DCT) were c

The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of

Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

In this paper flotation method experiments were performed to investigate the removal of lead and zinc. Various parameters such as pH, air flow rate, collector concentrations, collector type and initial metal concentrations were tested in a bubble column of 6 cm inside diameter. High recoveries of the two metals have been obtained by applying the foam flotation process, and at relatively short time 45 minutes . The results show that the best removal of lead about 95% was achieved at pH value of 8 and the best removal of zinc about 93% was achieved
at pH value of 10 by using 100 mg/l of Sodium dodecylsulfate (SDS) as a collector and 1% ethanol as a frother. The results show that the removal efficiency increased with increasing initial m

A simple, cheap, fast, accurate, Safety and sensitive spectrophotometric method for the determination of sulfamethaxazole (SFMx), in pure form and pharmaceutical dosage forms. has been described The Method is based on the diazotization of the drug by sodium nitrite in acidic medium at 5Cº followed by coupling with salbutamol sulphate (SBS) drug to form orange color the product was stabilized and measured at 452 nm Beer’s law is obeyed in the concentration range of 2.5-87.5 ?g ml-1 with molar absorptivity of 2.5x104 L mole-1 cm-1. All variables including the reagent concentration, reaction time, color stability period, and sulfamethaxazole /salbutamol ratio were studied in order to optimize the reaction conditions. No interferences were

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

      Manganese-zinc ferrite Mn_xZn_1-xFe₂O₄ (MnZnF) powder was prepared using the sol-gel method. The morphological, structural, and magnetic properties of MnZnF powder were studied using X-ray diffraction (XRD), atomic force microscopy (AFM), energy dispersive X-ray (EDX), field emission-scanning electron microscopes (FE-SEM), and vibrating sample magnetometers (VSM). The XRD results showed that the MnxZn1-xFe2O4 that was formed had a trigonal crystalline structure. AFM results showed that the average diameter of Manganese-Zinc Ferrite is 55.35 nm, indicating that the sample has a nanostructure dimension. The EDX spectrum revealed the presence of transition metals (Mn, Fe, Zn, and O) in Mang