ZSM-5 zeolite was synthesis under hydrothermal conditions at 175^oC. The synthesis parameters have been investigated to find optimum synthesis method. Firstly, the crystallization time has been investigated to find the optimum crystallization time. Also, the ageing time was studied. The morphology, structure, and composition of the synthesized ZSM-5 zeolite were characterized using scanning electron microscopy (SEM), pH meter, viscometer, and X-ray powder diffraction (XRD). The bulk Si/Al ratio of ZSM-5 zeolite was in the range of 9.5—11.7. The synthesized ZSM-5 zeolite with appropriate ageing time could adjust crystal size and degree of the crystallinity. The crystal size of ZSM-5 zeolite obtained at an agei

This study was conducted to determine the effects of concentration of hydrochloric acids, temperature, and time on the hydrolysis of soya proteins (defatted soya flour) by determining the value of total protein nitrogen  concentration, and amino nitrogen concentration of protein, peptides, and amino acids, and then calculated the hydrolysis rate of proteins.

        The variables of the conditions of hydrolysis process was achieved in this study with the following range value of tests parameter:

• Concentration of HCl solution ranged between 1-7 N,
• Hydrolysis temperature ranged between 35-95 °C, and
• The time of hydroly

This work has been done with using of epoxy resin mixed with Granite powder were weighted by percent volume (5,10,15, and 20)%and then mixed with epoxy polymer to compose polymer composite. Hand lay-up technique is used in fabrication of the composite samples. Hardness test was carried out for the proper samples in both normal condition and after immersion in HCL (1 M and 2 M) solutions for periods ranging up to 10 weeks. After comparing the results between the polymer and their composite, the hardness increased with increasing Granite weight percent, it was found that Hardness were greater for the composites before immersion compared with their values after immersion.

Background: Pain is one of the most reported side effects of orthodontic treatment despite the advanced technology in orthodontics. Many analgesics have been introduced to control orthodontic pain including acetaminophen and selective and nonselective nonsteroidal anti-inflammatory drugs. The great concern about these drugs is their adverse effect on rate of teeth movement. Aims: The purpose of this study was to evaluate and compare the effect of acetaminophen, ibuprofen and etoricoxib on pain perception and their influence on the rate of teeth movement during leveling and alignment stage. Methods: Forty patients were evenly and randomly distributed in a blinded way to one of four groups: placebo (starch capsules), acetaminophen 500mg th

The current research aims to identify the level of compulsive buying behavior and Histrionic Personality among a sample of primary school teachers for the academic year (2021-2022) and in the light of some variables

(sex, marital status). To measure the Histrionic Personality, the researcher applied two scales to a random stratified sample of (200) male and female teachers. The results showed statistically significant differences in the level of compulsive buying behavior according to the gender variable and in favor of female teachers. There are no statistically significant differences in terms of marital status. There are statistically significant differences in the Histrionic Personality based on gender variables in favor of f

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod