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

NiO0.99Cu0.01 films have been deposited using thermal evaporation
technique on glass substrates under vacuum 10-5mbar. The thickness
of the films was 220nm. The as -deposited films were annealed to
different annealing temperatures (373, 423, and 473) K under
vacuum 10-3mbar for 1 h. The structural properties of the films were
examined using X-ray diffraction (XRD). The results show that no
clear diffraction peaks in the range 2θ= (20-50)o for the as deposited
films. On the other hand, by annealing the films to 423K in vacuum
for 1 h, a weak reflection peak attributable to cubic NiO was
detected. On heating the films at 473K for 1 h, this peak was
observed to be stronger. The most intense peak is at 2θ = 37

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

Physiological status and litter size can indeed have a significant impact on ewes' ‎hematological parameters, which are essential indicators of their health. Therefore, this study ‎examined the hematological profiles of ewes during pregnancy with single and twins in the ‎Awassi ewes. The present study involved 232 ewes in good health and at sexual maturity. ‎Among them, 123 ewes had single pregnancies, while 109 ewes had twin pregnancies. The age ‎range of the ewes included in the study was between 3.5 and 4.5 years. Hematological tests ‎were conducted on the sheep's blood samples promptly following collection. The findings ‎demonstrated variations in hematological parameters among pregnant

This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.

The use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models                  

          In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear

Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

Paper type: