The current study included details of the anatomical characteristics of vegetative parts including the root, stem, leaf in cultivated Iraq for the species Brassciaaleraceacabbage, where the study dealt with the stomatal index and the rate of both the length and width of the stomatal complex and the thickness of the periderm, the tissue, cortex, vascular cylinder and pith. The parts were taken and measured after the plant was treated with brassinolide and the treated species with brassinolide and non-treated were measured and the study showed that there was a clear variation in the properties above.

Wastewater discharge containing organic dyes may pose a hazard to the environment, which necessitates that dye removal must occur prior to wastewater release into water bodies. Herein, copper oxide nanoparticles (CuO NPs) were prepared by a green precipitation method to enable decolorization of a cationic dye (methyl violet; MV) from aqueous media. Complementary tools were employed to characterize the CuO NPs adsorbent: spectroscopy (FTIR and UV-VIS), microscopy (FESEM and TEM), XRD, BET surface area analysis, and point of zero charge (pHPZC) via potentiometry. The FTIR bands at 722, 663, 569, and 465 cm−1 correspond to the vibrational modes of CuO NPs, along with the optical absorbance band at 275 nm that supports the formation of Cu

Wastewater discharge containing organic dyes may pose a hazard to the environment, which necessitates that dye removal must occur prior to wastewater release into water bodies. Herein, copper oxide nanoparticles (CuO NPs) were prepared by a green precipitation method to enable decolorization of a cationic dye (methyl violet; MV) from aqueous media. Complementary tools were employed to characterize the CuO NPs adsorbent: spectroscopy (FTIR and UV-VIS), microscopy (FESEM and TEM), XRD, BET surface area analysis, and point of zero charge (pHPZC) via potentiometry. The FTIR bands at 722, 663, 569, and 465 cm1 correspond to the vibrational modes of CuO NPs, along with the optical absorbance band at 275 nm that supports the formation of CuO NPs.

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

In the present work, steady, laminar natural convection in nonrectangular enclosures is analyzed numerically with and without fin. Vertical walls insulated while horizontal walls maintained isothermal at different temperature and the fin was placed on horizontal surface. The length of fin was equal (B/L=0.22, 0.44 and 0.66) and thickness of fin was constant. Various parameters are studied: Rayleigh number (from 104 to 107 ), Prandtl number (0.7), number of fin change from (1-3) and aspect ratio (H/L= 0.15 to 0.5). The problem is formulated in terms of the vorticity-stream function procedure. A numerical solution based on program in Fortran 90 with Tec plot program. The finite difference method is used. Streamlines and isotherms are prese

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da