This study was conducted to evaluate the efficacy of Saccharomyces cerevesiae as a growth promoting agent in tomato. Soaking the seeds in yeast suspension at 5 g/L for 12h increased germination percentage, root length, root fresh and dry weight, plant height, foliage fresh and dry weight, attained 88.5% ; 8.1 cm ; 84.3 mg ; 7.03 mg ; 10.75 cm ; 839 mg and 37.75 mg compared with 80% ; 5.33 cm ; 39 mg ; 4.8 mg ; 7.35 cm ; 608 mg and 25.5 mg in seedlings grown from non treated seeds respectively. Similar results were obtained with seedling from seeds soaked in S. cerevesiae filtrate for 12 hrs. with values of 77.5% ; 6.875 cm ; 91.5 mg ; 7.5 mg ; 9.5 cm ; 777 mg and 40.35 mg compared to 66% ; 5.8 cm ; 57.7 mg ; 5.03 mg ; 5.9 cm ; 493 mg

The calculation of the charge on an isolated dust grain immersed in plasma with different grain sizes is a challenging one, especially under moderately high plasma temperature when secondary electron emission significant. The discrete charging model is used to calculate the charges of dust grain in dusty plasma. In this model, we included the effect of grain size dependence on secondary electron emission. The results show that the secondary electron emission from the glass dust grains due to energetic electron (40eV) can lead to the small grain to be slightly more positive than the large grain. Under these conditions, the smaller and larger grains would be attracted rather than repelled, which possibly lead to enhanced coagulation rates.

       In the present paper, by making use of the new generalized operator, some results of third order differential subordination and differential superordination consequence for analytic functions are obtained. Also, some sandwich-type theorems are presented.

Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.

in this paper the collocation method will be solve ordinary differential equations of retarted arguments also some examples are presented in order to illustrate this approach

    In this paper, the finite difference method is used to solve fractional hyperbolic partial differential equations, by modifying the associated explicit and implicit difference methods used to solve fractional  partial differential equation. A comparison with the exact solution is presented and the results are given in tabulated form in order to give a good comparison with the exact solution

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2^nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for