In this paper, the effect size measures was discussed, which are useful in many estimation processes for direct effect and its relation with indirect and total effects. In addition, an algorithm to calculate the suggested measure of effect size was suggested that represent the ratio of direct effect to the effect of the estimated parameter using the Regression equation of the dependent variable on the mediator variable without using the independent variable in the model. Where this an algorithm clear the possibility to use this regression equation in Mediation Analysis, where usually used the Mediator and independent variable together when the dependent variable regresses on them. Also this an algorithm to show how effect of the

        The experimental and theoretical methods were studied for inhibition of the corrosion titanium in HCl by using neomycin sulfate drug. The results of neomycin sulfate drug had good corrosion protection for titanium in hydrochloric acid and the inhibition efficiency (%IE) increasing with increasing concentration of drug because the neomycin sulfate drug had adsorption from acid solution on surface of titanium metal. The program of hyperchem-8.07 was used for theoretical study of the drug by molecular mechanics and semi-empirical calculations. Quantum chemical was studied drug absorption and electron transferred from the drug to the Titanium metal, also inhibition potentials of drug attachment with the (LUMO-HOMO) energy gap,

Modern automation robotics have replaced many human workers in industrial factories around the globe. The robotic arms are used for several manufacturing applications, and their responses required optimal control. In this paper, a robust approach of optimal position control for a DC motor in the robotic arm system is proposed. The general component of the automation system is first introduced. The mathematical model and the corresponding transfer functions of a DC motor in the robotic arm system are presented.  The investigations of using DC motor in the robotic arm system without controller lead to poor system performance. Therefore, the analysis and design of a Proportional plus Integration plus Divertive (PID) controller is illustrated.

Male reproductive health is intricately regulated by molecular and physiological processes, with the aryl hydrocarbon receptor (AhR) playing a crucial role. AhR is activated by various ligands and influences the onset and progression of diseases. The aim of this study was to evaluate the role of AhR on spermatogenesis in adult male rats were affected by resveratrol (RES) and CH223191, an AhR antagonist. The study include forty rats were randomly divided into four equal groups: Control group, DMSO group, RES group and AhR‾ group, the rats received respective treatments intraperitoneally twice weekly for 60 days, and various parameters related to male reproductive health were evaluated. The AhR that activation by the RES treatment w

In this paper activated carbon adsorbents produced from waste tires by chemical activation methods and application of microwave assisted KOH activation. The influence of radiation time, radiation power, and impregnation ratio on the yield and oil removal which is one of the major environmental issues nowadays and considered persistent environmental contaminants and many of them are suspected of being carcinogenic. Based on Box-Wilson central composite design, polynomial models were developed to correlate the process variables to the two responses. From the analysis of variance the significant variables on each response were identified.  Optimum conditions of 4 min radiation time, 700 W radiation power and 0.5 g/g impregnation ratio

A field-pilot scale slow sand filter (SSF) was constructed at Al-Rustamiya Sewage Treatment Plant (STP) in Baghdad city to investigate the removal efficiency in terms of Biochemical Oxygen Demand (BOD5), Chemical oxygen demand (COD), Total Suspended Solids (TSS) and Chloride concentrations for achieving better secondary effluent quality from this treatment plant. The SSF was designed at a 0.2 m/h filtration rate with filter area 1 m2 and total filter depth of 2.3 m. A filter sand media 0.35 mm in size and 1 m depth was supported by 0.2 m layer of gravel of size 5 mm. The secondary effluent from Al-Rustamiya STP was used as the influent to the slow sand filter. The results showed that the removal of BOD5, COD, TSS, and Chloride were

Keys for 22 species representing 10 genera of Thripidae were provided collection of
samples carried out during 1999-2001 in different localities in the middle of Iraq. Of them
four species are described as new to science, Frankliniella megacephala sp. nov; Retithrips
bagdadensis sp. nov; Chirothrips imperatus sp. nov; Taeniothrips tigridis sp. nov; Another
fourteen species are recorded for the first time in Iraq; Thrips meridionalis (Pri.);
Microcephalothrips abdominils (Crawford Scolothrips sexmaculatus (Pergande),);Scolothrips
pallidus (Beach); Scritothrips mangiferae Pri.; Frankliniella tritici Bagnall; Frankliniella
schultzie Trybom; Frankliniella unicolor Morgan; Retithrips aegypticus Marchal; Retithrips
java

Abstraet

Students dropout from the Education has a negative phenomena on individual and society and even on different aspects of life especially on the economic aspect , Thus our research tries studying and analyzing the relation between the size of dropout and human development level in Iraq and as (research sample) the first decade of this century as a studying period, the study includes the dropout in Secondary schools and depending the formal records as a main source to evaluate the size of this problem in Iraq , which shows an increase in the size of dropout in this period in comparison with the last decades of the twentieth century, this produces a negative effect on human developme

     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