Lipid disorders and cardiovascular disease (CVD) risk are known to be increased in patients with diabetes mellitus. The effects of statins on serum lipid levels are well known; however, previous studies did not compare the effects of statins on serum lipid levels in diabetic patients with non-diabetic patients. To investigate the effects of Atorvastatin on serum lipid profiles in hyperlipidemic patients with type 2 diabetes mellitus in comparison with hyperlipidemic patients without diabetes.This study was conducted on 33 type 2 diabetic patients & 34 non-diabetic patients; their age range was 40-80 years, all of them were hyperlipidemic, who had been administered 10, 20, & 40 mg daily of Atorvastatin and completed a 6-month foll

This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

In this paper harmful phytoplankton and herbivorous zooplankton model with Hollimg type IV functional response is proposed and analyzed. The local stability analysis of the system is carried out. The global dynamics of the system is investigated with the help of the Lyapunov function. Finally, the analytical obtained results are supported with numerical simulation.

     The research deals with A very important two subjects, computer aided process planning (CAPP) and Quality of product with its dimintions which identified by the producer organization, the goal of the research is to Highlight and know the role of the CAPP technology to improve quality of the product of (rotor) in the engines factory in the general company for electrical industries, The research depends case study style by the direct visits of researcher to the work location to apply the operational paths generated by specialized computer program designed by researcher, and research divides into four axes, the first regard to the general structure of the research, the second to the theoretical review, the t

Water stress has a negative impact on the yield and growth of crops worldwide and consequently has a global impact on food security. Many biochemical changes occur in plants as a response to water stress, such as activation of antioxidant systems. Molybdenum (Mo) plays an important part in activating the expression of many enzymes, such as CAT, POD, and SOD, as well as increasing the proline content. Mo therefore supports the defence system in plants and plays an important role in the defence system of mung bean plants growing under water stress conditions. Four concentrations of Mo (0, 15, 30, and 45 mg·L−1) were applied to plants, using two approaches: (a) seed soaking and (b) foliar application. Mung bean plants were subject

Shade in house gardens is one of the problems that hinder the growth of lawn and its distribution in the soil, where the types of lawns differ in their durability and adaptation to shade. The research aims to know the resistance of some species of lawn plants to shade and to know the appropriate fertilization procedures that can be followed to reduce the negative effects. The study was conducted in the Amiriya district of Baghdad in a house garden. Three varieties of lawn plants Bermuda, Gazon, and Trifoglio were planted. Five fertilization treatments (contained N and P elements) and the control were used. The sunlight density with the temperature of the study field locations were estimated using the AMT-300 and the vegetation coverage perc

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca