Stable new derivative (L) Bis[O,O-2,3;O,O-5,6(carboxylic methyliden)]L-ascorbic acid was synthesized in good yield by the reaction of L-ascorbic acid with dichloroacetic acid with ratio (1:2) in presence of potassium hydroxide. The new (L) was characterized by 1H,13C-NMR, elemental analysis (C,H) and Fourier Transform Infrared (FTIR). The complexes of the ligand (L) with metal ion, M+2= (Cu, Co, Ni, Cd and Hg) were synthesized and characterized by FTIR, UV-Visible, Molar conductance, Atomic absorption and the Molar ratio. The analysis evidence showed the binding of the metal ions with (L) through bicarboxylato group manner resulting in six-coordinated metal ion.

Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

Objective(s): assessment of  the health follow up and weight control for women with osteoporosis and find out the relationship between their health follow up and weight control and their socio-demographic characteristics.

Methodology: A descriptive study was conducted on women with osteoporosis for the period of September, 26^th 2020 to Jun, 20th 2021. Non- probability (convenient) sample of (70) women with osteoporosis selected from (5) Private Clinics for Joints and Fractures in Baqubah City. A questionnaire was designed though extensive review of literatures and it consists of three parts: the first part includes women’s socio demographic characteristics, the second part inclu

According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

The composites were manufactured and study the effect of addition of filler (nanoparticles SiO2 treated with silane) at different weight ratios (1, 2, 3, 4 and 5) %, on electrical, mechanical and thermal properties. Materials were mixed with each other using an ultrasound, and then pour the mixture into the molds to suit all measurements. The electrical characteristics were studied within a range of frequencies (50-1M) Hz at room temperature, where the best results were shown at the fill ratio (1%), and thermal properties at (X=3 %), the mechanical properties at the filler ratio (2%).