Abstract

This study deals with the fluctuations of oil revenues and its effect on the public debt. This can be studied through the indicators of debt sustainability, the financial, and economic indicators which express the risk of debt. The study focuses on clarification of the public debt path and its management both domestic and foreign. The sustainability of debt takes an important role according the macroeconomic variables. This study stresses the relationship between the rental economy in Iraq and the risk of the public debt, it is very important to work high oil prices, and on investigating during high work to establish a fund to support the budget deficit. This will reduce future risks arising from the use of publi

The figure of personality modes determines its privileged style in the use of modern and advanced technological tools in the process of changing and developing in order to keep up with that. The proses of selection and choosing administrators in the appropriate places are the most important functions of senior management because it is easy to adopt factory buildings or establishments But this is a human world as that of machines world. So it is required to have people in the process of changing those who have a time, Knowledge, skill, ability and strong administrative personal skills, those people (leaders) should to put a clear vision for the selection and application of the change efforts and to create the necessary climate and

A sensitivity-turbidimetric method at (0-180^o) was used for detⁿ. of mebeverine in drugs by two solar cell and six source  with C.F.I.A.. The method was based on the formation  of  ion pair for the pinkish banana color  precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of   precipitated at 0-180^o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L^-1, the L.D. (S/N= 3)(3S_B) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D%

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi