Abstract The study aimed at demonstrating the reality of sectarian coexistence in Iraq, which was characterized by the tolerance and coercion caused by the successive government policies to govern Iraq and to this day. The study was based on the hypothesis that coexistence between Islamic sects in Iraq can be achieved as long as there are strong bonds linking its components, and these bonds can produce coexistence between the sects based on peace. The study concluded that the hypothesis is correct, in addition to drawing a set of observations aimed at identifying weaknesses for advancing them through the adoption of mechanisms that address these weaknesses to yield towards a genuine peaceful coexistence among Islamic sects in Iraq.

يتناول البحث دراسة تطبيق نظرية اساءة استعمال الحق في مجال المسؤولية التعاقدية

Euphemism is an important linguistic phenomenon that tends to soften written or oral expressions. Thus, when translators or interpreters face expressions including euphemism, they need to know how to deal with them. The problem of the current paper lies in the effect of rendering euphemistic expressions inaccurately, as such expressions represent the cultural and terminological sense of the original language. Thus, rendering them improperly will affect the sense of the interpreted speech. For this, it is essential for translators in general and simultaneous interpreters in particular to know the importance of utilizing euphemism in the simultaneous interpreting field, which is the main aim of this paper. To this end, a systematic review

The current research aims to know the complementary use of the paper book and the digital book by defining the paper book and the digital book and knowing the methods and methods of obtaining each of them and indicating the extent of their use and for what purpose and knowing the difficulties that researchers face in using each of them and which is better using the paper book or the digital book in preparing research Studies and for no reason. The research relied on the descriptive approach and the questionnaire as a tool for data collection, and it was distributed to professors and students of Iraqi universities. The research sample reached (219) individuals and reached a set of results, the most important of which are: Preference for the

Many problems were encountered during the drilling operations in Zubair oilfield. Stuckpipe, wellbore instability, breakouts and washouts, which increased the critical limits problems, were observed in many wells in this field, therefore an extra non-productive time added to the total drilling time, which will lead to an extra cost spent. A 1D Mechanical Earth Model (1D MEM) was built to suggest many solutions to such types of problems. An overpressured zone is noticed and an alternative mud weigh window is predicted depending on the results of the 1D MEM. Results of this study are diagnosed and wellbore instability problems are predicted in an efficient way using the 1D MEM. Suitable alternative solutions are presented

The problem of internal sulfate attack in concrete is widespread in Iraq and neighboring countries.This is because of the high sulfate content usually present in sand and gravel used in it. In the present study the total effective sulfate in concrete was used to calculate the optimum SO3 content. Regression models were developed based on linear regression analysis to predict the optimum SO3 content usually referred as (O.G.C) in concrete. The data is separated to 155 for the development of the models and 37 for checking the models. Eight models were built for 28-days age. Then a late age (greater than 28-days) model was developed based on the predicted optimum SO3 content of 28-days and late age. Eight developed models were built for all

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog