Mishrif Formation was deposited during The Cenomanian-Early Turonian, which has been studied in selected Tuba and Zubair OilFields, these wells (TU-5, TU-24, TU-40, ZB-41, ZB-42, and ZB-46) are located within Mesopotamian basin at southern Iraq and considered as a major carbonate reservoir in Iraq and the Arabian Gulf. The palaeontological investigations mainly depending on benthonic foraminifera of the studied wells of Tuba and Zubair Oilfields in Mishrif Formation, twenty-four species belonging to fourteen genera are recognized of benthonic foraminifera, which has been recognized through this study, especially benthonic foraminiferal, indicating four zones as follows:

The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests

Imposed on foreign oil companies from important sources in the financing of the general budget in most countries of the world income tax is considered as well as be used to achieve political, economic and social goals, and has developed the concept of the tax until it became play an important role in influencing the economic conditions of a country, and the aim of this research is to statement imposed on foreign oil companies operating in Iraq in the financing of the state budget income tax contribution, as well as clarify the contracts type contracts with these companies, which is in favor of Iraq, together with the Income Tax Law No. (19) for the year / 2010, and instructed No. (5) for the year / 2011, which organized the tax process s

Arsenic is a prevalent and pervasive environmental contaminant with varied amounts in drinking water. Arsenic exposure causes cancer, cardiovascular, liver, nerve, and ophthalmic diseases. The current study aimed to find the best conditions for eliminating arsenic from simulated wastewater and their effect on biomarkers of hepatic in mice. Adsorption tests including pH, contact duration, Al-kheriat dosage, and arsenic concentrations were evaluated. Seventy-two healthy albino mice (male) were accidentally allocated into nine groups (n = 8), the first group was considered as healthy control, the second group (AL-Kheriat), and other groups received AL-Kheriat and arsenic 25, 50, 75, 100, 125, 150 and 175 mg/kg, respectively. Next 10 days, the

ملخص البحث
تبحث الدراسھ عن تنفیذ افضل لمفھوم التعلم مدى الحیاة كھیكل موجھ للسیاسة التربویة في العراق بشكل عام وفي
التعلیم العالي بشكل خاص. تحدد الدراسة استراتجیات التعلم مدى الحیاة وتناقش اھمیتھ وسماتھ الرئیسیة لتسھیل
الوصول الى فرص تعلم متمیز و ملائم لحاجات الطلبة مدى الحیاة، كما تناقش دور الجامعة في تحقیق ھذا الھدف.

The measurements and tests of the samples conducted in the laboratories of the College of Agriculture included isolating bio-fertilizers and testing the efficiency of isolates that fix atmospheric nitrogen and solubilize phosphorous compounds. Bacteria were isolated and identified from the rhizosphere soils of different plants collected from various agricultural areas. A total of 74 bacterial isolates were obtained based on the phenotypic characteristics of the developing colonies, as well as biochemical and microscopic traits. The results of isolation and identification showed that among the 74 bacterial isolates, there were 15 isolates of A. chroococcum, 13 of Az. lipoferum, 13 of B. megaterium, 10 of P. putida, 10 of Actinomycetes, and n

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp