Abstract                                                                                                                       &nbsp

Leishmania major is a protozoan parasite that causes cutaneous Leishmaniasis disease in human beings and animals. The disease is prevalent in tropical and semitropical countries and has great health importance. The present study aimed to identify the histological changes in the organs infected with L. major and to provide a sophisticated diagnostic method for infection through detecting TGF-β cytokine by immunohistochemistry technique(IHC) from October 2020 to January 2021. A total of 40 samples of paraffin blocks were used for different organs including skin, spleen, liver, kidney, and heart of male and female BALB/c mice, aged 6-8 weeks, which were previously infected subcutaneously with L. major promastigotes at a dose of 1×107 promast

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

In this paper all possible regressions procedure as well as stepwise regression procedure were applied to select the best regression equation that explain the effect of human capital represented by different levels of human cadres on the productivity of the processing industries sector in Iraq by employing the data of a time series consisting of 21 years period. The statistical program SPSS was used to perform the required calculations.

God Almighty put in his great book secrets that do not end, and wonders that do not expire, for he is the one from which the scholars are not satisfied, and he does not create due to the multitude of response, and it is the comprehensive and inhibitory book that God conceals to the worlds, and he challenged the two heavyweights to come up with something like it.

At all times, issues arise in the Noble Qur’an that fit the needs of the people of that time and their culture, for it is an eternal book, characterized by the ability to give, extend and respond to addressing the problems of the age and its variables, when the Arabs had little luck at the time of the message’s descent from the scientific culture, and their proficienc

The aesthetic contents of data visualization is one of the contemporary areas through which data scientists and designers have been able to link data to humans, and even after reaching successful attempts to model data visualization, it wasn't clear how that reveals how it contributed to choosing the aesthetic content as an input to humanize these models, so the goal of the current research is to use The analytical descriptive approach aims to identify the aesthetic contents in data visualization, which the researchers interpreted through pragmatic philosophy and Kantian philosophy, and analyze a sample of data visualization models to reveal the aesthetic entrances in them to explain how to humanize them. The two researchers reached seve

Manufacturing industries are at the beginning of the thinking of those who put economic policies in developed countries and also more in developing countries, where manufacturing is the engine of industrial and economic development through its performance and its effective role in the formation of GDP, as well as the great advantages that characterize this sector and affect Largely on sustainable development, as well as its importance in its influential role in protecting national industry through increased exports and reduced imports.

      Iraq is one of the countries that rely on its oil economy to rely entirely on the provision of needs and requirements of the state, and this

Reconstruction project management in the cities of Mosul, Anbar, and Tikrit, in Iraq still faces major obstacles that impede the comprehensive performance of these projects. It is thus necessary to improve the arising challenge estimation in the implementation of reconstruction projects and evaluate their components: time, cost, quality, and scope. This study used the Analytical Hierarchy Process (AHP) to prioritize major and minor criteria in the influential causes of challenges and formulate a mathematical model to help decision-makers estimate them. Using the Super Decisions software, the final results indicated that changes in scope reached 40.8%, which is the greatest difficulty, followed by changes in cost at 27.6%, changes in