In light of crises, the need for efficient and flexible public administrations to make quick and decisive decisions, also institutions capable of directing the internal elements and components of them and adapting them to the requirements of rapid change due to crises and disasters, which led to scarce resources becoming scarcer and economic, political and social problems becomes more prominent. For the majority of developing countries, including Iraq, the increasing need for the importance of moving towards enhancing the efficiency of the performance of public institutions while trying to predict their future, can only be achieved. Through solid mechanisms and principles of governance that enhance the ability of institutions and make them

The Iraqi culture faced a set of challenges that can be diagnosed with the most prominent features as follows:

1. The dominance of authoritarian political systems which entails authoritarian regimes with the absence of contemporary political concepts of human rights.
2. The prevalence of non- informed cultural systems which have the shortage of capabilities that enable them to activate cultural elements in positive references, historical, or seclusion on itself and not be able to interact with the current active cultures.
3. Stagnant economic conditions have not had a decent life for individuals, or a certain level of well-being, as well as poor services and others.
4. Social life controlled by the prevai

The increasing use of antiseptic compounds creates selective pressure cause emergence of antiseptic resistance among Staphylococcus aureus .Resistance mechanism of antiseptic is driven mainly by multi drug resistant (MDR) efflux protein.Sixty five isolates of S.aureuswere collected from different clinical sources and subjected to 11 antibiotics most of them are recognized by efflux systems as extruded substrates. Range of efflux activity was estimated using cartwheel method. Simultaneous discrimination of antiseptic coding genes (qacA/B, smr and norA)as well as nuc and mecA genes among multidrug resistantS.aureus(MRSA) isolates was preformed using multiplex PCR assay

       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

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve