Iraq is highly dependent on international markets to provide food for its residents. As imported food prices are highly dependent on crude oil prices in global markets, any shock in oil prices will have an impact on food consumption in the country. As a result, it is essential to study the demand for imported food at every time period. To the best of our knowledge as researchers, as not even a single study is available in the literature, this paper is considered the first to study the demand for imported food groups in Iraq. Therefore, the main objective of this research is to estimate demand elasticities for several imported food categories in Iraq. This study uses an Almost Ideal Demand System model to analyze the demand for imported f

At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat

The thirties and the early forties and the at end of the World War II of the last century
witnessed several attempts carried out by the Public Health Directorate and by the Iraqi
Ministry of Foreign Affairs to persuade the Rockefeller Foundation to fund Iraq with its
health program which is carried out in several regions in the world to promote the health and
social situations since Iraq during that period in history was badly in need to such plans and
programs because of this lack of financial and technical possibilities necessary for the
advancement of health and social dire situation.
The details of these attempts are deposited in the documents of the diplomatic mail
records of the United States of America , an

        Investment Bases directly and closely to an environment characterized by political, social and economic stability, and through a range of policies and institutions and economic laws that affect investor confidence and convince him directing investments to country without the other, where inter conditions and circumstances affecting the trends of capital and settle in, and political situation of the country and what is characterized of stability or disorder as well as economic conditions that are affected by what is distinguishes the country from geographic and demographic characteristics are reflected on availability of production elements and country's infrastructure.

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THE EFFECT OF SPREACL of KNOWLEDGE ON ETHICS

Gypseous soil, which covers vast area in west, middle, east and south west regions of Iraq exhibit acceptable strength properties when dry, but it is weak and collapsible when it comes in touch with moisture from rain or other sources. When such weak soil is adopted for earth reinforced embankment construction, it may exhibit hazardous situation. Gypseous soil was investigated for the optimum liquid asphalt requirements of both cutback and emulsion using the one-dimensional unconfined compression strength test. The optimum fluid content was 13% (7% of cutback with 6% water content), and 17% (9% of emulsion with 8% water content). A laboratory model box of 50x50x25 cm was used as a representative of embankment; soil or asphalt stabilize

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c