Factor analysis is distinguished by its ability to shorten and arrange many variables in a small number of linear components. In this research, we will study the essential variables that affect the Coronavirus disease 2019 (COVID-19), which is supposed to contribute to the diagnosis of each patient group based on linear measurements of the disease and determine the method of treatment with application data for (600) patients registered in General AL-KARAMA Hospital in Baghdad from 1/4/2020 to 15/7/2020. The explanation of the variances from the total variance of each factor separately was obtained with six elements, which together explained 69.266% of the measure's variability. The most important variable are cough, idleness, fever, headach

This investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.

Recently, Qatar, a well-known oil production country, has been convinced as a successful case in attracting foreign direct investment (FDI) as a smaller economy. This paper aims to investigate how FDI inflows affect Qatar’s business cycles. Time series data was selected from 1990 to 2010 as available. The VAR Impulse Responses and the Granger Causality test were mainly employed by using Eviews. The derived result shows that the FDI inflows and the economic growth in Qatar interact with each other in a relatively long term.

In light of the enquiry raised by the Economist Mary Finn in 1995 concluding that high utilization in absorptive capacity of the economy is of inflationary tendency for industrial countries due to the equality between high rates of utilization of absorptive capacity and resource – shortage conditions leading to price inflation, the same idea was used to prove that budget utilization of operational costs and elevating absorptive capacity at the expense of investment budget leads to inflationary tendency that becomes a burden on financing the step- in policy of the Central bank to control prices through its foreign currency reserves at a time when the economy turned  into an importer of non- tradable goods and being subject

This study was designed to evaluate the effect of major surgery on thyroid hormones and thyrotropin in patient undergoing major lower abdominal surgery. The study included fifty patients scheduled for elective major lower abdominal surgery, the serum levels of T3, T4 and TSH were determined one day preoperatively, intraoperative, one day postoperatively, two days postoperatively, and rT3 was determined one day preoperatively, and one day postoperatively. We observed that the levels of (T3, T4, TSH) increased significantly (P<0.05) intraoperatively, one day postoperatively the levels of T3 and T4 reduced significantly (P<0.05), while TSH reduced not significantly (P>0.05), and two days postoperatively T4 and TSH returned to increase si

Background: Chronic periodontitis is an inflammatory disease of tissues supporting the teeth. Salivary compositions have been most intensely studied as a potential marker for periodontal disease. In this study, analysis of saliva provides a simple and non-invasive method of evaluating the role of salivary IgA (s-IgA) levels in periodontal disease by detecting the level of (s-IgA) in patients with chronic periodontitis smokers and non smokers patients and correlate the mean (s-IgA) levels with clinical periodontal parameters Plaque index (PLI) gingival index (GI), probing pocket depth (PPD) and clinical attachment level (CAL). Materials and Methods: The study samples consists of (15) patients with chronic periodontitis who were non smokers (

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

This paper demonstrates an experimental and numerical study on the behavior of reinforced concrete (RC) columns with longitudinal steel embedded tubes positioned at the center of the column cross-section. A total of 12 pin-ended square sectional columns of 150 × 150 mm having a total height of 1400 mm were investigated. The considered variables were the steel tube diameters of 29, 58, and 76 mm and the load eccentricity (0, 50, and 150) mm. Accordingly, these columns were divided into three groups (four columns in each group) depending on the load eccentricity (e) to column depth (h) ratio (e/h = 0, 1/3, and 1). For each group, one column was solid (reference), and the other three columns contained steel tubes with hollow rat

Background: Among individuals who have a stenotic aortic valve, a precise assessment of aortic valve area is essential for clinical judgment. So far, no studies have been conducted to investigate and assess the role of the three dimensional echo-cardiography in the assessment of the valve stenosis. This study aims to compare and assess the precision of the measurement of the stenosis area of the aortic valve by 2D versus 3D echo-cardiography.