Worldwide, hundreds of millions of people have been infected with COVID-19 since December 2019; however, about 20% or less developed severe symptoms. The main aim of the current study was to  assess  the  relationship  between  the  severity of Covid-19 and different clinical and laboratory parameters. A total number of 466 Arabs have willingly joined this prospective cohort. Out of the total number, 297 subjects (63.7%) had negative COVID-19 tests, and thus, they were recruited as controls, while 169 subjects (36.3%) who tested positive for COVID-19 were enrolled as cases. Out of the total number of COVID-19 patients, 127 (75.15%) presented with mild symptoms, and 42 (24.85%) had severe symptoms. The age range for the partic

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

The Strategy of employees' empowerment, organizational performance and total quality management represent three informative which were and still the hub of many studies and researches including the current study. The higher education is considered one of the most important services sectors and the main development as well as the civil progress in the society. It is the main source that provides the organizations with the human resources having scientific or practical professions. So Higher Education has been chosen especially Baghdad University as a sample of the study. The study problem is concentrated to find answers of the following   questions: What the level of the powers mandate in the organization concerning the

In this research, the effect of changing the flood level of Al-Shuwaija marsh was studied using the geographic information systems, specifically the QGIS program, and the STRM digital elevation model with a spatial analysis accuracy of 28 meters, was used to study the marsh. The hydraulic factors that characterize the marsh and affecting on the flooding such as the ranks of the water channels feeding the marsh and the degree of slope and flat areas in it are studied. The area of immersion water, the mean depth, and the accumulated water volume are calculated for each immersion level, thereby, this study finds the safe immersion level for this marsh was determined.

Abstract. Shatt Al-Arab River was the most important tide river in Iraq, it suffered from neglect and lack of maintenance in the past decades. The river embankment is constantly exposed to erosion processes due to several factors, one of the most important of these factors is the movement of water currents due to the tidal energy coming from the Arabian Gulf. In this study, one dimension unsteady-state model was implemented to study river flood capacity simulation by using HEC-RAS (5.0.7) software in Shatt Al Arab River and its tributaries. The data included flow rate, water level records were collected daily from 2018 to 2020 at different stations along the mentioned river and its feeders, additionally, the considered flood discharge data

The current study aims to find a new plan to manage the water quality of the western part of the Hammar Marsh to reduce the salts that cause problems for the marshes and preserve their environmental life by isolating the southwestern part of the Hammar Marsh by closing the outlet under the railway embankment. The outlet is discharging saline water to the east-western part of Al Hammar Marsh. After isolating the southwestern part of the marsh, a new outlet is proposed. The impact of the flow hydrodynamics on improving the water quality was simulated using the SMS model. The hydrodynamics and water quality simulation models for the marsh are : a hydrodynamic model and average depth (SMS RMA2) and a two-dimensional water quality model (SMS

This study was conducted to estimate the extent of damage to the population in Basra, southern Iraq, specifically the areas adjacent to the Shatt al-Arab and the Arabian Gulf, which are the Al-Fao district and the Al-Siba region. They are affected by the progression of saline water resulting from the lack of water imports and the Karun River interruption, which led to high concentrations of salts in the Shatt Al-Arabs. Consequently, its effect on lands and all life types in these areas requires correcting a map of the study area to drop the groundwater sites as well as calculate the total dissolved salts, electrical conductivity and pH. This study concluded that the groundwater contains very high percentages of total dissolved solid