LandSat Satellite ETM+ image have been analyzed to detect the different depths of regions inside the Tigris river in order to detect the regions that need to remove sedimentation in Baghdad in Iraq Country. The scene consisted of six bands (without the thermal band), It was captured in March ٢٠٠١. The variance in depth is determined by applying the rationing technique on the bands ٣ and ٥. GIS ٩. ١ program is used to apply the rationing technique and determined the results.

The present study is considered the first on this sector of the Tigris River after 2003. It is designed for two aims, the first is to demonstrate the seasonal variations in physicochemical parameters of Tharthar-Tigris Canal and Tigris River; the second is to explain the possible effects of canal on some environmental properties in the Tigris River. Water samples were being collected monthly. Six sampling sites were selected, two on Tharthar Canal and four along the Tigris River, one before the confluence as a control site and the others downstream the confluence with the canal. For a period from January to December 2020, nineteen physicochemical parameters were investigated including air and water temperature, turbidity, electrical cond

Many studies of the relationship between COVID-19 and different factors have been conducted since the beginning of the corona pandemic. The relationship between COVID-19 and different biomarkers including ABO blood groups, D-dimer, Ferritin and CRP, was examined. Six hundred (600) patients, were included in this trial among them, 324 (56%) females and the rest 276 (46%) were males. The frequencies of blood types A, B, AB, and O were 25.33, 38.00, 31.33, and 5.33%, respectively, in the case group. Association analysis between the ABO blood group and D-dimer, Ferritin and CRP of COVID-19 patients indicated that there was a statistically significant difference for Ferritin (P≤0.01), but no-significant differences for both D-dimer and CRP.

To assess the impact of COVID‐19 on oral hygiene (OH) awareness, attitude towards dental treatment, fear of infection and economic impact in the Middle East.

The aim of the research is the detection of heavy metals using (Inductively coupled Plasma ICP) for samples in Tigris river at intakes of water treatment plants Baghdad (Sharq dejla, Al-Wathba, Al-Wahda, and Al-Dora) and samples at Tigris banks near (Al-Adhamya, Al-Shuhda bridge and al-Jadrya).
All the recorded results were fitted with Iraqi standers No. 25 in 1967 for all samples with heavy metals (arsenic Ar, Cadmium Cd, Chromium Cr, Zinc Zn, Lead Pb, Copper Cu, Nickel Ni, Manganese Mn, Ferrous Fe) where all concentration were lower than standard values except Cadmium (0.01- 0.014) in plants intakes and (0.027- 0.048) in river samples while the standard value is (0.005).
Other tests such as chemical oxygen demand and oil &

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

    The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t

ABSTRACT Objective: Cardiovascular diseases are the first ranked cause of death worldwide. Adhering to health promoting lifestyle behaviors will maintain an individual’s cardiovascular health and decrease the risk of cardiovascular diseases. Methods: In this descriptive study, 150 nursing faculty were surveyed via a non-probability (purposive) sampling method to assess their adherence to health promoting lifestyle in order to know the risk of cardiovascular diseases. The Arabic version of Health-Promoting Lifestyle Profile II (HPLP-II) was used to achieve this goal. Results: Seventy-two nursing faculty completed the survey. The results indicated that the study sample had moderate level of health promotion based on Health-Promot

In this study water quality index (WQI) was calculated to classify the flowing water in the Tigris River in Baghdad city. GIS was used to develop colored water quality maps indicating the classification of the river for drinking water purposes. Water quality parameters including: Turbidity, pH, Alkalinity, Total hardness, Calcium, Magnesium, Iron, Chloride, Sulfate, Nitrite, Nitrate, Ammonia, Orthophosphate and Total dissolved solids were used for WQI determination. These parameters were recorded at the intakes of the WTPs in Baghdad for the period 2004 to 2011. The results from the annual average WQI analysis classified the Tigris River very poor to polluted at the north of Baghdad (Alkarkh WTP) while it was very poor to very polluted in t