Monthly variations in Physio-chemical parameters of Al-Garraf water in Waist province, one of the main tributaries of the Tigris River to investigate the water quality of the river from August 2014 to January 2015. The study location situated in the southeastern sector of Iraq and surrounded by wide and fertile agricultural lands. Three stations were selected for collecting samples monthly, samples were taken each month. Station one is located at 500 m of the AL - KUT Dam. The second is situated at distance of 15 Km away from the former (Kut- Muwafaqiya) and the latter station is located at 18 Km apart from the second one upon entering the river hand Muwafaqiya. In the present study fourteen physical and chemical
... Show MoreKey words:Jasminumsambac, Volatile oil, Antioxidant.
The purpose of present work is to study the relationship of the deformed shape of the nucleus with the radioactivity of nuclei for (Uranium-238 and Thorium-232) series. To achieve our purposes we have been calculated the quadruple deformation parameter (β2) and the eccentricity (e) and compare the radioactive series with the change of the and (e) as indicator for the changing in the nucleus shape with the radioactivity. To obtain the value of quadruple deformation parameter (β2), the adopted value of quadruple transition probability B (E2; 0+ → 2+) was calculated from Global Best fit equation. While the eccentricity (e) was calculated from the values of the minor and major ellipsoid axis’s (a & b). From the results, it is obvi
... Show MoreTo identify and explore the factors nurses perceive as influencing their knowledge acquisition in relation to diabetes care and its management in Saudi Arabia.
Diabetes continues to pose major healthcare challenges despite advances in diabetes management. Nurses have a crucial role in diabetes care, but diabetes knowledge deficits deter effective collaboration with other healthcare providers in educating patients about diabetes self‐management.
An exploratory descriptive qualitative design.
Coumarin is a natural substance isolated from different plants. It belonges to a group of benzobyrones which consists of a benzene ring joined to a pyrone nucleus. In the present research, a new series of coumarin derivatives were formed. Compound (1) (7-hydroxy-4-methyl Coumarin) was converted into 4-methylquinolin-2(H) derivative (2) by reaction with acetamide, and then reaction of (2) with thiosemicarbazide in ethanol leads to the synthesize of hydrazincarbothioamide derivative (3).The reaction of (3) with ethylchloroacetate in presence of sodium acetate leads to closure ring to get [(1-(5-oxo-2-thioxoimidazolidin-1-ylimino) ethyl)]quinolin-2(1H)-one (4). Mannich bases were prepared through the reaction of (4) with primary
... Show MoreBackground: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b
... Show MoreLung 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
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