The relationship of hyperuricemia to kidney disease, diabetes, hypertension and the risk of cardiovascular diseases remain controversial. The aim of this study is to evaluate the use of uric acid (UA) levels to find the higher risk of cardiovascular disease (CVD) in patients with end stage renal disease that have diabetic nephropathy (DN), nephropathy with hypertension (NH) and patients with both diabetic nephropathy with hypertension (DNH). This study deals with 115 patients with end-stage renal disease under hemodialysis sub-grouped into 35 patients with (DN), 40 patients with (NH), and 40 patients with (DNH). Some biochemical parameters were determined in the serum of all participants such as HbA1c, fasting blood glucose (FBG), UA, urea,

The effect of alcoholic extract (2%,4%, 12%) and the fruits aqueous extract (12%,15%,25%,35%) of Melia azedarach and actellic insecticide of 0.01 concentration were tested on the second instar larvae ofOryzaephilus surinamensis .The obtained resuls were reveated that the highest kill ratio 80% at the concentration 12% of the alchoholic extract and 85% of the aqueous extract this was reflected effect abstracts on low rate of age adult emerging of larve treated and low productivity

Background: Titanium implant is widely used in dentistry because of its extraordinary biocompatibility and mechanical properties. To increase bone–implant connection and provide early loading after placement, implant is stored in different storage medium and treated with UV light. Both of them are applicable methods to increase the bioactivity of titanium and overcome the biological aging. This study was designed to assess the effect of vacuum storage method and air storage with and without UV light treated of Cp Ti implant mechanically and histologically. Materials and methods: Titanium screws were acid etched and prepared in four different modes using different storage methods (air or vacuum and, with or without UV treatment. The implan

The impact of exposure to different sizes of particulate matter (PM1, PM2.5, PM7, and PM10) was evaluated in  Babylon concrete plant workers who had been exposed to concrete dust for at least 10 years.  The effects of  these particles on the hematological parameters, malondialdehyde (MDA) levels, and  antioxidant enzymes (catalase and glutathione peroxidase ) were examined. The results exhibited that the levels of PM2.5 and PM10 were higher than the acceptable limits approved by the National Ambient Air Quality Standards (NAAQS). The blood parameters, namely white blood cells (WBC), red blood cell (RBC) and platelets counts, demonstrated non-significant differences between workers exposed to the PM as compared to the control gro

Two quantitative, environment-friendly and easily monitored assays for Ni (II) and Co (III) ions analysis in different lipstick samples collected from 500-Iraqi dinars stores located in Baghdad were introduced. The study was based on the reaction of nickel (II) ions with dimethylglyoxime (DMG) reagent and the reaction of cobalt (III) ions with 1-nitroso-2-naphthol (NN) reagent to produce colored products. The color change was measured by spectrophotometric method at 565 nm and 430 nm for Ni and Co, respectively, with linear calibration graphs in the concentration range 0.25-100 mg L^-1 (Ni) and 0.5-100 mg L^-1 (Co) and LOD and LOQ of 0.11 mg L^-1 and 0.36 mg L^-1 (Ni), and 0.15 mg L^-1 an

The current research deals with spatial relations as a tool to link urban landmarks in a homogeneous composition with monumental sculptures, by identifying these landmarks and the extent of their impact on them, which constitutes an urgent need to evaluate the appropriate place and its effects on them, so that this analytical study is a critical approach adopted in artistic studies of monumental models in Arabcapitals .The current research came in four chapters, the first chapter of which dealt with the research problem, its importance and the need for it, then its objectives that were determined in revealing the spatial relations and their impact on

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med