The present study aimed to look for the differences in the oxidative stress status in sera and saliva samples of type 2 diabetic Iraqi patients with and without proliferative diabetic retinopathy. As well as to look for the possibility whether this status can be measured in saliva as an alternative sample to that of serum, hence to achieve that total oxidant status, total antioxidant status and oxidative stress index were measured in both sera and saliva samples of two groups of patients with type 2 diabetes mellitus and the healthy individuals. Upon the comparison between patients without proliferative diabetic retinopathy and the control sample the results showed presence of a significant increase (p < 0.05) of total oxidant st

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

(Sb₂S₃)_1-xSn_x thin films with different concentrations (0, 0.05 and
0.15) and thicknesses (300,500 and 700nm) have been deposited by
single source vacuum thermal evaporation onto glass substrates at
ambient temperature to study the effect of tin content, thickness and
on its structural morphology, and electrical properties. AFM study
revealed that microstructure parameters such as crystallite size, and
roughness found to depend upon deposition conditions. The DC
conductivity of the vacuum evaporated (Sb₂S₃)_1-x Sn_x thin films was
measured in the temperature range (293-473)K and was found to
increase on order of magnitude with

The main objective of this study is to experimentally investigate the effect of the CMC polymeric drag reducer on the pressure drop occurred along the annulus of the wellbore in drilling operation and investigate the optimum polymer concentration that give the minimum pressure drop. A flow loop was designed for this purpose consist from 14 m long with transparent test section and differential pressure transmitter that allows to sense and measure the pressure losses along the test section. The results from the experimental work show that increasing in polymer concentration help to reduce the pressure drop in annulus and the optimum polymer concentration with the maximum drag reducing is 0.8 kg/m³. Also increasing in flow rate a

Titanium-dioxide (TiO₂) nanoparticles suspended in water, and ethanol based fluids have been prepared using one step method and characterized by scanning electron microscopy (SEM), and UV–visible spectrophotometer. The TiO₂ nanoparticles were added to base fluids with different volume concentrations from 0.1% to1.5% by dispersing the synthesized nanoparticles in deionized water and ethanol solutions. The effective thermal conductivity, viscosity and pH of prepared nanofluids at different temperatures from 15 to 30 ^oC were carried out and investigated. It was observed that the thermal conductivity, pH, and viscosity of nanofluids increases with the increase in TiO₂ nanoparticle volume fraction

It was found that there was a significant correlation between all tests of the mechanical and electrical activity of the heart (systolic force FC, stroke volume SV, end-diastolic volume, EF volume, and left ventricular volume during diastole LVDD) with the test of the oxygen-phosphating energy system (Markaria). - As safe (Margaria-Kalamen( It was found that there is a significant correlation between all tests of the mechanical and electrical activity of the heart (myocardial systolic force FC, stroke volume SV, end-diastolic volume EDV, and the percentage of heart pumpingEF blood, and left ventricular volume during diastole (LVDD) with the Lactational Oxygen Energy System Test (Wingate Test 30 Second(

The reinforced fiberglass in cement slurry reflects the effect on its properties compared to usual additives. Fiberglass is typically used in cement slurry design for one or another of the following goals: (Earth earthquake, bearing storage, and with differential stresses, to enhance cement durability and increase its compressive strength). The main goal is to use glass fiber and ground fiberglass to improve the tensile strength and moderate compressive strength significantly. On the other hand, the use of glass fibers led to a slight increase in the value of thickening time, which is a desirable effect. Eleven glass fiber samples and milled glass fiber were used to show these materials' effect on Iraqi cement with (0.125, 0.25, 0.5