Multiple studies support a role for inflammation in the pathogenesis of coronary atherosclerosis and unstable cardiac syndromes. However, of the known pro-inflammatory cytokines, only elevated plasma levels of interleukin-6(IL-6) have been linked to Unstable Angina. We sought to examine the plasma levels of other major proinflammatory cytokines in similar clinical settings patients with unstable angina and acute myocardial infarction and the relationship extent between them. This study aimed to investigate and compare the level of IL-1 in Unstable Angina and Acute Myocardial Infarction patients. Thirty patients with unstable angina and thirty patients with Acute Myocardial Infarction, also thirty healthy individual as control were included in this study to measure the levels of IL-1alpha, lipid profile and Body Mass Index. There was a significant increase in the level of IL-1 ? in patients with acute myocardial infarction or with unstable angina compared with control group. IL-1 ? positively correlated with total cholesterol, triglycerides, Low Density Lipoprotein and Very Low Density Lipoprotein, while there was a negative correlation with High Density Lipoprotein. In conclusionInterleukin-1 ? significantly increases in patients with acute myocardial infarction or with unstable angina. There was no significant difference in level of IL-1? between AMI and unstable angina patients.
Human cystic echinococcosis caused by Echinococcus granulosus is one of most important and widespreadparasitic zoonoses in the world. The present study was aimed to identify the immunomodulatory activity ofaqueous extract of Cordia myxa fruit since this plant considers one of medically important plants, which is widely used for treatment of numerous diseases, that correlate with the effectiveness of immunized by hydatid cyst fluid antigen HCFAg. Forty Balb/c mice were divided into equal groups, first group was immunized with HCFAg, the second group was treated with aqueous extract of C. muxa fruit, the third group was immunized and treated, the fourth group was as a control. Delayed type hypersensitivity (DTH), Mitotic index (MI) and histop
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreNet pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.
This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.
The Mishrif formation was
... Show MoreIn this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.
Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
... Show MoreNon-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important rol
... Show MoreThis paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.