Most drugs undergo some metabolism in the liver before excretion by the kidneys or bile. Thus, it is not surprising that liver injury may be provoked due to its exposure to various drugs and compounds. Drug-induced cholestatic liver injury may occur particularly under conditions of increased drug concentrations, genetic alterations in expression of enzymes or transporters. Additionally, the drug-induced cholestasis can be caused by direct toxic effects of drugs or their metabolites on different hepatic cell types or through an immune-mediated process. Amoxicillin/ clavulanic acid, an antibiotic that is therapeutically utilized for the treatment of a number of bacterial infections. Omega-3 fatty acids are unsaturated fatty acids that have ro

The aim of this work is to evaluate some mechanical and physical
properties (i.e. the impact strength, hardness, flexural strength,
thermal conductivity and diffusion coefficient) of
(epoxy/polyurethane) blend reinforced with nano silica powder (2%
wt.). Hand lay-up technique was used to manufacture the composite
and a magnetic stirrer for blending the components. Results showed
that water had affected the bending flexural strength and hardness,
while impact strength increased and thermal conductivity decreased.
In addition to the above mentioned tests, the diffusion coefficient
was calculated using Fick’s 2nd law.

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

The dramatic series on television have a great impact on people’sattitudes towards dialects of language varieties, by relating theconceptual pictures or prototypes presented by series’ characters tothose dialects. This study aims to show the influence of TV series onIraqi university learners’ gender and age in relating positive ornegative semantic qualities to their dialects. To this end, 150 Iraqi EFLlearners have participated in this study to examine their attitudestowards Baghdadi, Mousli and Nasiriya dialects. The data arecollected by Lambert, Hodgson, Gardner, Fillenbaum's (1960)matched guise technique and then labeled by Willmorth’s (1988)subjective reaction test. A structured interview is conducted to supportthe data

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

Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

Background:This is a prospective study of three children presented to us in the Orbital clinic in AL ShahidGazi Al Hariri Hospital with painless proptosiswith suspension of Hydatid disease.Objectives: : Orbital hydatid disease is a rare lesion accounting for less than 1% of the total lesions of the body (1, 2). Orbital cysts presented as a primary lesion in our study which is rare to have such lesion without involvement of other organs (3). Humans represent the intermediate host where the commonly affected organ are liver and the lung (10-15%) (4). Methods:This is a prospective study of three Children presented to us in the Orbital clinic in Al Shahid Ghazi Alhariri Hospital with painless proptosis with suspension of Hydatid disease, dep