In our time, not too long ago, the universities of the world have been fast to take care of the study of an innovative type of technical and human studies, called the science of "comparative literature". Comparative research studies have grown and flourished rapidly in response to the demands of both mental and artistic life. This shows the increasing awareness at both the modern national and the international levels in order to develop through connecting with the international intellectual, nental and artistic currents to nurture ethics and originality. Comparative studies show that the beginning of the comparative literature goes back to the time when the Latin literature was connected to the Greek literature and th

Background: Adenoid cystic carcinoma (ACC) constitutes about 4% of salivary epithelial tumors and is the second common malignant epithelial salivary gland tumor involving both the major and minor salivary glands. Aims of the study is to evaluate immunohistochemical expression of Ki67 and p53 proteins in ACC. Materials and Methods: immunohistochemical analyses of fifteen cases of formalin – fixed paraffin – embedded tissues blocks of ACC of salivary glands using ki67 and p53 antibodies. Results: ki67 was expressed in 6 of 15 ACC (40%) while p53 aberration was demonstrated in 11 of tumor (73.3%). There was a statistically significant difference between the expression of ki67 and p53 proteins in ACC cases (p value = 0.041). Pearson’s cor

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

In this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which

This research aims to numerically solve a nonlinear initial value problem presented as a system of ordinary differential equations. Our focus is on epidemiological systems in particular. The accurate numerical method that is the Runge-Kutta method of order four has been used to solve this problem that is represented in the epidemic model. The COVID-19 mathematical epidemic model in Iraq from 2020 to the next years is the application under study. Finally, the results obtained for the COVID-19 model have been discussed tabular and graphically. The spread of the COVID-19 pandemic can be observed via the behavior of the different stages of the model that approximates the behavior of actual the COVID-19 epidemic in Iraq. In our study, the COV

The objective of this review was to describe the COVID-19 complications after recovery.

     The novel coronavirus 2019 (COVID-19) is a respiratory syndrome with similar traits to common pneumonia. This major pandemic has affected nations both socially and economically, disturbing everyday life and urging the scientific community to develop solutions for the diagnosis and prevention of COVID-19. Reverse transcriptase-polymerase chain reaction (RT–PCR) is the conventional approach used for detecting COVID-19. Nevertheless, the initial stage of the infection is less predictable in PCR tests, making early prediction challenging. A robust and alternative diagnostic method based on digital computerised technologies to support conventional methods would greatly help society. Therefore, this paper reviews recent research bas

Two Prototypes of Transversely Excited at atmospheric pressure (TEA) Nitrogen laser systems (One Stage Blumlein Circuit and Two Stage Blumlein Circuit) were fabricated and operated. High voltage power supply with variable operating voltage (0-20 kv) and operating current (1-3A) was built and tested successfully. The gas flow rate of 15 L/ min and 10 L/ min for OSBC and TSBC was used. The performance of the fabricated systems was studied extensively reaching to the optimum operating conditions. The obtained laser output energy for the first system has linear relationship with the applied voltage. The maximum output energy was about (1.14 mJ) with (10.40) ns pulse duration and the half-wave divergence angle was about (0.1455 m rad). In the

The invasion and spread of cancer cells are two of the most notable characteristics of malignant tumors. Recent studies suggest that the epithelial-mesenchymal transition (EMT) has been linked to this significant occurrence. It is linked to the absence of the epithelial brow and the presence of mesenchymal facial hair. The aims of the present study were to explore the immunohistochemical staining of vimentin and E-cadherin ex vivo as EMT markers and assess their potential as predictive biomarkers for transitional cell cancer (TCC). In this study, 55 paraffin-embedded biopsies from TCC patients and 10 autopsies that appeared to be normal were included. Immunohistochemistry was used to produce patterns of vimentin and E-cadherin expression. W