With the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Introduction: Selenium is an essential trace element involved in different physiological functions of the human body. An inverse relationship between serum selenium levels and cervical intraepithelial neoplasia has been reported. cervical intraepithelial neoplasia is regarded as a potentially premalignant transformation of squamous cells of the cervix. Objectives: To evaluate the relationship between the serum level of selenium and cervical intraepithelial neoplasia. Methods: A case-control study was conducted at Baghdad Teaching Hospital and Iraqi National Cancer Research Center in the University of Baghdad during the period from July 2021 to July 2022. A convenient sample of 100 women was enrolled in the current study and included

The current study aimed to isolate and diagnose the fungi associated with the inflammatory bowel disease patients with 150 samples distributed between 50 samples from Crohn's patients and 50 samples from ulcerative colitis patients, 50 control from Al-Kindy Al Teaching Hospital in Baghdad, Baghdad. Five types of yeast were isolated and identified, namely C. albicans, C.glabarta, Tropicales, C. parapsilosis, C. and C., krusi C. parapsilosis and.and Aspergillus, Penicillium, Muocer, Rhizopous, Saccharomycosis, and Cryptococcus, The results indicated the dominance of Candida spp. In crohn’s disease, the frequency of isolated Candida albicans was 24 (58.54%), Candida glabrata 11 (26.86%), Candida tropicalis 5 (12.2%) and Candida krusi was 1 (

Background: Aortic valve stenosis results from minor to severe degrees of aortic valve maldevelopment. This stenosis causes mild to severe obstruction of the left ventricular outflow .

Objectives : to study the immediate and intermediate results of percutaneous balloon aortic valvuloplasty in patients with congenital valvular aortic stenosis .

Type of the study: A prospective study.

Methods: The study was done on thirty five patients with congenital valvular aortic stenosis who had percutaneous balloon aortic valvuloplasty  in Ibn Al- Bitar Center for Cardiac Surgery from May 2009 to February 2011.

Results

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif