The present study discusses the names of the Day of Resurrection in Uri Rubin’s translations of the Holy Qur’an. To identify the translation difficulties and complications and to find out the Hebrew equivalence, the study, through the application of a comparative analytical approach, aims at analyzing the linguistic structures of Day of Resurrection names cited in the Holy Qur’an. Heavenly religions are rich with distinct and unique terms that distinguish and reflect their specificity of other religions; something requires a great accuracy in the translation of such terminology. By investigating selected examples of the names of the Day of Resurrection in Arabic and Hebrew, the present study sheds light on the morphological and semant

The optimal design of any structural elements requires examining all environmental risks, emergency accidents, and standard load cases. Exposure to fire is one of the most common safety threats. Nowadays wide developments are achieved in the field of concrete technology, therefore, experimental and theoretical investigations should be performed on the characteristics of such developed materials under different loading conditions. This study investigates the impact of fire exposure on the mechanical characteristics of self-compacting concrete, specifically compressive and tensile strength, modulus of elasticity, and stress-strain relation. The adopted fire exposure consisted of six steady-state temperatures (300, 400, 500, 600, 700,

The research article deals with the process of building or rebuilding the state in Iraq after 2003 in its various dimensions, in light of the vision and foundational procedures that were developed and supervised by the United States in cooperation with the new leaders of Iraq based on the mechanism of sectarianethnic representation, and diagnosing the imbalances that arose out of that vision and the accompanying procedures, which led to the emergence of new variables in the political process, especially in the post-ISIS* phase, which produced important challenges to the political system and the Iraqi state. The political dynamics and balances emerging after ISIS* represented at the same time opportunities and risks in the process of

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

       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 the present article, we implement the new iterative method proposed by Daftardar-Gejji and Jafari (NIM) [V. Daftardar-Gejji, H. Jafari, An iterative method for solving nonlinear functional equations, J. Math. Anal. Appl. 316 (2006) 753-763] to solve two problems; the first one is the problem of spread of a non-fatal disease in a population which is assumed to have constant size over the period of the epidemic, and the other one is the problem of the prey and predator. The results demonstrate that the method has many merits such as being derivative-free, overcome the difficulty arising in calculating Adomian polynomials to handle the nonlinear terms in Adomian Decomposition Method (ADM), does not require to calculate Lagrange multiplier a