Singing has significant importance being a major basis for the expressive and cultural production of the societies and a real companion that reflects their artistic career and is strongly connected to the reality of the peoples and the production of the individuals, who are geniuses of arts and culture.
Rural singing represents one of the most well-known artistic singing styles in Iraq, which truly embodied the Iraqi national identity. However, it remained confined to the countryside and did not spread due to the lack of mass media and the recording technologies at that time. It has been pure virgin singing art. The theoretical framework is divided into three axes:

• The Iraqi singing heritage in the twentieth century, a hi

Physiological status and litter size can indeed have a significant impact on ewes' ‎hematological parameters, which are essential indicators of their health. Therefore, this study ‎examined the hematological profiles of ewes during pregnancy with single and twins in the ‎Awassi ewes. The present study involved 232 ewes in good health and at sexual maturity. ‎Among them, 123 ewes had single pregnancies, while 109 ewes had twin pregnancies. The age ‎range of the ewes included in the study was between 3.5 and 4.5 years. Hematological tests ‎were conducted on the sheep's blood samples promptly following collection. The findings ‎demonstrated variations in hematological parameters among pregnant

Background: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need

A range of macrocyclic dinuclear metal (II) dithiocarbamate-based complexes are reported. The preparation of complexes was accomplished from either mixing of the prepared ligand with a metal ion or through a template one-pot reaction. The preparation of the bisamine precursor was achieved through several synthetic steps. The free ligand; potassium 2,2'-(biphenyl-4,4'-diylbis(azanediyl))bis(1-chloro-2-oxoethane-2,1diyl)bis(cyclohexylcarbamodithioate) (L) was yielded from the addition of CS2 to a bis-amine precursor in  KOH medium.A variety of analytical and physical methods were implemented to characterise ligand and its complexes. The analyses were based on spectroscopic techniques (FTIR, UV-Vis, mass spectroscopy and 1H, 13C-NMR sp

The research discusses the obstacles that faced the Iraqi strategic performance in achieving sustainable development after the election of the first Iraqi government in 2005 and the most important strategies to overcome these obstacles.

Background: The SARS-CoV-2 virus causes COVID-19, a respiratory syndrome. It causes inflammation and damages several organs in the body. miRNAs play a role in regulating the infection resulting from SARS-CoV-2. MicroRNA-155, a kind of microRNA linked to viral defences, can affect the immune responses during COVID-19. Objectives: Examination of the involvement of microRNA-155 in the development and severity of COVID-19, as well as finding the correlation between microRNA-155 and viral load (copies/mL) in severe cases of the disease. Materials and Method: A case-control research study was performed between October 2022 and June 2023. It included a cohort of 120 hospitalised individuals with severe cases of COVID-19, together with 115 individu

This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J

It is recognized that organisms live and interact in groups, exposing them to various elements like disease, fear, hunting cooperation, and others. As a result, in this paper, we adopted the construction of a mathematical model that describes the interaction of the prey with the predator when there is an infectious disease, as well as the predator community's characteristic of cooperation in hunting, which generates great fear in the prey community. Furthermore, the presence of an incubation period for the disease provides a delay in disease transmission from diseased predators to healthy predators. This research aims to examine the proposed mathematical model's solution behavior to better understand these elements' impact on an eco-epidemi

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr