Background: Parvovirus B19 is a human pathogenic virus associated with a wide range of clinical conditions. During pregnancy congenital infection with parvovirus B19 can be associated with poor outcome, including miscarriage, fetal anemia and non-immune hydrops.  

Objective: The study aimed to determine the prevalenceof Parvovirus B19 DNA in pregnant women attending the Military hospital in Khartoum, demonstrating the association between the virus and poor pregnancy outcomes.

Subjects and methods: This study was a cross sectional study, testing pregnant Sudanese women whole blood samples (n= 97) for the presence of Parvovirus B1

This study aims to determine the prevalence of Entamoeba histolytica, Entamoeba dispar and
Entamoeba moshkovskii by three methods of diagnosis (microscopic examination, cultivation and PCR) that
were compared to obtain an accurate diagnosis of Entamoeba spp. during amoebiasis. Total (n=150) stool
samples related to patients were (n = 100) and healthy controls (n= 50). Clinically diagnosed stool samples
(n=100) were collected from patients attending the consultant clinics of different hospitals in Basrah during
the period from January 2018 to January 2019. The results showed that 60% of collected samples were
positive in a direct microscopic examination. All samples were cultivated on different media; the Bra

The research aims to identify the importance of using analytical procedures in the detection of creative accounting practices. To achieve this goal, (100) questionnaires were prepared and distributed to the auditors in the Federal Financial Supervision Bureau and the authorized auditors' offices and practitioners of the auditing profession in Iraq. For the purpose of testing the research hypothesis and analyzing data, some appropriate statistical methods have been used and the use of the statistical program (SPSS) to analyze the data. The results of the research showed that the analytical procedures and tests applied by the auditor have a role in revealing and limiting creative accounting practices and methods and that auditors u

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a