Different factors have been examined to be related with the prevalence of Girdiasis in the north of Baghdad in human beings which were (gender, age , occupation ,family size,faecal status and presence of domestic animals) during the period from the beginning of April 2009 till the end of March 2010. This study revealed that the total rate of infection in human being was 11.66% , and no significant differences (p?0.05) were noticed between male and female as their rates of infection were 52.32% and 47.68% respectively , as well as no significant relation was observed between faecal status and the rate of infection, the percentage of positive cases in diarrheal patients was higher than the non diarrheal patients who were 74.41 and 25.59 respe

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

Background: The individual differences in emotional and behavioral style can be examined through personality instruments. These differences may explain the health status of the individuals. The purpose of the present study was to assess the influence of Personality Types on gingival and periodontal health status among teachers in Baghdad city in relation to selected salivary hormone (Dehydroepiandrosterone). Materials and methods: Females teachers 534 of randomly selected schools were subjected to personality questionnaire using The Riso-Hudson Enneagram Type Indicator. Teachers were examined to estimate the periodontal status according to the Community Periodontal Index (CPI). A group of teachers were selected for salivary analysis of Dehy

Background: Nutritional condition was reported as one of the factors affecting the oral health status, particularly among underprivileged groups. Orphans are one of the known high-risk groups. The aims of this study were to assess the nutritional status of orphans, and its impact on the oral health status. Materials and Methods: Five-hundred children aged 6-12 years old, 254 males and 246 females: institutionalized, non-institutionalized orphans and controls were participated in this study. Nutritional status assessed according to body mass index (BMI). Ramfjord index teeth were examined to assess oral cleanliness and gingival condition. All data were analyzed using SPSS version 23. Results this study revealed the institutionalized orphans

Vaccination is a vital cornerstone of public health, which has saved countless lives throughout history. Therefore, achieving high vaccination uptake rates is essential for successful vaccination programs. Unfortunately, vaccine uptake has been hindered by deferent factors and challenges. The objective of this study is to assess COVID-19 vaccine uptake and associated factors among the general population.

Diabetes mellitus type 2 (T2DM) formerly called non-insulin dependent diabetes mellitus (NIDDM) or adult-onset diabetes is a common disease. Rheumatoid factor is a well-established test used in the diagnosis and follows the prognosis of rheumatoid arthritis (RA). Rheumatoid factor is sometimes found in serum of patients with other diseases including diabetes mellitus (DM), due to the presence of pro-inflammatory cytokines such as TNF- α which play an important role in chronic inflammatory and autoimmune diseases like rheumatoid arthritis (RA). The aim of the study is to investigate the associations between type 2 diabetes mellitus (T2DM) and rheumatoid arthritis (RA) in scope of rheumatoid factor (RF), hyperglycemia a