Objective: To examined the common frequency of cervical cancer in Iraqi women. Study Design: Descriptive study Place and Duration of Study: This study was conducted at the Iraqi Cancer Agency and the Cancer Registry data from the Iraqi Ministry of Health provided assistance in data gathering from 1st April 2020 to 31st December 2021. Methods: The study examined 504 women diagnosed with cervical cancer. Their ages ranged from 20 to over 80 years. The data analysis employed descriptive statistics to determine the frequency, proportion, and incidence of cervical cancer. Results: The cervical cancer was predominantly caused by human papillomavirus in women in 2020 (1.29%) and 2021 (2.1%). In 2020, the number of cases of cervical can

This study focuses on the relative frequency of Streptococcus pneumoniae in children with culture-proven bacterial meningitis. The epidemiology has been investigated with clinical and laboratory findings in The Central Public Health Laboratory, Iraq from April to September, 2010. From (138) samples , (55) cases (39.85 %) were diagnosed by physician as bacterial meningitis, (23) cases (16.66 %) as viral menginitis , (18) cases (13.04 %) as different medical cases (e.g febrile convulsion , meningoencephalitis , epilepsy …etc) and (42) cases (30.43 %) as unidentified medical cases. For bacterial meningitis S.pneumoniae was isolated from (10) cases (18.18 %) only. The median age for bacterial meningitis was (130.75) month and the predomina

This study presents a comprehensive list of the freshwater and marine bivalves distributed in Iraq. A total of 51 species were recorded, and distributed as: 14 freshwater species, and 37 marine species, these species belonging to 25 families, all available remarks on the distribution, taxonomy, and nomenclature of these species were given. This study included the recently collected specimens along with those previously studied and recorded in Iraq.

During the syrvey on natural enemies of whiteflies in Iraq, the following. predators were recorded.

Pseudomonas aeruginosa is a common and major opportunistic human pathogen, its causes many and dangersinfectious diseases due to death in some timesex: cystic fibrosis , wounds inflammation , burns inflammation , urinary tract infection , other many infections otitis external , Endocarditis , nosocomial infection and also causes other blood infections (Bacteremia). thereforebecomes founding fast and exact identification of P. aeruginosafrom samples culture very important.However, identification of this species may be problematic due to the marked phenotypic variabilitydemonstrated by samples isolates and the presence of other closely related species. To facilitate species identification, we used 16S ribosomal DNA(rRNA) sequence data

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and