Uropathogenic Escherichia coli is the main cause of urinary tract infections, the ability of this bacteria to cause urinary tract infections is related to a variety of virulence factors that enhance colonization and evade the immune response, one of these virulence factors is cytotoxic necrotizing factor 1 toxin which converts the glutamine residue to glutamic acid to activated GTPase Rho family. The study was meant to find out the prevalence rate of the cnf1 gene in Uropathogenic Escherichia coli isolated from Iraqi patients. Conventional laboratory methods were used for primary bacterial identification and molecular methods were used to confirm bacterial identity and gene detection. Escherichia coli was identified in 89/165 (53.93%) of the urine specimens based on cultural characteristics on MacConkey and eosin methylene blue agar, concerning the results of 16SrRNA gene amplification for identification of Escherichia coli, this gene was present in all primary identified 89 isolates, which confirm the identification. cnf1 gene was detected in 37/89 (41.57 %), while 52/89 (58.42%) of isolates lack the cnf1 gene with no significant differences (P>0.05). Remarkably, the current and previous local investigations showed the prevalence rate of the cnf1 gene in uropathogenic Escherichia coli in Iraq has been increasing gradually during the past twelve years. The significant prevalence of cnf1-positive isolates in urinary tract infections suggests the spreading of severely gene-toxic isolates.
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
... Show MoreMethods 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
... Show MoreIt is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin
This work predicts the effect of thermal load distribution in polymer melt inside a mold and a die during injection and extrusion processes respectively on the structure properties of final product. Transient thermal and structure models of solidification process for polycarbonate polymer melt in a steel mold and die are studied in this research. Thermal solution obtained according to solidify the melt from 300 to 30Cand Biot number of 16 and 112 respectively for the mold and from 300 to 30 Cand Biot number of 16 for die. Thermal conductivity, and shear and Young Modulus of polycarbonate are temperature depending. Bonded contact between the polycarbonate and the steel surfaces is suggested to transfer the thermal load. The temperat
... Show MoreThe relationship between pollution levels in river sediment and fluctuating asymmetry of resident silurid fish species,
Systemic lupus erythematosus (SLE) is the prototypic multisystem autoimmune disorder with a broad spectrum of clinical presentations encompassing almost all organs and tissues. Aimes of study determination of integrin- linked kinase 1(ILK-1) and anti-smith antibody(ASAB) levels in serum of Iraqi patients with systemic lupus erythematosus, in addition, that ILK-1 may be as a diagnostic marker of SLE disease, and study the effect of systemic lupus erythematosus on renal function in these patients. This study included 100 females’ patients with systemic lupus erythematosus attending to the Rheumatology Unit in Baghdad Teaching Hospital, Medical City, (Baghdad), in addition to 30 healthy females as controller group were chosen without any chr
... Show MoreThis study focused on determining the markers of Macrophage migration inhibitor (MIF), as well as the N-telopeptides of type I bone collagen (NTX), and some other parameters (alkaline phosphatase (ALP), vitamin D (Vit D), calcium (Ca), phosphorus (P), and magnesium (Mg), and their correlation with other parameters in osteoporosis. One hundred ten subjects were involved in the current study. There were two groups of patients: group I (30) women with severe osteoporosis and group II (30) women with mild osteoporosis. For comparison, 50 apparently healthy individuals were included as a control. Serum levels of MIF, and NTX were significantly higher in groups I and II as compared to the control group, which indicate that these two parameters
... Show MoreIn the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T
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