Background: Many previous studies were concerned with
the relationship between gestational diabetes and the
development of vaginal candidiasis in pregnant women. In
this study, our aim is directed to uncover glucose tolerance
status in non-diabetic pregnant women inflicted with
candida albicans.
Methods: Thirty-four pregnant women with vaginal
condidiasis (as demonstrated by microscopy) were enrolled
in this study. The patients were nearly similar in their
anthropometric and demographic criteria with those of the
healthy pregnant women (control group, forty –two
women). Fasting plasma sugar and glucose tolerance test
were alone for all patients and control group.
Results: fasting plasma sugar was significantly higher in
the candidiasis-positive pregnant women in comparison to
those of candidiasis-negative subjects (5.09 mmol/L vs.
4.71, p <0.02). Plasma glucose level after 30 minutes of
performing oral glucose tolerance test was also significant
(8.47mmol/Lvs. 7.84, P <0.04). The same trend of
significance was noticed after 60 minutes and 120 minutes
of performing the corresponding test.
The results were (8.13 mmol/L vs. 7.10, P <0.02) and
(6.90mmol/L vs. 6.15, P<0.05) respectively.
Conclusion: the results reveal an impaired oral glucose
tolerance test in pregnant women with candida albicans
In this paper has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi
... Show MorePrediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered
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... Show MoreGlass Fiber Reinforced Polymer (GFRP) beams have gained attention due to their promising mechanical properties and potential for structural applications. Combining GFRP core and encasing materials creates a composite beam with superior mechanical properties. This paper describes the testing encased GFRP beams as composite Reinforced Concrete (RC) beams under low-velocity impact load. Theoretical analysis was used with practical results to simulate the tested beams' behavior and predict the generated energies during the impact loading. The impact response was investigated using repeated drops of 42.5 kg falling mass from various heights. An analysis was performed using accelerometer readings to calculate the generalized inertial load
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