Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete hazard function and the time-dependent parameters, two estimation methods have been used that depend on the Bayes method according to dynamic modeling: the Maximum A Posterior method (MAP) This method was done using numerical methods represented by a Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation maximization algorithm (EM), the other method is represented by the Hybrid Markov Chains Monte Carlo (HMCMC) method using the Metropolis Hasting algorithm (MH) and Gypsum sampling (GS). It was concluded that survival analysis by descretization the data into a set of intervals is more flexible and fluid, as this allows analyzing risks and diagnosing impacts that vary over time. The study was applied in the survival analysis on dialysis until either death occurred due to kidney failure or the competing event, represented by kidney transplantation. The most important variables affecting the patient’s cessation of dialysis were also identified for both events in this research.
Genetic polymorphisms of genes whose products are responsible for activities, such as xenobiotic metabolism, mutagen detoxification and DNA-repair, have been predicted to be associated with the risk of developing lung cancer (LC). The association of LC with tobacco smoking has been extensively investigated, but no studies have focused on the Arab ethnic- ity. Previously, we examined the association between genetic polymorphisms among Phase I and Phase II metabolism genes and the risk of LC. Here, we extend the data by examining the correlation of OGG1 Ser326Cys combined with CYP1A1 (Ile462Val and MspI) and GSTP1 (Ile105Val and Ala103Val) polymorphisms with the risk of LC. Polymerase chain reaction- restriction fragment length polymorphism (
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Background: Dental implant considers a unique treatment option for the replacement of missing dentition. The new trend of implants is looking for materials which accelerate bone formation in bone implant interface and enhance osseointegration to provide immediate loading directly after placement and decrease the time period which is disturbs patients and uncomfortable. The aim of the study was to evaluate the effect of nano zirconium oxide (ZrO2) and nano hydroxyapatite (Hap) mixture coating of screw shaped commercially pure titanium (cpTi) implants on bond strength at the bone implant interface with torque removal test and histological analysis in comparison with non coated implants. Materials and methods: Forty screws were machined from c
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Background: Malnutrition in human life may adversely affect various aspects of growth at different stages of life. Teeth are particularly sensitive to malnutrition. Malnutrition may affect odontometric measurement involving tooth size dimensions. The aim of this study is to estimate the effect of nutrition on teeth size dimension measurements among children aged 5 years old. Materials and methods: This study was conducted among malnourished group in comparison to well-nourished group matching with age and gender. The present study included 158 children aged 5 years (78 malnourished and 80 well-nourished). The assessment of nutritional status was done by using three nutritional indicators, namely Height-for-age, Weight-for-age and Weight-fo
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This paper introduces a relation between resultant and the Jacobian determinant
by generalizing Sakkalis theorem from two polynomials in two variables to the case of (n) polynomials in (n) variables. This leads us to study the results of the type: , and use this relation to attack the Jacobian problem. The last section shows our contribution to proving the conjecture.
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The aims of this study are to measure the defect rate and analyze the problems of production of ready concrete mixture plant by using Six Sigma methodology which is a business strategy for operations improvement depending basically on the application of its sub-methodology DMAIC improvement cycle and the basic statistical tools where the process sigma level of concrete production in the case study was 2.41 σ.
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