Survival analysis is widely applied to data that described by the length of time until the occurrence of an event under interest such as death or other important events. The purpose of this paper is to use the dynamic methodology which provides a flexible method, especially in the analysis of discrete survival time, to estimate the effect of covariate variables through time in the survival analysis on dialysis patients with kidney failure until death occurs. Where the estimations process is completely based on the Bayes approach by using two estimation methods: the maximum A Posterior (MAP) involved with Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation Maximization (EM) algorithm. While the other

Evaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed

      In this research, carbon nanotubes (CNTs) is prepared  through the Hummers method with a slight change in some of the work steps, thus, a new method has been created for preparing carbon nanotubes which is similar to the original Hummers method that is used to prepare graphene oxide. Then, the suspension carbon nanotubes is transferred to a simple electrode position platform consisting of two electrodes and the cell body for the coating and reduction of the carbon nanotubes on ITO glass which represents the cathode electrode while platinum represents the anode electrode. The deposited layer of carbon nanotubes is examined through the scanning electron microscope technique (SEM), and the images throughout the research show the

Objective: To assess the impact of pregnant women’s depression state upon their pregnancy outcome Methodology: A descriptive purposive study was used to assess the impact of pregnant women’s depression state on their pregnancy outcomes. The study was conducted from (22nd \ September \ 2020 to 15th \ February \ 2021). A non-probability sample (purposive sample) was selected from 100 women. Data were collected through an interview with the mother in the counseling clinic, during the third trimester of pregnancy, as well as after childbirth in the labour wards to assess the outcome of pregnancy. Data were analyzed through descriptive statistics (frequency and percentages). Results: The most important thing observed in this study was the ne

A rapid and sensitive method for analysis of amino acid hydrolysates of nigella sativa L seed has been developed using O-phthaldialehyde(OPA ) as a pre-column derivatizing agent. OPA reagents in the presence of mercaptoethanol react rapidly with primary amino acids ( less than 60 sec.) to form isindole derivatives which easily separated with good selectivity on ODS column. Resolution of amino acid derivatives is carried out with a methanol gradient in 0.01 maqueous sodium acetate. pH 7.1 . The quantitation of amino acid derivatives is reproducible within an average relative deviation of + 1.4% the linearity for most amino acids were more than 0.9993 with detection limit of 0.2 ppm. 15 amino acid were detected in the analysis of

Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr