In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

n each relapse. Objjec tt iiv es :: To sttudy diifffferentt ffacttors whiich miightt be associiatted or lleadiing tto
tthe occurrence off rellapse iin nephrottiic syndrome
Metthods:: A retrospective study of seventy patients with nephrotic syndrome with age range of 1-14 years, who were diagnosed and treated in Child's Central Teaching Hospital over the period of 1st of January and 1st of July 2008.
The patients were divided into three groups; frequent relapses group, infrequent relapses group and undetermined group. We compared between frequent relapses group and infrequent relapses group in regard to age, sex, type of presentation, biochemical findings which include; total serum protein, serum albumin and renal function test,

A simple, economical and selective method employing ion pair dispersive liquid−liquid microextraction (DLLME) coupled with spectrophotometric determination of carbamazepine (CBZ) in pharmaceutical preparations and biological samples was developed. The method is based on reduction of Mo(VI) to Mo(V) using a combination of ammonium thiocyanate and ascorbic acid in acidic medium to form a red binary Mo(V) thiocyanate complex. After addition of CBZ to the complex, extraction of the formed CBZ−Mo(V)−(SCN)6 was performed using a mixture of methylene chloride and methanol. Then, the measurement of target complex was performed at the wavelength of 470 nm. The important extraction parameters affecting the efficiency of DLLME were studied and o

Activation of farnesoid X receptor (FXR) markedly attenuates development of atherosclerosis in animal models. However, the underlying mechanism is not well elucidated. Here, we show that the FXR agonist, obeticholic acid (OCA), increases fecal cholesterol excretion and macrophage reverse cholesterol transport (RCT) dependent on activation of hepatic FXR. OCA does not increase biliary cholesterol secretion, but inhibits intestinal cholesterol absorption. OCA markedly inhibits hepatic cholesterol 7α‐hydroxylase (Cyp7a1) and sterol 12α‐hydroxylase (Cyp8b1) partly through inducing small heterodimer partner, leading to reduced bile acid pool size and al

A numerical study of the two-dimensional steady free convection flow in an inclined annulus between two concentric square cavities filled with a porous medium is presented in this paper for the case when the side outer walls are kept with differentially heated temperature while the horizontal outer walls and the inner walls are insulated. The heated wall is assumed to have spatial sinusoidal temperature variation about a constant mean value. The Darcy model is used and the fluid is assumed to be a standard Boussinesq fluid. For the Cartesian coordinate system, the governing equations which were used in stream function form are discretized by using the finite difference method with successive under – relaxation method (SUR) and are solv

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac