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-

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

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.

Background: Obesity is a serious public health concern that has reached epidemic proportions; the prevalence, as well as the severity of obesity in adolescents is increasing at an alarming rate. A close relationship was found between weight status and dental caries. Thus this research aimed to assess the prevalence and severity of dental caries among overweight adolescent females in relation to physicochemical characteristics of stimulated whole saliva in comparison with normal weight adolescent females. Materials and methods: The total sample involved for nutritional status assessment is composed of 2678 females aged 13-15 years. This was performed using Body Mass Index specific for age and gender according to CDC growth chart (2000). The

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,

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