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.

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

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

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

The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. E

KE Sharquie, AA Noaimi, MA Al-Shukri, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3

      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-

Background: A Catheter-associated with candidiasis infection is the most common nosocomial infection and the objective of this work is to isolate and identify Candida species from catheterized patients by ordinary culture and PCR.Objective:To study the isolation and identification of Candida species from catheterized patients by culture media and polymerase chain reaction(PCR).Methods: One hundred and thirty five Candida species isolates were obtained from urine culture of catheterized specimens from male and female patients , During the period between October 2011 to April 2012 , attending AL-Ramadi general teaching Hospital. A quantitative urine culture for isolation and identification of Candida species was. The isolation of Candida s

Hepatitis B virus (HBV) infection is a significant global health problem. Populations of different ethnicities show great heterogeneity in HBV genotype frequency distributions. A cross-sectional study was conducted during June–October 2018 to determine frequency of HBV genotypes among chronic HBV patients from Baghdad, Iraq. The method of detection was nested polymerase chain reaction system. Further, the study assessed the impact of HBV genotypes on serum level of liver-function tests: total serum bilirubin, alkaline phosphatase, alanine aminotransferase and aspartate aminotransferase. Eighty chronic HBV patients were enrolled in the study. Six HBV genotypes were identified (A, B, C, D, E and F). The most frequently encountered genotypes