MO Khudhair, 2020

Objectives: This study aimed to identify and study most properties of the specific and general health-related
quality-of-life (HRQoL) in prostate cancer patients, as well as creating a new measurement scale for assessing QoL
among prostate cancer patients.
Methodology: A cross sectional (descriptive) study was conducted to evaluate General Quality of life in patients
with prostate cancer. A sample of 100 prostate cancer patients from Al-Amal National hospital for cancer
management and Oncology Center in Baghdad Medical City. This study applied format of General World Health
Organization Quality of Life-BERF questionnaire. The methods used descriptive statistics to evaluate the General
QoL-Improvements, as well as inf

Aim of the study: This study's goal was to determine how laser surface alteration affected wettability of injectable thermoplastic acrylic and heat cure acrylic denture base materials. Materials and methods: Injectable thermoplastic acrylic resin (Deflex) and heat cure acrylic (Procryla) were used in this study to produce forty-disc shaped specimens, 20 specimens for each material type. The control group was made up of ten samples of each type of plastic denture base material. The other ten samples were treated with a nano-pulse fiber-optic lens Nd:YAG laser. The results were looked at with the Kruskal-Wallis test and the unpaired t-test (a=.05). Results: Compared to the control groups, the laser-treated groups were more likely to sti

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number