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Background: Antibacterial action of root canal filling is an important factor for successful root canal treatment, so the aim of the study was to identify and to compare the antimicrobial effect of new sealer (GuttaFlow) to commonly used endodontic sealers (AH Plus, Apexit and EndoFill) against four endodontic microbes. Materials and methods: Twenty patients aged (30-40) years with infected root canals were selected. Four types of microorganisms were isolated from root canals (E faecalis, Staphylococcus aureus, E coli and Candida albicans) and cultured on Mueller Hinton agar Petri-dishes. After identification and isolation of bacterial species, agar diffusion method was used to assess the antibacterial action of four contemporary endodontic

Urinary tract infection (UTI) is a considerable problem aecting the health of people each year. It is caused by various Gram-positive (G+ve) and Gram-negative (G-ve) pathogens. It is an important illness in the world aecting all age groups across their life span. Objectives: To identify the most common aerobic bacteria that cause UTIs and their antibiotic susceptibility and antimicrobial activity of plant extracts of the males' patients. Materials and methods: The study involved 35 midstream urine samples from the male students (University of Baghdad, Baghdad, Iraq) with suspicious symptoms of UTI, during the period from January-March 2018. Each urine sample was cultured rst on Mannitol Salt Agar and MacConkey agar plates to dierentiate

The oxidative degradation of Orange G dye by nanosized CeO₂ catalyst has been performed in this study. The catalyst was prepared by precipitation method. Various characterization techniques were carried out to study the physical and chemical properties of the synthesized catalyst. The XRD result confirms well the formation of CeO₂ cubic phase.  The FTIR result showed the effect of calcination temperature for CeO₂ was clearly observed due to reduction in band intensity compared to uncalcined Ce nitrate sample. Meanwhile, the diffused reflection spectra recorded reflection spectra at 414 nm with an energy gap of 3.2 ev. The decolorization of Orange G dye by oxidation process were carried out  unde

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This paper proposes improving the structure of the 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. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n