Background: The purpose of this study was to evaluate and compare centering ability and canal transportation of simulated S-shaped canals instrumented with four different types of rotary nickel-titanium systems. Materials and Methods: Forty simulated S-shaped canals in resin blocks were divided into four groups of ten each and were instrumented to an apical size 25 by different instrumentation technique using ProTaper Universal files (group A), ProTaperNext (group B), Reciproc (group C) and WaveOne (group D).Centering ability and canal transportation was measured at (11) measuring points from D0 to D10 bysuperimposion of the pre- and post-operative images obtained by using digital camera in standardized manner. An assessment of the canals shape was determined using Photoshop CS2 and AutoCAD software. The data were analyzed statistically using ANOVA and LSD test. Results: In terms of centering ratio values, there was no statistically significant difference among the four groups at the coronal portion of the canals, with ProTaper system showing the least centering ability at all levels except at apical foramen. At the apical curvature, the Reciproc and WaveOne groups showed better centering ability than ProTaperNext and the difference was statistically highly significant among them at these points, while at the coronal curvature the ProTaperNext showed better centering ability than Reciproc and WaveOne. Canal transportation was seen in all groups but the ProTaper systems showed more transportation values at almost levels when compared with the other groups with the least values by ProTaperNext at the coronal curvature and the least values by Reciproc and WaveOne at the apical curvature. Conclusions: Under the conditions of this study, ProtaperNext ,WaveOne and Reciproc instruments maintained the original curvature significantly better than ProTaperUniversal at almost levels. ProtaperNext showed a better shaping ability than Reciproc and WaveOne at the coronal curved section while at apical curved section Reciproc and WaveOne showed a better shaping ability than ProtaperNext. Key words: centering ability, canal transportation, ProTaperNext, Reciproc, WaveOne.
Background: Recurrent aphthous ulceration (RAU) is an inflammatory condition of unknown etiology characterized by painful recurrent (single or multiple) ulcerations of the oral mucosa. It is one of the most common and poorly understood mucosal disorders. It occurs more frequently in times of stress. Local and systemic conditions, genetic, immunologic, microbial factors, and oxidative stress may play a role in the pathogenesis of RAU. The objective of this study was to evaluate the free radical metabolism and antioxidant activity of RAU patients treated by lavender or flax oil paint.
Materials and Methods: Sixty-six RAU patients were enroll
... Show MoreThe current research aims to answer the following questions: what is the substance of democracy? What is the content of a democratic society? What is the role of university professor in the democratic development of the student university in light of the new Iraqi society? In order to achieve the goals of the research, the researcher developed an a questionnaire based on literature, Iraq's draft constitution in 2005, and his experience of the field of teaching human rights and public freedoms and the teaching of democracy. It was applied to a sample of faculty members in Department of Education and Psychology / College of Education / University Baghdad for the year 20014 were obtained their answers were then processed statistically. Henc
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The purpose of this paper is to give some results theorems , propositions and corollaries concerning new algebraic systems flower , garden and farm with accustomed algebraic systems groupoid , group and ring.
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
The purpose of this research is to find the estimator of the average proportion of defectives based on attribute samples. That have been curtailed either with rejection of a lot finding the kth defective or with acceptance on finding the kth non defective.
The MLE (Maximum likelihood estimator) is derived. And also the ASN in Single Curtailed Sampling has been derived and we obtain a simplified Formula All the Notations needed are explained.
DBN Dr. Liqaa Habeb, International Journal of Multidisciplinary Reseach, 2015