ABSTRACT— In primary teeth, root canal treatment is a time consuming and challenging procedure, particularly during the most important step in endodontic treatment which is the preparation of the canal. Pulpectomy is the treatment of choice in all the necrotic primary teeth. For better treatment protocol, advancing technology brought the rotary system to reduce the manual dexterity and improve the quality of treatment for pulpectomy. This study aimed to compare and assess the efficacy of cleaning and the time required for the instrumentation during the preparation of root canals of the primary molars using the rotary and the manual (conventional) systems. Thirty root canals of primary teeth were selected. These teeth submitted to access opening and then all the canals injected with Indian ink. Then, 48 hours later, the teeth were randomly classified into two groups: group A (n=fifteen tooth): where the manual preparation of the root canals was done by stainless steel K- files, while group B (n= fifteen tooth): consisted of the root canals that prepared with rotary two shape system. The total instrumentation time was measured using a digital stopwatch. After that, a disk bur was used to section the roots. Then, a digital camera was used to photograph the specimens to evaluate the root canal cleaning. The cleaning efficacy was compared at the coronal, middle and apical level. In the coronal third, rotary two shape system showed more removal to the ink than the K-file with statistical significant difference (p <0.05), however, for the middle third of the canal, no statistical difference was found between the two systems (p=0.05). While at the apical level, K-file showed more removal to the ink than the rotary two shape system and with statistical significant difference (p <0.05). Evaluation of the total samples revealed no statistical significant difference concerning the efficacy of cleaning between K-files and rotary two shape system files. The group that was rotary prepared took less time for the canal preparation as compared to the manual group (80.063 sec., 144.576 sec. respectively). No significant difference was found between the two systems concerning the cleaning efficacy. Instrumentation done by the rotary system took significantly less time than that of the manual. KEYWORDS: Cleaning efficacy, manual instrumentation, primary teeth, rotary instrumentation.
Aging of asphalt pavements typically occurs through oxidation of the asphalt and evaporation of the lighter maltenes from the binder. The main objective of this study is to evaluate influence of aging on performance of asphalt paving materials.nAsphalt concrete mixtures, were prepared, and subjected to short term aging (STA) procedure which involved heating the loose mixtures in an oven for two aging period of (4 and 8) hours at a temperature of 135 o C. Then it was subject to Long term aging (LTA) procedure using (2 and 5) days aging periods at 85 o C for Marshall compacted specimens. The effect of aging periods on properties of asphalt concrete at optimum asphalt content such as Marshall Properties, indirect tensile strength at 25 o C,
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This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec
... Show MoreArtificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and
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The researcher deals with an important issue in her research - especially as she progresses to the doctoral stage thanks to God (Almighty) and his mentor - the relationship of philosophy to nodal origins. Therefore, she studied the philosophy of Shirazi, which is the key to the mental solutions that the speakers and philosophers stopped. And to conclude scientific results as well as the study of philosophy researcher as a station in the doctoral stage, to be familiar with the philosophical interpretation and the origins of the faith and its philosophical vocabularies such as existence, self, movement, astronomy, time and others. At the same time draw the attention of science students to the issue of philosophical interpretation and its r
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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