Background: The fracture of instruments within root canal during endodontic treatment is a common incidence, fracture because of fatigue through flexure occurs due to metal fatigue, this study aimed to assess the effect of curvature angle and rotational speed on the cyclic fatigue of different type of Endodontic NiTi Rotary Instruments and compare among them. Materials and method: Three types of rotary instruments with tip size 0.25: ProTaPer F2 (Densply, Malifier) Revo-S SU( 0.06 taper, MicroMega) and RaCe system (0.06 taper, FKG, Dentaire), Forty file of each instrument were used within two canals with angle of curvature (40 &60 )at two speed (250&400)RPM, twelve group were formed for all instruments(total number=120),ten file for each group. The testing canals customized within stainless steel block covered with glass face, the time to fracture recorded and the mean of cycles to fracture (MCF) detected for each instrument. Data were analyzed statistically by ANOVA, LSD and Independent T-test at 5% significant level. Result: there was a highly significant difference of curvature angle and significant difference of rotational speed on the fracture resistance of instruments. RaCe revealed the best fracture resistance followed by ProTaper then Revo-S that showed the less resistance. Conclusion: The rotary instruments more prone to fracture when used at more curvature angle and higher rotational speed, as well as the rotary instruments differ from each other according to manufacturing process, taper, cross section and other factors.
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Many studies have been made and still concerning the field of translation. Since the mid-90's a considerable amount of researches has tackled the problem of gender and its effect on the process and the product of translation. Simon (1996, p 508) points out that when comparing women and men as translators and writers through history, women seem to be the weaker side. This paves the way to feminist movements which produce prominent studies concerning gender as a concept and translator's gender as practice on the quality and the accuracy of the translation.
Flotow (in Meschia, 2012, p 1-4) outlines several issues that can be
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Comparative morphological study has been treated for two species of the genus Chaenorhinum (D.C.) Richb., These species were: 1. Chaenorhinum calycinum 2. Chaenorhinum rubrifolium (Robill. & cast. Ex Lam. & DC.) Fourr. The genus belong to the family Scorphulariaceae. Morphological characters has been studies for: root, stem, leaves, flowers (calyx, corolla, androcium including filaments and anthers, gynocium including ovary, style and stigma), fruits and seeds also has been characterized. Key for there two species presented using some quantitative characters. Other characters like shape of fruits and seeds were used too, and they were of a useful taxonomic value
Comparative morphological study has been treated for two species of the genus Chaenorhinum (D.C.) Richb., These species were: 1. Chaenorhinum calycinum 2. Chaenorhinum rubrifolium (Robill. & cast. Ex Lam. & DC.) Fourr. The genus belong to the family Scorphulariaceae. Morphological characters has been studies for: root, stem, leaves, flowers (calyx, corolla, androcium including filaments and anthers, gynocium including ovary, style and stigma), fruits and seeds also has been characterized. Key for there two species presented using some quantitative characters. Other characters like shape of fruits and seeds were used too, and they were of a useful taxonomic value
<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope
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This paper studies the behavior of axially loaded RC columns which are confined with carbon fiber reinforced polymers’ sheet (CFRP) and steel jackets (SJ). The study is based on twelve axially loaded RC columns tested up to failure. It is divided into three schemes based on its strengthening type; each scheme has four columns. The main parameters in this study were the compressive strength of the concrete and steel reinforcement ratio. Furthermore, the results of the experimental test showed a substantial enhancement in the column's load-carrying capacity. When compared to the original columns, the CFRP sheet had a significant effect on improving the ductility of the column by increasing the axial deformation by about 59.2 to 95.7
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
... Show MoreIn the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
... Show MoreAn experiment was conducted to study how SAE 50 engine oil contaminated with diesel fuel affects engine performance. The engine oil was contaminated with diesel fuel at concentrations of 0%, 1%, and 3%. The following performance characteristics were studied: brake-specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature. Each treatment was tested three times. The three treatments (0%, 1%, and 3%) were analyzed statistically with a one-way ANOVA model at the 5% probability level to determine if the three treatments produced significant differences in engine performance. The statistical results showed that there were significant differences in engine performance metrics among the three treatments. The 3
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