Objectives: Successful endodontic treatment outcome requires effective shaping and cleaning of root canals. This study aims to evaluate the smear layer removal after continuous chelation (CC) ) NaOCL\HEDP( and sequential chelation (SC) )NaOCL\EDTA( and their influence on the push-out bond strength (POBS) of Bio-C sealer. Materials and Methods: Palatal roots of the maxillary first molar (n=72) were divided into four groups (n=18) as follows: 3% NaOCL, SC: 3% NaOCL followed by 17% EDTA, CC: 3% NaOCL \9% HEDP and Distilled water. Thirty-two roots (n=8/group) were split longitudinally for smear layer evaluation using SEM. Forty roots were obturated with Guttapercha and Bio-C sealer using a single cone technique. Three sections were taken horizontally from the coronal, middle, and apical third (1.5±0.1 mm thickness) for the push-out test using a universal testing machine. The Kruskal-Wallis and Mann-Whitney tests were used to analyze the SEM data, while the One-way analysis of variance (ANOVA) test and the Tukey test were used to analyze POBS data. Z test to compare failure mode. Results: There was no difference between SC and CC in the smear layer removal at all thirds (p>0.05). The POBS in CC was significantly higher than SC in all thirds (p
Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface
... Show MoreIn information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
... Show MoreThis paper presents a hybrid approach called Modified Full Bayesian Classifier (M-FBC) and Artificial Bee Colony (MFBC-ABC) for using it to medical diagnosis support system. The datasets are taken from Iraqi hospitals, these are for the heart diseases and the nervous system diseases. The M-FBC is depended on common structure known as naïve Bayes. The structure for network is represented by D-separated for structure's variables. Each variable has Condition Probability Tables (CPTs) and each table for disease has Probability. The ABC is easy technique for implementation, has fewer control parameters and it could be easier than other swarm optimization algorithms, so that hybrid with other algorithms to reach the optimal structure. In the
... Show MoreIn real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson†and the “Expectation-Maximization†techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i
... Show MoreThis review will focus on protein and peptide separation studies of the period 1995 to 2010. Peptide and protein analysis have developed dramatically after applying mass spectrometry (MS) technology and other related techniques, such as two-dimensional liquid chromatography and two-dimensional gel electrophoresis. Mass spectrometry involves measurements of mass-to-charge ratios of the ionized sample. High-performance liquid chromatography (HPLC) is an important technique that is usually applied before MS is conducted due to its efficient separation. Characterization of proteins provides a foundation for the fundamental understanding of biology aspects. In this review, instrumentation, principle, applications, developments, and accuracy o
... Show MoreThe introduction and importance of the research included that physical education and its various activities are important for the disabled. The exercise of physical activities by the disabled effectively contributes to raising their level of fitness and reducing diseases caused by lack of movement. Disabled people often suffer from psychological and social problems, and this feeling may be accompanied by a high level of anxiety, a lack of self-esteem and a loss of self-confidence. Psychological adaptation is one of the concepts of sports psychology interconnected with the psychological climate, as the process that the player seeks to meet his demands and needs. Adaptation includes the pursuit of emotional balance between the individual play
... Show MoreReservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and
... Show MoreAutoría: Muwafaq Obayes Khudhair. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.
Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a
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