Background: Cleaning and shaping of root canals successfully requires high volumes of irrigation solutions that can only be applied to the apical third of root canal after enlargement with instrument, so the aim of this study was to evaluate and to compare the efficiency of Maxi-I-probe (side-vented needle), in the amount of root canal irrigant penetration for five different master apical file sizes (MAF) and four different degrees of coronal and middle thirds flaring. Materials and Methods: Two hundred resin blocks with simulated root canals were used in this study and divided into 5 major groups (40 for each) based on the size of master apical files (#20, #25, #30, #35, and #40). Each major group was subdivided into 4 subgroups depending on different sizes and depth of flaring (10 for each).The instrumentation and flaring techniques were used as following: 1. without flaring group, root canal shape resembles shape of the master apical K-file, 2. flaring I group, flaring done with Gates Glidden I for 2 mm coronally, 3. flaring II group, flaring was done with Gates Glidden I for 4 mm coronally, Gates Glidden II for 2 mm, 4. flaring III group, flaring was done with Gates Glidden I for 6mm,Gates Glidden II 4mm and Gates Glidden III for 2 mm coronally. Irrigation was done with Max-i-probe gauge 28. Results: By comparing the five different master apical file sizes at four different degrees of flaring, there was an increase in the amount of irrigant penetration with increase MAF size, taper had more effect in small canals size and decreased with further enlargement of master apical file size until no benefit was achieved in large canals size. Conclusions: It was shown that, Max-i-probe had a limited amount of irrigant entrance. Flaring was more effective in small canals than the larger canals in an amount of irrigant entrance; increasing MAF size was effective in an increase amount of irrigant entrance.
Luminescent sensor membranes and sensor microplates are presented for continuous or high-throughput wide-range measurement of pH based on a europium probe.
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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The goal of this article is to construct fibrewise w-compact (resp. locally w-compact) spaces. Some related results and properties of these concepts will be investigated. Furthermore, we investigate various relationships between these concepts and three classes of fibrewise w-separation axioms.
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This research concerns study the crack growth in the wall of pipes made of low carbon steel under the impact load and using the effect of hygrothermal (rate of moisture 50% and 50℃ temperature). The environmental conditions were controlled using high accuracy digital control with sensors. The pipe have a crack already. The test was performed and on two type of specimens, one have length of 100cm and other have length 50cm. The results were, when the humidity was applied to the pipe, the crack would enhance to growth (i.e. the number of cycles needed to growth the crack will reduce). In addition, when the temperature was increase the number of cycles needed to growth the crack are reduced because the effect of heat on the mechanical pro
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Many industrial systems involve multiple criteria and objectives, and they are very complex problems in computational science, such as task scheduling. We propose bi-criteria and bi-objective scheduling problems, which are solved by two nature-inspired evolutionary algorithms, such as Simulated Annealing (SA) and Bee Algorithm (BA). This problem is characterized by scheduling a batch of tasks on multiple machines, and it is fundamental because the solution should focus on the simultaneous optimization of two conflicting objectives: the makespan minimization and the total tardiness minimization. This problem is NP-Hard, and therefore, two evolutionary methods were used to search for solutions intelligently in this huge, very complex
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