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Shear bond strength of endodontic sealers to dentin with and without smear layer and gutta percha (An in vitro study)
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Background: The bond strength of root canal sealers to dentin and gutta-percha seems to be an important property for maintaining the stability of root canal filling, which potentially influences both leakage and root strength. The objective of this, in vitro, study was to evaluate the shear bond strength of three different endodontic sealers (Gutta-Flow, AH Plus, Apexit Plus) to dentin, in the presence and absence of the smear layer and gutta percha. Material and Methods: After slicing off the occlusal 2mm of 60 extracted human maxillary premolar teeth, the exposed dentin served as the tested surfaces; the teeth were fixed with cold cure acrylic, and were divided into two groups according to the smear layer presence, group A without smear layer, when dentin surfaces were irrigated with EDTA 17% followed by distilled water then subdivided into 3 subgroups according to the type of sealer used; group B when dentin surfaces were washed with distilled water only, then subdivided into 3 subgroups. Thirty samples of gutta-percha were prepared and named as group C which was subdivided into 3 subgroups. Five mm long section of polyethylene tubes were placed on the dentin or gutta percha surfaces and filled with freshly mixed sealer. After one week, all the samples were tested for shear bond strength by the Instron Universal Testing Machine at a cross head speed of 0.5 mm/min. The data was calculated in MPa and was statistically analyzed Result: There was a highly significant difference in the shear bond strength (P < 0.05) in comparison among the tested groups, GuttaFlow showed non-significant difference in bond strength to dentin with and without smear layer, while AH Plus and Apexit Plus showed a high significant difference. Conclusions: AHPlus showed the highest shear bond strength in all the tested samples, while GuttaFlow was the least. Additionally, AH Plus and Apexit Plus shear bond strengths were affected by the smear layer removal, while GuttaFlow was not.

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Publication Date
Fri Jun 30 2023
Journal Name
نسق
the effect of the semantic map strategy on predictive thinking among fifth grade femal students
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Publication Date
Sat Jan 01 2022
Journal Name
Craniomaxillofacial Research &amp; Innovation
Partial Bone Necrosis Following Sagittal Split Ramus Osteotomy: Report of a Complicated Orthognathic Jaw Surgery
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Study Design

Case Report.

Objective

To present a case of a previous complicated mandibular orthognathic surgery that aimed to setback the mandible in a female cleft lip and palate (CLP) patient, which led to bone necrosis on one side with subsequent severe mandibular deviation and facial asymmetry. We additionally reviewed the previous reports of similar complications, the pathophysiology and the factors that could lead to this dreadful result.

Method

A 27-year-old female patient presented with a severe dentofacial deformity secondary to a complicated bilateral sagittal spli

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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effect of SPAWN Strategy on the Life Skills among the Second Grade Intermediate Students
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The aim of the research is to find out the effect of the SPAWN strategy on the life skills of second-intermediate-grade students. This study stage represented the research community within the intermediate and secondary governmental daytime schools affiliated with the Directorate of Education of Diwaniyah. The experiment was applied in Al-Razai Intermediate School on a sample of second-grade intermediate students, including 66 students distributed into two groups: (32) students within the experimental group and (34) students within the control group. The two groups were equivalent with a number of variables (chronological age, intelligence test, previous information test, life skills scale). The results indicated that the two groups were

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Publication Date
Mon Apr 04 2022
Journal Name
International Journal Of Early Childhood Special Educationpublishes
The impact of visual Management on the Strategic Acceleration; embedding knowledge as a Moderating Variable
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The research stems from its goal of identifying the impact of visual management on the strategic acceleration of business organizations and the state of this effect through the knowledge embedding in the Iraqi oil companies. The oil sector was tested, represented by (3) oil companies, and a sample of (151) individuals who participated in activating the visual management, distributed in higher management levels. The research relied on the descriptiveanalytical approach and the questionnaire was a main tool for collecting data and information. The results showed that visual management positively affects strategic acceleration. Moreover, This effect is amplified by the mediating role played by Embedding Knowledge.

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Publication Date
Tue Jun 01 2021
Journal Name
مجلة جامعة الانبار للعلوم البدنیة والریاضیة
The effect of the flipped classroom on cognitive achievement Some basic football skills for students
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The aim of the research is to design a test with cognitive achievement through the use of the inverted class strategy for some basic soccer skills for gyms for first-average students, within the curriculum of the Ministry of Education, where the researcher used the experimental approach. For the same division (B) and the number of each group (10) students, i.e. the total total of the research sample (20) students, and the pre-test for the research sample was applied through the design of the test prepared by the research after which the educational program with the strategy was applied to the research sample and continued (8) weeks after Completion of the tutorial has been post-tested for the research sample, In it, he reached significant r

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Thu Oct 15 2015
Journal Name
International Journal Of Computer Applications
Experimental Investigation for Small Horizontal Portable Wind Turbine of Different Blades Profiles under Laboratory Conditions
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Experimental investigation for small horizontal portable wind turbine (SHPWT) of NACA-44, BP-44, and NACA-63, BP-63 profiles under laboratory conditions at different wind velocity range of (3.7-5.8 m/s) achieved in present work. Experimental data tabulated for 2, 3, 4, and 6- bladed rotor of both profiles within range of blade pitch angles . A mathematical model formulated and computer Code for MATLAB software developed. The least-squares regression is used to fit experimental data. As the majority of previous works have been presented for large scale wind turbines, the aims were to present the performance of (SHPWT) and also to make a comparisons between both profiles to conclude which is the best performance. The overall efficiency and el

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Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Crossref (4)
Crossref
Publication Date
Mon Apr 24 2023
Journal Name
Materials Research Innovations
Surface modification of poly(methyl methacrylate)-sulphadiazine complexes as self photostabilizer against Ultraviolet (UV) Irradiation
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Scopus Crossref
Publication Date
Sat Jan 01 2011
Journal Name
Iraqi Journal Of Physics
Monte Carlo Simulation for Bremsstrahlung Buildup Factor Produced by Absorption of Y-91 Beta Rays
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This paper presents the first data for bremsstrahlung buildup factor (BBUF) produced by the complete absorption of Y-91 beta particles in different materials via the Monte Carlo simulation method. The bremsstrahlung buildup factors were computed for different thicknesses of water, concrete, aluminum, tin and lead. A single relation between the bremsstrahlung buildup factor BBUF with both the atomic number Z and thickness X of the shielding material has been suggested.

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