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Evaluation of a new orthodontic bonding system (Beauty Ortho Bond)
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Background: The purpose of the current study was to evaluate the efficacy of a new orthodontic bonding system (Beauty Ortho Bond) involving the shear bond strength in dry and wet environments, and adhesion remnant index (ARI) scores evaluation in regard to other bonding systems (Heliosit and Resilience Orthodontic Adhesives). Materials and methods: Sixty defect free extracted premolars were randomly divided into six groups of 10 teeth each, mounted in acrylic resin, three groups for a dry environment and three for a wet one. Shear bond strength test was performed with a cross head speed of 0.5 mm/min, while surfaces of enamel and bracket-adhesive-enamel surfaces were examined with stereomicroscope For ARI scores evaluation. Data were analyzed by one way analysis of variance, least significant difference, student's t-test, and Fisher exact test. Results: The mean shear bond strength showed highest values for Resilience adhesive followed by Beauty Ortho Bond and Heliosit adhesives respectively both in dry and wet environments. Interestingly, there was a non-significant difference (P<0.05) between Resilience and Beauty Ortho Bond adhesives using least significant difference at dry environment. In wet environment the Beauty Ortho Bond showed an acceptable mean shear bond strength value (6.39 Mpa) which is considered as a clinically acceptable value. Adhesive remnant index scores demonstrated a tendency towards score 1 in dry environment, and towards score 3 in wet environment, the scores also showed a non-significant difference (P<0.05) between Resilience and Beauty Ortho Bond adhesives using Fischer exact test. Conclusion: Beauty Ortho Bond is less sensitive to wet environment than Resilience and Heliosit adhesives, therefore it has an advantage during clean up, as it reduces the risk of enamel damage during debonding procedure. Keywords: Beauty Ortho Bond, Shear bond strength, light cured composite.

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Publication Date
Thu Nov 01 2012
Journal Name
Journal Of Cutaneous And Aesthetic Surgery
Topical zinc sulphate (25%) solution: a new therapy for actinic keratosis
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KE Sharquie, SA Al-Mashhadani, AA Noaimi, AA Hasan, Journal of Cutaneous and Aesthetic Surgery, 2012 - Cited by 19

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Publication Date
Sun Jul 01 1990
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
APANTELES ANGALETI (MUSEBECK). HYMENOPTERA BRACONIDAE A NEW RECORD SPECIES IN IRAQ
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Notes are given regarding new record species of the braconid parasite short note in Iraq. That is Apanteles angalcti it is found to parasitize early larval instaxs of Ectomyslois ceratontae, one of the most serious pests of pomegra- nate fruit.

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Publication Date
Tue Dec 07 2021
Journal Name
Tencon 2021 - 2021 Ieee Region 10 Conference (tencon)
Robust State Feedback Control of Electric Heating Furnace Using a New Disturbance Observer
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As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sun Aug 13 2023
Journal Name
Arpn Journal Of Engineering And Applied Sciences
A NEW APPROACH FOR MODELLING THE VIBRATION OF BEAMS UNDER MOVING LOAD EFFECT
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In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Mon Jan 01 2018
Journal Name
Image And Video Technology: 8th Pacific-rim Symposium
A New Scheme for QoE Management of Live Video Streaming in Cloud Environment
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Publication Date
Fri Mar 01 2024
Journal Name
Journal Of Applied Spectroscopy
Spectrophotometric Method for Determination of Cu(II) Using a New Schiff Base Ligand
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The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita

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Publication Date
Tue Oct 25 2022
Journal Name
Aip Conference Proceedings
A new class of K-uniformly starlike functions imposed by generalized Salagean’s operator
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Recently, numerous the generalizations of Hurwitz-Lerch zeta functions are investigated and introduced. In this paper, by using the extended generalized Hurwitz-Lerch zeta function, a new Salagean’s differential operator is studied. Based on this new operator, a new geometric class and yielded coefficient bounds, growth and distortion result, radii of convexity, star-likeness, close-to-convexity, as well as extreme points are discussed.

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Publication Date
Tue Feb 01 2022
Journal Name
Civil Engineering Journal
Calibration of a New Concrete Damage Plasticity Theoretical Model Based on Experimental Parameters
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The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

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