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Effects of vitamin D deficiency on bone and root re-sorption post-orthodontic retention in rats
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Background: Orthodontic therapy often causes external root resorption. Serum vitamin D (VD) level is important for tooth mineralization and bone remodeling. This study aimed to test the impact of vitamin D (VD) supplements on bone and root remodelling in a vitamin D (VD) deficient rat model following orthodontic retention. Methods and Material: 30 male Wistar rats were divided into three groups: a control group of 10 rats and two experimental groups of 10 rats each with vitamin D deficiency (VDD) induced by a VD-free diet for 21 days. And a third group with VD supplementAll groups received orthodontic active treatment using a modified orthodontic appliance that applied 50 gm of force for 14 days to move the maxillary right first molar mesially, followed by 7 days of retention and relapse. The VDD group received no intervention, while the VDS group received 40,000 IU/kg of systemic VD3 by intramuscular injection on the first and fifteenth day of orthodontic treatment. Histomorphometric analysis was performed to assess bone and cementum resorption and deposition. Results: The VDD group exhibited a significant increase in bone and root resorption and a decrease in bone deposition and ce-mentum deposition ratio. In addition, bone deposition and the ratio of cementum deposition were substantially greater in the VDS group compared to the control group. Conclusion: VDD may increase bone and root cementum resorption and decrease deposition after orthodontic retention, which may play a significant role in relapse after retention. Prior to beginning orthodontic treatment, routine VD screening may be beneficial.

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Publication Date
Tue Feb 28 2023
Journal Name
Applied System Innovation
Earthquake Hazard Mitigation for Uncertain Building Systems Based on Adaptive Synergetic Control
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This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

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Publication Date
Sun Sep 16 2018
Journal Name
British Journal Of Educational Technology
Group tagging: Using video tagging to facilitate reflection on small group activities
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Collaborative learning in class‐based teaching presents a challenge for a tutor to ensure every group and individual student has the best learning experience. We present Group Tagging, a web application that supports reflection on collaborative, group‐based classroom activities. Group Tagging provides students with an opportunity to record important moments within the class‐based group work and enables reflection on and promotion of professional skills such as communication, collaboration and critical thinking. After class, students use the tagged clips to create short videos showcasing their group work activities, which can later be reviewed by the teacher. We report on a deployment of Group Tagging in an undergraduate Computing Scie

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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formation Evaluation for Nasiriyah Oil Field Based on The Non-Conventional Techniques
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The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence. The techniques used in this paper are:

  • Apparent resistivity Rwa
  • Rxo /Rt

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

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Publication Date
Fri Feb 05 2021
Journal Name
Research In Intelligent And Computing In Engineering
Implementing Web Testing System Depending on Performance Testing Using Load Testing Method.
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Web testing is very important method for users and developers because it gives the ability to detect errors in applications and check their quality to perform services to users performance abilities, user interface, security and other different types of web testing that may occur in web application. This paper focuses on a major branch of the performance testing, which is called the load testing. Load testing depends on an important elements called request time and response time. From these elements, it can be decided if the performance time of a web application is good or not. In the experimental results, the load testing applied on the website (http://ihcoedu.uobaghdad.edu.iq) the main home page and all the science departments pages. In t

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Publication Date
Tue Jan 15 2013
Journal Name
Journal Of Kerbala University 11 (3)‏
Effect ofchemicalfertilizerand foliar spray ofgibberellicacidon mineral element andgibberellin-likesubstances content on someolivecultivars‏
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Publication Date
Sun Dec 31 2023
Journal Name
Sumer Journal For Pure Science
COVID-19Disease Diagnosis using Artificial Intelligence based on Gene Expression: A Review
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
A Suggested Proposal to Activate Educational Supervision Based on Professional Learning Societies
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Professional learning societies (PLS) are a systematic method for improving teaching and learning performance through designing and building professional learning societies. This leads to overcoming a culture of isolation and fragmenting the work of educational supervisors. Many studies show that constructing and developing strong professional learning societies - focused on improving education, curriculum and evaluation will lead to increased cooperation and participation of educational supervisors and teachers, as well as increases the application of effective educational practices in the classroom.

The roles of the educational supervisor to ensure the best and optimal implementation and activation of professional learning soci

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Publication Date
Sat Jan 05 2019
Journal Name
Iraqi Journal Of Physics
Solar cells based on natural dyes prepared using anatase phase titanium dioxide
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Natural dye sensitized solar cell was prepared using strawberry and pomegranate dyes with anatase nanocrystalline titanium dioxide powder. A study of the optical properties of the two dyes, involving the absorption spectrum was determined in the visible region. I-V characteristics under illumination were performed. The results showed that the two prepared dye sensitized solar cells have acceptable values efficiency about (0.94 with Fill factor (45)) and (0.74 with Fill factor (44)) for strawberry and pomegranate dyes, respectively.

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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