Background: Apexification is a method to induce a calcified barrier in a root with an open apex or the continued apical development of an incomplete root in teeth with necrotic pulp. MTA apexification has several advantages such as it neither gets resorbed, nor weakens the root canal dentin, and also sets in the wet environment. The aim of this study is to evaluate the effectiveness of the use of MTA in apexification and periapical healing of teeth with incomplete root formation and periapical infection. Materials and method: Apexification was carried out on fourteen permanent immature teeth of eleven children aged 7-12 years attended the teaching hospital of College of Dentistry, Baghdad University using mineral trioxide aggregate followed by obturation of the root canal using gutta percha. The teeth were monitored at 3, 6 and 12 months intervals by clinical examination and radiographical evaluation of root development and healing of periapical lesion. Results: After a 12 months interval, all the teeth appeared to be asymptomatic so that the rate of clinical success in all of the cases was (100%). Radiographically, the success rate was 100% for thirteen teeth while that tooth which was started the treatment with large periapical lesion, showed regression of the periapical destruction suggestive of bone healing and regeneration of the root apex around the MTA material, end with small one so that it started unhealthy but finished with improved healing process. Conclusion: Mineral trioxide aggregate showed both clinical and radiographical success as a material used to induce root-end closure in permanent teeth with immature root formation. This material had the primary advantage of reduction in the number of appointments, development of proper apical seal and healing of periapical lesions.
This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un
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This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
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