Background: It has been well known that the success of mandibular implant- retained overdenture heavily depends on initial stability, retention and long term osseointegration this is might be due to optimal stresses distribution in surrounding bones. Types of mandibular implant- retained overdenture anchorage system and number of dental implants play an important role in stresses distribution at the implant-bone interface. It is necessary to keep the stresses below the physiologic tolerance level of the bone .since. And it is difficult to measure these stresses around bone in vivo. In the present study, finite element analysis used to study the stresses distribution around dental implant supporting Mandible implant retained overdenture Materials and methods: Eight models were constructed including four designs of anchorage system (ball-cup, ball-O Ring, bar without distal extension and bar with distal extension).The first group of models were supported by four dental implant and second group of models were supported by two dental implant only. Models constructed from the data obtained directly from patient The contour of bone was obtained from C.T scan image of patient, then data transferred to ANSYS program for modeling then load applied and solve the equation by the program, Specified nodes were selected at the rings of crestal bone (cortical bone) and cortical cancellous interface around each dental implant and fixed for all models to monitor the stress change in that regions of different design of MIR-OD.. After load application, Specified nodes were selected at the rings of crestal bone (cortical bone) and cortical cancellous interface around each dental implant and fixed for all models to monitor the stress change in that regions of different design of MIR-OD . Results: In the present study the stress distribution and maximum stresses value around dental implant had a relationship to the number of dental implant. , The result appeared that the maximum stresses and means of stresses value was lower in the first group of models (which was supported through the use four dental implant) than the second group of models (which was supported through the use of two dental implant only). For the first group of models the maximum stresses value around mesial implant was11.67, 10.51, 10.98 and 10.72 Mpa, while the maximum stresses around distal implant was 21.33, 18.51, 18.86, and17.56 Mpa for models 1,2,3 and 4respectively ,and the stresses around implant supporting second group of models was 22.52, 22.16, 20.51 and 19.60 Mpa for models 5,6,7and8 respectively .Statistical analyses of means value appeared that there was statistically significant difference in stresses means value around implant of the second group with that’s values around mesial and distal implant supporting first group of model . Regarding the result of both ball and bar system, it has been demonstrated that stress was greater with ball attachment and MIR-OD supported by the use of four dental implants and anchored by bar attachments with distal extension gives the minimum values of stresses than the rest models. Also the results show that higher stresses value was appeared at the cortical bone ring surrounding dental implant especially the distal implant nearest to the free end extension area. Also it was appeared that the best model was Mandible implant- retained overdenture that’s anchored by bar with distal extension and support by four dental implant. Conclusions: Bar-clips with distal extension mode of attachment considered the best type in producing the least stresses around dental implant regardless number of dental implant used.
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The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana
... Show MoreThis paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4
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The research aims to identify the educational plan for the private and public kindergartens. The researchers selected a sample consisted of (59) female teachers for the private kindergartens and (150) female teachers for the public kindergartens in the city of Baghdad. As for the research tool, the two researchers designed a questionnaire to measure the educational plan for the private and public kindergartens. The results revealed that private kindergartens have educational plans that contribute considerably to classroom interaction, the public kindergartens lack for educational plans. In light of the findings of the research, the researchers recommend the following: the need to set up a unified educational plan for the priv
... Show MoreThe aim of this paper is to propose an efficient three steps iterative method for finding the zeros of the nonlinear equation f(x)=0 . Starting with a suitably chosen , the method generates a sequence of iterates converging to the root. The convergence analysis is proved to establish its five order of convergence. Several examples are given to illustrate the efficiency of the proposed new method and its comparison with other methods.
Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp
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