Background: Dimensional changes of acrylic denture bases after polymerization results in need for further adjustments or even ends with technical failure of the finished dentures. The purpose of this study was to estimate the linear dimensional changes for different palatal depths when using multiple investment materials and polymerization techniques. Materials and methods: Ninety upper complete denture bases were constructed for this study. They were divided into two main groups according to the polymerization methods: conventional water bath and experimental autoclave (short and long cycles). Each main group was further subdivided into three subgroups according to the palatal depth (shallow, medium and deep). Furthermore, for each palatal depth; complete denture bases were invested either with dental stone or laboratory silicone. For each upper complete denture, measurements of linear dimensional changes were done by fixation of metallic screws on the tissue surface of the denture base. The distances were measured by using travelling microscope with an accuracy of 0.001 %. The data were statistically analyzed using three way analysis of variance (ANOVA) for three variables, which were (palatal depth, investments and polymerization techniques), LSD test and student T test for comparisons between groups. Results: There were significant improvements in the dimensional accuracy of denture bases cured with autoclave compared with water bath. Also, silicone investments were a successful alternative to stone, study data shows that short autoclave processing with silicone reduces the magnitude of the linear dimensional changes. On the other hand, long autoclave processing and stone investments were better than silicone in reducing dimensional changes. Conclusion: The findings of this study indicates that the use of autoclave processing in acrylic curing is a promising alternative to the conventional water bath and leads to better dimensional stability for the finished dentures in all oral configurations and palatal depths. Also, Silicone is more preferable than stone, although it's not as strong investing materials when compared with stone.
Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method
Exposing the dorsal superficial skin of rats to partial-depth burn leads to bacterial and microbes Invasion. Topical treatment is required in most superficial burn cases Moist exposed burn ointment (MEBO) protects wounds from infection and enhances healing without any harmful effects of purified chemicals is caused. The topical using of HA gel in rat models with full and partial thickness surgical wounds shows enhancement in wound repair. In this study, we compared the healing efficacy of topical use of hyaluronic acid gel products with MEBO as standard management in rats that were exposed to a partial-thickness burn. The experiment included twenty-four (24) adult albino rats of male sex with weight (150-220 gm) of 3 months’ age divided i
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The research discussed the topic of the functional role of responsive materials in being elements of a functional transformation in the design of industrial products, based on the study of the structures of smart materials and their performance capabilities at the level of action and self-reaction that characterize this type of materials.
Basic features of responsive materials have been identified to be elements of self-functional insertion into the industrial product design, which contributes to raising the efficiency and functional capacity of the industrial product and enhancing the ability of products to perform self-acting interactions in the structural structure of the material structure of the product and its ability to res
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Municipal wastewater sources are becoming increasingly important for reuse, for irrigation purposes, so they must be treated to meet environmentally friendly local or global standards. The aim of this study is to establish, calibrate, and validate a model for predicting chemical oxygen demand for the pilot plant of mobile biofilm reactors operating from municipal wastewater in Maaymyrh located in Hilla city Using the approach of dimensional analysis. The approach of Buckingham's theorem was used to derive a model of dimensional analysis design for the forecast of (COD) in the pilot plant. The effluent concentration (COD) It has been derived as a result of the influential concentration of (COD), dissolved oxygen (DO), volume of pilot plant
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The study aims to make an in-depth analysis and the financial account components in the Iraqi balance of payments because it reflects the economic center of the country towards outside world, it also helps in making decision about monetary and financial policies, finance and foreign Trade the importance of FDI for Iraq lies as an important sources as wells provides advanced technology and job chances, It also avoids the country negative effects of borrowing processes from abroad . for analyzing direct and indirect foreign investment on the balance of payments and financial account in a period between (2003 to 2015), a community and research sample have been selected, presented in CBI/ Balance of payments. Department,
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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