733 resultados para Segmented HPGe


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper aims to discuss the directions of pharmaceutical education based on the new curriculum guidelines from MEC (Ministry of Education - Brazil). In the recent past, Brazilian pharmaceutical faculties prioritized the formation of professional resources in specific modalities in detriment of pharmacist's private field: the prescription filling and delivery at the drugstore. In order to avoid repeating the same mistake it is necessary to develop new competence, allowing the graduates to develop skills to connect the scientific and technological knowledge to Brazilian social context. The new curriculum guidelines are about to finish a time when the undergraduate studies seemed to split the pharmacist into two different professionals: one for the clinical analysis and other for the pharmaceutical industry. The previous educational model, which supposedly allows for pharmaceutical care without providing a broad integral knowledge of health sciences, cannot be repeated in the new curriculum. However, teaching subjects in a superficial and segmented manner, replete of predictable and repetitive technical practices and without a skilled teaching staff, will give no improvement in pharmacists education care. It is clear that the return of the formation of specific human resources in the field won't happen in short time.

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In this paper is presented a region-based methodology for Digital Elevation Model segmentation obtained from laser scanning data. The methodology is based on two sequential techniques, i.e., a recursive splitting technique using the quad tree structure followed by a region merging technique using the Markov Random Field model. The recursive splitting technique starts splitting the Digital Elevation Model into homogeneous regions. However, due to slight height differences in the Digital Elevation Model, region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Markov Random Field model is applied to the previously segmented data. The resulting regions are firstly structured by using the so-called Region Adjacency Graph. Each node of the Region Adjacency Graph represents a region of the Digital Elevation Model segmented and two nodes have connectivity between them if corresponding regions share a common boundary. Next it is assumed that the random variable related to each node, follows the Markov Random Field model. This hypothesis allows the derivation of the posteriori probability distribution function whose solution is obtained by the Maximum a Posteriori estimation. Regions presenting high probability of similarity are merged. Experiments carried out with laser scanning data showed that the methodology allows to separate the objects in the Digital Elevation Model with a low amount of fragmentation.

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A series of segmented poly(urethane-urea)s containing 1,3,5 triazine in the hard block and hexamethylene spacers in the soft block was prepared. The hard to soft segment ratio was varied systematically, to afford a series of polymers in which the chromophore concentration varied from 4.2% to 18.1%. Although triazine emission is located in the UV region, the films with higher content of the chromophore emitted a visible blue light (425 nm) when excited at the very red-edge of the absorption band. The photophysical properties of the materials were strongly dependent on the relative amount of triazine moieties along the main chain. Isolated moieties emit in copolymers with small amount of triazine groups, indicating that even though in solid state, these moieties tend to be apart. Two photophysical consequences were observed when the amount of triazine increases: there is some energy transfer process involving isolated moieties with consequent decrease of the lifetime and an additional red-edge emission attributed to aggregated lumophores. The mono-exponential decay observed for the isolated form is substituted by a bi-exponential decay of the aggregated species. The materials were not strong emitters, but since the N-containing triazine moieties are good electron transport groups, the polymers have potential application as electron transport enhancers in various applications. © 2006 Elsevier B.V. All rights reserved.

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This article evaluates space closure mechanics efficiency in an extraction case where maximum anchorage was a requirement. The Segmented Arch Technique (SAT) was utilized as an anchorage control strategy to obtain maximum anterior retraction and, in consequence, significant facial profile change. A 20-year-10-month old woman needed severe labial and profile changes. The patient had four premolars extracted and SAT with type A mechanics [1] (Marcotte [2] activation protocol) was applied. The results showed significant reduction in labial protrusion and incisal angulation with effective anchorage control. The results were compared to others available in the literature derived from different techniques, where anterior retraction was also accomplished with maximum anchorage [3-7]. In conclusion, the SAT with type A mechanics has been shown to be another treatment option when significant changes in the soft-tissue profile are needed in extraction cases. © 2008. CEO. Published by Elsevier Masson SAS. All rights reserved.

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Includes bibliography

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Includes bibliography

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This article describes an orthodontic system used to obtain active continuous torque with movement control of both active and reactive units; the system relies on principles of the segmented technique. A cantilever system with .017 x .025-in beta-titanium alloy wire was designed to provide the desirable moment on the active unit. A transpalatal bar or a lingual arch increases the anchorage and neutralizes the side effects on the reactive unit. This technique is an efficient approach for major corrections of buccolingual inclinations of certain teeth. © 2010 American Association of Orthodontists.

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In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work is the first into applying OPF for automatic cast iron segmentation. © 2010 Springer-Verlag.

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The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

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Includes bibliography