Microencapsulação por gelificação iônica e interação eletrostática do corante de buriti (Mauritia flexuosa L. f.)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação dos fatores de virulência, atividade antimicrobiana e viabilidade celular de bactéria cariogênica na presença do Terpinen-4-ol: estudo in vitro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito de diversos protocolos de dessensibilização dentinária na obliteração de túbulos dentinários, resistência de união do sistema adesivo e formação de camada hibrida na dentina cervical

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Extração automática de contornos de telhados usando dados de varredura a laser e campos randômicos de Markov

This paper proposes a methodology for automatic extraction of building roof contours from a Digital Elevation Model (DEM), which is generated through the regularization of an available laser point cloud. The methodology is based on two steps. First, in order to detect high objects (buildings, trees etc.), the DEM is segmented through a recursive splitting technique and a Bayesian merging technique. The recursive splitting technique uses the quadtree structure for subdividing the DEM into homogeneous regions. In order to minimize the fragmentation, which is commonly observed in the results of the recursive splitting segmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. The high object polygons are extracted by using vectorization and polygonization techniques. Second, the building roof contours are identified among all high objects extracted previously. Taking into account some roof properties and some feature measurements (e. g., area, rectangularity, and angles between principal axes of the roofs), an energy function was developed based on the Markov Random Field (MRF) model. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing (SA) algorithm. Experiments carried out with laser scanning DEM's showed that the methodology works properly, as it delivered roof contours with approximately 90% shape accuracy and no false positive was verified.

Uso de dados fotogramétricos no refinamento geométrico de contornos de telhados de edifícios extraídos de dados laser

In this paper, a methodology is proposed for the geometric refinement of laser scanning building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology takes for granted that the 3D description of each building roof reconstructed from the laser scanning data (i.e., a polyhedron) is topologically correct and that it is only necessary to improve its accuracy. Since roof ridges are accurately extracted from laser scanning data, our main objective is to use high-resolution aerial images to improve the accuracy of roof outlines. In order to meet this goal, the available roof contours are first projected onto the image-space. After that, the projected polygons and the straight lines extracted from the image are used to establish an MRF description, which is based on relations ( relative length, proximity, and orientation) between the two sets of straight lines. The energy function associated with the MRF is minimized by using a modified version of the brute force algorithm, resulting in the grouping of straight lines for each roof object. Finally, each grouping of straight lines is topologically reconstructed based on the topology of the corresponding laser scanning polygon projected onto the image-space. The preliminary results showed that the proposed methodology is promising, since most sides of the refined polygons are geometrically better than corresponding projected laser scanning straight lines.

Segmentação de dados de perfilamento a laser em áreas urbanas utilizando uma abordagem Bayesiana

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.

Extração de vias combinando métodos de detecção de regiões e linhas em imagens de intensidade de pulso laser

This paper aims at extracting street centerlines from previously isolated street regions by using the image of laser scanning intensity. In this image, streets are easily identified, since they manifest as dark, elongate ribbons contrasting with background objects. The intensity image is segmented by using the region growing technique, which generates regions representing the streets. From these regions, the street centerlines are extracted in two manners. The first one is through the Steger lines detection method combined with a line length thresholding by which lines being shorter than a minimum length are removed. The other manner is by combining the skeletonization method of regions based on the Medial Axis Transform and with a pruning process to eliminate as much as possible the ramifications. Experiments showed that the Steger-based method provided results better than the method based on skeletonization.

Photodynamic inactivation of biofilm: Taking a lightly colored approach to stubborn infection

Microbial biofilms are responsible for a variety of microbial infections in different parts of the body, such as urinary tract infections, catheter infections, middle-ear infections, gingivitis, caries, periodontitis, orthopedic implants, and so on. The microbial biofilm cells have properties and gene expression patterns distinct from planktonic cells, including phenotypic variations in enzymic activity, cell wall composition and surface structure, which increase the resistance to antibiotics and other antimicrobial treatments. There is consequently an urgent need for new approaches to attack biofilm-associated microorganisms, and antimicrobial photodynamic therapy (aPDT) may be a promising candidate. aPDT involves the combination of a nontoxic dye and low-intensity visible light which, in the presence of oxygen, produces cytotoxic reactive oxygen species. It has been demonstrated that many biofilms are susceptible to aPDT, particularly in dental disease. This review will focus on aspects of aPDT that are designed to increase efficiency against biofilms modalities to enhance penetration of photosensitizer into biofilm, and a combination of aPDT with biofilm-disrupting agents. © 2013 Informa UK Ltd.

Recent mouse and rat methods for the study of experimental oral candidiasis

The Candida genus expresses virulence factors that, when combined with immunosuppression and other risk factors, can cause different manifestations of oral candidiasis. The treatment of mucosal infections caused by Candida and the elucidation of the disease process have proven challenging. Therefore, the study of experimentally induced oral candidiasis in rats and mice is useful to clarify the etiopathology of this condition, improve diagnosis, and search for new therapeutic options because the disease process in these animals is similar to that of human candidiasis lesions. Here, we describe and discuss new studies involving rat and mouse models of oral candidiasis with respect to methods for inducing experimental infection, methods for evaluating the development of experimental candidiasis, and new treatment strategies for oral candidiasis. © 2013 Landes Bioscience.

Photogrammetric refinement of laser-based building roof contours

In this paper a photogrammetric method is proposed for refining 3D building roof contours extracted from airborne laser scanning data. It is assumed that laser-derived planar faces of roofs are potentially accurate, while laser-derived building roof contours are not well defined. First, polygons representing building roof contours are extracted from a high-resolution aerial image. In the sequence, straight-line segments delimitating each building roof polygon are projected onto the corresponding laser-derived roof planes by using a new line-based photogrammetric model. Finally, refined 3D building roof contours are reconstructed by connecting every pair of photogrammetrically- projected adjacent straight lines. The obtained results showed that the proposed approach worked properly, meaning that the integration of image data and laser scanning data allows better results to be obtained, when compared to the results generated by using only laser scanning data. © 2013 IEEE.

Efeito do sistema de acabamento e polimento na rugosidade superficial e formação in situ de biofilme dentário inicial em cerâmica feldspática micro-particulada

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detecção de regiões de via integrando dados de varredura a LASER aerotransportado e imagens de alta resolução

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reconstrução de contornos e cumeeiras de telhados de edifícios a partir de imagens aéreas de alta-resolução e poliedros representativos de edifícios extraídos de dados LASER

Pós-graduação em Ciências Cartográficas - FCT

Estudo do desempenho de filmes de Ti02 como aceptor de elétrons e obtenção de fases puras de nanopartículas de Ti02: anatase e rutila, sintetizado por uma nova rota química

Pós-graduação em Ciência dos Materiais - FEIS

Refinamento geométrico de contornos e cumeeiras de telhados de edifícios extraídos de dados laser com uso de imagem aérea

In this paper, a method is proposed to refine the LASER 3D roofs geometrically by using a high-resolution aerial image and Markov Random Field (MRF) models. In order to do so, a MRF description for grouping straight lines is developed, assuming that each projected side contour and ridge is topologically correct and that it is only necessary to improve its accuracy. Although the combination of laser data with data from image is most justified for refining roof contour, the structure of ridges can give greater robustness in the topological description of the roof structure. The MRF model is formulated based on relationships (length, proximity, and orientation) between the straight lines extracted from the image and projected polygon and also on retangularity and corner injunctions. The energy function associated with MRF is minimized by the genetic algorithm optimization method, resulting in the grouping of straight lines for each roof object. Finally, each grouping of straight lines is topologically reconstructed based on the topology of the corresponding LASER scanning polygon projected onto the image-space. The results obtained were satisfactory. This method was able to provide polygons roof refined buildings in which most of its contour sides and ridges were geometrically improved.