Síntese de pigmentos cerâmicos inorgânicos nanométricos e encapsulados com estrutura core-shell pela rota dos precursores poliméricos

The present work has as objective the development of ceramic pigments based in iron oxides and cobalt through the polymeric precursor method, as well as study their characteristics and properties using methods of physical, chemical, morphological and optical characterizations.In this work was used iron nitrate, and cobalt citrate as precursor and nanometer silica as a matrix. The synthesis was based on dissolving the citric acid as complexing agent, addition of metal oxides, such as chromophores ions and polymerization with ethylene glycol. The powder obtained has undergone pre-ignition, breakdown and thermal treatments at different calcination temperatures (700 °C, 800 °C, 900 °C, 1000 °C and 1100 °C). Thermogravimetric analyzes were performed (BT) and Differential Thermal Analysis (DTA), in order to evaluate the term decomposition of samples, beyond characterization by techniques such as BET, which classified as microporous materials samples calcined at 700 ° C, 800 º C and 900 º C and non-porous when annealed at 1000 ° C and 1100 º C, X-ray diffraction (XRD), which identified the formation of two crystalline phases, the Cobalt Ferrite (CoFe2O4) and Cristobalite (SiO2), Scanning Electron Microscopy (SEM) revealed the formation of agglomerates of particles slightly rounded;and Analysis of Colorimetry, temperature of 700 °C, 800 °C and 900 °C showed a brown color and 1000 °C and 1100 °C violet

Paralelização em GPU da segmentação vascular com extração de Centerlines por Height Ridges

The vascular segmentation is important in diagnosing vascular diseases like stroke and is hampered by noise in the image and very thin vessels that can pass unnoticed. One way to accomplish the segmentation is extracting the centerline of the vessel with height ridges, which uses the intensity as features for segmentation. This process can take from seconds to minutes, depending on the current technology employed. In order to accelerate the segmentation method proposed by Aylward [Aylward & Bullitt 2002] we have adapted it to run in parallel using CUDA architecture. The performance of the segmentation method running on GPU is compared to both the same method running on CPU and the original Aylward s method running also in CPU. The improvemente of the new method over the original one is twofold: the starting point for the segmentation process is not a single point in the blood vessel but a volume, thereby making it easier for the user to segment a region of interest, and; the overall gain method was 873 times faster running on GPU and 150 times more fast running on the CPU than the original CPU in Aylward