Propriedades de ZrO2 (Y2 O3) reciclado proveniente da confecção de próteses dentárias

RESUMO O objetivo deste trabalho foi a recuperação de descartes de ZrO2(Y2O3) oriundos de laboratórios de próteses dentárias, a partir do seu reprocessamento. Os descartes de ZrO2(Y2O3) foram fragmentados, peneirados e calcinados a 900ºC. Pós com tamanho menor que 32μm foram prensados uniaxialmente a 100MPa e sinterizados em temperaturas entre 1400 e 1600ºC-120min. Análise de difração de raios X realizadas nos materiais calcinados indicaram a presença majoritária da fase ZrO2 tetragonal. Os compactos apresentaram densidade a verde próximo a 47% e as amostras sinterizadas tiveram sua densidade relativa variando entre 83,5% e 95%, para temperaturas de sinterização de 1400 e 1600ºC, respectivamente. Os resultados da análise de difração de raios X indicaram a presença da fase ZrO2 tetragonal, com dureza Vickers e tenacidade máxima obtidos para as amostras sinterizadas a 1600ºC, da ordem de 1100 HV e 5,7 MPa.m1/2 respectivamente

Mixture Of Heterogeneous Experts Applied To Time Series: A Comparative Study

Prediction models for time series generally include preprocessing followed by the synthesis of an input-output mapping. Neural network models have been adopted to perform both steps, by means of unsupervised and supervised learning, respectively. The flexibility and the generalization capability are the most relevant attributes in favor of connectionist approaches. However, even though time series prediction can be roughly interpreted as learning from data, high levels of performance will solely be achieved if some peculiarities of each time series are properly considered in the design, particularly the existence of trend and seasonality. Instead of directly adopting detrend and/or deseasonality treatments, this paper proposes a novel paradigm for supervised learning based on a mixture of heterogeneous experts. Some mixture models have already been proved to produce good performance as predictors, but the present approach will be devoted to a hybrid mixture composed of a set of distinct experts. The purpose is not only to further explore the "divide-and-conquer" principle, but also to compare the performance of mixture of heterogeneous experts with the standard mixture of experts approach, using ten distinct time series. The obtained results indicate that mixture of heterogeneous experts generally requires a more elaborate gating device and performs better in the case of more challenging time series. © 2005 IEEE.211601165Box, G.E.P., Jenkins, G.M., (1976) Time Series Analysis: Forecasting, and Control, , Holden Day, San Francisco, CABridle, J.S., Probabilistic interpretation of feedforward classification network outputs with relationships to statistical pattern recognition (1990) Neurocomputing: Algorithms. Architectures, and Applications, pp. 227-236. , F. Fogelman Soulié and J. 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Dependência espacial em levantamentos do estoque de carbono em áreas de pastagens de Brachiaria brizantha cv. Marandu Spatial dependence in surveys of carbon storage in grassland areas of Brachiaria brizantha, Marandu grass

Foi conduzido um estudo utilizando análise de semivariogramas para quantificar a autocorrelação espacial dos estoques de carbono (EC) no solo, biomassa da gramínea e das plantas daninhas em três parcelas experimentais de pastagens de Brachiaria brizantha cv. Marandu com níveis baixo, médio e alto de degradação, cultivadas em Neossolo Quartzarênico Órtico. As coletas das plantas e do solo foram realizadas em malha de amostragem regular com distâncias de 5 x 5 m em área de 900 m². Os EC das pastagens foram submetidos às analises de estatística descritiva, ao teste não-paramétrico de Kruskal-Wallis ao nível de 5% de significância, ao estudo geoestatístico e interpolação por krigagem ordinária. A variabilidade espacial do EC foi observada dentro e entre as pastagens de capim-Marandu com níveis baixo, médio e alto de degradação. A pastagem de capim-Marandu com nível baixo de degradação teve menor continuidade espacial, por apresentar menores alcances no EC, na biomassa da gramínea e na biomassa total (gramínea + plantas daninhas), no solo e no sistema solo x pastagem (solo + biomassa total). A grade de 5 x 5 m foi adequada para caracterizar a variabilidade espacial de pastagens de capim-Marandu com níveis de degradação baixo e alto. Área de pastagem de capim-Marandu com grau médio de degradação apresenta coeficientes de variação altos entre os valores EC; o que comprometeu a modelagem espacial que também pode ter ocorrido devido ao baixo número de amostras realizadas (n=36). Assim, pontos de amostragem menores que 5 m podem melhorar a precisão dos ajustes dos semivariogramas.<br>A study was carried using semivariogram analysis to quantify spatial autocorrelation of carbon stock (CS) in soil, grass and weed species biomass in pastures of Brachiaria brizantha, Marandu grass with low, medium and high degradation, and grown an entisol. The sampling of plants and soil were carried out in regular grid with distances of 5x5 m in an area of 900 m². Grassland CS was assessed through descriptive statistics, comparison of averages through the test Kruskal-Wallis at 5% level of significance, geostatistics and ordinary kriging analysis. The spatial variability of CS was observed within and between pastures with low, medium and high degradation. Pastures with low levels of degradation had less spatial continuity due to smaller ranges in CS in grass biomass and total biomass (grass + weed species), in soil carbon and soil versus grass (total biomass + soil). The grid of 5x5 m was adequate to characterize the spatial variability of pasture with low and high levels of degradation. Areas of Marandu grass with average degree of degradation has high coefficients of variation (CV) between the CS values, which negative by affected the spatial modeling. High CV may also be due to the low number of samples taken (n = 36). Sampling points in grid lower than 5 m can improve the accuracy of the adjustment of semivariograms