The relationships between microstructure and crystal structure in zincite solid solutions

Single phase (Zn,Fe)(1-x) O zincite solid solution samples have been prepared by high temperature equilibration in air and in reducing atmospheres, followed by quenching to room temperature. The Fe2+/Fe3+ concentrations in the samples have been determined using wet chemical and XPS techniques. Iron is found to be present in zincite predominantly in the form of Fe3+ ions. The transition from an equiaxed grain morphology to plate-like zincite crystals is shown to be associated with increasing Fe3+ concentration, increasing elongation in < 001 > of the hexagonal crystals and increasing anisotropic strain along the c-axis. The plate-like crystals are shown to contain planar defects and zincite polytypes at high iron concentrations.

Efficiently computing weighted proximity relationships in spatial databases

Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.