Visualization is an efficient technology to display the information and the inherent properties of geographic data, mine the regularity and development trends between the data and give researchers the unexpected insight. As the using and distribution of visualization resources exists imbalance, in order to meet the need of Geography Science, this paper presented a Grid Computing-based High-performance Visualization Environment. This environment is based on the mature grid middleware, CGSP to achieve the Grid integration and sharing of the geo science visualization software. A demonstration application was discussed to verify the visualization environment. The environment would achieve the visualization of the massive geo-spatial data efficiently and expediently, enhance the collaborative research to solve problems and improve their research environment.

Abstract-Construction of university Data Center is the requirement of higher education to adapt to information society, is also an important part of the construction of universities. At present, due to the informationization construction of universities lacking of unified planning and deployment, as well as the research and application of the Data Center is not enough in-depth, the needs of current management and service works could not be meet that result in delaying the informationization development. Taking the construction of Cloud Data Center to realize wisdom campus as the goal, this paper puts forward a set of construction plan of Data Center based on Cloud Computing that suitable for the application characteristics of universities, and implemented the plan in the Cloud Data Center project in Lanzhou Jiaotong University. Implementation of Cloud Data Center project in university could create a reliable platform for construction, circulation and sharing of information resources, and have obvious advantages in promoting ability of informationization integration application, management efficiency of information system, and quality of Data Center operation and reducing operation cost.

There have been numerous studies focusing on normal aging in previous decades which is accompanied by the structural and functional decline in the hippocampus, while the pattern of hippocampal alteration with age remains unclear. Figuring out the mechanism of hippocampal changes precisely is beneficial for a better understanding of the aging process. In this study, we included a total of 451 T1 MRI scans of subjects of age 50–90 who were labeled as normal in the Alzheimer’s Disease Neuroimaging Initiative. Taking 10 years of age as an age band, we divided the subjects into four groups (denoted as HC1, HC2, HC3, and HC4, respectively), with the youngest being 50–60 and the oldest 81–90. Then the Multivariate Morphometry Statistics (MMS) of the hippocampus segmented from the four groups were extracted by surface reconstruction, mesh generation, and surface registration. Finally, the significant differences between the youngest group and the other three were statistically analyzed. Results showed that the earliest deformation region of the left hippocampus located in the frontal subiculum and the dorsal CA1 of the tail part and gradually expanded with aging, while the right hippocampal deformation mainly concentrated in the dorsal CA1 and spread to the posterior CA2-3, which occurred later than that of the left. All the results illustrated that the hippocampus is truly a vulnerable structure in the course of aging, and the MMS are sensitive metrics for detecting the changes in the subcortical convex structure.