Our study emphasises the importance of both body mass and immune function in studying metabolic and body composition abnormalities associated with HIV-1 infection. The association of increased waist-to-hip ratios and hyperinsulinemia suggestive of insulin resistance in non-wasting individuals with AIDS suggest that the tendency towards these metabolic abnormalities may be related to the HIV infectious process or to factors associated with immunologic dysfunction.
A user profile contains information about a user. A substantial effort has been made so as to understand users' behavior through analyzing their profile data. Online social networks provide an enormous amount of such information for researchers. Sina Weibo, a Twitter-like microblogging platform, has achieved a great success in China although studies on it are still in an initial state. This paper aims to explore the relationships among different profile attributes in Sina Weibo. We use the techniques of association rule mining to identify the dependency among the attributes and we found that if a user's posts are welcomed, he or she is more likely to have a large number of followers. Our results demonstrate how the relationships among the profile attributes are affected by a user's verified type. We also put some efforts on data transformation and analyze the influence of the statistical properties of the data distribution on data discretization.
The k-dominant skyline query which can return small result set in high dimensional space is very convenient for user to make decision. But all the existent algorithms are for single dataset, not suitable for two or more datasets being combined. To solve this problem, this paper proposed a new idea to get the newk-dominant skyline by computing the partial points of each dataset based on their existentk-dominant skylines. Furthermore, detailed theoretical analyses and extensive experiments demonstrate that the algorithms can effectively reduce redundant work, and keep the result correctly.
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