HiTrust: building cross-organizational trust relationship based on a hybrid negotiation tree

Small-world phenomena have been observed in existing peer-to-peer (P2P) networks which has proved useful in the design of P2P file-sharing systems. Most studies of constructing small world behaviours on P2P are based on the concept of clustering peer nodes into groups, communities, or clusters. However, managing additional multilayer topology increases maintenance overhead, especially in highly dynamic environments. In this paper, we present Social-like P2P systems (Social-P2Ps) for object discovery by self-managing P2P topology with human tactics in social networks. In Social-P2Ps, queries are routed intelligently even with limited cached knowledge and node connections. Unlike community-based P2P file-sharing systems, we do not intend to create and maintain peer groups or communities consciously. In contrast, each node connects to other peer nodes with the same interests spontaneously by the result of daily searches

Updating DL-Lite ontologies through first-order queries

In this paper we study instance-level update in DL-LiteA, the description logic underlying the OWL 2 QL standard. In particular we focus on formula-based approaches to ABox insertion and deletion. We show that DL-LiteA, which is well-known for enjoying first-order rewritability of query answering, enjoys a first-order rewritability property also for updates. That is, every update can be reformulated into a set of insertion and deletion instructions computable through a nonrecursive datalog program. Such a program is readily translatable into a first-order query over the ABox considered as a database, and hence into SQL. By exploiting this result, we implement an update component for DLLiteA-based systems and perform some experiments showing that the approach works in practice.Peer ReviewedPostprint (author's final draft

Negotiating Trust on the Grid

Grids support dynamically evolving collections of resources and users, usually spanning multiple administrative domains. The dynamic and crossorganizational aspects of Grids introduce challenging management and policy issues for controlling access to Grid resources. In this paper we show how to extend the Grid Security Infrastructure to provide better support for the dynamic and cross-organizational aspects of Grid activities, by adding facilities for dynamic establishment of trust between parties. We present the PeerTrust language for access control policies, which is based on guarded distributed logic programs, and show how to use PeerTrust to model common Grid trust needs

Prion Formation and Polyglutamine Aggregation Are Controlled by Two Classes of Genes

Prions are self-perpetuating aggregated proteins that are not limited to mammalian systems but also exist in lower eukaryotes including yeast. While much work has focused around chaperones involved in prion maintenance, including Hsp104, little is known about factors involved in the appearance of prions. De novo appearance of the [PSI+] prion, which is the aggregated form of the Sup35 protein, is dramatically enhanced by transient overexpression of SUP35 in the presence of the prion form of the Rnq1 protein, [PIN+]. When fused to GFP and overexpressed in [ps−] [PIN+] cells, Sup35 forms fluorescent rings, and cells with these rings bud off [PSI+] daughters. We investigated the effects of over 400 gene deletions on this de novo induction of [PSI+]. Two classes of gene deletions were identified. Class I deletions (bug1Δ, bem1Δ, arf1Δ, and hog1Δ) reduced the efficiency of [PSI+] induction, but formed rings normally. Class II deletions (las17Δ, vps5Δ, and sac6Δ) inhibited both [PSI+] induction and ring formation. Furthermore, class II deletions reduced, while class I deletions enhanced, toxicity associated with the expanded glutamine repeats of the huntingtin protein exon 1 that causes Huntington's disease. This suggests that prion formation and polyglutamine aggregation involve a multi-phase process that can be inhibited at different steps.National Institutes of Health (U.S.) (grant GM56350)National Institutes of Health (U.S.) (NSRA F32 postdoctoral fellowship GM072340)National Institutes of Health (U.S.) (grant GM25874)Howard Hughes Medical Institut

Finding regions of interest on toroidal meshes

Fusion promises to provide clean and safe energy, and a considerable amount of research effort is underway to turn this aspiration intoreality. This work focuses on a building block for analyzing data produced from the simulation of microturbulence in magnetic confinementfusion devices: the task of efficiently extracting regions of interest. Like many other simulations where a large amount of data are produced,the careful study of ``interesting'' parts of the data is critical to gain understanding. In this paper, we present an efficient approach forfinding these regions of interest. Our approach takes full advantage of the underlying mesh structure in magnetic coordinates to produce acompact representation of the mesh points inside the regions and an efficient connected component labeling algorithm for constructingregions from points. This approach scales linearly with the surface area of the regions of interest instead of the volume as shown with bothcomputational complexity analysis and experimental measurements. Furthermore, this new approach is 100s of times faster than a recentlypublished method based on Cartesian coordinates