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  1. ; ; ; ; ( , WOC'20: Proceedings of the 2020 6th International Workshop on Container Technologies and Container Clouds)
    null (Ed.)
    While distributed application-layer tracing is widely used for performance diagnosis in microservices, its coarse granularity at the service level limits its applicability towards detecting more fine-grained system level issues. To address this problem, cross-layer stitching of tracing information has been proposed. However, all existing cross-layer stitching approaches either require modification of the kernel or need updates in the application-layer tracing library to propagate stitching information, both of which add further complex modifications to existing tracing tools. This paper introduces Deepstitch, a deep learning based approach to stitch cross-layer tracing information without requiring any changes to existing application layer tracing tools. Deepstitch leverages a global view of a distributed application composed of multiple services and learns the global system call sequences across all services involved. This knowledge is then used to stitch system call sequences with service-level traces obtained from a deployed application. Our proof of concept experiments show that the proposed approach successfully maps application-level interaction into the system call sequences and can identify thread-level interactions. 
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  2. ; ; ; ; ( , SIGMOD '20: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data)
    Nowadays an emerging class of applications are based oncollaboration over a shared database among different entities. However, the existing solutions on shared database may require trust on others, have high hardware demand that is unaffordable for individual users, or have relatively low performance. In other words, there is a trilemma among security, compatibility and efficiency. In this paper, we present FalconDB, which enables different parties with limited hardware resources to efficiently and securely collaborate on a database. FalconDB adopts database servers with verification interfaces accessible to clients and stores the digests for query/update authentications on a blockchain. Using blockchain as a consensus platform and a distributed ledger, FalconDB is able to work without any trust on each other. Meanwhile, FalconDB requires only minimal storage cost on each client, and provides anywhere-available, real-time and concurrent access to the database. As a result, FalconDB over-comes the disadvantages of previous solutions, and enables individual users to participate in the collaboration with high efficiency, low storage cost and blockchain-level security guarantees. 
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  3. ; ; ; ; ; ; ; ; ( , Molecular Nutrition & Food Research)
    Scope

    Enhancing the formation and function of brown adipose tissue (BAT) increases thermogenesis and hence reduces obesity. Thus, we investigate the effects of resveratrol (Resv) on brown adipocyte formation and function in mouse interscapular BAT (iBAT).

     Methods and results

    CD1 mice and stromal vascular cells (SVCs) isolated from iBAT were treated with Resv. Expression of brown adipogenic and thermogenic markers, and involvement of AMP‐activated protein kinase (AMPK)α1 were assessed. In vivo, Resv‐enhanced expression of brown adipogenic markers, PR domain‐containing 16 (PRDM16) and thermogenic genes, uncoupling protein 1 (UCP1) and cytochrome C in iBAT, along with smaller lipid droplets, elevated AMPKα activity and increased oxygen consumption. Meanwhile, Resv promoted expression of PRDM16, UCP1, PGC1α, cytochrome C and pyruvate dehydrogenase (PDH) in differentiated iBAT SVCs, suggesting that Resv enhanced brown adipocyte formation and function in vitro. In addition, Resv stimulated AMPKα and oxygen consumption in differentiated iBAT SVCs. However, the promotional effects of Resv were diminished by AMPK inhibition or AMPKα1 knockout, implying the involvement of AMPKα1 in this process.

     Conclusion

    Resv enhanced brown adipocyte formation and thermogenic function in mouse iBAT by promoting the expression of brown adipogenic markers via activating AMPKα1, which contributed to the anti‐obesity effects of Resv.

     
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