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关键词： Laser ranging   ILRS   IAG   Space geodesy   GGOS   Reference frames   Tracking networks   Precise orbit determination   Earth orientation parameters  

摘要： The International Laser Ranging Service (ILRS) through its permanent components (Tracking Stations, Operations Centers, Data Centers, Analysis Centers, Central Bureau, and Governing Board) distributes satellite and lunar laser ranging data and derived products to support global, multidisciplinary scientific research. The ILRS Data Centers and Central Bureau serve as the primary source for information, data, and products for this global user community. The ILRS website, , is a key tool for communication for the service, providing background information on the ILRS, its organization and operation, and detailed descriptions of ILRS components, data, and products. Links are provided to extensive information on the supported satellite missions and ILRS network stations including performance assessments and data quality evaluations. Furthermore, the website connects users to archives of laser ranging data and derived products available through the data centers. In this paper, we discuss the development of the ILRS infrastructure, its current status, website resources, description of laser ranging data and products, and plans for future enhancements.

关键词： Massively-parallel search engine   DB-IR integration   Pre-join   Multiple-keyword search queries   Distributed memory  

摘要： We propose two-dimensional indexing—a novel in-memory indexing architecture that operates over distributed memory of a massively-parallel search engine. The goal of two-dimensional indexing is to provide a one-integrated-memory view as in a single node system using one large integrated memory. In two-dimensional indexing, we partition the entire index into n× m fragments and distribute them over the memories of multiple nodes in such a way that each fragment is entirely stored in main memory of one node. The proposed architecture is not only scalable as it uses a scaled-out shared-nothing architecture but also is capable of achieving low query response time as it processes queries in main memory. We also propose the concept of the one-memory point, which is the amount of the memory space required to completely store the entire index in main memory providing a one-integrated-memory view. We first prove the effectiveness of two-dimensional indexing with single-keyword queries, and then, extend the notion so as to be able to handle multiple-keyword queries. To handle multiple-keyword queries, we adopt pre-join that materializes a multiple-keyword query a priori as well as a new notion of semi-memory join that obviates extensive communication overhead to perform join across multiple nodes. In experiments using the real-life search query set over a database consisting of 100 million Web documents crawled, we show that two-dimensional indexing can effectively provide a one-integrated-memory view without too much of additional memory compared with the single node system using one large integrated memory. We also show that, with a six-node prototype, in an ideal case, it significantly improves the query processing performance over a disk-based search engine with an equivalent amount of in-memory buffer but without two-dimensional indexing — by up to 535.54 times. This improvement is expected to get larger as the system is scaled-out with a larger number of machines.

关键词： 数据处理   应用   院校图书馆   图书馆工作   研究  

ISBN: (纸本)9787206165474

摘要： 本书以“大数据环境下图书馆文献信息资源建设与利用”为选题，从文献信息资源的概念与特点、网络文献信息资源以及大数据资源平台的整合与图书馆信息管理为切入，探讨图书馆文献信息资源建设、图书馆文献信息资源的检索与利用以及大数据环境下图书馆文献信息资源的管理策略与创新。本书在理清大数据与高校图书馆个性化信息服务概念和特征基础上，找到两者契合点，着眼于高校图书馆个性化信息服务发展趋势，发现两者存在结合的可能性，这对数据环境下图书馆文献信息资源建设与利用具有非常重要的意义。

关键词： Mutations   Isoforms   Variants   Cloud   Bolt   Proteomics  

摘要： Today we have unprecedented access to human genomic and proteomic data that appear to be rapidly approaching our current understanding of comprehensive coverage. Combining genomic information with shotgun proteomics remains challenging due to the large increase in proteomics search space. However, making this connection between genomic and proteomic information is critical for cancer studies to vaccine development. Furthermore, as we progress towards personalized medicine, it will be essential for proteomics analysis to identify individual mutations and variants in order to fully understand protein networks and to develop personalized therapies. While these advantages are well-established, only a few studies have demonstrated the successful integration of proteomic data with large genomic input. We present and examine the abilities of Bolt, a new cloud-based proteomics search engine to search for the presence of over 2.3 million known cancer mutations in a matter of minutes while still performing a standard proteomics search that includes 31 post translational modifications. We use previously published proteomics data sets and identify mutations that are verified using genomic studies as well as previous proteomics efforts. Our results also emphasize the need to search for mutations in a comprehensive manner while still searching for both common and rare PTMs. Significance: We present and examine the abilities of Bolt, a new cloud-based proteomics search engine to search for the presence of over 2.3 million known cancer mutations in a matter of minutes while still performing a standard proteomics search that includes 31 post translational modifications. No other proteomics search software can do so.

关键词： 信息资源共享   高校   档案管理模式  

摘要： 高校在信息资源共享下构建新型档案管理模式,需要强调高校共享档案信息资源的重要意义,结合现有档案管理实际情况,实施建立信息服务中心、构建用户反馈模式、完善信息集成体系、创建数字化管理模式等革新策略,满足高校建立档案共享管理模式的发展需求。基于此,本文主要分析了信息资源共享视角下高校档案管理模式。