Wild bee toxicity data for pesticide risk assessments

Pollination services are vital for agriculture, food security and biodiversity. Although many insect species provide pollination services, honeybees are thought to be the major provider of this service to agriculture. However, the importance of wild bees in this respect should not be overlooked. Whilst regulatory risk assessment processes have, for a long time, included that for pollinators, using honeybees (Apis mellifera) as a protective surrogate, there are concerns that this approach may not be suffciently adequate particularly because of global declines in pollinating insects. Consequently, risk assessments are now being expanded to include wild bee species such as bumblebees (Bombus spp.) and solitary bees (Osmia spp.). However, toxicity data for these species is scarce and are absent from the main pesticide reference resources. The aim of the study described here was to collate data relating to the acute toxicity of pesticides to wild bee species (both topical and dietary exposure) from published regulatory documents and peer reviewed literature, and to incorporate this into one of the main online resources for pesticide risk assessment data: The Pesticide Properties Database, thus ensuring that the data is maintained and continuously kept up to date. The outcome of this study is a dataset collated from 316 regulatory and peer reviewed articles that contains 178 records covering 120 different pesticides and their variants which includes 142 records for bumblebees and a further 115 records for other wild bee species.Peer reviewe

Astronomical Data Center Bulletin, volume 1, no. 1

Information about work in progress on astronomical catalogs is presented. In addition to progress reports, an upadated status list for astronomical catalogs available at the Astronomical Data Center is included. Papers from observatories and individuals involved with astronomical data are also presented

Special Libraries, March 1955

Volume 46, Issue 3https://scholarworks.sjsu.edu/sla_sl_1955/1002/thumbnail.jp

RefConcile – automated online reconciliation of bibliographic references

Comprehensive bibliographies often rely on community contributions. In such a setting, de-duplication is mandatory for the bibliography to be useful. Ideally, it works online, i.e., during the addition of new references, so the bibliography remains duplicate-free at all times. While de-duplication is well researched, generic approaches do not achieve the result quality required for automated reconciliation. To overcome this problem, we propose a new duplicate detection and reconciliation technique called RefConcile. Aimed specifically at bibliographic references, it uses dedicated blocking and matching techniques tailored to this type of data. Our evaluation based on a large real-world collection of bibliographic references shows that RefConcile scales well, and that it detects and reconciles duplicates highly accurately

Description and Access in Rare Books Cataloging: A Historical Survey

Rare book cataloging codes and practices have been shaped by a constant interplay between the tradition of descriptive bibliography and the evolution of library cataloging codes. At the same time, technological changes, such as the emergence of bibliographic databases and online catalogs, have led to promises of increased flexibility and usability in records for rare books. This article will focus on the development of modern Anglo-American rare book cataloging, highlighting special access points that often appear to exist outside the mainstream of library cataloging. By focusing on the treatment of several “hallmarks” of rare book records in codes published during the second half of the twentieth century, the development of rare book cataloging and its relationship to the traditions of bibliography and general library emerge

Structure and content semantic similarity detection of eXtensible markup language documents using keys

XML (eXtensible Mark-up Language) has become the fundamental standard for efficient data management and exchange. Due to the widespread use of XML for describing and exchanging data on the web, XML-based comparison is central issues in database management and information retrieval. In fact, although many heterogeneous XML sources have similar content, they may be described using different tag names and structures. This work proposes a series of algorithms for detection of structural and content changes among XML data. The first is an algorithm called XDoI (XML Data Integration Based on Content and Structure Similarity Using Keys) that clusters XML documents into subtrees using leaf-node parents as clustering points. This algorithm matches subtrees using the key concept and compares unmatched subtrees for similarities in both content and structure. The experimental results show that this approach finds much more accurate matches with or without the presence of keys in the subtrees. A second algorithm proposed here is called XDI-CSSK (a system for detecting xml similarity in content and structure using relational database); it eliminates unnecessary clustering points using instance statistics and a taxonomic analyzer. As the number of subtrees to be compared is reduced, the overall execution time is reduced dramatically. Semantic similarity plays a crucial role in precise computational similarity measures. A third algorithm, called XML-SIM (structure and content semantic similarity detection using keys) is based on previous work to detect XML semantic similarity based on structure and content. This algorithm is an improvement over XDI-CSSK and XDoI in that it determines content similarity based on semantic structural similarity. In an experimental evaluation, it outperformed previous approaches in terms of both execution time and false positive rates. Information changes periodically; therefore, it is important to be able to detect changes among different versions of an XML document and use that information to identify semantic similarities. Finally, this work introduces an approach to detect XML similarity and thus to join XML document versions using a change detection mechanism. In this approach, subtree keys still play an important role in order to avoid unnecessary subtree comparisons within multiple versions of the same document. Real data sets from bibliographic domains demonstrate the effectiveness of all these algorithms --Abstract, page iv-v

Special Libraries, July-August 1958

Volume 49, Issue 6https://scholarworks.sjsu.edu/sla_sl_1958/1005/thumbnail.jp