A laboratory information management system (LIMS) is central to the informatics infrastructure that underlies biobanking activities. To date, a wide range of commercial and open-source LIMSs are available and the decision to opt for one LIMS over another is often influenced by the needs of the biobank clients and researchers, as well as available financial resources. The Baobab LIMS was developed by customizing the Bika LIMS software () to meet the requirements of biobanking best practices. The need to implement biobank standard operation procedures as well as stimulate the use of standards for biobank data representation motivated the implementation of Baobab LIMS, an open-source LIMS for Biobanking. Baobab LIMS comprises modules for biospecimen kit assembly, shipping of biospecimen kits, storage management, analysis requests, reporting, and invoicing. The Baobab LIMS is based on the Plone web-content management framework. All the system requirements for Plone are applicable to Baobab LIMS, including the need for a server with at least 8 GB RAM and 120 GB hard disk space. Baobab LIMS is a server–client-based system, whereby the end user is able to access the system securely through the internet on a standard web browser, thereby eliminating the need for standalone installations on all machines.
Regulatory agencies often define strict, decibel-denominated thresholds of significance of noise impacts to protect some fraction of the residential population from exposure to highly annoying noise. Definitions of the "significance" of aircraft noise impacts and recommendations of land use "compatibility," however, typically lack detailed, systematic rationales. Instead, the definitions are justified by reference to decades-old policies that were adopted without benefit of modern understandings of noise-induced annoyance, by appeals to authority, and by generic citations of non-peer reviewed documents. Although regulatory policy decisions may properly take into consideration political and economic consequences, aspects of them are amenable to logical formalization. In particular, advances in understanding of community reaction to transportation noise now permit a systematic rationale for aircraft noise regulation. The current analyses show how regulatory policy positions can be derived from two parameters: (1) the minimal percentage of the population of a nominally average community to be protected from exposure to highly annoying noise; and (2) the percentage of all communities to which this degree of protection is intended to apply. Together with a reliable dosage-response relationship, these two parameters permit quantitatively justifiable definitions of significant noise impact.
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