Overview of FEED, the feeding experiments end-user database.

The Feeding Experiments End-user Database (FEED) is a research tool developed by the Mammalian Feeding Working Group at the National Evolutionary Synthesis Center that permits synthetic, evolutionary analyses of the physiology of mammalian feeding. The tasks of the Working Group are to compile physiologic data sets into a uniform digital format stored at a central source, develop a standardized terminology for describing and organizing the data, and carry out a set of novel analyses using FEED. FEED contains raw physiologic data linked to extensive metadata. It serves as an archive for a large number of existing data sets and a repository for future data sets. The metadata are stored as text and images that describe experimental protocols, research subjects, and anatomical information. The metadata incorporate controlled vocabularies to allow consistent use of the terms used to describe and organize the physiologic data. The planned analyses address long-standing questions concerning the phylogenetic distribution of phenotypes involving muscle anatomy and feeding physiology among mammals, the presence and nature of motor pattern conservation in the mammalian feeding muscles, and the extent to which suckling constrains the evolution of feeding behavior in adult mammals. We expect FEED to be a growing digital archive that will facilitate new research into understanding the evolution of feeding anatomy.

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 December 2009-31 January 2010

This article documents the addition of 220 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Allanblackia floribunda, Amblyraja radiata, Bactrocera cucurbitae, Brachycaudus helichrysi, Calopogonium mucunoides, Dissodactylus primitivus, Elodea canadensis, Ephydatia fluviatilis, Galapaganus howdenae howdenae, Hoplostethus atlanticus, Ischnura elegans, Larimichthys polyactis, Opheodrys vernalis, Pelteobagrus fulvidraco, Phragmidium violaceum, Pistacia vera, and Thunnus thynnus. These loci were cross-tested on the following species: Allanblackia gabonensis, Allanblackia stanerana, Neoceratitis cyanescens, Dacus ciliatus, Dacus demmerezi, Bactrocera zonata, Ceratitis capitata, Ceratitis rosa, Ceratits catoirii, Dacus punctatifrons, Ephydatia mülleri, Spongilla lacustris, Geodia cydonium, Axinella sp. Ischnura graellsii, Ischnura ramburii, Ischnura pumilio, Pistacia integerrima and Pistacia terebinthus. © 2010 Blackwell Publishing Ltd.

The HITRAN 2008 molecular spectroscopic database

This paper describes the status of the 2008 edition of the HITRAN molecular spectroscopic database. The new edition is the first official public release since the 2004 edition, although a number of crucial updates had been made available online since 2004. The HITRAN compilation consists of several components that serve as input for radiative-transfer calculation codes: individual line parameters for the microwave through visible spectra of molecules in the gas phase; absorption cross-sections for molecules having dense spectral features, i.e. spectra in which the individual lines are not resolved; individual line parameters and absorption cross-sections for bands in the ultraviolet; refractive indices of aerosols, tables and files of general properties associated with the database; and database management software. The line-by-line portion of the database contains spectroscopic parameters for 42 molecules including many of their isotopologues. © 2009 Elsevier Ltd.

The HITRAN molecular spectroscopic database: Edition of 2000 including updates through 2001

This paper describes the status circa 2001, of the HITRAN compilation that comprises the public edition available through 2001. The HITRAN compilation consists of several components useful for radiative transfer calculation codes: high-resolution spectroscopic parameters of molecules in the gas phase, absorption cross-sections for molecules with very dense spectral features, aerosol refractive indices, ultraviolet line-by-line parameters and absorption cross-sections, and associated database management software. The line-by-line portion of the database contains spectroscopic parameters for 38 molecules and their isotopologues and isotopomers suitable for calculating atmospheric transmission and radiance properties. Many more molecular species are presented in the infrared cross-section data than in the previous edition, especially the chlorofluorocarbons and their replacement gases. There is now sufficient representation so that quasi-quantitative simulations can be obtained with the standard radiance codes. In addition to the description and justification of new or modified data that have been incorporated since the last edition of HITRAN (1996), future modifications are indicated for cases considered to have a significant impact on remote-sensing experiments. © 2003 Elsevier Ltd. All rights reserved.

The HITRAN 2004 molecular spectroscopic database

info:eu-repo/semantics/published

AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

An aircraft accident database of human experience in evacuation derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However, such models have a heavy dependency on real evacuation data. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (Aircraft Accident Statistics and Knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

[Book Review] A database of North American tertiary mammals

Review of: Janis, C.M., Scott, K.M., & Jacobs, L.L. (eds.) 1998. Evolution of Tertiary Mammals of North America Volume 1: Terrestrial Carnivores, Ungulates, and Ungulatelike Mammals, i-x, 1491. Cambridge University Press, Cambridge, UK. £165

An analysis of human behaviour during aircraft evacuation situations using the AASK v3.0 database

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.

The AASK Database V3.0: a database of human experience during aircraft evacuation incidents

This paper describes recent developments with the Aircraft Accident Statistics and Knowledge (AASK) database. The AASK database is a repository of survivor accounts from aviation accidents developed by the Fire Safety Engineering Group of the University of Greenwich with support from the UK CAA. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. Access to the latest version of the database (AASK V3.0) is available over the Internet. AASK consists of information derived from both passenger and cabin crew interviews, information concerning fatalities and basic accident details. Also provided with AASK is the Seat Plan Viewer that graphically displays the starting locations of all the passengers - both survivors and fatalities - as well as the exits used by the survivors. Data entered into the AASK database is extracted from the transcripts supplied by the National Transportation Safety Board in the US and the Air Accident Investigation Branch in the UK. The quality and quantity of the data was very variable ranging from short summary reports of the accidents to boxes of individual accounts from passengers, crew and investigators. Data imported into AASK V3.0 includes information from 55 accidents and individual accounts from 1295 passengers and 110 crew.

The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents

This paper describes the AASK database. The AASK database is unique as it is a record of human behaviour during survivable aviation accidents. The AASK database is compiled from interview data compiled by agencies such as the NTSB and the AAIB. The database can be found on the website http://fseg.gre.ac.uk

Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of passenger accounts from survivable aviation accidents/incidents compiled from interview data collected by agencies such as the US NTSB. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It also plays a significant role in the development of the airEXODUS aircraft evacuation model, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes the latest version of the database (Version 4.0) and includes some analysis of passenger behavior during actual accidents/incidents.

CAA paper 2006/01: a database to record human experience of evacuation in aviation accidents: the aircraft accident statistics and knowledge database (AASK)

This report concerns the development of the AASK V4.0 database (CAA Project 560/SRG/R+AD). AASK is the Aircraft Accident Statistics and Knowledge database, which is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from interviews of the occupants involved in aircraft accidents. The AASK database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. With support from the UK CAA (Project 277/SRG/R&AD), AASK V3.0 was developed. This was an on-line prototype system available over the internet to selected users and included a significantly increased number of passenger accounts compared with earlier versions, the introduction of cabin crew accounts, the introduction of fatality information and improved functionality through the seat plan viewer utility. The most recently completed AASK project (Project 560/SRG/R+AD) involved four main components: a) analysis of the data collected in V3.0; b) continued collection and entry of data into AASK; c) maintenance and functional development of the AASK database; and d) user feedback survey. All four components have been pursued and completed in this two-year project. The current version developed in the last year of the project is referred to as AASK V4.0. This report provides summaries of the work done and the results obtained in relation to the project deliverables.

Creating a modern database from archive material - The Norman Holme archive: Interpretation of marine field research notebooks in the historical context of the MBA, 1958-83

This document provides details of the transfer of the Norman Holme archive data held in the National Marine Biological Library onto a modern database, specifically Marine Recorder. A key part in the creation of the database was the retrieval of a large amount of information recorded in field notebooks and on loosely-bound sheets of paper. As this work involved amending, interpreting and updating the available information, it was felt that an accurate record of this process should exist to allow scientists of the future to be able to clearly link the modern database to the archive material. This document also provides details of external information sources that were used to enhance and qualify the historical interpretation, such as estimating volumes and species abundances.