Marine microplankton diversity database

Many macroecological theories have been developed to study the diversity on our planet. All these theories require the existence of consistent databases to test their predictions. In this work, we compiled a data set of marine microplankton species abundances at 788 stations with an extensive geographical coverage. Data were collected on different oceanographic cruises between 1992 and 2002. This database consists of abundances (cells/mL) for each species at each station and depth, together with estimates of the biomass and biovolume for each species. One of the key strengths in this database is that species identifications were made by the same taxonomist, which provides greater strength to the collection and ensures that estimates of species diversity are reliable. Environmental information has also been compiled at each station (chlorophyll, temperature, photosynthetically active radiation [PAR], nutrients) in order to have a characterization of the study area and to be used in studies on the environmental and biological controls of marine biodiversity.

CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters.

The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950. The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

A marine reservoir correction database and on-line interface

Calibration is essential for interpretation of radiocarbon dates, especially when the 14C dates are compared to historical or climatic records with a different chronological basis. 14C ages of samples from the marine environment, such as shells or fish bones, or samples with a marine component, such as human bone in coastal regions, require an additional consideration because of the reservoir age of the ocean. While the pre-industrial global mean reservoir correction, R(t), is about 400 years, local variations (?R) can be several hundred years or more. ?R compilations on a global scale have been undertaken previously (Stuiver et al. 1986; Stuiver and Braziunas 1993), but have not been updated recently. Here we describe an on-line reservoir correction database accessed via mapping software. Rather than publishing a static ?R compilation, new data will be incorporated when it becomes available. The on-line marine reservoir correction database can be accessed at the website http://www.calib.org/.

The UMIST Database for Astrochemistry 2006

We present a new version of the UMIST Database for Astrochemistry, the fourth such version to be released to the public. The current version contains some 4573 binary gas-phase reactions, an increase of 10% from the previous (1999) version, among 420 species, of which 23 are new to the database. Major updates have been made to ion-neutral reactions, neutral-neutral reactions, particularly at low temperature, and dissociative recombination reactions. We have included for the first time the interstellar chemistry of fluorine. In addition to the usual database, we have also released a reaction set in which the effects of dipole-enhanced ion-neutral rate coefficients are included. These two reactions sets have been used in a dark cloud model and the results of these models are presented and discussed briefly. The database and associated software are available on the World Wide Web at www.udfa.net. Tables 1, 2, 4 and 9 are only available in electronic form at http://www.aanda.org

FPGA-based minutia matching for biometric fingerprint image database retrieval

In this paper, a parallel-matching processor architecture with early jump-out (EJO) control is proposed to carry out high-speed biometric fingerprint database retrieval. The processor performs the fingerprint retrieval by using minutia point matching. An EJO method is applied to the proposed architecture to speed up the large database retrieval. The processor is implemented on a Xilinx Virtex-E, and occupies 6,825 slices and runs at up to 65 MHz. The software/hardware co-simulation benchmark with a database of 10,000 fingerprints verifies that the matching speed can achieve the rate of up to 1.22 million fingerprints per second. EJO results in about a 22% gain in computing efficiency.