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The Resource Manager is a SOA based service in charge of managing gCube Scope contexts. The Resource Manager 2.0, by coordinating five distinguished services (Deployer, Software Gateway, Resource Broker, gCube Hosting Node Manager, Web Hosting Node Manager), realizes the VRE dynamic deployment by, respectively, collecting service implementations, selecting target nodes for deployment within the infrastructure, and hosting resources implementations at selected nodes. The primary role assigned to this service is to collects and manage all the resources and service implementations related to a specific Virtual Organization.

A tool for multidimensional variational analysis (divand) is presented. It allows the interpolation and analysis of observations on curvilinear orthogonal grids in an arbitrary high dimensional space by minimizing a cost function. This cost function penalizes the deviation from the observations, the deviation from a first guess and abruptly varying fields based on a given correlation length (potentially varying in space and time). Additional constraints can be added to this cost function such as an advection constraint which forces the analysed field to align with the ocean current. The method decouples naturally disconnected areas based on topography and topology. This is useful in oceanography where disconnected water masses often have different physical properties. Individual elements of the a priori and a posteriori error covariance matrix can also be computed, in particular expected error variances of the analysis. A multidimensional approach (as opposed to stacking 2-dimensional analysis) has the benefit of providing a smooth analysis in all dimensions, although the computational cost is increased. Primal (problem solved in the grid space) and dual formulations (problem solved in the observational space) are implemented using either direct solvers (based on Cholesky factorization) or iterative solvers (conjugate gradient method). In most applications the primal formulation with the direct solver is the fastest, especially if an a posteriori error estimate is needed. However, for correlated observation errors the dual formulation with an iterative solver is more efficient. The method is tested by using pseudo observations from a global model. The distribution of the observations is based on the position of the ARGO floats. The benefit of the 3-dimensional analysis (longitude, latitude and time) compared to 2-dimensional analysis (longitude and latitude) and the role of the advection constraint are highlighted. The tool divand is free software, and is distributed under the terms of the GPL license (http://modb.oce.ulg.ac.be/mediawiki/index.php/divand). PREDANTAR, EMODNET Chemistry 2, SeaDataNet II

The gCube social networking facilities manifest in a number of applications made available through a thin Web browser are conceptually close to the common facilities promoted by social networks - e.g., posting news, commenting on posted news - yet adapted to deal with large scale collaboration and cooperation on comprehensive scientific products, data sets, theories and tools. Social Profile allow users to enter their professional data and contact information. It also allows to import the profile data directly from LinkedIn via the OAuth 2.0 protocol.

IRMNG SPD plugin is a plugin of the Species Products Discovery service that interacts with IRMNG, the Interim Register of Marine and Nonmarine Genera, through the Darwin Core Archive format. The data exchange format for publishing checklist data based on Darwin Core (DwC), a standard for biodiversity data.

The Species Discovery Service support species queries based on the SPQL language. This library offers a parser for the SPQL language.

The advancement of Coastal Ocean Forecasting Systems (COFS) requires the support of continuous scientific progress addressing: (a) the primary mechanisms driving coastal circulation; (b) methods to achieve fully integrated coastal systems (observations and models), that are dynamically embedded in larger scale systems; and (c) methods to adequately represent air-sea and biophysical interactions. Issues of downscaling, data assimilation, atmosphere-wave-ocean couplings and ecosystem dynamics in the coastal ocean are discussed. These science topics are fundamental for successful COFS, which are connected to evolving downstream applications, dictated by the socioeconomic needs of rapidly increasing coastal populations.

Macroalgae, and particularly their lignin-free polysaccharides, are increasingly used for their gelling and therapeutic properties and for the production of biofuels and renewable chemical compounds. To extract, hydrolyze and purify this biomass, algae hydrolyzing enzymes are needed. Our work aims to identify and characterize algal biomass hydrolyzing enzymes expressed by microorganisms living on the surface of algae, by functional metagenomics. Therefore, a microbial DNA extraction method was developed to isolate the gDNA from the microorganisms of the brown algae Ascophyllum nodosum and a metagenomic library was constructed in Escherichia coli. The library was screened for diverse enzymatic activities (esterases, xylanases, cellulases, α-amylases, arabinanases, caseinases and β-glucosidases) on agar plates with specific enzymes substrates. Several new microbial enzymes (esterases, β-glucosidases, α-amylases and cellulases) were identified revealing the wealth of our library. Furthermore, those enzymes had less than 50% sequence identity with known protein sequences; meaning that our approach allows to identify new microbial enzymes expressed by uncultured microorganisms. Plate tests for medium-throughput screening of specific enzymes hydrolyzing algal polysaccharides (agarases, carrageenases and alginate lyases) are currently being developed. Our approach will probably allow us to identify new families of those ill-known enzymes, with particular enzymatic activities.

Brazilian Flora SPD plugin is a plugin of the Species Products Discovery service that interacts with The List of Species of the Brazilian Flora. The data exchange format for publishing checklist data based on Darwin Core (DwC), a standard for biodiversity data.

The Statistical Manager (SM) is a cross usage service aiming at providing users and services with tools for performing data mining operations. The goal of this service is to offer a unique access for performing data mining or statistical operations on heterogeneous data. These can reside on client side in the form of csv files or they can be remotely hosted, possibly in a database. The Service is able to take inputs and execute the operation requested by a client invoking the suited computational infrastructure from a set of available possibilities. Executions can run on multi-core machines or on different computational infrastructures, like the D4Science, Windows Azure and other different private and commercial Cloud providers.

The Black Sea northwestern shelf (NWS) is a shallow eutrophic area in which the seasonal stratification of the water column isolates the bottom waters from the atmosphere. This prevents ventilation from counterbalancing the large consumption of oxygen due to respiration in the bottom waters and in the sediments, and sets the stage for the development of seasonal hypoxia. A three-dimensional (3-D) coupled physical–biogeochemical model is used to investigate the dynamics of bottom hypoxia in the Black Sea NWS, first at seasonal and then at interannual scales (1981–2009), and to differentiate its driving factors (climatic versus eutrophication). Model skills are evaluated by a quantitative comparison of the model results to 14 123 in situ oxygen measurements available in the NOAA World Ocean and the Black Sea Commission databases, using different error metrics. This validation exercise shows that the model is able to represent the seasonal and interannual variability of the oxygen concentration and of the occurrence of hypoxia, as well as the spatial distribution of oxygen-depleted waters. During the period 1981–2009, each year exhibits seasonal bottom hypoxia at the end of summer. This phenomenon essentially covers the northern part of the NWS – which receives large inputs of nutrients from the Danube, Dniester and Dnieper rivers – and extends, during the years of severe hypoxia, towards the Romanian bay of Constanta. An index H which merges the aspects of the spatial and temporal extension of the hypoxic event is proposed to quantify, for each year, the intensity of hypoxia as an environmental stressor. In order to explain the interannual variability of H and to disentangle its drivers, we analyze the long time series of model results by means of a stepwise multiple linear regression. This statistical model gives a general relationship that links the intensity of hypoxia to eutrophication and climate-related variables. A total of 82% of the interannual variability of H is explained by the combination of four predictors: the annual riverine nitrate load (N), the sea surface temperature in the month preceding stratification (Ts), the amount of semi-labile organic matter accumulated in the sediments (C) and the sea surface temperature during late summer (Tf). Partial regression indicates that the climatic impact on hypoxia is almost as important as that of eutrophication. Accumulation of organic matter in the sediments introduces an important inertia in the recovery process after eutrophication, with a typical timescale of 9.3 yr. Seasonal fluctuations and the heterogeneous spatial distribution complicate the monitoring of bottom hypoxia, leading to contradictory conclusions when the interpretation is done from different sets of data. In particular, it appears that the recovery reported in the literature after 1995 was overestimated due to the use of observations concentrated in areas and months not typically affected by hypoxia. This stresses the urgent need for a dedicated monitoring effort in the Black Sea NWS focused on the areas and months concerned by recurrent hypoxic events.