dataesr/scientific-paragraphs-categorization huggingface dataset:
We calculated the total phytoplankton biomass by multiplying the WOA 2005 chlorophyll concentration by the C : Chl ratio profile of the PlankTOM5. 3 model  (Buitenhuis et al. , 2013, Fig. 2d ). The sum of our phytoplankton PFT biomass inventories is between 0. 7 and 1. 6 times the total phytoplankton derived from WOA chlorophyll down to 250 m (Fig. 2d ), despite the fact that we did not include a large part of the nanophytoplankton nor the autotrophic dinoflagellates. One of the reasons for the overestimate at the surface is probably a strong sampling bias in the Phaeocystis dataset towards high values, as suggested above. Dividing our phytoplankton carbon without Phaeocystis by WOA chlorophyll results in C : Chl ratios of between 44 and 99 down to 250 m, except at 125 m where diatom biomass is unexpectedly high.
These questions indicate that despite the scarcity of data for most groups we still know much more about the abundance of organisms than Earth Syst. Sci. Data, 5, 227-239, 2013  www. earth-syst-sci-data. net/5/227/2013/ about their carbon content/elemental composition, and much more about places where organisms are abundant than about the much larger volumes of global ocean where biomass is relatively low. Information becomes even more anecdotal, and understanding more tenuous, when looking at time scales longer than a few seasons. For large regions of the global ocean, systematic changes at an interannual scale (or longer) are largely unknown for most PFTs. Extending our perspective to the longer term and geological time scales, MAREDAT data may lead to a better understanding of both environmental and climate change, and the rate of CO 2 increase experienced over not only glacial-interglacial cycles but also since the beginning of industrialisation.
The Malaspina 2010 expedition (http://www. expedicionmalaspina. es) completed its journey in 2011, and collected samples from the deep oceans, at depths down to several thousand metres  (Laursen, 2011). The latter expedition will furnish us with new data to increase our understanding of deep ocean ecosystems, while the former will increase data coverage in the upper layers of the ocean. The ranges of global biomass inventories we calculated from the profiles of median and mean biomass in several cases span more than an order of magnitude. Despite this uncertainty they indicate that heterotrophic PFTs are at least as abundant as autotrophic PFTs (Table  2 ; Figs. 2d, 5 ), even if we account for the risk of double counting foraminifers as microzooplankton and pteropods as macrozooplankton in the sum of the zooplankton biomass.
Within the uncertainty in the data this is in agreement with  Gasol et al. (1997) , who estimated that the open ocean biomass of phytoplankton, total zooplankton and picoheterotrophs is roughly the same. We have compared our estimates of the sum of the available total phytoplankton biomass estimates with in situ chlorophyll. We find the sum of phytoplankton biomass is higher than biomass estimated from chlorophyll. All these databases are biased towards oversampling of the coastal ocean. The coastal ocean represents 5 % of the ocean area, but the phytoplankton biomass in the coastal ocean represents between 7 % (diazotrophs) and 34 % (Phaeocystis and diatoms) of the respective databases, while the WOA 2005 in situ chlorophyll represents 20 % of that database. In future updates of the databases we intend to diminish this bias by including additional observational data and improving the cell to carbon conversion algorithms, in particular for those PFTs with a large range of morphotypes and cell sizes.
This will allow a better determination of total phytoplankton biomass in the global ocean. Plankton are governed by physical, chemical and biological processes that occur on a vast variety of temporal and spatial scales. This is one reason why large datasets are needed to reliably estimate the global biomass distribution of any PFT. Physical processes can drive patchiness in PFTs on scales from millimetres to thousands of kilometres  (Pinel-Alloul, 1993; Folt and Burns, 1999). Over fine scales, millimetres to tens of metres, biological processes are often more important. For the picoheterotrophs, the estimated global biomass using the median and mean concentrations is very similar, indicating that the horizontal variation in biomass makes only a small contribution to the uncertainty in the estimated global biomass.
Growth rates for a number of groups within the macrozooplankton, particularly the gelatinous members, salps, ctenophores, cnidarians and appendicularians, are higher than those of mesozooplankton copepods  (Hirst and Bunker, 2003). The ability of these groups to "bloom" or swarm, through a combination of high grazing rates, growth rates and life history, when food concentration or other environmental factors are favourable, means that macrozooplankton may reach high biomass concentrations in areas where they amass, resulting in a spatially heterogeneous distribution. We show that the patchiness of PFT biomass increases with size. In terms of database synthesis, this means that more data would be needed for larger organisms before we can reliably generate interpolated datasets of biomass. In terms of model representation, it suggests that it will be more difficult to accurately represent individual data points, and that it will only be possible to represent the mean state or to build stochastic representations.
It should be noted that by using point measurements (usually representative of < 1 m 2 ) and binning these into a horizontal grid spacing of 1 • , there is potential for distorting the results. On the one hand, using gridded data means that the calculation cannot detect variations in patchiness that are smaller than 1 •. On the other hand, there are not enough data points in each grid point to obtain a true reflection of the average biomass in that grid cell, and therefore fine scale variability could potentially be ascribed to a larger scale. There is no indication that the latter invalidates the increase in patchiness with size that we find, since if it did then patchiness should be significantly higher for smaller datasets, which is not the case (p = 0. 5, n = 11). In addition to the depth and coastal ocean bias already noted for the phytoplankton, all of the heterotroph databases also have a depth bias (62-96 % of samples at < 225 m) and all but one have a coastal bias (13-28 % of samples in the coast).
The exception is foraminifers (2 %). In addition, 9 of the databases show a substantial bias towards samples in the Northern Hemisphere (64-100 % of the databases). The exceptions are pigments and coccolithophores, while macrozooplankton show a bias towards the Southern Hemisphere (70 %). The databases also tend to show some bias towards spring and summer (56-86 % of the databases). Qualitative information on the presence or absence of specific autotrophic groups from MAREDAT may help guide the a priori selection of pigment ratios that is essential for quantifying algal type abundance through Bayesian-type analyses  (Mackey et al. , 1996; Van der Meersche et al. , 2008). Conversely, the biomass databases from MAREDAT will be instrumental in evaluating those quantitative results, which may help bridge some of the information gaps in phytoplankton distributions.
Summary This introduction to MAREDAT and the data, results and discussion presented here represents what was at one point an almost impossible goal for many of those involved in this project. We are now in a position to make the first data based estimates of global annual average biomass for 11 PFTs and to validate biogeochemical models. PFT modelling is a relatively new development in ocean biogeochemical modelling, and global models embedded in general circulation models (GCMs) have only been available for the last 10 yr  (Aumont et al. , 2003). Improved validation of these models will also support climate change research, helping early detection of impacts and feedbacks from current climate change, and building better models for projections into the future. The MAREDAT data will also be fundamental for the investigation of global plankton biogeography and ecology.
Similar efforts have been suggested to collect other marine ecological data, such as phytoplankton traits (e. g. Barton et al. , 2013). The general weaknesses, e. g. fundamental lack of open water data and lack of elemental information for a variety of taxa, have also been recognised. Another major weakness of the initiative was that it was not possible to include some existing published and unpublished datasets, either because they were not publicly available, due to a lack of time for data retrieval, or because the response rates of the data owners to our data call were low. However, we have now set a precedent within the community for publishing this type of data and giving full accreditation to those involved in gathering it. Hopefully this will encourage data holders to contribute data in the future.
The authors involved in this special issue have agreed that datasets and documentation will be updated for the next release of MAREDAT, planned for 2015. The experience gained from this MARE-DAT iteration and the subsequent analysis of plankton ecology based on this data will help inform MAREDAT2015. Overall, this special issue has brought together abundance and biomass data for most of the PFTs in the lower trophic levels of the ocean ecosystem, as well as a global database of HPLC-based phytoplankton pigments. In several cases the biomass databases represent the first of their kind to cover all ocean basins, and in the remaining cases they are substantially larger than what has been available so far. In all, we have brought together 436 887 biomass measurements in 12 databases. The gridded data products have been provided for the ocean ecosystem modelling community.
Acknowledgements. We thank  Marie-Pierre Gosselin  for collecting the first versions of several PFT databases, funded by  EUR-OCEANS. We thank the guest editors  Stéphane Pesant  and  Walker O. Smith , the  ESSD  editorial team  Dave Carlson  and  Hans Pfeiffenberger , and the PANGAEA team. We acknowledge funding from the  EU  (to ETB, EMBRACE, contract  282672 , to COB, Greencycles, contract  238366 , to RM, FAASIS,  MEST- CT-2004-514159 ),  ETH Zürich  (to MV), and the  National Science Foundation  (to SCD and YL,  NSF-EF-0424599 ). Edited by:  W. Smith.
93 4. 29 8147 187 al- gorithms that distinguish multiple plankton groups. 2 Data Both the raw data files and the gridded files that were compiled for the 11 PFTs and the phytoplankton pigments are publicly available at the PANGAEA Data Publisher for Earth and Environmental Science (http://www. pangaea. de/ search?&q=maredat) and the MAREDAT website (http:// www. maredat. info). The latter also includes a technical cor- ner with the gridding program, QC script, etc. Each of the 12 datasets can be cited with the DOIs reported in Table 1. The raw data include longitude, latitude, depth, date, abundance, biomass conversion factors, biomass, references and quality control flags. The pigment database contains pigment con- centrations instead of abundance, biomass and biomass con- version factors.
The Phaeocystis database contains biomass information with and without an estimate of the gelatinous mucus surrounding colonial cells. The diazotroph database includes biomass information based on cell counts and on nif H gene counts. The biomass concentrations of coccol- ithophores and foraminifers are organic carbon only, while the pteropod biomass concentrations include both organic and inorganic carbon. In this paper, we only use the Phaeo- cystis biomass without mucus, and the diazotroph biomass based on cell counts. a Out of 539 ocean boxes. b The Chauvenet's criterion for the diazotroph database was calculated separately for the different data sources, but here we calculate one value for the standard deviation and zc for comparison to the other databases. enough information to furnish filled (interpolated) datasets.
evaluates where additional refinement is needed and grid generation procedures dynamically create or remove fine-grid patches as resolution requirements change. The method was implemented in the software MELODIE, developed by the French Institute for Radiological Protection and Nuclear Safety (IRSN, Institut de Radioprotection et de Suˆrete´Nucle´aire). The algorithm is then used to simulate the evolution of radionuclide migration from the waste packages through a heterogeneous disposal, demonstrating its capability to capture complex behavior of the resulting flow.
Le premier est local en temps et en espace et constitue un outil efficace pour l'adaptation du maillage ac haque pas de temps. Le second est global en espace mais local en temps et peut eˆtre utiliseṕ our l'adaptation en temps. La me´thode propose´e a e´te´inte´gre´e en deux dimensions d'espace dans le logiciel MELODIE de´veloppe´par l'Institut de Radioprotection et de Suˆrete´Nucle´aire (IRSN). La me´thodologie d'adaptation de maillage de´crite dans cet article est utilise´e pour simuler des exemples de relaˆchement et de migration de radionucle´ides dans un stockage ge´ologique de de´chets radioactifs. Des re´sultats nume´riques d'adaptation dynamique de maillages sont pre´sente´s et montrent l'efficacite´et la robustesse de la me´thode. Abstract -Adaptive Mesh Refinement for a Finite Volume Method for Flow and Transport of Radionuclides in Heterogeneous Porous Media -In this paper, we consider adaptive numerical simulation of miscible displacement problems in porous media, which are modeled by single phase flow equations.
Closely related to our work, we refer for instance to  [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25]  and the references therein. The French Institute for Radiological Protection and Nuclear Safety (IRSN) developed the code MELODIE, see for instance  [26]  and  [27] , and is constantly upgrading it, for numerical modeling of the physico-chemical phenomena involved in the release and in the migration of radionuclides from waste packages to the geosphere outlets (in deep geological formations, and more recently at surface or sub-surface locations). The mathematical formulation of these type of flow leads to a coupled system of partial differential equations, which includes an elliptic pressure-velocity equation and a diffusion-convection concentration equation.
A vertex-centred finite volume method is employed to discretize the coupled system: the Darcy flow equation and the diffusion-convection concentration equation. The convection term is approximated with a Godunov scheme over the dual finite volume mesh, whereas the diffusion-dispersion term is discretized by piecewise linear conforming finite elements. The motivation for applying such finite volume procedure for modeling flow in porous media arises from the fact that this scheme is mass conservative element by element and satisfies a discrete maximum principle. IRSN is constantly upgrading MELODIE to improve the resolution time, the accuracy and the confidence in the results of the simulations. The purpose of this paper is to build a posteriori error estimators with a strategy of adaptive mesh refinement, implement the method in the code MELODIE and present numerical simulations.
Discretization of the Transport Equation Discretization of the concentration Equation (  3 ) is performed by using a vertex-centred finite volume method, (e. g. ,  [2] ), with a semi-implicit time stepping, the time discretization is implicit for the diffusion term and it is explicit for the convective term. The diffusion term is discretized by piecewise linear conforming finite elements, whereas the convective term is approximated with the aid of a Godunov scheme. Let us mention that a fully implicit scheme is also available in the code MELODIE. Let C n i be an approximation of C at the point ðx i ; t n Þ. First, we integrate Equation (3) over the control volume V i , we apply the divergence theorem, a semi-implicit time discretization, the mass lumping in the accumulation term and a full upwind stabilization in the convective term, resulting in the following discrete concentration equation: x i V i j j C n i À C nÀ1 i s n À Z oV i DrC n À qC nÀ1 À Á :ñdr ¼ V i j jf n i ð13Þ where x i ¼ 1 jV i j R V i xðxÞdx and f n i ¼ 1 jV i j R V i f ðx; t n Þdx The discretization for the diffusive flux in (  13 ) is performed using the same steps as above for the pressure equation.
CONCLUSION In this paper, we presented an adaptive mesh refinement algorithm for single phase flow in porous media. The processes modeled are miscible flow of an incompressible fluid with a dissolved radioactive solute to simulate the evolution of radionuclide migration in a nuclear waste repository. The resulting system is discretized by a vertex-centred finite volume method. The method was implemented in the software MELODIE. This leads to a considerable improvement in computational efficiency. The adaptive strategy has been illustrated by means of numerical examples in an academic scenario and a realistic scenario. The above results illustrate that the proposed adaptive mesh refinement is capable of tackling in a robust and accurate fashion various physical phenomena relevant to flow and transport of radionuclides in heterogeneous porous media.
This approach respond to a need of simplicity because even if it exists several tools to make a complete survey of a site (photogrammetric softwares, 3D modelling tools, databases,. ), there is not at this time a single tool that can manage the whole process of survey from the data acquisition until integration of semantic data. This new platform will be the base for developing new functionalities in order to satisfy specific needs like the visual representation of stratigraphic and temporal relations between archaeological contexts of a site or the survey of coral growing along time.
The effect of pH of the solution has been also considered. A specific modeling including chemistry, transport and mechanical aspects has been developed  [10]. This model, implemented in the software ALLIANCES (coupling chemical, transport and mechanical codes), is able to predict in the case of leaching the degradation fronts of minerals, the evolutions of the diffusion properties of the degraded zone and its Young's modulus (Figure  3 ) as a function of the mineral assemblage thanks to multiscale homogenization techniques. Macroscopic cracking is also described by a specific orthotropic damage model  [11]. At this moment, tests and modeling approach are realized for more realistic conditions. Cementitious materials are exposed to a solution representative of the clayey geological layer (multi-ionic attack) or directly to the natural clay (specific device ABIE able to keep the confinement of clay in contact with cement paste) (Figure  4a ).
It has been implemented in the finite element code Cast3M developed at CEA, and applied to the simulation of a reinforced concrete structure MAQBETH. This structure is constituted of a hollow cylinder with external diameter of 2. 2 m and height of 3 m, and it has undergone a thermal loading at 200°C in the inner surface during several hundreds of hours (Figure  7 ). The model capacity to reproduce the main features of the concrete structure including the reinforcement rebars has then been demonstrated through the comparison between numerical and experimental results in terms of evolutions of temperatures, gas pressures, relative humidity and strains in the median plan of the structure as a function of time  [18]. Note that the simulation has been carried out in 2D on 2 different meshes adapted for solving the thermo-hydric and mechanical problems, respectively, in an axisymmetric formulation (Figure  7 ).
A. SiVIC-RTMaps™ interconnection Our CS simulation architecture is based on the interconnection of the sensors simulation platform SiVIC and the prototyping platform RTMaps™. The interconnection between SiVIC and RTMaps™ allows replacing real measurements by simulated ones, creating a fully Software-Inthe-Loop (SIL) development and prototyping approach. 1) The SiVIC platform SiVIC  [3]  is a platform designed to enhance the process of developing and evaluating ADAS. This platform enables the simulation of multi-frequency sensors embedded in static or dynamic devices, equipments and vehicles commonly used in ADAS scenarios. The SiVIC platform is a very efficient tool to develop, prototype and evaluate high level ADAS (see Fig. 1 ), including CS applications. SiVIC can be easily interconnected with several external platforms such as RTMaps™ (see section II-A2) or Matlab™ (from Mathworks).
This interconnection interface is efficient and useful to perform a great number of developments in a SIL approach. Once the application is evaluated in virtual condition and validated in simulation, it can be integrated and tested into a real embedded hardware architecture (on vehicle) further towards the end of the development cycle. SiVIC uses a realistic graphical environment (Fig. 2 ), supported by physically accurate behaviours for vehicles and sensors. It can generate a flow of time-stamped and synchronised data that can be recorded and/or interacted with by prototyping and/or data treatment platforms such as RTMaps™ or Matlab™. Furthermore, SiVIC can generate multiple scenarios with events-driven mechanisms, so that the robustness and reliability of control and perception algorithms can be extensively tested on many parameters.
B. Overall architecture The developed CS simulation architecture can be applied to any kind of CS usage scenario. It is partially scenariospecific, both in SiVIC and RTMaps. Scenarios are built in SiVIC by using script files, that specify the location of objects and many other parameters. The actual CS application needs to be developed and implemented in RTMaps. While developing our architecture, in order to simplify our work, we focused at first on simulating strings of IVC-equipped vehicles, specifically for EEBL applications. However, developments such as vehicles' control mechanisms and the 802. 11p simulation are not scenario-dependent and are an integral part of SiVIC. Fig. 3  shows the data flow and relationships between the environment, sensors and algorithms as implemented in the SiVIC-RTMaps™ environment.
ACKNOWLEDGEMENT This work is supported by the  Commonwealth of Australia  through the  Cooperative Research Centre for Advanced Automotive Technology , as well as by the  French Institute of Science and Technology for Transport, Development and Networks. A sub part of this work has been developed in the  CooPerCom  project, a 3-year international research project ( Canada-France ). The authors would like to thank the  National Science and Engineering Research Council (NSERC) of Canada  and the  Agence nationale de la recherche (ANR) in France  for supporting the project.
Internet-Based Monitoring System "Babies at home" We developed the Internet-based monitoring tool "Babies at home" as a dynamic server-side website based on PHP language and MySQL database on a Linux/Apache server. All the development phases, from the structural design to the content formulation, evolved in close collaboration with the medical/nursing staff. The application comprises three main areas: 1. Free-access Area: open platform where all parents can find extensive high-quality information about baby care and useful links to breastfeeding and neonatal nursing association websites (see Multimedia Appendix 2). 2. Parents' Area: restricted area where only registered parents can access after authentication (see Multimedia Appendix 3). They are asked to answer twice a week a questionnaire from the neonatal nurses about the baby's conditions (weight, feeding, sleeping, body temperature, skin color, etc.