dataesr/scientific-paragraphs-categorization huggingface dataset:
These developments required important changes in the model, as well as the improvement of many processes already included in the previous version: the Fast-JX module for realistic evaluation of the photolysis rates has been added and allows the calculation of updated photolysis rates at each physical time step, including the optical effects of clouds and aerosols. The mineral dust emissions have been upgraded in order to estimate fluxes in any region. In addition, this new version has also been an opportunity to update the representation of chemical processes by giving the user the choice to use the SAPRC chemical mechanism, which is more widely used than the MELCHIOR chemical scheme developed for the CHIMERE model. In the same line, chlorine chemistry has been included, and the representation of physical processes affecting the aerosols, such as nucleation, coagulation, and wet deposition has been improved, while a scheme for resuspension of particulate matter in urbanized areas has been included in the model.
CHIMERE being both used for analysis and forecast, a particular attention was given to the optimization of computational performance. Numerous improvements were made in the code and are completely transparent for the user: these changes are described in Section 2. Section 3 presents the changes in the model geometry, including the vertical mesh, as well as changes in the horizontal coordinate system allowing the application of the model to hemispheric scale domains. Section 4 presents the improvements in the representation of anthropogenic emissions, including the use of the global HTAP emission dataset for anthropogenic emissions, and the improvements in modelling mineral dust emissions. Section 5 describes the changes in the representation of various physical and chemical processes in the model, such as inclusion of the SAPRC scheme for gaseous chemistry or inclusion of chlorine chemistry in the model.
This section also presents the evolutions in the modelling of the physical processes affecting aerosols, as well as the implementation of the Fast-JX module for radiative transfers. Another major improvement presented in this section is the ability of CHIMERE-2016 to provide LIDAR observables as a model output. Section 6 presents the application of CHIMERE-2016 to simulations of three winter months and three summer months in a domain covering continental Europe at 50 km resolution, and the scores obtained by the model in comparison with background observations of gaseous and particulate species in this configuration. Section 7 presents the application of the new model version to the simulation of the eruption of the Puyehue-Cordon Caulle volcano, in the Chilean Andes, in June 2011. This event provides a good testbed for this new version, since the volcanic plume from this volcanic eruption was dense enough to be observed by satellites all along its circumpolar transport around the South Pole.
Therefore, in the CHIMERE-2016 version, this master process has been removed: using the parallel input/output routines of the Parallel-Netcdf library  (Li et al. , 2003) , each worker process now reads the netcdf input files and writes the output data for its own sub-domain, removing the bottleneck effect due to the centralization of input/output tasks. This induces some major simplifications of CHIMERE code, including reduction of inter-process communications related to the parallelization of the input/output processes, which were performed in a central way by the master process in previous model version.
4. scaling and reformatting of the raw emissions from the EMEP emission inventory at 50 km resolution, but can be adapted by users to any other raw dataset they need to use. The main steps for this are described in  Menut et al. (2012 Menut et al. ( , 2013a)) : -A first step projects the annual masses from the "raw" EMEP grid to the CHIMERE grid. The spatial emission distribution from the EMEP grid to the CHIMERE grid is performed using proxys like population density, as described by Figs. 5a-d. Proxies used by emisurf for this process include land use data (either GLCF, USGS or GlobCover), large point source database (such as the EPER database for Europe), etc. -Second, monthly, weekly and hourly profiles are prescribed to convert annual totals to hourly fluxes used as input for CHIMERE. These factors are derived largely from data provided by the University of Stuttgart (IER) as part of the GEN-EMIS project  (Friedrich and Reis, 2004) , and are available as data files from the EMEP model website, www.
emep. int. -A last step consists in converting the species available in the raw data into the model species. Generally, a minimum of seven species are available: CO, SO x , NO x , NH 3 , NMVOC, PM 2. 5 and PM coarse (difference between PM 10 and PM 2. 5 ). In CHIMERE, depending on the chemical scheme, about 30 species are emitted. NO x is split into NO, NO 2 and HONO. Usually, 5 to 10 % is assigned for NO 2 emissions for all sectors, except for traffic emissions where a 20% should assigned to NO 2 for modern fleet (post 2010). For NMVOC, the VOC data used are derived from the detailed United Kingdom speciation given in  Passant (2002). For SO x , 99% is assigned to SO 2 and 1% for primary sulphate to account for very fast and local sulphate production. The lumping procedure accounts for the reactivity of VOC species following  Middleton et al.
Recent changes The main recent changes have been focused on the use of proxies to better reallocate in space the raw emissions. This specialization can be performed from the raw gridded data or directly from the annual country totals  (Terrenoire et al. , 2015). The European Pollutant Release and Transfer Register (E-PRTR) data are used to precisely place the emissions from the main industrial sources. E-PRTR is the Europe-wide register that provides easily accessible key environmental data from industrial facilities in European Union Member States and in Iceland, Liechtenstein, Norway, Serbia and Switzerland. For road traffic emissions, a new spatial proxy was developed based on the correlation between the French bottom-up emission inventory at 1km resolution and different spatial databases.
Mineral dust emissions Mineral dust modelling is an important process for climate processes but also for air quality regional modelling. For many regions over the world, it becomes necessary to manage air pollution knowing the relative part of anthropogenic and natural contributions. For this, even over small regions, it is important to have the same level of knowledge on mineral dust emissions as for anthopogenic or biogenic emissions. In this new model version, many improvements were done for mineral dust emissions. They are related to input databases, the emission schemes themselves and additional options to better take into the impact of meteorological conditions on emissions.
Soil, landuse and roughness length For the calculation of mineral dust emissions, several variables have to be known: landuse, soil characteristics, aeolian roughness length and erodibility. Originally, CHIMERE used a database limited to North Africa and the Arabian peninsula. For simulations over Africa or Europe, this spatially limited database was considered adequate, Sahara being the major source in this region. But for this new CHIMERE-2016 version, the goal is to enable calculations of mineral dust emissions anywhere in the world. It is then necessary to change all required databases and to move to global databases. A large part of this change was already done in  Menut et al. (2013c)  for landuse, soil and roughness length. The soil and landuse used are now those from NCAR USGS landuse dataset  (Homer et al.
, 2004)  and STATSGO-FAO soil dataset  (Wolock, 1994). The roughness length is estimated using the global 6km horizontal resolution GARLAP (Global Aeolian Roughness Lengths from ASCAT and PARASOL) dataset  (Prigent et al. , 2012). In addition to these changes, the possibility to evaluate the soil erodibility based on satellite data was added. In the previous versions, the erodibility was based on the landuse database: cropland, grassland, shrubland and barren or sparsely vegetated areas were considered as erodible. In this case, constant percentages are applied for each landuse. While this possibility is maintained in CHIMERE-2016, a new option uses the global erodibility dataset derived from MODIS, as presented in  Grini et al. (2005) , and already included in CHIMERE and used, as described by  Beegum et al.
Modelling strategy CHIMERE-2016 includes the module Fast-JX version 7. 0b  (Wild et al. , 2000; Bian et al. , 2002)  for the online calculation of the photolysis rates. Fast-JX is a module which solves the equations of radiative transfer in an atmospheric column taking into account the Solar zenithal angle, the vertical profile of ozone and water vapor concentrations, the ice-and water-clouds, the radiative effect of scattering and absorption by aerosols and the surface albedo. Taking these factors (and their real-time simulated variations) into account, Fast-JX computes the photolysis rates for all the relevant photochemical reactions that has been designed in order to be easily introduced in Chemistry-transport models, which has already been done in various CTMs such as PHOTOMCAT  (Voulgarakis et al.
While this set of approximations was acceptable when the CHIMERE model was used as boundary-layer regional CTM for locations in Europe, this had strong limitations for its use for longer-term simulations including long-range transport in the free troposphere over geographical domains including polar and/or tropical zones. Therefore, the Fast-JX module has been included in CHIMERE-2016. Photolysis rates for the photodissociation of ozone and nitrogen dioxide as computed by the Fast-JX model inside CHIMERE have been compared favorably to in situ measurements at the island of Lampedusa (Italy), including in presence of aerosols  (Mailler et al. , 2016).
Species Real part of the refractive index Imaginary part of the refractive index λ 200 nm 300 nm 400 nm 600 nm 1000 nm 200 nm 300 nm 400 nm 600 nm 1000 nm Table  4. Refractive indices for the main aerosol species in CHIMERE at 200, 300, 400, 600 and 1000 nm After the preprocessing phase, at each time step and in each model column, the Fast-JX module resolves the radiative transfer in the model atmospheric column, computing the actinic fluxes at each model level and integrating them over N wavelength bins in order to produce accurate photolysis rates. In the configuration adopted for CHIMERE-2016, N is set to 12, which is the value recommanded by Fast-JX developers for tropospheric studies. These 12 wavelength bins include the 7 standard Fast-J wavelength bins from 291 nm to 850 nm, as described in  Wild et al.
Anthropogenic and natural emissions Anthropogenic and natural emissions have been modelled as described above. The anthropogenic emissions have been produced from the HTAP dataset, while biogenic emissions have been produced from the MEGAN model. Mineral dust emissions have not been included in this simulation, since the focus of this testbed study was in the circumpolar transport of ash emissions from the Puyehue volcano. 04/06 10 794. 9 1. 99×10 06 2. 86×10 10 1. 14×10 10 05/06 10 794. 9 1. 99×10 06 1. 72×10 11 6. 87×10 10 06/06 10 794. 9 1. 99×10 06 1. 72×10 11 6. 87×10 10 07/06 6. 5 133. 0 3. 33×10 05 2. 87×10 10 1. 15×10 The simulation, covering from May 15 through June 30 can be divided into two successive phases : first, from May 14 to June 4, the model undergoes a spinup period, with the concentrations of gaseous and particulate species building up due to the emissions of sea-salt and anthropogenic contaminants (Fig.
(2013) and Global Volcanism Program (2013). Fig. 8b  for June 6 at 12UTC (8AM local time) can be compared to Figure  2  of  Klüser et al. (2013)  (lower left panel), which shows that at this time, about 36 hours Argentina, covering a large part of southern Brazil in the model but not so in the infrared AOD data provided by  Klüser et al. (2013). Finally, the plume from the initial explosions are located at that time in the souther ocean, in-between the southern tip of the African continent and the Antarctic. It can also be observed that while the ash plume is continuous in the CHIMERE simulation, it is not so in the observations. This reflects the succession of explosive phases and quiet phases of the volcanic eruption, while the flux imposed to the CHIMERE model is continuous, as discussed in  Boichu et al.
Other countries are only covered by the world roadmap and population data. 11Geosci. ModelDev. Discuss. , doi:10. 5194/gmd-2016-196, 2016   Manuscript under review for journal Geosci. Model Dev. Published: 7 September 2016 c Author(s) 2016. CC-BY 3. 0 License. For shipping emissions (SNAP 8), a proxy was developed using an inventory of shipping routes obtained from the US National Center for Ecological Analysis and Synthesis (NCEAS). An inventory was developed for the year 2008 by Halpern et al. (2015)  but the dataset remains non-exhaustive, the data being collected only on voluntary vessels.
Acknowledgements. For anthropogenic emissions, EuroglobalMap products includes Intellectual Property from European National Mapping and Cadastral Authorities and is licensed on behalf of these by EuroGeographics. Original product is freely available at www. eurogeographics. org. Terms of the licence available at http://www. eurogeographics. org/form/topographic-data-eurogeographics. The MACC boundary conditions data set was provided by the  MACC-II  project, which is funded through the  European Union   Framework 7 programme. It is based on the MACC-II reanalysis for atmospheric composition; full access to and more information about this data can 34  Geosci. Model Dev. Discuss. , doi:10. 5194/gmd-2016-196,2016 Manuscript under review for journal  Geosci. Model Dev. Published: 7 September 2016 c Author(s)  2016.
10- Other countries are only covered by the world roadmap and population data. 11Geosci. ModelDev. Discuss. , doi:10. 5194/gmd-2016-196, 2016   Manuscript under review for journal Geosci. Model Dev. Published: 7 September 2016 c Author(s) 2016. CC-BY 3. 0 License. For shipping emissions (SNAP 8), a proxy was developed using an inventory of shipping routes obtained from the US National Center for Ecological Analysis and Synthesis (NCEAS). An inventory was developed for the year 2008 by Halpern et al. (2015)  but the dataset remains non-exhaustive, the data being collected only on voluntary vessels.
The nuclear markers were only used in representative specimens according to geographical (one specimen per population) and topological criteria. For each amplification reaction, we obtained both forward and reverse sequences. In some specimens, and due to difficulties of amplification, we used internal primers for the fragment COI-3 , obtaining two fragments of 400 bp each. The obtained products were purified by standard ethanol precipitation and sent to external facilities for sequencing after purification (LMU Genomics Service Unit, Martinsried, Germany). DNA sequences were assembled and edited using the GENEIOUS 6 software (Biomatters Ltd, Auckland, New Zealand). New Deronectes sequences (a total of 791) have been deposited in GenBank with accession numbers LT601818-LT602609, and Wolbachia sequences (  23 ) with numbers LT602610-LT602633 (Table  S1 ).
Phylogenetic and phylogeographic analyses Edited sequences were aligned with MAFFT v. 6 using the G-INS algorithm and default values for other parameters  (Katoh & Toh, 2008). We employed six partitions corresponding to the gene fragments COI-5 , COI-3 , 16S rRNA+tRNA-Leu, nad1, H3 and Wg, and used Partition Finder 1. 1. 1 (Lanfear et al. , 2012)  to estimate the best partitioning scheme (each gene separately or combining genes in a partition by codons) and the evolutionary model that best fitted the data for each partition separately, using the AIC (Akaike Information Criterion) as selection criteria. We performed two types of analyses using different datasets: (1) a global phylogeny/phylogeography to estimate the relationships of the main lineages within each group and root them; and (2) demographic analyses of the best population coalescent model for each group, including a reconstruction of the geographical history estimated from the distribution of the sampled localities.
A resource can easily be thought of as an object as in OOP (Object-Oriented Programming). It consists in identifying the resources and determining how they are related to each other. As illustrated in Fig. 2  ADR is the representation of resource model in the platform. The new component added to this model is the service class, which describes the RESTful API service delivered by each digital resource. After identifying the resource, the next step is to define a way to represent these resources in our system. To do so, we make use of JSONLD (JavaScript Object Notation for Linked Data)  [26]  data format. JSON-LD is a subset of the key-value based JSON document format that provides a way of describing machine-readable information with semantic context. JSON is used as a base data format for search engines such as Elastic Search  [27]  and NoSQL data store which is used by our platform architecture.
Research is needed to demonstrate how resources can be linked to meet various needs. Strategies to assist learners in analyzing and interpreting resources in terms of their validity and reliability are also needed  [40]. Our objective was to well define this process to integrate multiple resources into a coherent learning environment based on the digital resource retrieval and interoperability enhancement. Learning Object Metadata initiative published in 2002  [41]  is one of the widest adopted standards for educational resource description. IEEE-LOM gives the opportunity for education resource producers to describe their resources. But for their retrieval, we need to build search engines such as MERLOT or GLOBE. The main issue of these systems lies in the lack of web service that allows consumers to integrate the resources retrieved into the user personal environment.
The Cherenkov Telescope Array (CTA), a ground-based facility for very-high-energy (VHE) gamma-ray astronomy, will operate as an open observatory, serving a wide scientific community to explore and to study the non-thermal universe. Open community access is a novelty in this domain, putting a challenge on the implementation of services that make VHE gamma-ray astronomy as accessible as any other waveband. We present here the design of the CTA Observer Access system that comprises support of scientific users, dissemination of data and software, tools for scientific analysis, and the system to submit observing proposals. We outline the scientific user workflows and provide the status of the current developments.
Event lists, relevant instrument response functions (IRFs), and auxiliary data will be delivered to the user in FITS format, together with a dedicated software package for data analysis. After a proprietary period of one year, during which users granted observation time will have exclusive access to data, the data will be made publicly and openly available in the CTA data archive. Highlevel data, such as sky maps, spectra, light curves, and source catalogues, will be distributed using Virtual Observatory (VO) protocols. The distribution of event lists through VO protocols is under investigation. Observer Access is one of the five work packages of the CTA Data Management work package and provides all services and tools that are needed by Guest Observers and CTA Archive Users to perform a successful scientific analysis of CTA data.
Work Flow Guest Observers will start with writing and submitting Guest Observer proposals to CTA in response to an Announcement of Opportunity. In preparing their proposals, Guest Observers will make use of calculators that provide information about array sensitivity, target visibility, or required exposure time. Once submitted, Guest Observer proposals will be evaluated by a Time Allocation Committee (TAC) that has been appointed by the CTA Observatory. The Guest Observers will be informed about the outcome of this process, and successful proposals will be scheduled for observation. Guest Observers will be able to follow the status of the observations online, including the scheduling, the data acquisition, the data processing, the data distribution and the ingestion of the data in the public archive after the end of the proprietary period.
Guest Observers will download the processed data as well as the software tools that are necessary for the scientific analysis from the web. Science analysis will be performed on the Guest Observers' own computing infrastructure. Web-based information about the data and the analysis software, comprising user manuals, cook books, etc. will also be available. Eventually, Guest Observers will have attended dedicated CTA analysis schools or hands-on workshops to familiarise themselves with the CTA Observatory, the CTA data, and the CTA analysis software. If further assistance is needed, Guest Observers can contact a help desk (by web or by e-mail). Archive Users will browse the public archive to access CTA data. They either may download existing event data based on specific selection criteria (source location, observation time interval, observation condition criteria, etc.
), or they may "prune" the public CTA event database to extract a specific dataset that meets the needs (e. g. , specific event class selection, energy range, etc. ). CTA images, spectra, light curves and event lists can also be accessed through Virtual Observatory (VO) protocols. Archive Users will also download the analysis software, access any supporting material as needed, and analyse the data on their own computing infrastructure. Archive Users may also have attended dedicated CTA analysis schools or hands-on workshops to familiarise themselves with CTA, the data and the software. Archive Users may of course also contact the help desk to ask for assistance. Figure  1  illustrates the overall work flow for Guest Observers and Archive Users. The figure distinguishes the four components that are needed to implement the services and tools in this work flow: User Support, Science Tools, Dissemination and Proposal Handling.
Observer Access Products The first two levels of the Observer Access work package Product Breakdown Structure (PBS) is represented in Fig. 2. Besides work package documentation, the Observer Access work package comprises four products. The User Support product provides the elements that are needed to support the scientific users of CTA. This comprises user documentation (user manuals, cookbooks, FAQ), knowledge dissemination (forum and e-mail list, newsletters, organisation of analysis schools), as well as a human-staffed help desk. The Dissemination product provides all software that is needed to access data (data access), documentation (document access), and software (software access). The Science Tools product provides the software that enables the user to derive images, spectra and light curves from calibrated, reconstructed and background reduced CTA event data.
The proposal package will comprise a web interface with web forms to provide proposal information (e. g. , name and affiliation of Principal Investigator, target name and coordinates, requested array and configuration, executive summary, etc. ). It also includes a template for the scientific justification that will accompany the proposal. All proposals will be handled by a dedicated Proposal Management System. The system will comprise a proposal database, a proposal database management system, and a system allowing Guest Observers to retrieve the status of their proposals, including information about proposal evaluation, scheduling, data availability and release of the data into the public archive after the end of the proprietary period. Proposals submitted through the web interface will be ingested by the Proposal Management System.