dataesr/scientific-paragraphs-categorization huggingface dataset:
2014). Therefore, PRDX4 remains a strong candidate gene for this QTL. The three other nsSNPs were detected within three genes: EIF2S3, PCYT1B, and E1BTD2 (Table  2 ). EIF2S3 has been described to contribute to the early stage of protein synthesis by interacting with guanosine-59-triphosphate and initiator transfer RNA to form a ternary complex and binding to a 40S ribosomal subunit (Entrez Gene: EIF2S3). PCYT1B is an enzyme and involved in the regulation of phosphatidylcholine biosynthesis. Several alternatively spliced transcript variants encoding different isoforms have been found for this gene  (Wang et al. 2005). Another gene, E1BTD2, is uncharacterized. By using BLAST, the predicted function of E1BTD2 was "organic solute a PASE score comprises physicochemical properties scores and sequence conservation scores.
ACKNOWLEDGMENTS Two referees are kindly acknowledged for their suggestions, which improved the manuscript. J. N. was funded by the  Marie Curie Host Fellowships for Early Stage Research Training , as part of the  6th Framework Program  of the  European Commission. D. J. K. and I. D. acknowledge support from the  BBSRC  through The  Roslin Institute Strategic Programme Grant. The sequencing results are part of the  SABRE  research project that has been co-financed by the  European Commission , within the  6th Framework Program , contract no. FOOD-CT-2006-016250. This publication represents the views of the authors, not the  European Commission. LITERATURE CITED.
PHASE 8: Programming (Prototyping) A system incorporating Virtual Reality (VR) relies first and foremost on a computer environment (computer, work station, cluster of computers, etc. ) to which all the peripheral devices needed for the system are connected. The prototype phase is therefore principally the responsibility of the computer specialists. Even if some software presents an interface that is easily accessible to non programmers, it is illusory to think that a team without a computer specialist would be able to develop an efficient system. With ongoing contact with the computer specialists, the project leader ensures the system definition file is followed and will, if needed, learn to communicate with them (computer specialists sometimes have a vision of the system that is structured around blocks of lines of codes and think more in terms of producing computer functions rather the global function of the system)  [21].
Two-dimensional solid-state X-ray detectors can now operate at considerable data throughput rates that allow full three-dimensional sampling of scattering data from extended volumes of reciprocal space within second to minute timescales. For such experiments, simultaneous analysis and visualization allows for remeasurements and a more dynamic measurement strategy. A new software, Nebula, is presented. It efficiently reconstructs X-ray scattering data, generates three-dimensional reciprocal space data sets that can be visualized interactively, and aims to enable real-time processing in high-throughput measurements by employing parallel computing on commodity hardware.
Visualization The sparse data sets are visualized using volume ray casting  (Levoy, 1988; Drebin et al. , 1988). In short, each texel on the screen used for rendering corresponds to a ray penetrating the volume containing the data set. The direction and extent of each ray is determined by a viewing frustum extending from a hypothetical camera point. The rays traverse the data and samples are taken along each ray in a front-to-back manner, with each intensity sample matched to an RGBA color value. The colors are blended together, and the texel takes the value of the accumulated color upon completing the ray traversal (cf. Figs. 2  and 3 ). This mode of visualization is the default and is referred to as normal color blending. The visualization greatly depends on the choice of transfer function, i.
Performance The bottleneck for three-dimensional visualization algorithms is computer processing power, which has increased rapidly with continued advances in lithography. Fully capable hardware can now be acquired off the shelf. Notably, this software benefits greatly from using a dedicated graphics processing unit -a common component in most modern computers. This enables the use of OpenCL to parallelize tasks that would otherwise be considerable bottlenecks in the program work flow. In particular, parts of the reconstruction and volume rendering algorithms benefit greatly from parallelization. Consequently, the software requires an OpenCL capable graphics card with sufficient video memory to store data sets during rendering. During reconstruction, the most time-consuming task is typically to read and decompress data from the hard drive.
Software and hardware environment The program is written in C++ and uses OpenGL and OpenCL for rendering and parallelized computations, respectively. The graphical user interface is provided by Qt 5. The software has been tested under 64 bit Arch Linux and 64 bit Windows 7, with the hardware specifications as shown in Table  1. The minimum hardware requirement is an OpenCL 1. 1 and OpenGL 4. 0 capable graphics card and 2 GB of system RAM. The maximum data set size is limited by the available system RAM, the graphics card RAM and the system hard drive space, but there are no fixed lower bounds on the latter two.
Availability and documentation The source code is available under the GNU General Public License at https://github. com/Natnux/nebula. Documentation for users exists in the wiki on the same page. Anyone is invited to browse the source code, and code contributions through Git are greatly appreciated. Thanks are extended to Dag Breiby (Department of Physics, NTNU), Jostein Fløystad (SINTEF Energy Research) and Thomas Falck (Department of Computer and Information Science, NTNU) for inspiration in the early phase of development, and to Thomas Tybell (Department of Electronics and Telecommunications, NTNU) for providing the sample used to collect the data presented in Fig. 3.
Project description The Pan-European Species-directories Infrastructure (PESI) provides a mechanism to deliver an integrated, annotated checklist of the species occurring in 'geographic Europe', aiming to cover the Western Paleartic biogeographic region. The PESI checklist (also called EU-nomen) serves as a taxonomic standard and backbone for Europe. At the core of EU-nomen are five community networks, with common nomenclatures or systems designations: Zoology, Botany, Marine Biota, Mycology and Phycology. These five community networks are integrated in five infrastructural components (Fig. 1 ): expert networks (knowledge), focal point networks (consensus), conceptual integration (standards), technical integration (data) and e-Services (dissemination). The databases from the community networks Euro+Med PlantBase (E+M); Fauna Europaea (FaEu); the E uropean Register of Marine Species (ERMS), and Species Fungorum Europe (SF-EU)feed into a single data warehouse that supports the PESI Portal, a service webportal developed during the project phase of PESI  (May 2008 to May 2011).
Surrounding this core, PESI includes the interactions with the geographic focal point networks, a network of taxonomic experts and global species databases. PESI merges data from multiple sources and publishes it online. This requires a mapping between the different schemas used by the different data sources and/or an implementation of standards within those data sources. A pragmatic approach was taken for the main databases. A bespoke procedure was developed at the Botanic Garden and Botanical Museum Berlin-Dahlem (BGBM) using the EDIT Common Data Model-based Platform for Cybertaxonomy to merge Euro+Med PlantBase and Fauna Europaea. These data are merged with ERMS and additional data provided by these checklists (such as distribution details) in the PESI Data Warehouse. This procedure is repeated periodically to keep the data warehouse synchronised with the source databases.
The Flanders Marine Institute (VLIZ), that manages the portal, adds further information (such as images, vernacular names and priority status) and gathers information from other portals, such as the World Register of Marine Species. In order for the data sets to be merged in this way they need to share common vocabularies for some fields -these include: taxon status, nomenclatural status and occurrence status. PESI provides species lists based on geographic regions and European legislation (e. g. the Habitat Directive, Birds Directive, CITES and IUCN (conservation status) directives). The resulting dataset includes a total of nearly 450,000 scientific names (which include 240,000 valid species and infraspecific names) and 190,800 vernacular names in 117 languages. In the PESI portal, each species has its own result page including a map of its geographical distribution, and many have deep links to additional data (photos, videos, literature, global prioritised species databases).
The portal further includes: a Taxon Search Tool, a Taxon Match Tool (for users to match their species names against the names in PESI to check spelling, synonymy and classificaiton), a metadata database on taxonomic resources and expertise (provided by focal point partners all over Europe and adjacent countries), Web Services and links to existing nomenclators. The Project website provides information about the PESI project and the available communication tools. PESI builds upon previous European taxonomic projects (like EDIT, ENBI and EuroCAT) and strengthens the taxonomic networks to ensure that data are updated and that relevant social networks and research communities are maintained and developed. PESI contributes to building the capacity necessary to support a growing number of international initiatives such as the Global Biodiversity Information Facility (GBIF), LifeWatch (LW), the Catalogue of Life (CoL), the Encyclopedia of Life (EoL), the Global Names Architecture (GNA), GÉANT, and Research Data Alliance (RDA).
Towards a European taxonomic workforce (ETW) A pan-European Taxonomic Workforce (ETW), consisting of all people who carry out taxonomic work in Europe, was identified as pivotal for the integration and coordination of the current and future expert networks within Europe (Fig. 2 ). This task force integrates the already existing expert networks supporting the pan-European checklists, extended by the collaborative capacity of the EDIT institutional staff previously assembled within the EDIT Expert Database (Fig. 3 ). The additional inclusion of the Focal Point network was an important step forward carried out by PESI. A report on the tasks, activities and operational standards necessary for a functional ETW was drafted (Suppl. material 2), taking into account the concepts of an Open Source Society model (Fig.
Quality control and standards PESI has set out a working Intellectual Property Rights (IPR) model, based on the SMEBD model, under which PESI can proceed with its aim to integrate taxonomic databases in Europe, ensuring the free and wide dissemination of data, and promoting the further virtualisation efforts (e-Taxonomy; e-Science; e-Publishing) in this field. The SMEBD model encourages scientists to input their data without being burdened with its upkeep. This allows scientists to retain full ownership of their work, knowing that data stewards are managing their data accordingly. This IPR model proposes a Creative Commons Attribution (cc-BY) license that allows for the wide dissemination of data to other scientists material 3) that contributing databases adopt a standard citation system to simplify the citation system in PESI and that the date accessed be automatically added, as already done in ERMS.
Recently the hosting of the EDIT Expert Database (including the ETW) at the Zoological Museum Copenhagen has ended in favour of a less centralised model, hosting the relevant (zoological, botanical, marine, terrestrial, etc. ) expert data in the respective pan-European checklists databases. A collaboration with CETAF on the governance of taxonomic knowledge networks is under consideration (see section 'Progressions'). The continuity of relevant electronic taxonomic biodiversity data resources and expertise networks were examined (Suppl. material 6), also as an input to the PESI business plan (Suppl. material 7   non-contracted, Focal  Points being members of the consortium from 47 countries (Fig. 5 ). In addition to the expert networks (organised around a taxonomic group), the Focal Point networks in PESI provide a complementary organisation of taxonomic expertise according to their geographical, national and regional focus (Fig.
The next successful steps are already visible through a number of projects and initiatives (e. g. LifeWatch, EU BON, and COST action applications). At this moment the public PESI Portal includes a large number of taxonomic-related data provided by the Focal Points. These data comprise contact and expertise details of nearly 2,000 experts and more than 500 organizations (from professional institutions to amateur societies) in Europe, in addition to the European Taxonomic Workforce (ETW) and EDIT Expert Database (see above, Fig. 3 ). It also contains almost 2,000 scientific publications in 700 journals and more than 100 URLs of websites with information on local fauna and flora. In addition there are 190,800 vernacular names of species and higher taxa in 117 languages. To keep the Focal Point Networks active, a Focal Point sustainability plan was drawn (Suppl.
• Examining the rationale, logistics and challenges to coordinate a set of independent initiatives that collectively catalogue nomenclatural acts according to the different codes of nomenclature, allowing a differentiation between nomenclature and taxonomy and proposing a strategy for linking nomenclators to PESI (Suppl. material 12). For this purpose a series of workshops was organised in collaboration with EDIT, including a "GNOMA" workshop, to develop a common terminology and define common services and formats for a 'Global Nomenclators Architecture' (Suppl. material 13), and workshops focused on identifying strategies for populating ZooBank, the developing registry for animal names (Pyle and Michel 2008), inviting ICZN commissioners, data managers from a number of large zoological databases, representatives from Zoological Record, and representatives from other nomenclatural databases regarding common issues such as the registration of new species names (Suppl.
• Identifying the opportunities for PESI to contribute to the setting up of a global system for managing scientific names of organisms and potential pitfalls (Suppl. material 16). PESI researched and proposed standards for working with data associated with biological organisms, including: • A management classification integrating the schemes used in the component datasets. • An informal classification using informal names for higher groupings familiar to the non-expert (terms such as: snails, butterflies, dragonflies).
The Platform is based on the EDIT Common Data Model (CDM), which is an agreed and comprehensive object-oriented information model covering the taxonomic workflow from fieldwork to data publication in electronic form and on paper (Fig. 7 ). The model can be deployed using almost any Database Management System (DBMS). Application programmers can develop all kinds of systems (e. g. portals, editor software, import and export functions) using well defined APIs (Application Programming Interfaces) exposed as a Java Library (wp5. e-taxonomy. eu/cdmlib) and as generic web-services (wp5. e-taxonomy. eu/cdmlib/rest-api. html).
Sustainability of European GSDs PESI supported the development of governance plans for EU-based Global or Regional Species Databases (GSDs/RSDs) in the following ways: (a) as a European taxonomic infrastructural component, (b) as a contribution to global efforts like the Catalogue of Life (Fig. 9 ), (c) by evaluating the costs for future maintenance (maintenance and updating) and (d) by providing recommendations to optimise the collation and integration of taxonomic data in terms of expert network management, data hosting, and data interoperability (Suppl. materials 22, 23).
PESI portal The PESI web portal is the interface to the European Taxonomic Backbone (Fig. 10 ) developed and hosted by the Flanders Marine Institute in Belgium (Suppl. material 24). The portal provides an integrated view of the pan-European checklists. Still operating separately, the register's data are merged about every year in the PESI Data Warehouse and are made available through this single portal. In addition to taxonomic information, PESI harvests information on species (images, literature, conservation status) and provides links to other portals (e. g. national checklists, red species lists and other bioinformatics databases such as the Biodiversity Heritage Library for literature and the DNA databases of the Barcode of Life and GenBank). So far three editions of the European Taxonomic Backbone have been released (see section 'Dissemination').
Search parameters The advanced search interface provides a number of fields to generate output based on selected parameters (Fig. 12 ). This can be seen as applying filters on a database. The parameters can be combined (Fig. 13 ), and none of the fields are mandatory, which means that a search without setting a parameter will output the entire database. The occurrence status "present" includes all other statuses except for "absent". The list of areas is linked to the Marine Regions gazetteer. This hierarchical gazetteer of place names makes it possible to add relationships to areas. The users can, for example, generate a list of species from France and the system automatically includes the species that are recorded as present in Corsica. Besides creating lists of species, the user can search for a particular taxon by entering (part of) the scientific name, name authority or common name.
E-services for taxonomic standardisation The PESI web portal also provides a number of tools for quality control and to standardise a user's own species names. The 'taxon match' is an intelligent name validation service to cross-match external species lists against names in PESI. In addition, if an external species list is restricted to a particular area, you can also check if this corresponds to the occurrences in the PESI database. Once you have run the match, the tool exports the results (exact and suggested spellings, the higher classification, occurrence status and the checklist's Globally Unique Identifiers) as a spreadsheet file. The PESI taxon match tool has been promoted as an important tool within the PESI focal points network and at various other meetings (e. g. GBIF EU-nodes meetings).
During the project phase, as part of the PESI Focal Points validation process, 357 files have been uploaded and matched. In contrast to the taxon match, where users have to upload a species list, the portal also provides a platform-independent SOAP/WSDL web service. This web service allows users to dynamically link their own applications to the PESI database and will allow them to match a locally stored species list and add taxonomic and additional information derived from PESI. A few examples of possible applications: • getGUID: Get the first exact matching GUID for a given name. • getPESIRecords: Get one or more matching (max. 50) PESIRecords for a given name. • getPESINameByGUID: Get the correct name for a given GUID. • getPESIRecordByGUID: Get the complete PESI Record for a given GUID.
Additional (other than taxonomic) information on the web portal The PESI portal shows species distribution maps, if occurrence details are available. There are over 6 million distribution records in the PESI database. The maps are built on OpenLa yers. The backend of both occurrence types is GeoServer, an open source implementation of WMS that implements the Open Geospatial Consortium (OGC) standards. There are two types of occurrence data on the portal: 1. The first type is provided by the component databases and directly included in the PESI Data Warehouse. The areas used have been standardised to TDWG areas for terrestrial areas and for marine areas to the IHO/EEZ Intersect, which is a standard proposed by VLIZ. These occurrences are shown on the map as polygons and coloured according to the Occurrence Status.
Deep links to other biodiversity information systems The PESI portal provides links to other portals (see above). On name matching, more specifically: The Biodiversity Heritage Library (BHL) API is queried for scientific names (redirecting to the Global Names recognition and discovery tools and services). If matches are found, the information is cached in our database for one month. The next time someone loads a particular taxon page within the same month, the cached information is displayed. If the request time compared to the last update in the database is above one month, re-querying the BHL web service refreshes the information. GenBank provides a standard method for linking to their pages. We retrieve the information from their Taxon Browser tool. If the link exists, it is displayed on the species page.
e-Publications The PESI project recognises the need to link the conventional scientific publications to the species databases to provide users with a more comprehensive resource. To that end the project engaged with major publishers of scientific journals to understand how their online information systems were developing, and to explain how the species databases were evolving. A first workshop was held on 16th July 2009 in Amsterdam inviting key publishers, including PLoS, InterResearch, Allen Press, CRC Press (Taylor & Francis), Oxford University Press, Scopus, Science Direct, Elsevier, ISI Web of Science of Thomson Reuters, OvidSP (Biological Abstracts), Wiley, ProQuest (part of Cambridge), and JSTOR (Suppl. material 5). The process of contacting publishers revealed that most publishers were very limited in the functionality they had on their websites, and constrained by the limitations of the commercially provided software they used to provide added functionality.
A first step in that regard has been the initiation of a special PLoS ONE Collection of scientific papers arising from the World Register of Marine Species (WoRMS). WoRMS is a superset of the European Register of Marine Species, which is one of the three primary European species databases that form the core of the PESI project. At present, more than 19 papers have been published  (Costello et al. 2013b). Each paper should be directly linked to the WoRMS database so readers will get openaccess to the primary data and information. A similar approach was followed later on by Fauna Europaea in collaboration with Pensoft, supported by the FP-7 ViBRANT project, starting the publishing of so-called 'Contributions on Fauna Europaea' as a special series of the Biological Data Journal (BDJ), with 10 data papers published so far.
Euro+Med from the beginning took a distinctive approach towards updating the database. For instance, all occurrence records for a species in Euro+Med must have been published in a peer-reviewed paper. To accommodate miscellaneous new data, a series of "Euro+Med Notulae" was initiated in 2005 (Greuter and Raab-Straube 2005). Another conclusion of this publishers workshop was that an important, practical, option to link to a wider range of journals would be the use of RSS feeds, because this would provide no or little action on the side of the journal. Such a system would need the feeds to be aware of what species (or higher taxonomic) names to search and match to the published papers. The Global Biodiversity Information Facility (GBIF) communicated their advances on developing a relevant tool.