dataesr/scientific-paragraphs-categorization huggingface dataset:
The availability of identifiers and life-cycle attributes will facilitate the updating processes, will allow the distribution to the users of incremental updates and the relationships with related databases (addresses, map names, etc) to facilitate, for example, the propagation of changes. The design of the new model will also guaranty the compatibility between the concepts existing in the ICGC data model if they exist in other models and standards, as CityGML and INSPIRE. Main issues in this work are the identification of real customer needs and the achievement of a balance between the complexity of the model and the cost to be maintained during the updating processes. Regarding to the customers need: although the model is designed as a corporative task involving producers and users of the data of different government administrations being mainly municipalities, at the moment the main use is still visualization.
3D products from oblique images and LiDAR data Additional to the 3D vector data, ICGC is providing also 3D products based on raster data collected using the recently acquired Leica RCD30 Oblique Camera and, since 2002, the LiDAR systems. One of the main uses of the oblique images is the generation of the textures to the LoD2 buildings of the new topographic model and the generation of 3D raster models. Current vector LoD1 data is provided without textures. Although some pilot projects have been performed to add textures to the model using aerial or terrestrial images, the results have been poor or too costly. Multiple views from the oblique camera images will allow the addition of the textures to the LoD2 buildings of the new topographic model, solving the previous limitations (Figure  3  and Figure  4 ).
Because the new topographic model is yet in design phase, and it will require some time before to get it implemented in the production environments and to have a significant coverage of data available, it has been considered that the production of 3D raster models based on hyperrealistic textured triangulations can provide a 3D product very useful for most visualization applications (Figure  5 ). ICGC is preparing a workflow to generate automatically this product, shortcoming the problems of the software provided together with the oblique camera, which is not robust enough to manage the huge volume of data required to generate the ICGC annual production. First coverage of LiDAR data was collected between 2008 and 2011 at 0,5 points/m2, and the main uses were related to flood analysis. Since 2008 regular flights have been collecting higher density LiDAR data, at 1 point/m2 along the coast for monitoring the littoral changes and at 4 points/m2 in populated areas for deriving urban applications, for example the analysis of the solar potential of the buildings (Figure  6 ).
Dissemination of 3D data Nowadays ICGC data can be accessed through a portal, used through geoservices and downloaded in several vector formats, as SHAPE, DGN, DXF or KMZ, and also raster formats. LiDAR data are available in LAZ format. By the moment data is mainly used for 2D applications, and, although there is a huge potential of city model applications (urban planning, telecommunications, energy, environment, smart cities, simulations, etc. ), visualization is the most common while the other ones are not yet enough developed. For the visualization of 3D datasets, ICGC is currently studying a 3D viewer based in Cesium technology and the first prototypes are in test phases. The WebGL Cesium library allows the presentation of 3D graphics in web pages, and taking advantage of the acceleration provided the user computer, achieves an excellent quality and speed from the web browser.
Work has begun with the Geological Survey of Sweden, the Swedish Maritime Administration, the Swedish Transport Administration, Swedish forest agency and the municipalities. Experience to date shows that (see Figure  7 ): 1. The existing elevation models in 2. 5D from different agencies can be displayed in a common application after some editing and knowledge on quality. The models tested together are DTM, DSM, a seabed model and a bedrock model. It is possible to set up these height models as WCS services at the responsible authority for real-time delivery. It is planned to use ALS (4-12 points/m2) and 2D outlines of buildings from Topographic Objects Database as a main data source. Whole process of production is going to be outsourced, quality control will be conducted mainly by external contractor however final verification will take place in-house.
Terms of Reference are being prepared in close cooperation with defined customers. In 2014 GUGiK conducted a survey regarding customers needs and received feedback from 650 public and private organizations followed by dedicated meetings with further 92 organizations in a second step of consultations. First 3D data will be available in second half of 2017 and whole dataset will be ready for use before end of 2018. GUGIK considers to distribute 3D database as an open dataset which will potentially strengthen application of data and economic grow in sector of geo-bussines in Poland. In addition to 3D database it is planned in CAPAP initiative to implement analytical environment for customers facilitating utilization of 3D data as an extension of geoportal. gov. pl environment. To meet customers expectations GUGiK is in testing procedure of 3D web viewer with analytical functionalities (see Figure  8 ).
In contrast land cover, areas of specific interests and the hydrographic network are mapped in 2D and draped over the terrain model, resulting in 2. 5D objects. swissBUILDINGS 3D is the 3D vector data set representing over 3 million buildings of Switzerland. The roofs are manually acquired in 3D from aerial digital images with a precision of better than 50 cm in all dimensions and complemented with attributes. The additional building elements (facades, footprints and roof overhangs) originate from automatic procedures (only where third party information is missing). Swisstopo fosters actually a big national effort which will allow for a simultaneous use of the geometric 3D data of swissBUIDINGS 3D , the statistical information about households and living from national surveys and the legal and local information from the cantonal cadastral services: in the near future the swisstopo buildings and the cadastral building entities will refer both to the unique national statistical building identifier.
3D NATIONAL MAPPING IN THE NETHERLANDS For several years, 3D mapping at the national level has got attention in The Netherlands. This is driven by a growing need for 3D data in applications such as noise calculation, flooding simulation, solar potential analysis, maintenance of dikes. For that reason, the standard for large scale topography (IMGeo: Information Model Geography) is modelled as an Application Domain Extension of CityGML (Van den Brink et al, 2013a; 2013b). The standard was established in 2012. All organisations responsible for collecting large scale topography are obliged to provide such data according to the IMGeo standard from 2016 onwards. The 2D part is mandatory; the 3D part is optional. In sequential research, we are investigating several issues to further develop towards a base 3D data provision.
A national 3D data portal At first we are investigating how we can publish governmental 3D data (which can be 3D IMGeo, but also other 3D data like cables and pipelines, 3D data bout the geological underground etc) via a national portal. 2D data is being published via a national portal called Publieke Dienstverlening Op de Kaart In a testbed we will investigate with the community what the best options are for the interactive visualisation of 3D data via the Internet. Candidates for testing are Cesium, i3S (the open standard developed by Esri that contains an Indexed 3D Scene delivery format and the Scene Layer Package definition both encoded using  JSON, Esri, 2016). We also plan to investigate the recently established 3D Portrayal Service from the Open Geospatial Consortium. The main challenge will be to publish both semantics and geometry at the same time and preferably directly from the database, without the conversion to other formats.
3D data reconstruction at national coverage A second item for research is the national wide 3D data reconstruction. The extension of IMGeo towards 3D is the responsibility of individual organisations and thus not ready yet to provide a countrywide 3D data set. Therefore, in 2014 a countrywide 3D dataset has been generated from the object-oriented data at scale 1:10k (the largest scale as maintained by the Netherlands' Kadaster) in combination with high-resolution airborne LiDAR data (10+ points/m 2 , available as open data). The 3D model was reconstructed in a consortium composed of Kadaster, the Delft University of Technology, the Twente University and the Free of Amsterdam. For the 3D reconstruction the opensource tool was used developed by  (Oude Elberink and Vosselman, 2009a; 2009b; Oude Elberink et al, 2013).
The tools reconstruct a surface representation for each class in the 2D map by the integration of the 2D data and high resolution LiDAR data. For the volumetric objects (buildings and plant cover) the 3D reconstruction has until now been limited to LoD1 (block models). The reconstruction is driven by rules that prescribe how to process the LiDAR data, how to model specific object types, and how to connect neighbouring objects in 3D  (Oude Elberink and Vosselman, 2009a; 2009b). The lessons learnt from the reconstruction of 3D TOP10NL data are currently being used to develop a 3D reconstruction tool for 3D IMGeo (i. e. at more detailed level), based on 2D IMGeo data and height points (see Figure  12 ). Since the 2D source data set contains significantly more 2D features at higher detail, and since the original process was computational expensive (several fitting of planes with leastsquare adjustment), we are currently investigating simpler alternatives to assigning elevations to the features.
CONCLUSIONS AND FUTURE WORK In this paper we summarised recent developments on national 3D mapping for a selection of NMAs. It shows that NMAs are making significant steps to collect, maintain and provide 3D data to serve a wide variety of applications. Despite the potentials of 3D, all NMAs observe an underuse of the 3D data they produce. To better understand the mismatch between the availability of 3D data and the use of it (beyond visualisation), the EuroSDR 3D SIG has started a research project on the identification of economic value of 3D geo data. The project is funded through "crowdfunding": eleven National Mapping Agencies (NMAs) and EuroSDR as 12th partner each contribute financially. The results of the project will give the participating NMAs understanding in the business case of 3D data: In what applications does 3D give added value?; What are the required 3D data for these applications?; What are the costs and benefits to collect and maintain these 3D data nationwide? The project has started early 2016 and is expected to run for one year.
Another related activity is the development of common specifications for 3D mapping. The objective of this shared specification for 3D mapping is to define how objects in existing 2D map databases at NMAs could be represented geometrically in 3D. It builds on existing concepts like the Levels of Details, commonly used in CityGML and semantic data specifications of INSPIRE. These common specifications for 3D mapping will support joining 3D experiences and efforts in different countries. In addition they will enable to build on each other's developments and to articulate 3D mapping needs to industry, academia and standardization organisations and initiatives like OGC and INSPIRE.
Thiodiazotropha endoloripes and in both Ca. Thiosymbion oneisti draft symbiont genomes (Fig. 2 ). Nematode    Figure 1 | Phylogenomic tree of sulfur-oxidizing Gammaproteobacteria. Phylogenomic tree of free-living and symbiotic sulfur oxidizers from the Gammaproteobacteria. The 25 single-copy genes used in the analysis were defined based on the AMPHORA2 core bacterial phylogenetic marker database  66. SUP05 bin refers to the genomic assembly from the metagenome study by Walsh and co-authors  81. The betaproteobacterial sulfur oxidizer Thiobacillus denitrificans was used as the outgroup. SH-like support values were above 90% for all nodes of the tree. Genomes encoding nitrogenase genes are indicated with an asterisk and bold text. Sequences from this study are shown in red.
Symbionts of L. lucinalis and L. oneistus encode nitrogenases. Surprisingly, the five draft genomes of Ca. Thiodiazotropha endoloripes and both draft genomes of Ca. Thiosymbion oneisti contained large clusters of genes involved in nitrogen fixation, including the structural genes for the iron-molybdenum dinitrogenase (nifD and nifK), the dinitrogenase reductase subunit (nifH), ferredoxins, and maturation and regulatory factors (Fig. 3 , Supplementary Discussion and Supplementary Figs  1  and 2 ). The nifH gene is commonly used as a functional marker for nitrogen fixation, so many nifH genes are available in public databases. Our phylogenetic analyses showed that the sulfur-oxidizing symbiont sequences clustered together with Group 1 molybdenum-dependent NifH sequences as defined by Raymond  23  (Fig.
Single reads were excluded from the analysis. To largely remove the host genomic reads for the lucinid samples, the reads were split based on a kmer frequency analysis performed with bbnorm. Only reads with average kmer frequencies of 30 for L. lucinalis A, B and D, 25 for L. lucinalis C, 50 for L. lucinalis E and 25 for L. oneistus A and B were kept using bbnorm (https://sourceforge. net/projects/bbmap/). The assembly was carried out using kmers 21, 33, 55 and 77. The initial binning was done using Metawatt 2. 1 (ref. 52). Final binning was done interactively by collecting all contigs linked to this initial high confidence bin using the FASTG linkage information provided from the SPAdes assembly program with gbtools version 2. 4. 4 (ref. 53). We binned a draft symbiont genome from each of five individuals of L.
For protein identification, a database was created using all protein sequences predicted from the Ca. Thiodiazotropha endoloripes genomes published in this study. CD-HIT was used to remove redundant sequences from the database  61. The cRAP protein sequence database (http://www. thegpm. org/crap/) containing protein sequences of common laboratory contaminants was appended to the database. The final database contained 6,816 protein sequences. The database was submitted to the PRIDE repository (see section 'Data availability'). For protein identification, MS/MS spectra were searched against the database using the Sequest HT node in Proteome Discoverer version 2. 0. 0. 802 (Thermo Fisher Scientific) with the following parameters: Trypsin (Full), max. 2 missed cleavages, 10 ppm precursor mass tolerance, 0.
1 Da fragment mass tolerance and max. 3 equal dynamic modifications per peptide. The following three dynamic modifications were considered: oxidation on M (+15. 995 Da), carbamidomethyl on C (+57. 021 Da) and acetyl on the protein N terminus (+42. 011 Da). False discovery rates (FDRs) for peptide spectral matches (PSMs) were calculated and filtered using the Percolator Node in Proteome Discoverer. The Percolator algorithm 'uses semi-supervised learning and a decoy database search strategy to learn to distinguish between correct and incorrect PSMs'  62. Percolator was run with the following settings: maximum Delta Cn 0. 05, a strict target FDR of 0. 01, a relaxed target FDR of 0. 05 and validation based on q-value. The Protein FDR Validator Node in Proteome Discoverer was used to classify protein identifications based on q-value.
DNA extracted from diverse lucinid species was used as a template for amplification using 16S rRNA-and nifH-specific primers and the DreamTaq DNA Polymerase (Thermo Fisher Scientific). Primers 27F and 1492R were used to amplify the 16S rRNA gene  64. Degenerate primers IGK3/DVV were used to amplify the nifH gene  65. The reaction conditions were as follows: one cycle at 94 °C (4 min); 32 cycles and 34 cycles (for the 16S rRNA and nifH genes, respectively) at 94 °C (30 s), 52 °C (45 s) and 72 °C (45 s); plus one final cycle at 72 °C (10 min). The resulting PCR products were purified with a QIAquick PCR Purification Kit from Qiagen and Sanger sequenced by Microsynth AG. Phylogenomic analysis. Available genomes of gammaproteobacterial sulfur oxidizers were retrieved from GenBank and the Joint Genome Institute's Integrated Microbial Genomes database (JGI-IMG).
Phylogenomic treeing of these genomes along with the lucinid and stilbonematid symbiont genomes was performed using scripts that were available at phylogenomics-tools (doi:10. 5281/zenodo. 46122). Marker proteins that are universally conserved across the bacterial domain were extracted from the sulfur-oxidizer genomes using the Amphora2 pipeline  66. Twenty-five markers ( frr, infC, nusA, pgk, pyrG, rplB, rplC, rplD, rplE, rplF, rplM, rplN, rplP, rplS, rplT, rpmA, rpsB, rpsC, rpsE, rpsI, rpsJ, rpsK, rpsM, rpsS and tsf ) that were identified to be occurring in single copy in all of the genomes were used for alignment on Muscle  67. An alignment mask was generated using Zorro  68. Poorly aligned regions or misaligned regions were visually identified and removed from the alignments. The marker alignments were further concatenated into a single partitioned alignment and the best protein substitution model for each of the markers ( frr, nusA, pyrG, rplB, rplC, rplD, rplE, rplF, rplM, rplP, rplS, rplT, rpsB, rpsC, rpsM, tsf: LG; infC, rpsE, rpsJ, rpsS: JTT; pgk, rpmA: WAG; rplN, rpsK: RTREV; rpsI: JTTDCMUT) was predicted using the concat_align.
pl script (phylogenomicstools). The best tree with SH-like aLRT support values  69  was finally defined on RAxML (ref. 70) using the tree_calculations. pl script on phylogenomics-tools. Phylogenetic analysis of NifH and NifD. Symbiont nifH and nifD gene sequences were obtained from the RAST annotations. Gene sequences from S. thiotaurini SIP-G1 (ref. 71) were downloaded from GenBank (CP011412). Sequences were imported using ARB  72  into curated databases for nifH (http://wwwzehr. pmc. ucsc. edu/nifH_Database_Public/)  73  and nifD (http://www. css. cornell. edu/faculty/ buckley/nifh. htm  74 ) respectively and approximate placements were found with the parsimony quick-add feature in ARB. Group I nifH sequences were exported and dereplicated at 95% identity with Usearch 8. 1 cluster-fast algorithm (length-sorted)  75.
Acknowledgements The authors thank  J. Taylor  from the  Natural History Museum in London  and  N. Higgs  from the  University of Plymouth  for providing samples. Thanks go to the  Parc National du Banc d'Arguin (PNBA)  for permission to work in the park and for use of the facilities at the  Iwik  field station. The authors thank  A. Richter ,  W. Wanek  and  M. Watzka  from the  Division of Terrestrial Ecosystem Research at the University of Vienna  and  M. Smit  and  J. Ossebaar  from  NIOZ , for stable isotope analyses. The authors also thank  S. Wetzel  and  M. Sadowski  for technical assistance,  M. Smit ,  A. Cado van der Lely  and the team at the  HYDRA Institute  for support during fieldwork,  N. Dubilier  for supporting the project and  M. Strous  for access to proteomics equipment.
The purchase of the proteomics equipment was supported by a grant of the  Canadian Foundation for Innovation  to  Marc Strous. M. v. d. G. was supported by a post-doctoral fellowship of the  Mediterranean Centre for Environment and Biodiversity (LabEx-CeMEB ) and an  NWO-WOTRO Integrated Programme grant  ( W. 01. 65. 221. 00 ) to Theunis Piersma. M. K. was supported by a  NSERC   Banting Postdoctoral Fellowship. This work was funded by the  Max Planck Society , the  Vienna Science and Technology Fund (WWTF)  through project  VRG14-021  to J. M. P. and a  Fast Track grant  from the  Robert Bosch Foundation  to J. M. P. Finally, the authors thank three anonymous reviewers for their input.
Data availability. Genome and transcriptome data from L. lucinalis have been submitted to NCBI in BioProject PRJNA314435. The draft genome sequences from lucinid symbionts are available under accession nos. LVJW00000000 (Ca. Thiodiazotropha endoloripes A), LVJX00000000 (Ca. Thiodiazotropha endoloripes B), LVJY00000000 (Ca. Thiodiazotropha endoloripes C), LVJZ00000000 (Ca. Thiodiazotropha endoloripes D) and LVKA00000000 (Ca. Thiodiazotropha endoloripes E). Transcriptome sequences can be found at the NCBI Short Read Archive under accession no. SRP073135. Draft genome sequences from stilbonematid nematodes have been submitted to ENA under project no. PRJEB14785 and can be found under accession nos. FLUZ00000000 (Ca. Thiosymbion oneisti A) and FLUY00000000 (Ca. Thiosymbion oneisti B). PCR-amplified nifH sequences can be found under accession nos.
Sampling This cross-sectional feasibility study was based in the North Central Province of Sri Lanka in a rural village with a mixture of agricultural and non-agricultural households. This area has both rice and vegetable farmers, and therefore represents a village with moderate/high levels of chronic exposure. Using key informants we invited villagers to a public meeting to describe the study. Participants were recruited via home visits and we purposively sampled 50 adults (Z 18 years) in order to collect data from broad age and gender categories during the area′s dry season (Yala). The amount of pesticide used in the Yala season by rice farmers (and hence acute exposure) is likely to be less than during the main rice cultivation season (Maha)  Konradsen et al. (2007). Participants were asked to give a hair sample of a pencil width diameter from the back of their head.
To calculate δ 15 N(NO - 3 ) in the snow, the nitrate photolysis fractionation factor ( 15 ε pho ) is calculated at each time step and is dependent upon the spectral distribution of the UV irradiance at the snow surface  (Bernhau et al. , 2014; Erbland et al. , 2015). Calculated 15 ε pho values range from -88 to -35 ‰ between the snow pits and are constant with snow depth. In this study, TRANSITS is run at hourly resolution and is spun up beginning 27 days before the start of the campaign using available atmospheric chemical (boundary layer, gasphase, and aerosol-phase nitrate) and meteorological data (air, temperature, and pressure). A constant model boundary layer height of 50 m is assumed, which is a rough estimate of daily averaged boundary layer heights based on sodar facsimile data from NOAA.
Acknowledgements. We gratefully acknowledge support from 155 backers from http://www. experiment. com, NSF   PLR 1244817 , PMEL contribution number  4468 , and an  EPA   STAR fellowship  to  M. C. Zatko. The  Uintah Basin Winter Ozone Studies  were a collaborative project led and coordinated by the  Utah Department of Environmental Quality (UDEQ)  with support from the  Uintah Impact Mitigation Special Service District (UIMSSD) , the  Bureau of Land Management (BLM) , the  Environmental Protection Agency (EPA) , and  Utah State University. The authors acknowledge the  NOAA/ESRL Chemical Sciences Division and Questar Energy Products  for site preparation and support. We thank  Kristen Shultz ,  Jim Johnson ,  Drew Hamilton , and  Derek Coffman  for all of their help before, during, and after the field campaign.