dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements Ada van Staalduinen  and  Sandra Scherbeijn  are thanked for excellent technical assistance. Barteld de Jongh  is thanked for useful discussion about case 1. Kristel Fraaij-Grotenhuis  is acknowledged for referring case 2 to the  Harbour Hospital in Rotterdam. This study was partially funded by  EU  grant  FP7-261504  EDENext and is catalogued by the EDENext Steering Committee as EDENext439 (www. edenext. eu). The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the  European Commission. The Viroscience reference laboratory received funding from  H2020  programs  EMERGE  (grant agreement no. 677066 ) and  EVAg  (grant agreement no. 653316 ) and the  National Institute for Public Health  and the Environment.
Zebrafish have two P54 DEAD box RNA helicases Human Rck/p54 and Caenorhabditis elegans cgh-1 belong to a family of DEAD box RNA helicases, closely related to eIF4A that allows translation initiation by mRNA unwinding  (Linder and Fuller-Pace, 2013). In the zebrafish (Danio rerio) genome, we found two open reading frames in the Ensembl databases; ENSDARP00000081816. 5 (Chromosome 18:43. 87 Mb) and ENSDARP00000129311. 1 (Chromosome 16:25. 76 Mb). According to protein sequence multiple alignment and phylogenetic analysis (Fig. 1 ) we found both genes to be orthologs of CGH-1 in C. elegans, Me31B in Drosophila melanogaster, DDX6 in Xenopus laevis and the human Rck/p54 family of DEAD box RNA helicases. We named them P54a and P54b, respectively. All conserved domains from this DEAD box protein family are also conserved in zebrafish P54a and P54b, including the ATP-binding domain I and RNA-binding motifs IV and V.
Bioinformatics analysis We used the human RCK amino acid sequence (NM_001257191) as bait in BLAST searches against the zebrafish genome sequence using Ensembl databases. We obtained two annotated sequences, ENSDARP00000081816. 5 (Chromosome 18:43. 87 Mb) and ENSDARP00000129311. 1 (Chromosome 16:25. 76 Mb). These proteins were identified as P54 RNA DEAD box helicases after multiple alignment and phylogenetic tree construction. P54 RNA helicase sequences from zebrafish and other organisms (human RCK, mouse DDX6, C elegans CGH_1, Drosophila Me31B, Xenopus DDX6, medaka DDX6_A and medaka DDX6_B) were aligned using ClustalW2. Pro-Test 3. 2 was used to calculate the substitution model, and RAxML was used generate the phylogenetic tree  (Stamatakis et al. , 2008)  and to determine the identity between homologous sequences.
Visualizing zebrafish embryos Treated embryos were mounted in 2% agarose in embryo medium, and images were obtained with a confocal microscope (FV10i Olympus). Some images were obtained with an epifluorescence microscope (Axioimager Zeiss) equipped with an AxioCam MRc camera and the ZEN image capture software (Zeiss). All images were processed with Illustrator CS6 software (Adobe). Embryos treated for ISH were photographed with a Sony Cybershot camera DSC-H20 attached to a Stereoscopic microscope SMZ-645 (Nikon) by means of a MM99 adaptor (Martin Microscopes Company). In embryos from immunostaining or expression experiments two images were obtained, one in a low amplification (10×) and one in high amplification (60×). The low amplification image was used as a reference of the body region were the image was obtained (see insets in Fig.
Quantitative hydraulic data such as the extent and depths of inundated areas  (Fohringer et al. 2015)  or flow rate estimates  (Fujita et al. 2013 , Le Boursicaud et al. 2016 ) can be computed using messages, photos and videos from eyewitnesses and help improve the understanding and modelling of flood hazard. This way, ordinary citizens or some enthusiastic flood chasers can contribute to hydrological science in the same way the so-called storm chasers have historically contributed to meteorological science since the Tornado Intercept Project (1975) of the National Severe Storm Laboratory (USA). Projects encouraging the public to act as citizen scientists in flood hydrology still appear to be scarce. The main well-established initiative of that kind is the CrowdHydrology h project  (Lowry and Fienen, 2013) , which encourage citizens to read and text the station number and the water level to the phone number listed on the gauge of gauging stations in the USA.
The water level is then added to a publicly available database. To our best knowledge, besides the CrowdHydrology project there is no available feedback on such specific projects, and more generally there is a lack of feedback and guidance on the failure and success factors of data crowdsourcing and citizen science projects for flood hydrology. We introduce three recent citizen science initiatives which have been launched independently by research organisations to document floods in some catchments and urban areas of Argentina, France and New Zealand. These projects were specifically designed to derive quantitative hydraulic data from digital photos d http://noah. dost. gov. ph/ e http://www. signalert. eu/ f http://www. nssl. noaa. gov/projects/ping/ g http://flash. ou. edu/flocast/ and videos from the public for further retrospective analysis and modelling of the flood processes.
Objectives The mountainous rivers of the Córdoba province, Argentina, are characterised by the occurrence of flash floods with very high volumes of fast flows during the rainy season (October to April). Due to the sudden nature of flash floods, it is very unlikely to be able to survey several river sections of interest using instruments and techniques suitable for recording the peak flow and its temporal evolution during the flood. Even when it is possible to visit the study sites in time, flow velocities and floating river debris endanger both the instruments and operators. Considering this issue, the researchers of the National University of Córdoba have developed and implemented the Flood Chasers Project ("Cazadores de crecidas" in Spanish,  Patalano et al. , 2015)  to populate a database of videos and photos of flash floods in rivers of the province of Córdoba recorded and shared by citizens using advanced digital technology (cell phones, digital cameras, tablets, etc.
Implementation The first step of the Flood Chasers Project was to create a website with domain of the University, then perform an intensive dissemination of the existence of this webpage in major newspapers and some television channels. On the Project website (Figure  1 ) people can upload their flood videos along with metadata (recording date and time, location of the river section, etc. ). In case the recording conditions are favourable, the videos are manually screened, analysed and processed using the Large Scale Particle Image Velocimetry technique (LSPIV,  Fujita et al. , 1998). This technique allows quantifying the surface velocity field of the rivers remotely. The website provides guidelines for users without prior knowledge of hydraulics about the best way to make contributions that are useful for quantifying flood discharges.
Examples of results The methodology was applied to a video recorded by the witness of a flash flood that occurred in the Ceballos River in the city of Río Ceballos (31°10′S; 64°19′W), Province of Córdoba, Argentina, after an extreme rainfall event occurred on the morning of 15 th February 2015. The return period of the rainfall event was estimated to be more than 100 years with observed rainfall depth of about 250 mm during 12 hours. The witness uploaded the video to the project website (Figure  1 ) with the sufficient metadata so the scientists could reach the place where the video was recorded. Subsequently, the scientists went to the place and surveyed the river cross-section bathymetry using a topographic total station. The camera movement during the record due to the videographer holding the camera by hand without a tripod was preliminarily corrected.
(b) Author-produced version of the article published in Journal of Hydrology (  2016 ) 541, 766-777 The original publication is available at http://www. sciencedirect. com/science/article/pii/S0022169416304668 , doi : 10. 1016/j. jhydrol. 2016. 07. 036 ©. This manuscript version is made available under the CC-BY-NC-ND 4. 0 license http://creativecommons. org/licenses/by-nc-nd/4. 0/ The computed surface velocity data in the area of interest were used for the calibration of the hydraulic numerical model (HEC-RAS) implemented to simulate the flow conditions of the analysed event. The Digital Terrain Model of the whole reach of interest required to implement the hydraulic model was provided by the government of the Córdoba Province. Based on the surface velocity field and the water level data at the measured section, the bed and banks roughness could be estimated iteratively and the flow discharge computed.
Using flood home movies therefore requires some image pre-processing to be applied before the LSPIV analysis, such as:  Correction of hand-held camera movement: image alignment;  Correction of distortion due to non rectilinear camera lenses;  Relative positioning of the free-surface. The project followed a fully reproducible approach, based on free software only. LSPIV analysis was conducted using Fudaa-LSPIV (Le were sampled from the video at an adequate time rate using ffmpeg n , and image pre-processing was conducted using Hugin o. The complete procedure to collect and pre-process home movies for further LSPIV analysis comes as a short methodological guide (Le  Boursicaud et al. , 2015). Simple procedures for taking useful flood videos, highlighting safety warning (Figure  5 ) have been disseminated to the public through various media including the project website.
Implementation Two days after the flood peak, members of the public were invited, via press releases to mainstream media, a scientific blog u and outreach via social media (Facebook, Twitter), to send photos of maximum flood levels to NIWA, indicating when and where each photo was taken. The photos were assessed by professionals in terms of the ability to identify a clear water level around the time of the peak inundation. Water surface levels were derived from the photos in conjunction with LiDAR scans of the city. In locations where photos did not permit clear identification of water levels, field visits were carried out to make supplemental measurements. The resulting point data were interpolated, along with additional survey data, to derive a RiskScape flood hazard model to calculate flood risk and potential losses across the city.
Author-produced version of the article published in Journal of Hydrology (  2016 ) 541, 766-777 The original publication is available at http://www. sciencedirect. com/science/article/pii/S0022169416304668 , doi : 10. 1016/j. jhydrol. 2016. 07. 036 ©. This manuscript version is made available under the CC-BY-NC-ND 4. 0 license http://creativecommons. org/licenses/by-nc-nd/4. 0/ The resultant information has been invaluable in understanding the changed flood risk for postearthquake Christchurch. These data were used to validate hydrodynamic models and are being used to plan mitigation, response and evacuation plans and to calculate human and economic costs of flooding. The widespread use of camera phones provided data on flood levels and extent that could not have been obtained by field surveys by hydrology technicians due to insufficient resources to cover the wide extent of relatively short duration flooding.
Write a clear and simple procedure Once the objectives and tools of the project have been defined, a clear and simple procedure has to be written for the attention of the public. This is a key driver of the success of all citizen science projects. The three projects have produced procedures in the form of simple instructions for recording the images and sending the data in good agreement with their distinct objectives, either flood mapping or flood discharge estimation. The type of images and metadata, the protocols to send them to the scientists and the safety and copyright aspects were dealt with in a concise and precise manner. However, the simple but more demanding requirements on flood videos for LSPIV applications in the Flood Chasers and FloodScale projects proved to be much less followed than those on flood mark photos for the RiskScape project.
Implement an efficient communication plan Communication is key to efficiently mobilise flood observers, make them aware of flood-related dangers (and discourage them from risking their lives), avoid conflicts with local authorities, and provide feedback on the use of collected data. Simple and direct explanations are essential, even when it comes to science or legal terms. Such initiatives are usually well received by the locals and the media. Communication efforts should be directed at both the general public and specific community groups such as kayakers or storm/flood chasers. It is important to communicate with and train groups of more advanced operators (firemen, civil defence, hydrologic services, volunteers, etc. ) so they can make better quality videos that fit the requirements of the data processing, in optimal safety conditions.
Public awareness and engagement matter The call is much more successful when the public and the media are prepared and aware of natural hazards, as was the case in Christchurch, New Zealand, after the earthquakes of 2010 and 2011. During this time, both the public and media became more attuned to natural hazard science, and also became more receptive to citizen science-based initiatives such as the earthquake felt reports on GeoNet website w. This was not the case for Dunedin, hence one potential reason for the failure to receive photographs, although there are others (e. g. , flooding was not as extensive and occurred during the end of the day). Provided there is sufficient expert oversight during project design and data analysis, such citizen science seems a viable means of improving our understanding of flood risk.
In turn, the reported projects highlight the value of citizen science initiatives as a means of both gathering data and engaging with the community. In some cases, the value of the obtained data is much less than the impact and engagement of the citizen community  (Lowry and Fienen, 2013). Feedback to the public is absolutely essential, through any available means: project website, online database, publication of results, follow-ups on scientific blogs xy and communication through the media. Social studies could also profit from such crowdsourced feedback from people on how they have been affected by the flood and how they have reacted, as done through calls and interviews in social science projects like in HyMex z project  (Ruin et al. 2008). Not only eyewitnesses of the flood but broader communities, which are not always visible in more formal reporting procedures, may use social media to express their feelings and contribute to the public debate (Al-Saggaf and Simmons 2015).
Conclusions The reported three projects are typical of emerging citizen science initiatives for crowdsourcing flood hydrology data. These photo-based flood mapping (RiskScape, New Zealand) and video-based flow estimation (Flood Chasers, Argentina, and FloodScale, France) projects were specifically designed to produce georeferenced and time-stamped hydraulic quantities readily usable for flood hydrology studies and hydraulic modelling. Compared to other similar projects, they involved similarly simple procedures for the public, but more advanced data processing and reviewing by the scientists. An exciting perspective would be to combine such 'measurement-oriented' and 'citizen hydrologists' approaches with the powerful tools developed in other projects for data mining the social media contents and conducting the spatial analysis of volunteered geographic information.
Acknowledgements All the citizens who have provided images and data for the three projects are gratefully thanked, as well as the field hydrologists who conducted the supplemental surveys. The Flood Chasers project acknowledges the support of the  Government of the Córdoba Province, Argentina , through the  PROTRI  project. The  FloodScale  project was funded by the  French National Agency for Research (ANR)  under Contract No ANR  2011 BS56 027 , which contributes to the  HyMeX program. Catherine Ambroise-Rendu and Thierry Fournier (Irstea)  contributed to the  FloodScale communication campaign. Collaboration between NIWA  and Irstea was enhanced by the  PHC   Dumont D ' Urville  project  34185SH  ( 2015-2016 ) and the  Irstea grant  and  NIWA  support for the one-year scientific visit of  J.
As documentary content allows access to political processes that would otherwise be inaccessible  (Harrison 2001) , this research analysed policy documents and media articulations of certain policy developments produced by selected organisations between 2003 and 2012. The increasing number of organisations involved in the delivery of the Games  (Chappelet & Kübler-Mabbott 2008)  further emphasises the practical need to limit the organisations selected for analysis, and data collection therefore focussed upon policy published by four state organisations: the UK Government's Department for Culture, Media and Sport (DCMS), the Department for Health (DH), Sport England and the Greater London Authority (GLA) along with the London 2012 Bid Team/LOCOG. The emphasis upon state organisations is attributable to the fact that host governments are chiefly responsible for Olympic legacy planning.
In order to address these gaps, a further 30 pages of data were collected, which took the form of speeches and media articulations of specific policy developments. The overall dataset consisted of 22 different sources which contained a total of 672 pages of content. A full timeline of the key events in the development of the sport/PA participation legacy and the documents used for analysis is provided in Table  1. Analysis of the selected documents followed  Braun and Clarke's (2006)  six phases of thematic analysis (familiarisation with data, generating initial codes, searching for themes, reviewing themes, defining and naming themes, producing the report), but with one modification. This concerned the initial reading of the documents, where one preliminary stage was added in order to establish whether content related to sport and activity participation legacy -with unrelated content being disregarded.
Clinical risk classification. In 2005, we published an algorithm based on a predictive database, TdPScreen ™ , which compared reference compounds tested in an in vitro model utilizing canine Purkinje fibers with clinical data available on the same compounds  40, 43. This algorithm enabled a classification of drugs, according to their electrophysiological effects, into three groups. Group A compounds that either exaggeratedly prolong the AP (subgroup A1) or induce a triangulation of the AP without APD shortening (subgroup A2). The reference compounds in this group are the most torsadogenic molecules. Group B compounds induce unexacerbated APD prolongation or a triangulation with APD shortening. The reference compounds in this group are drugs causing QT prolongation without TdP or TdP at a very low frequency (≤ 2 cases).
Interestingly, the two dimethylated arginines are both located in short motifs displaying a unique consensus sequence SxGGxRxY. R7 and R24 belong to the RRM domain of RSF1 (Fig. 8 ). According to a model based on the structure of SRSF7 (PDB ID 2hvz), these residues would be located in an a helix and in a b strand, respectively, with their side chains exposed at the surface of the domain and therefore accessible to the methyltransferase. The four other methylation sites would be located in the unfolded arginine-rich C-terminal part of RSF1.
PRMT2 cloning, expression, and purification The D. rerio prmt2 gene sequence (Genbank BC129171. 1) corresponding to the full-length protein and to the PRMT core (residues 73-408) were amplified by PCR from a cDNA clone (Source BioScience, Nottingham, UK; IRAK293-C16). The M. musculus prmt2 full-length gene sequence (Genbank BC122563. 1) was amplified by PCR from a cDNA clone (Source BioScience IRCL32A04). The sequences were cloned in the pDONR207 TM (Fisher Scientific, Illkirch, France) vector using a BP reaction (Gateway Ò Cloning; Thermo Fisher Scientific, Waltham, MA, USA). The positive clones were confirmed by sequencing (GATC BIOTECH, Konstance, Germany). The sequences were subcloned in a pDEST20 TM vector (for D. rerio prmt2) or a pBacGGWA vector  [53]  (for M. musculus prmt2) using a LR reaction.
0, 9% (w/v) PEG 20 000, and 300 mM NaCl. Single diffracting crystals grew to 50 9 40 9 20 lm within 3 days. First hits for mPRMT2 were obtained in several conditions of the PACT (Molecular Dimensions, Newmarket, UK) and The Peg Suite (Qiagen, Hilden, Germany) crystallization screens. Crystallization conditions were further optimized in 24-well VDX plates (Hampton Research, Aliso Viejo, CA, USA). Crystals used for X-ray diffraction were obtained within days at 20 °C in a hanging drop made with 1 lL mPRMT2 at 3. 5 mgÁmL À1 , mixed with 1 mM inhibitor, and 1 lL reservoir solution containing 16% (w/v) PEG 6000, 100 mM Hepes-NaOH pH 7. 0 and 100 mM CaCl 2. Data collection and structure solution zPRMT2 crystals were soaked in the reservoir solution supplemented with 15-20% (v/v) PEG 400 or 20% (v/v) ethylene glycol and flash-cooled in liquid nitrogen.
The diffraction datasets were collected on the SOLEIL PROXIMA1 and PROXIMA2 beamlines, using a PILA-TUS 6M (DECTRIS, Baden-D€ attwil, Switzerland) or a Quantum 315 (ADSC, Poway, CA, USA) detector and processed with XDS  [54] , Imosflm  [55] , and HKL-2000  [56]. The crystals belonged to the H32 space group with one zPRMT2 molecule in the asymmetric unit. The dataset was submitted to the BALBES server for automated molecular replacement at York Structural Biology Laboratory  [57]  after unsuccessful manual attempts with known PRMT structures or models. An initial solution with a BALBES template based on CARM1 from Homo sapiens (PDB ID 2y1w) and the sequence of zPRMT2 was obtained with one monomer in the asymmetric unit. mPRMT2 crystals were cryoprotected by a short soak in 20% (w/v) PEG 6000, 100 mM Hepes pH 7.
0, 100 mM CaCl 2 , 15% (v/v) PEG 400, and flash-cooled in liquid nitrogen for data collection. Diffraction datasets were collected on the ID23-2 beamline at the ESRF using a PILA-TUS 2M detector (DECTRIS) and processed with XDS. The crystal belonged to the C222 1 space group with one mPRMT2 molecule in the asymmetric unit. The structure was solved by molecular replacement using PHASER and zPRMT2 structure as a starting model. Iterative cycles of model building and refinement were carried out using COOT  [58] , PHENIX  [59] , and BUSTER  [60]. TLS refinement with four groups per polypeptide chain was used. All other crystallographic calculations were carried out with the CCP4 package  [61]. A summary of the data statistics for the refined structure is provided in Table  1. The atomic coordinates and experimental data (PDB ID 5g02, 5fub, 5ful, 5fwa) have been deposited in the Protein Data Bank.
CARM1 purification, crystallization, and structure determination A construct of mouse CARM1 from residues 130 to 487 (mCARM1 130-487 ) was expressed as a GST fusion protein using the baculovirus system, purified as previously described  [62]  and crystallized in 15% (w/v) PEG 2000MME, 100 mM Tris/HCl pH 8. 0, 100 mM NaCl in the presence of 1 mM Cp1 at 20 °C. mCARM1 crystals were cryoprotected by a short soak in 22% (w/v) PEG 2000MME, 100 mM Tris/HCl pH 8. 0, 100 mM NaCl, 15% (v/v) PEG 400, and flash-cooled in liquid nitrogen. Diffraction datasets were collected on SOLEIL PROXIMA2 beamline, using a Quantum 315 (ADSC) detector and processed with XDS. The structure was solved and refined using PHENIX. Model building and refinement were carried out using COOT  [58] , PHENIX  [59] , and BUSTER  [60].