dataesr/scientific-paragraphs-categorization huggingface dataset:
Because the 20 TFs are differentially regulated in a wide range of stress-related datasets, we speculate that these genes, or at least part of them, function as a hub for the cross talk between different input signals and the downstream effector genes. However, the intensity and the timing of the induction likely depend on the input signal. The dynamics of the network thus change upon different stresses, resulting in different possible output signals and plant responses. In addition to their differential expression upon other abiotic or biotic stresses, multiple studies also investigated the precise role of several TFs in diverse stress responses. Transgenic lines of multiple TFs showed a sensitivity phenotype upon several stresses, which also points to a broader function of the mannitol-induced GRN upon stress.
Per leaf, approximately 100 abaxial epidermal cells were drawn with a DMLB microscope (Leica) fitted with a drawing tube and a differential interference contrast objective. Pictures of the cell drawings were used to measure the average pavement cell area and number with ImageJ as described before  (Dubois et al, 2015). For the statistical analysis of the rosette area, an ANOVA was performed for each line separately in R (version 3. 3. 2) (http:// www. R-project. org/) (R Core Team, 2015). Fixed factors in the model were line, treatment, their interaction term. Each experiment was repeated three times, and the factor repeat was included as a block effect. Model building was used to achieve the best model. A linear mixed model was fitted to the leaf area data. The data are clustered as measurements were done on leaves originating from the same plant.
05 significance level. Simple F-tests of effect for genotype were carried out at each leaf. For those leaves showing a significant F-test (P < 0. 05), pairwise comparisons were estimated between genotype and wild type. At each leaf, correction for multiple testing was done applying the Dunnett method. The analysis was performed with the mixed and plm procedure of SAS (Version 9. 4 of the SAS System for Windows 7 64 bit, Copyright © 2002-2012 SAS Institute Inc. Cary, NC, USA [www. sas. com]). Residual diagnostics were carefully examined.
Phenotypic analysis of the crosses The 35S::TF-GR lines were crossed with each other (double cross) and with a 35S::GFP-GR line (single cross). The F1 generation was used to perform the phenotypic analysis. Six or seven lines were grown on a 23-cm square plate. Per biological repeat, eight to nine seeds per line were sown on solid (9 g/l agar, Sigma) 1/2 MS medium with the addition of 5 lM dexamethasone (Sigma). During growth, the plates were randomized. The different lines were grown together on one plate with the appropriate control lines, 35S::GFP-GR or the single crosses. At 22 DAS, a picture of the square plates was taken and the projected rosette area was measured using the software program ImageJ version 1. 45 (National Institutes of Health; http://rsb. info. nih. gov/ij/). To estimate the interaction between two genes, following parameterization was used.
All samples were ground with a Retsch machine and 3-mm metal beads. Subsequently, RNA was extracted with TriZol (Invitrogen) and further purified with the RNeasy plant mini kit (Qiagen). An amount of 100 ng with 5 ll extra for quality control was sent to the Nucleomics Core in Leuven for an nCounter Nanostring â analysis (http://www. nanostring. com/ applications/technology). Five housekeeping genes (AT1G13320, AT2G32170, AT2G28390, AT5G15710, AT4G24550) were included to normalize the data. Two sequence-specific probes were designed and synthesized at Nanostring Technologies (Seattle, USA) for 36 genes (including five housekeeping genes, Dataset EV1 and Source Data for Fig  3 ). One probe was used to hybridize and immobilize the complementary RNA molecules. The other probe was used to detect the individual RNA molecules.
The induced overexpression was confirmed for all GOF lines in the Nanostring experiment, except for the ZAT6-GR line. For the statistical analysis of the expression analysis in wild-type plants, Student's t-tests were performed on log 2 -normalized values for each gene separately. The retrieved P-values were adjusted for multiple testing with the FDR method in R (version 3. 3. 2). For the statistical analysis of the expression analysis in the GR lines, a mixed model analysis was performed on log 2 -normalized values for each experiment and each gene separately using the mixed procedure in SAS (Version 9. 4 of the SAS System for Windows 7 64 bit. Copyright © 2002 -2012 SAS Institute Inc. Cary, NC, USA [www. sas. com] ). Fixed factors in the model were line and time and their interaction term.
Each experiment was repeated three times, and the factor repeat was put as random effect in the model to account for correlations between data observed within the same repeat. Denominator degrees of freedom were calculated using Satterthwaite's approximation as implemented in SAS. The contrasts of estimate were the differences between each line and the reference line at each time point. All P-values from one experiment were adjusted for multiple testing with the FDR method as implemented in the multitest procedure from SAS  (Benjamini & Hochberg, 1995). For the initial selection of the TFs (as shown in Appendix Fig S1 ), the expression level of OBP1, MEE3, AT5G58900, and WRKY18 was measured at 15 DAS with qRT-PCR. To confirm the overexpression of ZAT6 in the 35S::ZAT6-GR line, the ZAT6 expression was measured in the previously described samples with qRT-PCR.
For cDNA synthesis, the iScript cDNASynthesis Kit (Bio-Rad) was used using 1,000 ng of RNA as starting material. qRT-PCR was performed with the LightCycler 480 Real-Time SYBR Green PCR System (Roche). The data were normalized against the average of housekeeping genes AT1G13320 and AT2G28390, as followed: dC t = C t (gene) À C t (average [housekeeping genes]) and ddC t = dC t (Control) À dC t (Treatment). C t represents the number of cycles at which the SYBR Green fluorescence reached a threshold during the exponential phase of amplification. Primers were designed with the QuantPrime web site (http://www. quantprime. de/) and are as followed: OBP1 (AT3G50410), TCAGCTTTGGACTCGGAAGAGC, and TCGTCGTTGTCGCAGTACCAAC; MEE3 (AT2G21650), TCACG TGCCATTCCCTGACTAC, and TGCAGCTTCATGCTTCTCATCCTC; MYBx (AT5G58900), CTTGGACGGAGGAAGAACACAAGC, and TTG TGTTGGCGTTCGCGTTATC; WRKY18 (AT4G31800), TGGACGGTT CTTCGTTTCTCGAC, and TCGTAACTCACTTGCGCTCTCG; ZAT6 (AT5G04340), TCTACAAGCCACGTCAGCAGTG, and TTCCGGTATC GGCGGTATGTTG; Housekeeping gene 1 (AT1G13320), TTGGTGCT CAGATGAGGGAGAG and TTCACCAGCTGAAAGTCGCTTAG; Housekeeping gene 2 (AT2G28390), CAAGGCAGGAAATCACCAGGTTG and CTGTACAGCTGATGCAGACCAG.
Motif analysis The position-specific scoring matrices (PSSMs) from the DNAbinding motifs of the TFs were retrieved from the CIS-BP database (http://cisbp. ccbr. utoronto. ca/; Weirauch et al, 2014). For five genes, ERF9, WRKY6, WRKY28, ZAT6, and MYB51, the binding motif was not yet experimentally determined and was left out of the analysis. The PSSMs were converted from cis-bp format to transfac format with the convert matrix tool on RSAT (http://floresta. eead. c sic. es/rsat/; Medina-Rivera et al, 2015). To retrieve the exact positions and significance of motifs in the different promoters, the pattern-matching tool in RSAT was used (Source Data for Appendix Fig  S25 ). A matrix scan (full options) with an organism-specific background model (Arabidopsis thaliana), no masking, and a Pvalue threshold of 0.
Acknowledgements We thank the  Systems Biology of Yield group  for all the helpful discussions and the inspiring environment,  Katrien Maleux ,  Twiggy Vandaele , and  Liesbeth De Milde  for the practical help,  Nico Smet ,  Thomas Farla ,  Miguel Riobello y Barea ,  Wilson Ardiles-Diaz , and  Carina Braeckman  for all the technical support, and  Alexandra Baekelandt ,  Hannes Claeys ,  Hannes Vanhaeren ,  Annick Bleys , and  Nathalie Gonzalez  for help in improving the article. This research received funding from the  Bijzonder Onderzoeksfonds Methusalem Project  ( BOF08/ 01M00408 ). L. V. d. B is a predoctoral fellow of the  FWO SB  (project no. 131013 ). [ Bijzonder Onderzoeksfonds  (BOF);  Fonds Wetenschappelijk Onderzoek (FWO) ].
With biodiversity research activities being increasingly shifted to the web, the need for a system of persistent and stable identifiers for physical collection objects becomes increasingly pressing. The Consortium of European Taxonomic Facilities agreed on a common system of HTTP-URI-based stable identifiers which is now rolled out to its member organizations. The system follows Linked Open Data principles and implements redirection mechanisms to human-readable and machine-readable representations of specimens facilitating seamless integration into the growing semantic web. The implementation of stable identifiers across collection organizations is supported with open source provider software scripts, best practices documentations and recommendations for RDF metadata elements facilitating harmonized access to collection information in web portals.
By August 2016, biodiversity information networks such as GBIF (http:// www. gbif. org), BioCASe [(3), http://www. biocase. org] or SpeciesLink [(4), http://splink. cria. org. br/], provide access to approximately 650 million occurrence records, 125 million of which belong to individual physical specimens held by museum or university collections. Searching this information space is mediated by a wide range of portals serving specific thematic or geographic user requirements based on a set of globally accepted data access protocols such as the BioCASE-Protocol  (5) , Distributed Generic Information Retrieval (DiGIR, http://digir. sourceforge. net), and the TDWG Access Protocol for Information Retrieval [TAPIR  (6) ] together with the community data standards Darwin Core  (7)  and ABCD [Access to Biological Collection Data  (8) ].
At present, 13 CETAF member institutions have implemented stable URIs. Establishing the system at 80% of CETAF institutions is part of the CETAF Strategy and Strategic Development Plan for this decade 2015-2025  (14). The new CETAF stable identifiers are increasingly used for referencing specimens in taxonomic publications, data portals, and web service interfaces. In addition, several pilot projects are underway to demonstrate the integration into Linked Open Data based applications.
The identifiers' full potential unfolds with the implementation of redirection mechanisms. Users trying to access a specimen using a web-browser and the specimen identifier will be redirected to a human-readable representation of the objects, typically an HTML-webpage. On the other hand software-systems requiring machine-readable representations of the object will be redirected to a (preferably) RDFencoded metadata record (Figure  2 ). The redirection mechanisms have to be setup locally by participating organizations. For ease of implementation working example PHP scripts are provided on a SourceForge site (https://sourceforge. net/projects/stablecol lectionidentifiers), which can easily be modified to meet the local technical requirements. The software includes a function for transforming specimen metadata into a simple set of RDF elements mainly consisting of concepts defined by the Darwin Core and Dublin Core (17) standards.
The 'CETAF Specimen Preview Profile' (CSPP) constitutes such an element set composed of 13 agreed and easy-to-provide Darwin Core and Dublin Core concepts considered useful for preview functions, such as decorated links and search results, in data portals. The CSPP-elements are title, kindOfMaterial, scientificNameCurrent, family, scientificNameOriginal, collectorNumber, collectorName, webscaledImageLink, latitude, longitude, isoCountry, collectionDate and sourceLink  (19). In addition, the capabilities of Linked Open Data to facilitate cross-institutional thematic information systems are demonstrated on the example of the 'Wallich Catalogue Online' system developed by the Royal Botanic Garden Edinburgh. The Catalogue provides an interactive tool helping researchers understand the Wallich Catalogue and interpret the herbarium specimens Nathaniel Wallich distributed on behalf of the British East India Company between 1829 and 1847 (Figure  5 , http://wallich.
rbge. info). The informatics challenge this project faced was to allow users to browse specimen information from multiple herbaria without building a new database that duplicated specimen information. The system's focus is on curating information about the catalogue whilst leaving individual herbaria to curate authorative information on the specimens they hold. The solution adopted was to store only the HTTP URIs for the remote specimens in the database and pull specimen data in when the user required it. For efficiency, the specimen data is cached briefly but not stored in the database. Data supplied in a CSPP response are used to display core specimen information, a thumbnail image and a link to the original source. An example of the use of this functionality is quickly spotting specimens that don't look like they are true duplicate specimens simply by hovering the mouse over the Wallich Catalogue page entry.
Discussion and outlook In this paper, we have provided an overview of the status of the initiative of the Consortium of European Taxonomic Facilities CETAF to implement an agreed system of stable HTTP-URI-based identifiers for specimens. The system has been successfully implemented in 13 member institutions. Best practices documentations and reusable open source software components support institutions which now want to join. The new identifiers are already used in publications and data portals. A pilot system has been put up demonstrating the integration of distributed collection information using the Linked Open Data capabilities of HTTP URIs. Apart from implementing CETAF stable identifiers in further organizations, the next steps will focus on improving the interoperability of linked open collection data.
This involves (i) the development of machine-readable catalogues of specimens, which can be used as an access point for harvesting metadata, (ii) the development of aggregators facilitating fast indexing and searching across collections and (iii) linking out from collection data to external information resources describing, for example, scientific names, geographic entities and persons. The implementation of a central index will provide the ground for effective quality control measures which are difficult to realise in a purely distributed system. A first prototype of such an index has been integrated into the URI tester. The extension to other physical and virtual object types should be considered. With this, the Natural History Collection domain will bridge the gap to other disciplines and open the door to new ways of accessibility, semantic enrichment and inference.
CETAF stable identifiers are likely to play an important role also in referencing to particular specimens in formal nomenclature acts (both in publications publishing these acts and in respective databases) that are performed in accordance with the International Code of Zoological Nomenclature  (20)  and the International Code of Nomenclature for algae, fungi and plants  (21). Currently a web portal for registration of new and past lectotypifications is being developed and stable identifier link to the newly (or past) designated lectotypes of names are likely to be very useful permanent references to specimens. There are already examples of papers using CETAF stable identifiers in formal nomenclature acts  (22, 23). Stable identifiers will have numerous advantages for researchers, data managers, collection managers, policymakers and institutions.
For example, the delay between information gathering and creating actionable evidence for conservation is slow. Stable identifiers can underpin reproducible workflows for research, because they facilitate the automation of processes without losing the providence of data. Such automated workflows can be repeated as soon as new data become available, shrinking the time between observation and action, but also reducing uncertainty. Another potential of stable web URIs dynamically generated from 2D, QR-or matrix-code accession numbers pinned or glued on the physical objects lies in their integration into collection workflows. A web query for identifiers, done by researchers and collection managers working in the collection magazines, e. g. using mobile apps, will return the direct link to web pages with accredited, objectrelated information-after this information is published by the object-owning institution.
For the average effective area of XGRE, the calculation gives σ  A full line indicates that the spectroscopy is possible at the given energy, and a dot line indicates that it is not. TARANIS XGRE and IDEE data come from GEANT4 simulations performed for this work. Concerning photon response (a), the data for Fermi-GBM were obtained by averaging about 100 response matrices generated from publicly available tools provided by the Fermi-GBM collaboration. For RHESSI, the data were extracted from the response matrix provided by D. Smith. For AGILE-MCAL, this data are reproduced from literature. Concerning the response to electrons and positrons (b and c), these results are obtained from GEANT4 and GEANT3 simulations using the mass models of the spacecrafts (or an approximative version for Fermi).
TGF detection performance The Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) is a NASA spacecraft designed for the study of high-energy radiation from the sun. It uses an array of nine high-purity germanium detectors cooled down to liquid nitrogen temperature. A detailed description of the detector is presented in  Lin et al. (2002) ;  Smith et al. (2002). A response matrix of the RHESSI detector in the TGF context is publicly available (see Sect. 7 on data availability). The provided matrix is already averaged for the spacecraft position and attitude. From this matrix, we can deduce the effective area vs. energy of the detector, which is presented in Fig. 2a. As indicated in  Ostgaard et al. (2012) , RHESSI has an effective area for detecting TGF σ TGF R of about 256 cm 2. The Astro-Rivelatore Gamma a Immagini Leggero (AG-ILE) is a satellite from the Italian Space Agency dedicated to the study of high-energy gamma rays (typically above 50 MeV) in the universe.
Estimating a map of TGFs that can be detected by satellites An approximative map of TGFs that can be detected by satellites was built, based on the TRMM-LISS and OTD global lightning density map  (Cecil et al. , 2014). Compared to this distribution, it was noticed that the TGF density detected by satellites tends to be higher towards the equator. This is supposed to be due to the fact that the tropopause is higher for latitudes closer to zero, where TGF photons have to cross less atmosphere before reaching space, and can be more easily detected by satellites. Let ρ L (θ, φ) be the lightning density from the LISS/OTD database for a given latitude and longitude. Let T (θ ) be an approximative profile of the tropopause height as function of latitude. We used data obtained from  Lewis (2009) , which were fit by a simple normal distribution T (θ ) ∝ exp ((θθ 0 )/2σ θ ) 2 with parameters θ 0 = 0.
8746 • and σ θ = 37. 49 •. Then the TGF density at a given latitude and longitude is assumed as follows: ρ TGF (θ, φ) ∝ ρ L (θ, φ) × [T (θ )] β. (1) The proportionality sign (∝) denotes the fact that we do not define an absolute scale for this density, and therefore all the estimations given afterwards will only use ratios of summed values of ρ TGF (θ, φ). Equation (  1 ) shows that the tropopause profile is set at a power β that we are using as a free parameter, and will be adjusted to get the best possible agreement between this simple model and the observations. This estimated TGF global production map is displayed in Fig. 4. This figure also shows the ground tracks of RHESSI, Fermi, AGILE and TARANIS (planned). They have been calculated using the two-line element from the CE-LESTRACK database (https://www.
Acknowledgements. We thanks  David M. Smith  for providing the mass model, the RHESSI spacecraft, and discussion about its response to electrons. We thank  Micheal S. Briggs  for his help in estimating of the  Fermi-GBM  response to electrons. We thank  Martino Marisaldi ,  Francesco Longo  and  Marcello Galli  for providing the mass model of the AGILE spacecraft, and their help in discussing the response of MCAL to electrons. This work was granted access to the HPC resources of CALMIP supercomputing centre under the allocation 2015-p1505. We thank the  CNES  ( Centre National d'Etudes Spatiales)  for its financial support. The work of  Lubomir Prech  was supported by the  Czech Science Foundation  contract  17-06065S. We would like to thank the two anonymous referees for their valuable comments and suggestions that helped to improve the quality of this work.
Data availability. The data generated for this work can be requested from the corresponding author: contact David Sarria (david. sarria. 89@gmail. com). The response matrices of Fermi GBM detectors are publicly available using the gbmrspgen tool, the usage of which is documented in the following website https://fermi. gsfc. nasa. gov/ssc/ data/analysis/scitools/gbmrspgen. html. The response matrix of the RHESSI instrument in the TGF context was made publicly available by D. M. Smith in the following website: http://scipp. ucsc. edu/ ~dsmith/tgflib_public/. The effective area vs. energy against X-ray and gamma ray photons (in the TGF context) for AGILE-MCAL is taken from  Marisaldi et al. (2015). The V2. 3. 2014 gridded satellite lightning data were produced by the NASA LIS/OTD Science Team (Principal Investigator, Dr.
A basecaller then determines the sequence of bases through the pore according to the observed variation in ionic current. To date, various basecallers are available: from an older Hidden-Markov-Model based (HMM) one to more recent ones based on Recurrent Neural Networks (f. i. Nanonet https://github. com/nanoporetech/nanonet). For the data analysed in this study, we used the HMM-based basecaller, which was the first made available by Oxford Nanopore. This basecalling package infers the sequence of successive k-mer words (5-mer or 6-mer) that passed through a particular pore by analyzing the current variations in time. According to their estimated qualities, the reads are collected into a 'Fail' or a 'Pass' directory, the latter only including the highest quality bi-directional (2D) reads, for which both strands (template and complement) of a DNA molecule have been sequenced and then merged in a single read.
3. The R9 flowcells generated data with higher accuracy than that of the R7. 3 ones (91% against a R7. 3 average of 88%). The R9 total 2D-All and 2D-Pass throughputs, 700 Mb and 60 Mb respectively, were too low for an independent study, so we merged the R7. 3 and R9 reads to get a dataset of 61X depth 2D-All and a dataset of 31X depth 2D-Pass, upon which our assembly comparisons are based. To compare the capabilities of the assembly pipelines we used the S288C strain data, so that assembly quality and accuracy could be easily and directly determined by mapping against its well known reference. Our S288C ONT and PacBio datasets have very different read depths: ONT only 31X (2D-Pass), while PacBio about 120X. By assembling the whole PacBio dataset we obtained contiguous assemblies with accuracy up to 99.