dataesr/scientific-paragraphs-categorization huggingface dataset:
Technical Validation TOFF is managed on a voluntary basis by an editorial board and database administrators. We develop a four-stage quality control of data and managing procedure. First, people willing (i. e. new contributor access) to be database contributors (or to be member of editorial board) must notify their demand to the editorial board through the TOFF website (http://toff-project. univ-lorraine. fr). They will receive an account and an access to the database through on-line system. Second, new data added by database contributors are not directly integrated to the main database but store in temporary repository. The integration of such new data in TOFF requires a prerequisite assessment by the editorial board (i. e. editor approval). Third, data issues noted by users can be reported to the editorial board through the TOFF website (i.
e. user feedback). Fourth, in order to avoid duplicate, measurements with the same value, reference, location, and species will be automatically detected during the integration of database contributors to the main database. Further developments. Currently, TOFF contains traits of only a fraction of fish species (e. g. , lacking marine species) compare to the large number of species and thus some taxonomic classes are completely absent. Indeed, developing an extensive database is a long and challenging endeavor difficult for only few researchers. Therefore, TOFF is designed as a collaborative platform to integrate a large group of researchers worldwide in TOFF further developments. This means that the taxonomic coverages, the functional trait list, the relevant environmental descriptors, and the editor board will evolve over time thanks to contributions of interested researchers.
1b ). SMB across both divide ridges is strongly asymmetric with the western downwind side of the divide receiving much less accumulation (< 0. 6 m yr -1 ice equivalent) than the eastern side (up to 2. 9 m yr -1 ice equivalent)  (Drews et al. , 2013; Lenaerts et al. , 2014). The catchment is a suitable test site to study the dynamics of ice rises because the boundary input datasets such as subglacial topography, ice thickness, and ice surface elevation are well constrained (with many flight lines across the region due to the vicinity of the Neumayer III station). In addition, the confined geometry of both ice rises suggests that significant lateral buttressing is provided by the Ekström and Jelbart ice shelves. This means that the buttressing the Ekström and Jelbart ice shelves provide also restricts ice flow across the grounding line from both ice rises, making the divide position potentially sensitive to ocean forcing.
For the ice-shelf-front boundary, the true vertical distribution of the hydrostatic water pressure is applied and the calving front is held fixed throughout the simulations. We assume the ice is isothermal with a constant temperature of -10 • C. We specify depth-independent horizontal ice velocities taken from the MEaSUREs dataset  (Rignot et al. , 2011)  at all lateral boundaries other than the ice-shelf front. To solve the presented system of equations with the appropriate boundary conditions, we use the open-source finite element code Elmer/Ice  (Gagliardini et al. , 2013).
Initial geometry and input data To initialise the model geometry, subglacial topography was taken from the BEDMAP2 dataset  (Fretwell et al. , 2013). Our surface elevation is a merged product of CryoSat-2 and, where available, higher-resolution TanDEM-X digital elevation models  (Veit Helm, personal communication, 2018). SMB ( ȧs , Eq. 5) in our simulations was taken from regional climate model simulations with RACMO2. 3  (Lenaerts et al. , 2014). This model reproduces the commonly observed asymmetric SMB across ice rises  (Callens et al. , 2016). Velocity observations to match modelled ice velocities in the inversion procedure were taken from the MEaSUREs dataset  (Rignot et al. , 2011).
In all perturbation simulations the grounding line is permitted to freely evolve. All perturbation simulations are run forward for 1000 years, which is about the characteristic time T (T = ice thickness/accumulation) for the Halvfarryggen and Söråsen ice rises  (Drews et al. , 2013). After one characteristic time, the formation of synclines in the internal stratigraphy can usually be observed  (Martín et al. , 2014). Most of the simulations are performed with two different mesh resolutions (Fig. 4 ). The first isotropic mesh uses a horizontal resolution of ∼ 2 km throughout the domain (henceforth regular mesh), whereas for the second mesh (henceforth refined mesh), we initially use the same footprint as for the regular mesh but use the meshing software MMG (http://www. mmgtools. org/, last access: 2 October 2019) to refine the mesh along the grounding line and all ice-divide ridges to a resolution of ∼ 500 m.
The model setup is suitable for glacial/interglacial simulations on the catchment scale, providing the next step forward to unravel the ice-dynamic history stored in ice rises all around Antarctica. compute and data resources provided by the Leibniz Supercomputing Centre (https://www. lrz. de/, last access: 2 October 2019). We thank the editor Carlos Martin and two anonymous reviewers for comments which improved the manuscript. Financial support. This research has been supported by the Deutsche Forschungsgemeinschaft (grant nos. MA 3347/10-1 and EH329/11-1). This open-access publication was funded by the University of Tübingen. Review statement. This paper was edited by Carlos Martin and reviewed by two anonymous referees.
Acknowledgements. We thank  Veit Helm  for providing us with the TanDEM-X digital elevation models. Clemens Schannwell was supported by the  Deutsche Forschungsgemeinschaft (DFG)  grant  EH329/11-1  (to TAE) in the framework of the priority programme " Antarctic Research with comparative investigations in Arctic ice areas". Reinhard Drews  was funded in the same project under MA  3347/10-1. Reinhard Drews  is supported by the  DFG Emmy Noether  grant  DR 822/3-1. The authors gratefully acknowledge the www. the-cryosphere. net/13/2673/2019/The Cryosphere, 13, 2673-2691, 2019.
Code and data availability. The Elmer/Ice code is publicly available through GitHub (https://github. com/ElmerCSC/elmerfem, last access: 10 September 2019). All simulations were performed with version 8. 3 (rev. 74a4936). Elmer/Ice sample scripts and input files for the runs 3-5 and 7-9 are available at https://doi. org/10. 5281/zenodo. 3469937 (Schannwell 2019 , last access: 2 October 2019).
The data were analyzed using CFX Manager software, and the relative levels of gene expression were determined following the method of  Hellemans et al. (2007)  with either EF1α (leaf, green stem and root), 60SRP (leaf) or UBE2 (green stem and root) used as internal reference genes according to the organ (Table  1 ). Results correspond to the relative gene expression in organs of treated plants at flowering and at berry maturity compared to the controls at corresponding timepoints. The value obtained for one treated plant correspond to the mean of the values of the relative gene expression of the treated plant compared to each individual control. In 2015, five biological replicates were used per condition and ten in 2016. The analyzed genes were considered up-or downregulated when the value of relative expression was >2-fold or <0.
Moreover, October is the only period during which LSG male and female profiles appeared significantly different (p < 0. 0033), mainly because of a weak proportion of 6 compounds, unfortunately not all identified (ATG34, ATG44, ATG46, ATG48, ATG49 and ATG50, Kruskal-Wallis, p < 0. 05) compared to male profile. The flank organs were described in several vole species, and were proposed to play a role in male dominance  17  , but behavioural data are scarce and contradictory  18. This work did not evidence a male-specific profile that could support this hypothesis  17. Only behavioural analyses with LSG secretion could bring information on their role in the water vole chemical communication. The water vole specific profile of urinary volatiles. In male and female urine, 29 compounds were detected by SPME-GC/MS and numbered according to the retention time (A.
The water vole genome was not available in any database, but thanks to the closely related species M. glareolus, peptides of A. terrestris urinary proteins were blasted by Mascot software and matched to published urinary MglaOBP1, MglaOBP2 and MglaOBP3 11. A fourth sequence was identified in M. glareolus urine at the protein level by mass spectrometry, glareosin, as male-specific and restricted to the breeding season  12. We thus added the glareosin protein sequence in a home-made database for mass spectrometry analyses. Results showed that each band contains peptides, which are homologous to those of MglaOBP-like and glareosin-like proteins (Supplementary Table  S4 ). Few peptides were identified (1 to 3 for each protein) that led to weak percentages of sequence recovery (8-17%), suggesting that A.
org). These sequences were aligned  26. The novel protein from A. terrestris was named "arvicolin" and was deposited in GenBank database under accession number MK984608. Arvicolin shares 69. 3% identity (90% similarity) with glareosin and 48. 6% (79. 1% similar) with aphrodisin. The detailed results obtained by Blastp search are provided in Supplementary Table  S6  and were used to construct a phylogenetic tree of OBPs in the Rodentia order (Fig. 6 ). Arvicolin peptides were identified in bands 2, 5, 9, and also in bands 1, 4, 6, 7 and 8. The fact that the same arvicolin peptides were identified at apparent molecular masses of 15 kDa and 30 kDa is not unusual for OBPs, which form dimers when concentrated, visible even in denaturing conditions  27. As mass spectrometry data have indicated other potential sequences related to peptides from MglaOBPs (Supplementary Table  S4 ), and to be confident in the assessment that only arvicolin is expressed in male urine, the liver transcriptome of 3 males and 3 females was sequenced by Illumina.
We were able to assemble the full-length sequence of arvicolin in all conditions. Aligning 23 genes of Cricetidae species (Supplementary Fig. S3 ) with MegaBlast on the assemblies indicated that none of these proteins is expressed in males or in females. The number of reads aligned on the arvicolin transcript sequence strongly varies between animals. Even if counted in females (Dot plot in Supplementary Fig. S4 ), the arvicolin transcripts are much more numerous in males (from 1,000 for F2 to 50, 000 reads per million reads (FPM) for M4). The female (F2) that expresses the highest number of transcripts was pregnant. The analysis of differentially expressed genes indicated that 325 contigs are differentially expressed between males and females (FDR < 0. 05). The sex difference in arvicolin expression is not higher than the difference in expression of any other gene of the set (AT-F7 k43 Locus 18919 Transcript 2.
The identification of O-GlcNAc sites by mass spectrometry is not possible by using the HCD mode of ionisation, as the energy is too high to conserve the sugar that is very labile. Conversely, two phosphorylated peptides were identified when database searching was performed with phosphorylation as variable modification. Comparison between the fragmentation profiles of the phosphorylated peptide and the corresponding naked peptide, the shift in retention time and the m/z of the precursors, clearly confirmed the identification (Supplementary Fig. S6 ). Two phosphate groups were detected on peptide 103-123 (TSNMIYVYGKGQPLTPEQYEK), but the fragmentation did not allow to precise the exact position of the phosphorylation between Thr103, Ser104 and Tyr108 (both predicted by NetPhos), and Tyr110 (spectra in Supplementary Fig.
Methods Animals and sampling. Wild males and females were caught in France, in a land parcel of experimental INRA domain of Marcenat (Latitude 46. 2338, longitude 3. 3979) and Laqueuille (Latitude 45. 65, longitude 2. 7333) in a zone of water vole A. terrestris outbreak. Urine was sampled by natural miction or by soft massage of the pubis directly above glass vials. For each animal, body, and testis or uterus weight were registered in a laboratory close to the field. Control of parasite (echinococcosis) was assessed by visual examination of the liver, and infected animals were not included in this study. Lateral scent glands (LSG) were also excised, put in a glass vial by pair for each animal and stored at -80 °C in 2 mL dichloromethane. Samples of soil were collected as control. Three campaigns were run in October 2016 (8 males and 12 females), May (10 males and 16 females) and July 2017 (8 males and 17 females), to link the data to the reproduction period.
Before the first analysis and between analyses, the fibre was conditioned by heating in the GC injection port at 260 °C during 3 min, following manufacturer's instructions. The fibre was desorpted into the GC/MS and compounds were separated according to the following program: Splitless 3 min, 40 °C to 255 °C in 10 °C/min, 255 °C to 315 °C in 5 °C/min, 315 °C to 340 °C in 2 °C/min. Carrier gas was helium at a 1 mL/min flow. Samples were analysed in triplicate. Compounds were identified by comparison of spectra with those of the implemented National Institute Search Technology NIST98 library using Excalibur software (Thermo Fisher Scientific), and by manual analysis of fragmented ions in spectra. Then, identification was confirmed by comparison to authentic standard spectrum obtained by co-injection in the same GC/MS conditions, when commercially available.
Each sample was injected three times and relative quantification of each compound was determined by peak area value. Raw data were subjected to Principal Component Analysis (PCA) by using the package FactoMineR of the R software (R 3. 5. 1 GUI 1. 70) to discriminate biologically meaningful clusters. A comparison using a non-parametric Kruskal-Wallis test was also performed. Statistical analyses data were performed using the R software (R 3. 5. 1 GUI 1. 70). Data were subjected to Redundancy analysis (RDA) to discriminate biologically meaningful clusters using the script provided by Hervé et al. (Example 2) 42 and 3 R packages ("Hotelling", "Vegan", "RVAdeMemoire"). Briefly, the analysis consisted in two steps: 1/fitting a multivariate linear regression between chemical data and the experimental variables (sex and period) followed by 2/a principal component analysis (PCA).
Peptides were extracted and automatically fractionated onto an Ultimate 3000 RSLC nano system with a commercial C18 reverse phase column (75 µm × 150 mm, 2-µm particle). Elution was performed at a flow rate of 300 nL/min and a gradient separation from 5% to 25% ACN and 0. 1% FA during 12 min. The eluted peptides were analysed by a Q-Exactive Orbitrap scanning in full MS over m/z 300-1200 range with a resolution of 35000 at m/z 200. Three most intense peaks with charge state between 2 and 4 were fragmented in the HCD collision cell with normalised collision energy of 35%, and tandem mass spectra were acquired with a resolution of 17500 at m/z 200. Dynamic exclusion was set to 7 s. Raw data collected during nano-LC-MS/MS analyses were processed and converted into *. mgf peak list format with Proteome Discoverer 1.
4. MS/MS data were interpreted using search engine Mascot (version 2. 4. 0) installed on a local server. Searches were performed with a tolerance on mass measurement of 0. 2 Da for precursor and 0. 2 Da for fragment-ion, against a composite target decoy database built with M. glareolus UniProt database (taxon 447135, May 2018, 1311 entries) fused with the sequence of M. glareolus glareosin protein  12  , recombinant trypsin and a list of classical contaminants (119 entries). For each sample, peptides were filtered out according to the cut-off set for proteins hits with one or more peptides taller than nine residues, ion score >10, identity score >4, and 1% false positive rate. All tandem mass spectra were also sequenced by de novo pipeline of MSDA platform (https://doi. org/10. 1002/pmic. 201300415).
Same both search parameters and database than automated Mascot searches were applied for de novo sequencing and homology searches. All interesting spectra were manually annotated according de novo tag identification, precursor mass and M. glareolus protein sequences. RNA extraction and molecular cloning of glareosin-like sequence. The liver of 3 males (AT-M1, AT-M3, AT-M4) and 3 females (AT-F2, AT-F7, AT-F8) was resected and immediately put into RNAlater (QIAGEN). Total RNA was extracted from 30 mg liver of each animal with the RNeasy Universal Mini kit containing Qiazol Lysis Reagent (QIAGEN). Purity of RNA was checked in a BioPhotometer D30 (Eppendorf). Reverse transcription was performed using the Superscript IV First-Strand Synthesis System (Invitrogen) with 3′ specific primer designed from mass spectrometry "de novo" sequencing with M.
RNA sequencing and data analysis. RNA-seq libraries (same 3 males and 3 females as above) have been prepared according to Illumina's protocols using the Illumina TruSeq Stranded mRNA sample prep kit to analyse mRNA. Briefly, mRNAs were selected using poly-T beads, then fragmented to generate double stranded cDNA. Adaptors were ligated to be sequenced after 11 cycles of PCR to amplify libraries. Library quality was assessed using Fragment Analyzer and libraries were quantified by qPCR using the Kapa Library Quantification kit. RNA-seq experiments have been performed on an Illumina HiSeq 3000 device using a paired-end read length of 2 × 150 pb with the Illumina HiSeq 3000 sequencing kits. The six conditions were individually assembled with runDrap for DRAP (version 1. 91)  44  using Oases with the standard multiple kmer approach.
26. 1. Molecular Phylogenetic analysis by Maximum Likelihood method. The evolutionary history was inferred by using the Maximum Likelihood method based on the JTT matrix-based model  45. The tree with the highest log likelihood (-4331. 33) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT model, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 29 amino acid sequences (Supplementary Table  S6 ). All positions containing gaps and missing data were eliminated. There was a total of 106 positions in the final dataset. Evolutionary analyses were conducted in MEGA7  46.
Homology modelling. The model of the structure of arvicolin was calculated using I-TASSER  47. Only one model was generated with a C-score of 1. 01. Among the top 10 identified structural analogues in the protein data bank (PDB) used to generate the model, arvicolin shared 47. 9% identity with aphrodisin of female hamster (PDB entry code 1E5P, https://doi. org/10. 2210/pdb1E5P/pdb)  34 and 98% with the model superimposed with 1E5P, at a root mean square deviation of 1. 26 Å.
Acknowledgements This work was funded by " Conseil Régional Auvergne-Rhône-Alpes" (Délibération n° 1250 ) and  French National Institute for Agronomic Research (INRA). MK, DC, and KP thank the  INRA "Herbipôle" Experimental Unit in Marcenat and Laqueuille , especially  Pascal D'Hour  and  Philippe Pradel  for allowing them to use their facility, as well as the technicians for their help during the trapping of animals. PNLM and AD thank  Peruth Ihimbazwe  for her technical help in performing 1-DE, 2-DE gels and creatinine assays on urine samples. PNLM thanks  Paul Cann  for the building of the phylogenetic tree. RNAseq was performed in collaboration with the  GeT core facility, Toulouse, France  (http://get. genotoul. fr),and was supported by  France Génomique National  infrastructure, funded as part of " Investissement d'avenir" program  managed by  Agence Nationale pour la Recherche  (contract  ANR-10-INBS-09 ).
Data availability The GC/MS spectra of lateral scent glands and urine content generated during this study will be provided to any qualified researcher upon request. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  48  partner repository with the dataset identifier PXD013803 and 10. 6019/PXD013803. The full-length nucleotide sequence of arvicolin was deposited in GenBank database under accession number MK984608. Raw data coming from the sequencing by Illumina of the liver transcriptome of the six animals were deposited in the sequence Read Archive of NCBI under Bioproject #PRJNA545200.
Studied sites The first site is Merguellil site located on the plain of Kairouan  (Zribi et al. , 2011b) , located in the center of Tunisia. This region is characterized by a semi-arid climate with 300mm of annual precipitation. The site is agricultural, with mainly annual crops (wheat, barley, vegetables) and olive groves. The second site of 20km by 20km is identified on the basin of Urgell in Spain  (Gao et al. , 2017). It is a semi-arid site with annual rainfall of 370 mm. It is an agricultural site with a strong presence of irrigation. Soil property measurements are carried out on the different study sites. This is particularly the point soil moisture measured simultaneously to the passage of the satellite S1 for different reference fields. These data are used to calibrate and validate the algorithms proposed in this study.
Satellite data Sentienl-1A and Sentinel-1B images were acquired between December 2015 and March 2017. The two satellites are in the same orbit. They operate in C-band (5. 4 GHz) and Interferometric Wideswath (IW) mode, with a spatial resolution of 10 m. Each satellite has a revisit time of 12 days, which implies a final revisit time equal to six days. The sensors provide dual-polarization imagery (VV and VH) at an incidence angle ranged between 39° and 40°. We used Level-1 Ground range detection (GRD) products that consist of focused SAR that has been detected, multi-looked and projected to groundrange using an Earth Ellipsoid Model. The image processing was executed using the Toolbox in the Sentinel Application Platform (SNAP). The first step was to convert the signal in order to obtain the backscattering coefficient.
A terrain correction was then applied to correct geometric distortions using a Digital Elevation Model (DEM), more precisely those proposed by the SRTM (Shuttle Radar Topography Mission) at 30 m spatial resolution. Finally, thermal noise removal and a Lee filter were applied to reduce the speckle effect. The backscattering coefficient was averaged for each reference field. Optical images were obtained from the Sentinel-2A satellite on dates close to Sentinel-1 images acquired from December 2015 to March 2017. The S-2A images were downloaded and processed from THEIA, a French open-source land data service center website (https://www. theia-land. fr/). The data were derived from cloud-free images with radiometric and atmospheric corrections. The Normalized Difference Vegetation Index (NDVI) was then computed, using Band 4 and Band 8, which represent the Red Reflectance (RED) and the Near-Infrared Reflectance (NIR), expressed by: 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 = (NIR -RED) (NIR + RED) � (1) The NDVI values were averaged for each reference field to characterize the vegetation.
Neural network Our first approach for soil moisture estimates uses the neural networks technique to invert the radar signal and estimate the soil moisture  (Paloscia et al. , 2013 , El Hajj et al. , 2017). First, a parameterized Water Cloud Model combined with the Integral Equation Model (IEM) were used to generate a synthetic database of the backscattering coefficient in the polarizations VV and VH (incidence angle between 20° and 45°) for a wide range of soil moisture (2 < mv (vol. %) < 40), soil roughness (0. 5 < Hrms (cm) < 3. 8), and vegetation conditions (0 < NDVI <0. 75). Second, a gaussian noise is added to synthetic database to obtain more realistic data. These databases were divided in two sets, a first one to train the neural network, a second one to validate the trained neural network.