dataesr/scientific-paragraphs-categorization huggingface dataset:
Data at a total of 134 unique wavelengths, between 405 and 1022. 1 nm, were compiled. All chlorophyll data were considered, but for a given station HPLC data were selected if available. Colours indicate the number of stations available for each variable, as a function of months and the hemispheres of data acquisition (N -Northern Hemisphere; S -Southern Hemisphere). (∼ 25 • N, ∼ 53 • E), COVE_SEAPRISM (∼ 36 • N, ∼ 75 • W), Gloria (∼ 44 • N, ∼ 29 • E), Gustav_Dalen_Tower (∼ 58 • N, ∼ 17 • E), Helsinki Lighthouse (∼ 59 • N, ∼ 24 • E), LISCO (∼ 40 • N, ∼ 73 • W), Lucinda (∼ 18 • S, ∼ 146 • E), MVCO (∼ 41 • N, ∼ 70 • W), Pal- grunden (∼ 58 • N, ∼ 13 • E), Venice (∼ 45 • N, ∼ 12 • E) and WaveCIS_Site_CSI_6 (∼ 28 • N, ∼ 90 • W). Data by HPLC methods (chla_hplc). A comparison of both measurements (Fig.
6 ), when available at the same station shows good agreement  (Trees et al. , 1985). As stated before, the analysis was done on the final merged table; thus, no data were filtered and the good relation can in part be explained by the quality control implemented by the data providers and curators of repositories such as NOMAD and SeaBASS  (Werdell and Bailey, 2005). The total number of rows with concurrent chla_fluor and chla_hplc is 2002, with contributions from NOMAD (32 %), SeaBASS (47 %), MER-MAID (11 %), HOT (7 %), AMT (2 %) and GeP&CO (1 %). The chla_fluor observations are available at 27 933 stations (rows), with values ranging from 0. 0011 to 100 mg m -3 (Fig. 7 ). They are from NOMAD (2350), SeaBASS (15 728),   (677). To maximise the number of ratios per dataset, a search window of up to 12 nm was used when the four wavelengths  (412, 443, 490, 555)  were not simultaneously available.
The effect of different search windows was negligible in the ratio distribution. (164). The total number of chla_hplc observations is 13 918, ranging from 0. 006 to 99. 8 mg m -3 (Fig. 7 ), with contributions from NOMAD (1309), SeaBASS (5920), MERMAID (707), ICES (2994), HOT (153), GeP&CO (1536), BOUS-SOLE (397) and AMT (902). The combined chlorophyll dataset (all chlorophyll data considered, but for a given station HPLC data were selected if available) has a total of 39 849 observations, with 11, 41 and 48 % from oligotrophic (< 0. 1 mg m -3 ), mesotrophic (0. 1-1 mg m -3 ) and eutrophic (> 1 mg m -3 ) waters, respectively. When compared with the proportions of the world ocean in these trophic classes, i. e. 56 % oligotrophic, 42 % mesotrophic and 2 % eutrophic (An-   All chlorophyll data were considered, but for a given station HPLC data were selected if available.
Indian oceans). Of the contributing datasets, NOMAD and SeaBASS provide a good spatial coverage in many regions (Fig. 9 ). The ICES and MERMAID data are mainly located along the coastal regions of Europe. The AMT data cover the central part of the Atlantic Ocean. For additional analysis and as an example of the applications of the compiled dataset, the combined chlorophyll data (chla_fluor and chla_hplc) were partitioned into 5 • × 5 • boxes and for each box the number of observations, average value and standard deviation were computed (Fig. 10 a, b  and c , respectively). The number of observations can be very high (> 1000) in some boxes along the European and North American coastlines and relatively low (< 20) in oceanic regions. Again there is an appearance in the average value map (Fig.
The relationship between maximum band ratio and chlorophyll is close to the NASA OC4 and OC4E v6 standard algorithm (http://oceancolor. gsfc. nasa. gov/cms/atbd/chlor_a), equally based on maximum band ratios, providing confidence in the quality of the compiled data. The inherent optical properties (aph, adg and bbp) are available at 27 unique wavelengths between 405 and 683 nm. There are a total of 1276, 1123 and 638 observations for aph, adg and bbp, respectively. For aph the total number of observations is distributed among NOMAD (1190), SeaBASS (  14 ) and MERMAID (72). For adg the contributions are as follows: NOMAD (1079), SeaBASS (11) and MERMAID (33). The bbp observations come from NO-MAD (371), SeaBASS (32) and MERMAID (235). Data distribution of aph, adg and bbp at 44X and 55X nm for each dataset is provided in Fig.
12a-f. Median values of aph, adg and bbp at 44X and 55X nm for each dataset are summarised in Table  3. For additional analysis, the following band ratios for the absorption coefficients were calculated: aph(490) / aph(443), aph(412) / aph(443), adg(443) / adg(490) and adg(412) / adg(443). Data within 2 nm of the wavelengths were used to maximise the number of points. The distribution of the ratios is shown in Fig. 13. Several observations were found to be above the thresholds used in the IOCCG report 5  (IOCCG, 2006)  for quality control (see dotted vertical black lines in Fig. 13 ). These points are highlighted here for information but retained in the database, as these were mostly from NOMAD and there was an interest to preserve this dataset as a whole. Also, not discarding this data allows further manipulation with different quality control criteria.
On the annual scale, the observations of the inherent optical properties are strongly underrepresented in the Southern Hemisphere where there is a complete absence of data in several months of the year (Fig. 3 ). Overall, the geographic coverage for observations of aph, adg and bbp (Fig. 14 ) is poor, with most open-ocean regions not being sampled, with the exception of the Atlantic Ocean. Small clusters of data are located in particular coastal regions. Finally, for the diffuse attenuation coefficient for downward irradiance (kd), there are 25 unique wavelengths between 405 and 709 nm. There are a total of 2454 obser-  vations, from NOMAD (2266), SeaBASS (118) and MER-MAID (70). Data distribution of kd at 44X and 55X nm for each dataset is shown in Fig. 12g  and h. No kd data at these wavelengths were available for the SeaBASS dataset (only at 490 nm).
Median values of kd at 44X nm span between 0. 08 m -1 (NOMAD) to 0. 1 m -1 (MERMAID), whereas at 55X nm the kd values are approximately 0. 1 m -1 (NOMAD and MERMAID). NOMAD provides the best geographic coverage (Fig. 15 ), with a higher coverage in the Atlantic, compared with other oceans. With the exception of the coastal regions of North America and the Japan Sea, most coastal regions are not sampled. In the Northern Hemisphere, kd is distributed roughly evenly across all months of the year, but in the Southern Hemisphere there are few data points during the austral winter and none at all in September (Fig. 3 ). Although most of the stations with concurrent variables are mainly from the NOMAD dataset, for complete- ness, an examination of bio-optical relationships is provided (Fig. 16 ).
The relation between aph at 443 nm and chlorophyll a (Fig. 16a ) agrees with the relation proposed by  Bricaud et al. (2004). A total of 1070 points exist with these two variables available (93 % from NOMAD). The relation between the sum of aph and adg at 443 nm and rrs at 443 nm (Fig. 16b ) shows a similar dispersion, with the exception of some scattered points, to an equivalent analysis on the IOCCG report 5 (see their Fig. 2. 3). Again, the scattered data were retained in the final table to preserve the NOMAD dataset. A total of 1112 points exist for which these three variables are available (97 % from NOMAD). The relation between the ratio rrs(490) / rrs(555) and kd(490) (Fig. 16c ) shows a good agreement with the NASA KD2S standard algorithm (http://oceancolor. gsfc. nasa. gov/cms/atbd/kd_490).
Acknowledgements. This paper is a contribution to the  ESA OC-CCI  project. This work is also a contribution to project  PEst-OE/MAR/UI0199/2014. We are grateful for the efforts of the teams responsible for the collection of the data in the field and of the teams responsible for processing and storing the data in archives, without which this work would not be possible. We thank  Tamoghna Acharyya  and  Robert Brewin  at  Plymouth Marine Laboratory  for their initial contribution to this work. We thank the  NOAA (US)  for making available the MOBY data and  Yong Sung Kim  for the help with questions about MOBY data. BOUSSOLE is supported and funded by the  European Space Agency (ESA) , the  Centre National d'Etudes Spatiales (CNES) , the  Centre National de la Recherche Scientifique (CNRS) , the  Institut National des Sciences de l'Univers (INSU) , the  Université Pierre et Marie Curie (UPMC)  and the  Observatoire Océanologique de Villefranche -sur-mer (OOV).
We thank  ACRI-ST, ARGANS  and  ESA  for access to the MERMAID Database (http://hermes. acri. fr/mermaid). We thank  Annelies Hommersom ,  Pierre Yves Deschamps  and  David Siegel  for allowing the use of MERMAID data for which they are principal investigators. We thank the  British Oceanographic Data Centre (BODC)  for access to AMT data and in particular  Polly Hadziabdic  and  Rob Thomas  for their help with questions about the AMT dataset. We thank  Victoria Hill ,  Patrick Holligan ,  Gerald Moore  and  Emilio Suarez  for the use of AMT data for which they are principal investigators. We thank  Sam Ahmed ,  Hui Feng ,  Alex Gilerson  and  Brent Holben  for allowing the use of the AERONET-OC data for which they are principal investigators. We thank also the  AERONET  staff and site support people.
table. table is comprised of in situ observations between 1997 and 2012, with a global distribution, and include the fol- lowing variables: remote-sensing reflectance (rrs), chloro- phyll a concentration (chla), algal pigment absorption co- efficient (aph), detrital and coloured dissolved organic mat- ter absorption (adg), particle backscattering coefficient (bbp), and diffuse attenuation coefficient for downward irradiance (kd). All observations in the table were processed in such a way that they can be compared directly with satellite-derived ocean-colour data. The table consists of 80 524 rows and 267 columns. Each row represents a unique station in space and time, separated from each other by at least 5 min and 200 m. For each observation in a given station, there are three metadata strings: dataset, subdataset and pi.
The columns of the table take the form described in Table 1. The contrib- utors of data in the table are shown in Table 2. Regarding spectral variables, all original wavelengths were preserved, which requires a large number of unique wavelengths to be maintained in the database. No band shifting was performed (though some archived data in SeaBASS and MERMAID may have been merged with nearby wavelengths) and no minimum number of wavelengths per observation was im- The posed. This allows further manipulation of the table for different purposes. In the following paragraphs, the table is analysed and the final group of observations is described for each contributing dataset; however, the numbers reported here do not reflect the original numbers in each dataset, since duplicates across contributing datasets were removed (e.
Bioinformatic analysis A collection of 240 GBS genomes was used for phylogenetic analysis: 229 of them were reported previously by Da Cunha et al. [18] , an other 10 were available at Gen-Bank (SS1, NZ_CP010867. 1; 09mas018883, NC_021485. 1; NGBS061, NZ_CP007631. 1; A909, NC_007432. 1; GD201008-001, NC_018646. 1; 2603V/R, NC_004368. 1; GBS2-NM, NZ_CP007571. 1; GBS6, NZ_CP007572. 1; GBS1-NY, NZ_CP007570. 1; NEM316, NC_004368. 1), and another one was sequenced in this work (HRC, see below). MobM-related relaxases were searched in whole genomes by using the 300 N-terminal amino acid residues of the MobM relaxase of plasmid pMV158; they were used as the query in a PSI-BLAST search (e-value: 1 Â 10 26 , limited to 100 non-redundant hits), and the homologues found were aligned using the program MUSCLE as described previously for the family of plasmid-encoded relaxases related to MobM  [27].
The core genome phylogeny of these 240 GBS strains was performed using the parsnp program from the Harvest suite  [28]. The core genome SNPs of all strains were aligned against the reference genome sequence of the 2603 V/R strain (NC_004116) using MUSCLE and ignoring MUMi recruitment regions of recombination; alignments were filtered using PHIPACK  [29]  rsob. royalsocietypublishing. org Open Biol. 6: 160084 and the phylogeny was reconstructed by FASTTREE2  [30]. The tree was annotated using iTOL: interactive tree of life  [31] , an online phylogenetic tree viewer (http://itol. embl. de/). The limits of the mobile elements ( prophages, ICEs, IMEs, CIMEs) were determined after identification of the attachment (att) sites using the REPEAT FINDER program (http://www. cbcb. umd. edu/software/RepeatFinder/).
Whole genome sequencing The S. agalactiae HRC genome was sequenced at the Institute of Tropical Diseases and Public Health of the Canary Islands (University of La Laguna, Tenerife, Spain). The library was constructed in the AB Library Builder system (Thermo Fisher Scientific, Inc. ) and its length, size distribution and concentration were assessed in the Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). Samples were subjected to emulsion PCR and enrichment by the OneTouch system (using the Ion One-Touch 200 Template v2DL kit), loaded in one Ion314 chip and sequenced in the Ion Torrent Personal Genome Machine (PGM) platform (Thermo Fischer Scientific, Inc. ) with the 200 bp sequencing chemistry. A total of 121 Mb was obtained (686 800 reads, mean read length approximately 177 bp). Raw sequence data were deposited in the Sequence Read Archive under the accession number SRP060555.
Functional assays and nick site determination Relaxation of supercoiled plasmid DNA by purified MobSag protein was performed as previously described  [37]. Reactions were carried out by incubating supercoiled DNA of plasmids pMVS or pMVSag (8 nM) without or with protein MobSag in buffer B (20 mM Tris-HCl pH 7. 6, 0. 1 mM EDTA, 1% glycerol (w/v), 1 mM dithiothreitol, and 8 mM MnCl 2 ) for 20 min. Different protein concentrations (from 8 to 418 nM), incubation temperatures (from 20 to 708C) and times (from 1 to 40 min) were tested. Generation of relaxed (FII forms) from supercoiled DNA (FI forms) was analysed by electrophoresis on 1% agarose gels stained with GelRed 1Â. Densitometric analyses were done using the QUANTITYONE software (Bio-Rad USA, Hercules, CA). The amount of relaxed DNA forms observed in the control was subtracted in each assay.
Analysis of the mobilome of S. agalactiae HRC allowed us to determine that it carries the plasmid pST2426, previously identified in Streptococcus tigurinus  [40, 41] , as well as eight putative ICEs and related mobile genetic elements (figure  4a ; electronic supplementary material, table  S4 ). The type-A IMESag-rpsI encoded by S. agalactiae HRC spans 9496 bp and is flanked by two attachment sites (att). This IME contains 13 ORFs, eight of them annotated as: a site-specific recombinase (Phage_integrase; PF00589), a transcriptional regulator from the Cro/CI family (HTH_3; PF01381), the N-terminus of an initiator protein A (RepA_N; PF06970), a replication initiator belonging to the rolling circle family (Rep_trans; PF02486), a conjugative relaxase from the MOB V family (Mob_Pre; PF01076), and a type II toxin-antitoxin system from the RelBE family (RelB; PF04221 and RelE; PF06296; figure  4b ).
In vivo activity of the IMESag-rpsI conjugative transfer module The conjugative transfer capacities of IMESag-rpsI from strain HRC were further investigated. Apart from a gene coding a putative relaxase (that we have designated mobSag), no other putative conjugative elements, such as coupling protein or elements participating in T4SS, were observed. The upstream and downstream regions of the mobSag gene encompassed a putative oriT and a type-A lagging-strand origin (ssoA)  [43] , respectively (figure  4c ). The oriT of IMESag-rpsI (named oriT Sag ) rsob. royalsocietypublishing. org Open Biol. 6: 160084 spans 42 bp and, similarly to the oriT of plasmid pMV158, contains three partially overlapping inverted (IR1 to IR3). Based on its conservation among the oriT sequences of the pMV158 family  [27] , a possible nick site within the sequence 5 0 -GTGCG/T-3 0 was also predicted ('/' denoting the phosphodiester bond cleaved by the cognate relaxase).
Under denaturing conditions (SDS-PAGE), the protein migration agreed with the protein protomer's predicted size of 48. 7 kDa (figure  6a ). The analysis by gel filtration chromatography resulted in a single elution peak that fits with a MobSag homodimer (figure  6a ). Prediction of the secondary structure of MobSag was achieved by computational and circular dichroism (CD) approaches (see electronic supplementary material, Methods). Employment of the program SABLE  [46]  showed the presence of the a/b-fold (a-helices alternating with b-strands), which is the typical distribution on the HUHrelaxases  [15]  (electronic supplementary material, figure  S1a ). This prediction was experimentally tested by CD in the far-UV region (electronic supplementary material, figure  S1b ). The CD spectrum of MobSag showed two minima at 208 nm and 222 nm, a typical feature of a-helical structures.
Acknowledgements. Thanks are due to  Teresa Coque  for providing us with the strain HRC of S. agalactiae studied here, to  Veronica Navarro  for technical help, and to  Mariano Herna  ´ndez and  Basilio Valladares  for their support with the PGM sequencing platform. The authors also want to thank the anonymous reviewers for their thorough and in-depth review of the manuscript.
Oral cancer is a major health challenge in the Indian subcontinent and a dreadful form of cancers worldwide. The current study is focused on the identification of distinguished metabolites of oral cancer tissue samples in comparison with precancerous and control tissue samples using gas chromatography coupled with triple quadrupole tandem mass spectrometry and chemometric analyses. Metabolites obtained were identified through National Institute of Standards and Technology (NIST) mass spectral (Wiley registry) library. Mass Profiler Professional (MPP) software was used for the alignment and for all the statistical analysis. 31 compounds out of 735 found distinguishing among oral cancer, precancerous and control group samples using p-value ≤ 0. 05. Partial Least Square Discriminant Analysis (PLSDA) model was generated using statistically significant metabolites gave an overall accuracy of 90.
25 mm film thickness) was used. Helium was used as the carrier gas at 1. 0 mL/min and the sample was injected in splitless mode. The injector and source temperatures were 250 °C. The oven temperature was initially maintained at 40 °C, and was then increased at 10 °C min to 300 °C and retained at 300 °C for 9 min. In post run, temperature was further increased to 305 °C, for remaining 1 min. Retention time was locked to myristic-d27 acid at 15. 167 min. Electron ionization (EI) is used as an ionization source. Data processing was performed using the Agilent Mass Hunter Qualitative Analysis (version B. 04. 00). Putative identification of low molecular weight metabolites were established by comparing the mass spectra of the peaks with those available in the NIST mass spectral (Wiley registry NIST 11) library.
7% was 93. 3%, respectively, while the overall accuracy of the model was 90. 2% as mentioned in Supplementary Table  3. Receiver Operating Characteristics (ROC) curve was also produced for PLS-DA (Supplementary Figure  4 ). Pathway Analysis. MetaboAnalyst 3. 0 (www. metaboanalyst. ca/) was used to identify metabolic pathways which were disturbed in diseased samples as compared to control using differentiated and identified metabolites. The summaries of pathway analysis created on the basis of hypergeometric test and relative-betweens centrality in pathway topology analysis by this program using differentiated metabolites are shown in Fig. 4. The list of discriminating identified pathways is provided in Table  3  and Supplementary Table  4. Total twenty four pathways were found to be deregulated with the highest impact of 0.
Material and methods The 3-D reconstruction of the Drus west face was carried out using 30 Web-retrieved images from different picturehosting services (Flickr. com, SummitPost. org and Camptocamp. org; see Appendix A) and a commercial photogrammetric  (Agisoft PhotoScan, 2014)  software (version 1. 0. 3). The georeferencing-alignment procedure of point clouds was done with CloudCompare (Girardeau-Montaut, 2015) software (version 2. 7. 0), and an estimation of the missing volume was then performed using 3DReshaper (Technodigit, 2014) software (2014 MR1 version) by comparing the SfM point cloud with terrestrial lidar scans acquired after the event.
Selection of photographs from the Internet Before the 30 June 2005 rock avalanche, the Drus west face was affected by major rockfalls in September 1997 (27 500 ± 2500 m 3 ; 17-18 and 28 September) and August 2003 (6500 ± 500 m 3 ; 2-3 August)  (Ravanel and Deline, 2008). These events significantly modified the morphology of the pillar between 3160 and 3460 m a. s. l. (Fig. 1d ), and we thus looked for photographs taken between early August 2003 and the end of June 2005. This was carried out by looking at the Exif metadata which are publicly available within the three abovementioned imagery repositories. After a visual check, 30 pictures taken from different viewpoints and with a mean size of 500 Ko were selected (Fig. 2  and Appendix A ). Note that, due to a limited number of available images, we were forced to choose pictures taken in different seasons.
Ground-based lidar data acquisition In order to obtain a 3-D model of the entire Drus west face with a high and homogeneous density of points (∼ 250 points m -2 , i. e. , 1 point every 6. 2 cm), we merged the lidar scans from two different measurement campaigns carried out in October 2005 and November 2011. The 2005 point cloud (assembly of three scans, 7. 5 million points) represent only the upper part of the face and was acquired from the Flammes de Pierre ridge (Fig. 2 ) with a mediumrange laser scanner (Optech ILRIS-3-D)  (Ravanel and Deline, 2006). The 2011 point cloud (assembly of three scans, 24 million points) of the whole face has been acquired with a long-range laser scanner (Optech ILRIS-LR) from the right lateral moraine of the Drus glacier, situated around 2500 m a. s. l. (Fig.
Georeferencing and alignment of lidar scans In the absence of a fairly accurate DEM (the resolution of the IGN's DEM is only 30 m in this sector), both datasets were georeferenced using the scanner position measured by dGPS, then aligned with respect to the vertical axis using the coordinates of several points distributed in the cliff and measured with a total station. The scans were then aligned with each other using iterative closest point (ICP) algorithms  (Besl and McKay, 1992)  but only applied to stable parts (manually selected because of the different viewpoints) because between these two acquisitions two major rockfalls occurred in September 2011 (4530 ± 200 m 3 ) and October 2011 (54 730 ± 400 m 3 ) in the June 2005 rock avalanche scar area (Fig. 6d ). These volumes were determined by comparing the 2005 and 2011 lidar acquisitions and include the "small" rockfalls (range of volumes: 1-426 m 3 ) detected between October 2005 and September 2008 by an annual li-dar monitoring carried out from the Flammes de Pierre ridge  (Ravanel, 2010).
Acknowledgements. The authors would like to acknowledge the  Swiss National Science Foundation  (SNSF, grants  200020_146426  and  200020_159221 ) for supporting this research. The second author was granted a  Marie Curie fellowship  (project ref. : 705215). In addition, we would like to thank the authors of the pictures extracted from Flickr, SummitPost and Camptocamp (see Appendix A for a detailed description) and also express our appreciation for the support of the  Chamonix Mont-Blanc Helicopters (CMBH)  company for reaching the stations from which terrestrial lidar acquisitions were performed. Finally, special thanks go to  Jean-Luc Epard  for his explanations concerning the interpretation of the geotectonic setting of Mont Banc massif. Edited by: Oded Katz Reviewed by: two anonymous referees.