dataesr/scientific-paragraphs-categorization huggingface dataset:
14-17501S ,  Czech Republic ;  Centre de Calcul IN2P3/CNRS ,  Centre National de la Recherche Scientifique (CNRS) ,  Conseil Régional Ile-de-France ,  Département Physique Nucléaire et Corpusculaire  ( PNC-IN2P3/CNRS ),  Département Sciences de l'Univers (SDU-INSU/CNRS) ,  Institut Lagrange de Paris (ILP)  Grant No. LABEX ANR-10-LABX-63 , within the  Investissements d'Avenir Programme  Grant No. ANR-11-IDEX-0004-02 , France;  Bundesministerium für Bildung und Forschung (BMBF) ,  Deutsche Forschungsgemeinschaft (DFG) ,  Finanzministerium Baden-Württemberg ,  Helmholtz Alliance for Astroparticle Physics (HAP) ,  Helmholtz-Gemeinschaft Deutscher Forschungszentrum (HGF) ,  Helmholtz Alliance for Astroparticle Physics (HAP) ,  Ministerium für Wissenschaft und Forschung ,  Nordrhein Westfalen, Ministerium für Wissenschaft, Forschung und Kunst, Baden-Württemberg, Germany ;  Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR) ,  Gran Sasso Center for Astroparticle Physics (CFA) ,  CETEMPS Center of Excellence, Italy ;  Consejo Nacional de Ciencia y Tecnología (CONACYT) ,  Mexico ;  Ministerie van Onderwijs, Cultuur en Wetenschap ,  Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) ,  Stichting voor Fundamenteel Onderzoek der Materie (FOM) ,  Netherlands ;  National Centre for Research and Development , Grants No.
Problem Behaviours Assessment (PBA) The short version of the PBA-s  [35]  is a concise version of the Problem Behaviours Assessment for HD (PBA-HD)  [17]. It is a semi-structured interview designedtoassesselevenpsychiatricsymptomsthought to be potentially most relevant to HD: low mood, suicidal ideation, anxiety, irritability, angry or aggressive behaviour, apathy, perseverative thinking or behaviour, obsessive compulsive behaviour, paranoid/delusional thinking or behaviour, hallucinations and behaviour suggesting disorientation. Individual items are scored on a five-point scale for severity and frequency respectively (previous four weeks) and multiplied for an overall score. Raters were trained, and all interviews recorded with a random subsample reviewed by an experienced rater. Factor analysis of PBA-HD data  [8, 17]  identified three main factors: apathy, irritability/ aggression, and affective symptoms.
Imaging data acquisition Structural imaging data collection has been described previously  [33]. DTI data were acquired using 3T MRI Siemens Trio (London and Paris) and Philips (Leiden) scanners (see Supplementary information for Quality Control information). Diffusion-weighted images with 42 unique gradient directions (b = 1000 sec/mm 2 ) were collected with either seven images (Siemens) with no diffusion weighting or one image with no diffusion weighting  (Phillips). For scans collected in London, dimensions were 128 pixels × 96 pixels × 65 slices per volume, with TE = 84 ms and TR = 7600 ms; for Paris, dimensions were 128 pixels × 128 pixels × 75 slices per volume, with TE = 88 ms and TR = 13100 ms and for Leiden, dimensions were 112 pixels × 112 pixels × 55 slices per volume, with TE = 56 ms and TR = 8078 ms.
Data analyses Demographic, clinical and neuropsychiatric data were analysed using independent t-tests and Chi-Squared tests in SPSS v. 19. 0. Prior to analysis, each DTI dataset was manually scanned for artefacts, signal drop-out, and motion; quality assurance was performed after each pre-processing step. The diffusion data were pre-processed using standard pipelines within the FSL data analysis package  [39]. Data were first corrected for distortions caused by eddy currents, and motion using FSL's eddy correct and vector gradient information was updated accordingly. The no-gradient (b = 0) image was then skull-stripped using the Brain Extraction Tool (BET), manually examined, corrected if required, and diffusion-tensor fit to the corrected data. For the TBSS analysis  [31] , all diffusion tensor data were then registered to a customized diffusion tensor template using DTI-TK  [40]  to achieve optimal alignment of white matter.
05). Again this was widespread across the brain in the same white matter regions in which we saw negative correlations between irritability/aggression and FA (Table  3 ; Fig. 2a ). For lower CPO, FA decreased as PBA irritability/aggression scores increased; negative relationship was reversed as CPO increased (Fig. 2b ). These results remained significant when controlling for the effects of all medication (corrected P < 0. 05). We predicted that elevated irritability/aggression would be associated with frontal white matter anomalies. Thus, we examined white matter changes in the frontal lobe at an uncorrected threshold and identified similar negative correlations in the left uncinate fasciculus (uncorrected P < 0. 001) (See Supplementary Data for site-specific analyses).
ACKNOWLEDGMENTS Track-HD is funded by the  CHDI foundation , a not for profit organization dedicated to finding treatments for Huntington's disease, the  Wellcome Trust (GR) , and the  Medical Research Council (SJT). We thank the  TRACK-HD  study participants and their families, and also acknowledge the support of the  National Institute for Health Research University College London Hospitals Biomedical Research Centre  and the  Manchester Biomedical Research Centre. All authors have contributed to the work, agree with the presented findings, and that the work has not been published before nor is being considered for publication in another journal.
With our study we aim to get a better constrain of the bright end of the [Oii] LF by using new deep spectroscopic measurements. In this study, we gather an  [Oii]  emission line sample from publicly available data to which we add newly acquired spectroscopy. In section 2, we describe current publicly available  [Oii]  data and the new flux-calibrated spectroscopic data acquired by ESO VLT/FORS2 and by SDSS-III/BOSS spectrograph. With this combined sample we measure the [Oii] luminosity function, in section 3. We also project the luminosity function to inform the planning of future surveys. Finally, we compare our measurement with semi-analytical models in section 4. Although this new sample is suited for such an analysis, we do not perform a new calibration of the relation [Oii] -SFR -dust, and leave it for future studies.
Data reduction, spectroscopic redshifts The data processing pipeline performs an extraction of the spectrum that allows the estimation of the flux in the [Oii] emission line. This procedure has two steps. 1. We apply the scripts and procedures from the ESO pipeline document 2. We use fors_bias for the master bias creation, fors_calib for the master calibration creation, and 2 ftp://ftp. eso. org/pub/dfs/pipelines/fors/fors-pipeline-manual-4. 4. pdf fors_science to apply the calibrations and subtract the sky. Figures 8. 2 and 8. 3 from that document show an example of the data reduction cascade. We use the 'unmapped' result obtained in the middle of the fors_science part of the reduction, and the matching frames containing the wavelength values. Both 'average' and 'minimum' combinations of the 2 frames are obtained on each mask.
CFHT-LS ugri selection During a first observation run, a total of 2292 fibers were allocated over 7. 1 deg 2 (the area of an SDSS-III plate). The ELG were observed during 2 hours with the spectrograph  (Smee et al. 2013 ) of the 2. 5m telescope located at Apache Point Observatory, New Mexico, USA,  (Gunn et al. 2006 ). The targets were selected from the Canada-France-Hawaii Telescope Legacy Survey (CFHT-LS) Wide W3 field catalogue with ugri bands. The data and cataloguing methods are described in  Ilbert et al. (2006) ;  Coupon et al. (2009) , and the T0007 release document  3. The color selection used is -0. 5 < ur < 0. 7 • (gi) + 0. 1 and 20 < g < 22. 8. The selection function focuses on the brightest and bluest galaxy population; see Fig. 9. The selection provides 3784 targets, we observed 2292 of them.
Final sample We combine the data samples previously described, to measure the observed [Oii] LF in the redshift range 0. 1 < z < 1. 65. We set 8 redshift bins of width ∼1 Gyr. We select reliable redshifts that have well-defined photometry in the two or three of the ugriz optical bands that we are using for the weighting scheme (see next paragraph). Moreover, we request a detection of the [Oii] lines with a signal to noise ratio greater than 5. In total, we use around 20 000 spectra. The total amount of spectra provided by each survey as a function of redshift is given in Table  4. This conjunction of surveys has a gap in redshift around redshift 0. 45. We minimized the impact of this gap by shrinking to the minimum the redshift bin 0. 4 < z < 0. 5 and removed it from the analysis. We tested the robustness of LF against the SNR limits between 3 and 10.
2012 ) that span 3. 19 deg 2 and 275 deg 2 , respectively. For redshifts z < 0. 7, we use the number densities observed on the Stripe 82 SDSS Coadd. For redshifts above, we the CFHT-LS deep photometric redshift catalog to obtain the best possible estimate of the parent density of galaxies (note that it is not necessary to have the parent photometry and the observed data on the same location of the sky). We convert all the magnitudes to the CFHT Megacam system using the calibrations of  Regnault et al. (2009)  to have a consistent weighting scheme among the various surveys.
We set two redshift ranges : -0. 7 < z < 1. 1 corresponding to eBOSS-ELG and where the [Oii] data is complete to a luminosity of 10 41 erg • s -1 , which corresponds to a flux 2. 3 × 10 -17 erg • s -1 • cm -2 at redshift 0. 9. -1. 1 < z < 1. 6 corresponding to DESi-ELG and where the [Oii] data is complete to a luminosity of 10 42 erg • s -1 , which corresponds to a flux 8. 2 × 10 -17 erg • s -1 • cm -2 at redshift 1. 3. The magnitude that correlates best with the [Oii] flux is the g band in the redshift range 0. 7 < z < 1. 1 and the r band in the range 1. 1 < z < 1. 6; see Fig. 15. These bands should thus be used to construct in the most efficient way an [Oii] flux limited sample. The correlation in the higher redshift bin might be biased because below the flux completeness limit the data is not representative of the complete population: u or g band could also be used for targeting at redshift 1.
Acknowledgements We thank  Alvaro Orsi  for sending us his model predictions and for the useful discussion. We thank the referee for constructive and insightful comments on the draft. JC acknowledges financial support from  MINECO (Spain)  under project number  AYA2012-31101. JR acknowledges support from the  ERC  starting grant  CAL-ENDS. JPK and TD acknowledge support from the  LIDA ERC  advanced grant. Funding for SDSS-III has been provided by the  Alfred P. Sloan Foundation , the Participating Institutions, the  National Science Foundation , and the  U. S. Department of Energy Office of Science. The  SDSS-III  web site is http://www. sdss3. org. SDSS-III is managed by the  Astrophysical Research Consortium  for the Participating Institutions of the  SDSS-III Collaboration  including the  University of Arizona , the  Brazilian Participation Group ,  Brookhaven National Laboratory, University of Cambridge, Carnegie Mellon University, University of Florida , the  French Participation Group , the  German Participation Group, Harvard University , the  Instituto de Astrofisica de Canarias , the  Michigan State/Notre Dame/JINA Participation Group ,  Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington , and  Yale University.
The BOSS French Participation Group is supported by  Agence Nationale de la Recherche  under grant  ANR-08-BLAN-0222. This work used the DiRAC Data Centric system at Durham University, operated by the  Institute for Computational Cosmology  on behalf of the  STFC DiRAC HPC Facility  (www. dirac. ac. uk). This equipment was funded by  BIS National E-infrastructure capital  grant  ST/K00042X/1 ,  STFC  capital grant  ST/H008519/1 , and  STFC DiRAC Operations  grant  ST/K003267/1  and  Durham University. DiRAC is part of the  National E-Infrastructure. VGP acknowledges support from a  European Research Council   Starting Grant  ( DEGAS-259586 ) and the  Science and Technology Facilities Council  (grant number  ST/F001166/1 ). Based on observations obtained with  MegaPrime/Megacam , a joint project of CFHT and CEA/DAPNIA, at the  Canada-France-Hawaii Telescope (CFHT)  which is operated by the  National Research Council (NRC)  of  Canada , the  Institut National des Science de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France , and the  University of Hawaii.
DATA AND METHODS As state institutions have failed to monitor the shea value chain, no reliable data on stakeholders involved in the chain were available and random sampling was consequently impossible. Instead we selected informants based on a snowball effect, starting from the top of the pyramid and moving to the bottom to be sure of covering the diversity of actors in the chain (Table  1 ). We started by interviewing the best known traders in each of the 13 provincial capitals in western Burkina Faso (Figure  3 ) and asked them to give us the name and contact information of other stakeholders they knew either as partners or competitors. Data were collected at the end of the 2012-13 marketing year. In total, we interviewed 194 traders. Although our panel is not a random sample, we are confident that it is a reasonably accurate representation of the actual range of shea traders.
The Albicidin Locus and other NRPS Loci NRPS is a pathway based on multimodular megasynthetases used by bacteria and fungi to produce peptides in a ribosome-independent manner  [43]. The NRPS albicidin locus is present in the "X. pseudalbilineans" strain MUS 060 draft genome but not in the genome of the "X. pseudalbilineans" strain GPE 39, confirming the results of albicidin production bioassays (data not shown). The albicidin locus of strain MUS 060 contains all the albicidin biosynthesis genes described in X. albilineans, except alb18 encoding an aminodeoxychorismate lyase, which is most likely complemented by a gene present elsewhere in the genome encoding the same enzyme (ortholog of gene XALc_0280 in strain GPE PC73). Interestingly, alb18 is also partially frameshifted in X. albilineans strains GPE PC73 and Xa23R1, supporting the hypothesis of complementation with the ortholog of XALc_0280.
HPLC analysis of an albicidin extract from strain MUS 060 showed a chromatographic profile very similar to those usually observed for extracts of X. albilineans strains  [11] ; peaks containing albicidin antibiotic activity eluted at similar retention times for both species. The absence of the albicidin locus in strain GPE 39 is in accordance with the inability of this isolate to produce albicidin. The gene encoding the phosphopantetheinyl-transferase required for albicidin production and for post-translational activation of NRPS megasynthetases, which is present outside the albicidin locus, is conserved in strains MUS 060, GPE 39, Xa23R1 and GPE PC73 and is located at the same position in these genomes (between orthologs of XALc_1735 and XALc_1737). Previous genome mining data has led to the identification of a new NRPS locus, named META-B, present in the genome of five strains: X.
albilineans strains GPE PC73 and Xa23R1 and "X. pseudalbilineans" strains GPE 39 and MUS 060), as well as by Xanthomonas campestris pv. raphani  [7, 56]. Interestingly, regarding CRISPR-2, the nucleic acid sequences of the repeats are 100% identical among the four strains, thus confirming the common origin of this locus. In contrast, no common CRISPR-2 spacers are shared by the four strains, underlying distinct phage exposure and strain adaptation according to their respective environment. Furthermore, spacers of MUS 060 and GPE 39 isolates show no identity to phages described in GenBank to date. None of the CRISPR-2 spacers of strain MUS 060 exhibit identity with other nucleic acid sequences of its own genome or with genomes of strains GPE PC73, Xa23R1 and GPE 39. Also, none of the CRISPR-2 spacers of strain GPE 39 share identity with other nucleic acid sequences of its own genome, but spacer-2 is 96% identical to spacer-13 of the CRISPR-1 system of GPE PC73, and spacer-54 is 100% identical to a gene sequence located in one of the three plasmids of strain GPE PC73 (XALr_3262).
Strain GPE 39 possesses two other type II restriction endonucleases: (i) PaeR71 associated with N4/N6 methyltransferase PaeR71, which is 100% identical to those found in a X. axonopodis strain (GenBank Accession No. WP_017173568 and WP_017173569, respectively) and (ii) another type II restriction endonuclease associated with a C-5 cytosine methyltransferase (nucleic acid sequence of these genes is provided in Supplementary File S4). The presence of such restriction-modification systems as well as of CRISPR-1 in both GPE PC73 and GPE 39, but not in Xa23R1 and MUS 060, suggests that strains GPE PC73 and GPE 39 are better adapted to both phage-containing environments and epiphytic survival.
According to their protein domains, the encoded proteins are predicted to correspond to a glycosyl transferase, a polysaccharide biosynthesis protein, a pyridoxal phosphate-dependent transferase, an acyl-CoA N-acyltransferase, a glycosyl hydrolase, a sugar O-acyltransferase and a dTDP-6-deoxy-3,4-keto-hexulose isomerase. (ii) a large CDS (1450 amino acids) that shows no significant amino acid similarity to other bacteria found in GenBank, but which consists of a C-terminal autotransporter domain associated with an N-terminal passenger domain as well as four autotransporter-associated beta-stranded repeat domains and a left-handed parallel beta-helix (LbH) domain. The presence of such domains, usually found in autotransporter proteins of the type V secretion system of Gram-negative bacteria, suggests a possible adhesion function associated with this CDS; however, the involvement of this protein in bacterial virulence and attachment to leaves remains to be demonstrated.
DNA Sequencing and Assembly Shotgun sequencing of strains Xa23R1 and GPE 39 was performed on a Solexa GAIIx (Illumina) sequencer (Genoscope, Évry, France), yielding 35,491,178 and 32,445,653 76-bp paired-end reads, respectively, with an insert size of 200 bp. Whole genome shotgun (WGS) BioProject sequences of strains Xa23R1 and GPE 39 have been deposited with the BioProject/GenBank databases under the references PRJNA270034 and PRJNA270166, respectively. Shotgun sequencing of strain MUS 060 was performed on a MiSeq 2000 sequencer (Fasteris, Geneva, Switzerland), yielding 3,139,946 125-bp paired-end reads. WGS BioProject of strain MUS 060 has been deposited with the BioProject/GenBank database under the reference PRJNA270312. The draft assemblies of strains Xa23R1, GPE 39 and MUS 060 are available from the DDBJ/EMBL/GenBank databases under accession numbers JZIK00000000, JZHZ00000000 and JZIM00000000, respectively.
Genotyping with 16S-23S rRNA ITS and 16S rRNA Gene Sequence 16S ribosomal RNA (rRNA) gene sequences and the 16S-23S rRNA internal transcribed spacer region (ITS) of strains MUS 060, GPE 39, X. sacchari LMG 476, X. sacchari NCPPB4393, X. sacchari R1 and X. albilineans Xa23R1 were searched on their respective draft genome sequences (see corresponding accessions in Table  1 ) using blastn (http://blast. ncbi. nlm. nih. gov/blast/Blast. cgi? CMD=Web&PAGE_TYPE=BlastHome  [68] ) with the query being the 16S ribosomal DNA sequence provided by the reference strain GPE PC73. The seven resulting sequences were compared using the MAFFT alignment program (http://mafft. cbrc. jp/alignment/software/ [69]  (see sequences and alignments in Supplementary Files S1 and S2, respectively).
Phylogenetic Core Genome Analysis: MLSA MLSA based on seven complete housekeeping genes (atpD, dnaK, efp, glnA, groL, gyrB and recA) was performed on MUS 060 and GPE 39 isolates, on X. sacchari strains (strains NCPPB4393, R1 and LMG 476), on X. albilineans strains (strains GPE PC73 and Xa23R1) as well as on Xanthomonas axonopodis pv. vesicatoria strain 85-10 (see Table  1  for references and GenBank accessions of available genome sequences). Alignment of concatenated nucleotide gene sequences performed with MAFFT alignment program using default parameters  [69]  resulted in a 10,490-bp long sequence (including gaps) (see alignment in Supplementary File S5). The phylogenetic core genome MLSA tree was generated using the maximum likelihood method implemented in the PhyML program version 3  [70]  with GTR as substitution model and four gamma-distributed rate categories to account for rate heterogeneity across sites.
Whole-Genome Sequences Analyses: ANI Calculation Genomic relatedness between strain MUS 060, strain GPE 39, X. albilineans strains GPE PC73 and Xa23R1, and X. sacchari strains NCPPB4393, R1 and LMG 476 was estimated using whole-genome sequencing data of each strain. Average nucleotide identity (ANI) was calculated with ANIb and ANIm software, respectively, based on BLASTN and MUMmer algorithms using the tool JSpecies and default parameters (http://www. imedea. uib. es/jspecies/ [32] ) (see ANI scores in Supplementary File S3).
Conclusions In this study, we analyzed draft genome sequences of two previously collected isolates belonging to the Xanthomonas genus: strain GPE 39 isolated from water droplets on S. officinarum leaves in Guadeloupe, and strain MUS 060 collected from P. dilatatum in Mauritius. Our comparative study also included genome sequencing data of two strains of X. albilineans and three strains belonging to X. sacchari. Comparative analyses, including ANI and MLSA analyses, revealed that GPE 39 and MUS 060 belong to a new species. Because GPE 39 and MUS 060 are close to the X. albilineans species, with which they form a phylogenetic sister clade, we hereby propose the name "X. pseudalbilineans" for this novel species. Compared to X. sacchari, X. albilineans and "X. pseudalbilineans" species have experienced genome erosion that probably occurred predominantly in the common progenitor of both species.
Acknowledgments We thank  Martial Briand  for his help in using the ANI calculation software, and  François Bonnot  for his help in R-analysis of OrthoMCL data. We are indebted to  Valérie Barbe at Genoscope  for sequencing of strains Xa23R1 and GPE 39. This work was supported by  Genoscope ,  Institut de génomique CEA/DSV, Evry, France  ( AP10/11-28  projet Xanthomonas numéro 28 ROTT). We are indebted to  Fasteris Company  for sequencing of strain MUS 060. We thank  Helen Rothnie  for English editing.
73 (true positive rate). We have also estimated the false positive rate, which is 0. 092. These parameters indicated that the dataset we have generated was sufficiently robust to be further analysed. The differences observed between the present Y1H screen and the data gathered from the literature most probably reflect the fact that the interactions between the R2R3-MYBs and their DNA targets had been assessed using various in vitro and in vivo methods  [13, 14, 17, 21, 22, 27]. This later point being highlighted by the fact that out of the 21 positive interactions that were not confirmed in this study, 14 were issued from EMSA or oligo arrays. Hierarchical clustering analysis of the 1904 tested interactions (using the EPCLUST tool;  [28] ) revealed that the cis-elements could be divided into two groups (Fig  1A ).