dataesr/scientific-paragraphs-categorization huggingface dataset:
Data sets To calculate specialization and rarity indices we used the botanical and ecological database SOPHY (France GIVD ID EU-FR-003  [7] ). This database compiles over 200,000 surveys of vascular plant species recorded in France between 1915 and 2010 in a wide variety of habitats (mostly in natural or semi-natural habitats such as forests, meadows and grasslands, but also in anthropogenic habitats such as crop fields  [7] ). The nomenclature used in the SOPHY database and in this paper follows Bock  [2]. We merged all vegetation layers and worked with presence-absence data for all species. Specialization and rarity indices were calculated only for species observed in at least 50 plots (2879 species out of a total of 5267 species in the database; 135,002 plots).
Sources of virus, insects and plants. TYLCV from Israel (GenBank X15656. 1) was maintained in tomato plants (cv. Daniella) by whitefly-mediated inoculation  20  and served as source of CP and V2. Whiteflies (B. tabaci B biotype) were reared on cotton plants grown in insect-proof cages at 26 °C, as described  26. Tomato plants at their 3-5 true leaf stage were caged with viruliferous whiteflies (about 50 insects per plant at the onset of infection) for the duration of the experiments. Whiteflies were discarded before tissue sampling. Nicotiana benthamiana plants, four weeks after sowing, were used for infiltration experiments. All plants were grown in a greenhouse kept at 24 °C (10 h, light) to 18 °C (14 h, dark).
Acknowledgments The V2:GFP construct was a gift from  Prof. Y. Gafni ,  Volcani Center ,  Bet Dagan , Israel. This research was supported by a grant from the  Israel Science foundation ISF  to R. G. and H. C. ( 1037/13 ) and by a grant from the  U. S. Agency for International Development, Middle East Research and Cooperation (MERC program ) to H. C. ( GEG-G-00-02-00003-00 , Project  M21-037 ). A. M. was rewarded with a  Short-Term Scientific Mission grant  from  COST   FA0806.
6 mm; Sigma-Aldrich) with a mobile phase of acetonitrile : methanol (85 : 15, v/v) in an isocratic system. Quantification was obtained from calibration curves using a standard solution of trans-total retinol (Sigma-Aldrich). Vitamin A concentration was expressed in μg/ml fluid milk, from the amount of lyophilized milk weighed from a known amount of fluid milk. Statistical analyses. Data for plasma lipid profile, ALAT and g-GT activities obtained on day 1 were used as covariates. Data recorded on day 31 were analyzed using the MIXED procedure of SAS (Statistical Analysis System, Version 9. 1, 2003), Data for milk yield and composition, milk FA, cholesterol, and vitamin A concentrations recorded the day before the addition of oil (day -1) were used as covariates. These data were analyzed as repeated measures using the MIXED procedure of SAS.
ACKNOWLEDGMENTS We like to acknowledge  Mariet Hefting ,  Jos Verhoeven , and  Dennis Whigham  for their help in collecting the mangrove soil samples. We also want to thank  Pieter Kleingeld  for his technical assistance with the flow-through reactors, and  Yamini Satyawali  and  Winnie Dejonghe  from the  Flemish Institute for Technological Research (VITO) in Belgium  for the analyses of total organic carbon and mean soil particle size. The study was supported by the  Center-in-Development Award  to  Utrecht University  ( KUK-C1-017-12 ) made available by the  King Abdullah University of Science and Technology (KAUST) ,  Thuwal ,  Saudi Arabia , and by the  Netherlands Organization for Scientific Research (NWO) / SRON User Support Program Planetary Science  (Project no. ALW-Geo-PL/10 ). This is publication number 2015 of the  Netherlands Institute of Ecology  and publication number 983 of the  Smithsonian Marine Station.
Study site and population Demographic data were collected for an F. eskia population in the Pyrenees (Guzet, N 42. 78528°E 1. 29806°, 1800 m above sea level). In June 2008, 100 symbiotic (S) and 100 nonsymbiotic (NS) plants were randomly selected and labeled. This sample corresponds to 80% of the population. The endophytic status of each plant was determined with Phytoscreen Tissueprint immunoblot kits (Agrinostics Ltd, Inc. , Watkinsville, GA, USA). The presence of E. festucae in plant tissues was confirmed for a subset of plants, by microscopy, as described by Hiatt et al. [25]. The endophytic fungus was identified as E. festucae by PCR, on the basis of β-tubulin sequences  [10]. The environmental conditions were manipulated by adding nutrients to the soil, for half the population. Two nutrient resource treatments were established: natural and high-resource level (F+) treatments.
Simulation of population growth and disturbance analysis For each of the six transition matrices, the asymptotic population growth rate (λ) was calculated by Monte Carlo simulation (50 time steps, 1000 trajectories), with ULM (Unified Life Model) software  [28, 29]. We used Monte Carlo simulation, to include uncertainty due to the well known strong endophyte Ã plant genotype effect in the population growth rates (see  [4] ). For model A, we performed prospective and retrospective analyses, to explore the effect on population growth rate of differences in vital rates  [30]. Prospective analyses (i. e elasticity analysis) consider the consequences of potential future changes in vital rates for population growth  [30]. The retrospective analyses (i. e. fixed-effect life table reponse experiment LTRE) were designed to quantify the contribution of each vital rate to the effect of endophytic status and resource level on population growth rate  [21, 30].
Statistical analyses, availability of code and data We used a generalized linear model with a logit link function to check for differences in model parameters between endophyte statuses and resource levels, assuming that the errors were binomially distributed. The model considered three factors as fixed effects: endophytic status, edaphic resource level and their interaction. Significance was assessed in a χ 2 analysis of deviance. Differences in mean population growth rates were analyzed in t-tests. All analyses were conducted with R software  [31]  or ULM (Unified Life Model) software  [28, 29]. The elasticity analysis was performed with ULM software. The fixed-effect life table response experiment (LTRE-a retrospective approach) was conducted with R software version 3. 1. 2 [31]  and the popbio package  [32] , using Caswell's equations.
2 It comprises physical urticaria, which can be made worse by occupational activities, and contact urticaria due to causative agents, proteins or chemicals, with an immunological or nonimmunological mechanism. 4 Because symptoms can be severe in certain circumstances, the problem of OCU needs to be addressed. However, while the causes of immunological contact urticaria are known,  [5] [6] [7]  only some of these causes have been identified as being related to workplace exposure. 4 [10] [11] [12] [13]  Data concerning OSD in French workers are very limited. 14 n France the only national statistics available come from Public Insurance Compensation. Even then, only OCU caused by latex proteins is compensated for and recorded. Furthermore, these data have certain biases: they do not take into account nonsalaried workers, and compensation criteria are based more on administrative criteria than on clinical diagnosis.
Data collection and study database Data collection from RNV3P has been described previously. 14 he experienced occupational physicians based in the 32 centres systematically complete standardized forms for each new referred patient and report all new cases of occupational diseases. Only the final diagnosis was used for data collection. 14, 15 Data included diagnosed diseases (among them OSD and OCU), exposures and occupations and/or activity sectors. All data are coded using the standardized International Classification of Diseases 10th revision (ICD-10). 15 The medical experts rated imputability, which is the evidence of association between the occupational exposure and the disease on a fourlevel scale including null, possible, probable and certain. The quality of data was optimized using computerized tools for coding and monitoring data consistency, regular quality training and centralized quality controls.
14, 15 he study database consisted of 69 779 work-related disease events recorded in the RNV3P between 2001 and 2010, with completed data on occupational exposure (substances and occupation) and the potential association between occupational exposure and disease. 14 The present analysis deals with 7146 cases of OSD (neoplasia excepted) considered as being probably or certainly associated with exposure (ICD-10 codes L00-L99) (Fig. 1 ). The RNV3P network received approval for this study from the national board enforcing data protection legislation.
Data analysis Descriptive analyses were performed on occupations, industrial activities and agents related to the OCU cases reported in RNV3P during the study period. Trend analyses were carried out when the numbers of cases were adequate (n ≥ 50) and were based on previously used methods. 14, 16, 17 Analysed data consisted of the number of new notified cases in the national database for a given year. The odds (called reporting odds) of OCU or OCU related to specific occupational exposure (namely a causal agent, an industrial sector or both) for a given year were defined by the ratio between the number of OCU cases or OCU cases associated with this exposure and the number of all other cases of OSD in this year. The reporting odds ratio (ROR)  18  for each year was calculated with reference to the year 2001 using a logistic regression model that controlled for age and sex; the dependent variable was OCU cases vs.
Furthermore, this network probably provides the only reliable statistics on OCU at a national level. One limiting factor in our study is that it is based not on the entire French occupational population, but on a specific subpopulation captured by the centres. 14, 15 In order to address this bias, we used the subgroup of all OSDs reported in our network as the reference population, with these data being supplied by the physicians who made the same clinical investigations for the diagnosis of contact dermatitis and urticaria. The study design allows measurement of the disproportionality of the occurrence of a specific OCU (case) relative to all other occurrences of all other OSDs in the network (not cases), thus enabling oversignals in the reporting database to be detected over a period of 1 year.
In conclusion, we have used data taken from the RNV3P over a 10-year period to study, for the first time, the causes of OCU in the workplace by activity sector and time frame. The significant decrease in OCU related to NRL in the HSW sector following preventive measures enforced in the middle 2000s in French hospitals would appear to endorse the efficacy of such measures. As OCU related to other agents has been shown to be stable, we suggest that other occupational groups and sectors could also benefit from preventive measures.
Acknowledgements AS and PBS were the recipients of predoctoral ( Formación de Personal Investigador) and postdoctoral (Marie Curie ) contracts, respectively. We thank  Martin Crespi  for help with in situ RNA hybridization and  Simon Avery  for sharing the yeast mutant and for helpful advice. This work was supported by  Ministerio de Economía y Competitividad-Fondo Europeo de Desarrollo Regional  ( AGL2011-24524  and  AGL2014-53717-R ). The  UMR1136  is supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  'Investissements d'Avenir' programme  ( ANR-11-LABX-0002-01 ,  Lab of Excellence ARBRE ). MM and KJD acknowledge support within  SPP1710. The proteomic analysis was performed in the  CSIC/UAB Proteomics Facility of IIBB-CSIC  that belongs to ProteoRed,  PRB2-ISCIII , supported by grant  PT13/0001.
EAN1pec genome sequence (GenBank accession no. CP000820) was exploited as an "untrusted reference"  (10). The genome sequence has been annotated using the RAST annotation suite  (11). This permitted us to identify loci involved in bacteriaplant symbioses, such as those for nitrogen fixation, uptake hydrogenases, hopanoid biosynthesis, and iron-sulfur cluster biosynthesis that are upregulated in symbiotic Frankia alni  (8)  as well as several genes that are specific to Frankia R43  (12). Nucleotide sequence accession number. The draft genome sequence of Frankia R43 was deposited at NCBI GenBank under the accession no. LFCW00000000.
ACKNOWLEDGMENTS A. Sellstedt  and  K. H. Richau  are supported by the  C. Tryggers Foundation, Sweden. P. P. , P. F. , P. N. , A. B. , and  A. Sorokin  are supported by the  French ANR grants (projects PathoBactEvol and BugsInACell). A. L. is supported by the  Russian Science Foundation  (grant no. 14-50-00069 ).
These accessions were collected from a large number of localities within a large geographical sampling area that is representative of the distribution area of the genus Hevea. The collection sites are illustrated in Fig  1  The detailed data on the accessions are available in S1 Table. Notably, 52 accessions were putatively analyzed twice (i. e. , the accessions appeared under the same name but originated from different collection sites). These repeated accessions will provide further insight into the reliability of the applied methods of genetic analysis and the confidence that can be achieved when conserving the name of an accession across various ex situ collections.
Characterization of genetic diversity Analysis of population genetic parameters. A descriptive statistical analysis for all of the SSR loci and the number of alleles per locus (Na), information index (I), observed heterozygosity (H O ), expected heterozygosity (H E ), fixation index (F) and private alleles (Pa) were calculated using GenAlEx v. 6. 5  [25]. The confidence intervals of the different parameters were calculated using 1,000 bootstrap iterations. The analysis of molecular variance (AMOVA) and calculation of F ST and Nei's G ST among the groups were performed with GenAlEx v. 6. 501  [25]  to detect the molecular genetic variances within and among the accessions, considering both the collection sites (geographical regions) and the groups suggested by our analysis with the program STRUCTURE.
The GenAlEx software was also used to identify private and rare alleles (frequency < 0. 05). Genetic structure analysis. Different statistical procedures were used to describe the genetic diversity of the collected germplasm, including (i) a model-based method for inferring population structure by clustering genotypes; (ii) a distance-based model using a dissimilarity matrix; and (iii) a factorial analysis through principal coordinates analysis (PCoA). The model-based approach consisted of a Bayesian analysis implemented under the STRUCTURE program version 2. 3. 4  [26, 27]. All 1,117 of the genotyped accessions were analyzed using an admixture model with independent allele frequencies in each group. The number of groups (K) to which the genotypes were assigned was systematically tested from 1 to 10; for each value of K, 20 independent iterations of the Bayesian model-based analysis were performed.
Analyses of secondary structures were performed (with K = 1-10) using only the genotypes corresponding to the clustered group to detect sub-structuring. The distance-based model was implemented in the DARwin 5. 0. 158 software  [31]. A dissimilarity matrix was computed with a simple-matching index, and a neighbor-joining tree was constructed. A factorial analysis (PCoA) was performed using GenAlEx  [25]. These latter methods were used simultaneously to better investigate the precise structure of our sample.
Data homogenization As explained in the previous section, the allelic sizes of the PCR products were estimated using the following two technologies: LI-COR technology (electrophoresis in polyacrylamide gels) for 353 accessions and ABI3500 (capillary electrophoresis) for the remaining 764 accessions. Although both technologies are accurate and reliable, deviations may exist between the data obtained from these two sources due to the use of different calibration curves. The analysis of common control genotypes using both technologies allowed us to standardize the sizes of the different allelic products for each microsatellite marker. Moreover, the presence of 52 pairs of accessions among the analyzed samples identified under the same name and analyzed with the two technologies helped us to confirm the goodness of data homogeneity.
However, the majority of these collections are composed of accessions from the 1981 IRRDB survey  [47]. None of these accessions contain as much diversity as described in the present study for the accessions collected during the last extensive survey performed in 1995 in the Brazilian states of Pará and Amazonas. The present study addressed this topic by providing a molecular database that should facilitate the management of the Hevea germplasm. Moreover, we identified a large number of private alleles and high genetic variability in the accessions from the 1995 germplasm. Although the planted and recently domesticated populations exhibited greater genetic diversity, the wild populations have preserved the most private and rare alleles, causing these populations to be the most important reservoirs of genetic variation.
The authors gratefully acknowledge the  Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP)  ( 2007/50392-1; 2012/50491-8 ) for financial support and scholarships to CCM ( 2011/ 50188-0 ),  CCS  ( 2009/52975-0 ), and  LMS  ( 2012/ 05473-1 ), the  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)  for financial support ( 478701/2012-8 ;  402954/2012-2 ) and research fellowships to APS and  PSG , and the H. from Amazonas was observed. facilitate the management of the  Hevea germplasm  and its use for subsequent genetic and genomic breeding. Coordenação de Aperfeiçoamento do Pessoal de Nível Superior (CAPES)  for financial support ( Computational Biology Program  and  CAPES-Agropolis Program ) and a graduate scholarship to AROC.
Primer pairs were developed to quantify expression levels of TaNRT1 (GenBank AY587264), TaNRT2. 1 (GenBank AF332214. 1), TaGS2 (GenBank DQ124212. 1), TaNR, TaNiR, TaFd-GOGAT and TaNADH-GOGAT (whose partial sequence coming from Boisson et al. [44] ) (S2 Table ). All couples developed were generic and, thus, amplified three homeologous copies. The specificity of the primer pairs and their efficiency were validated between 85 and 100%. The quantitative real-time PCR experiment (qPCR) was carried out on a LightCycler 480 system (Roche, Indianapolis, Indiana) with the LightCycler 480 SYBR Green 1 Master Kit. The qPCR program involved pre-incubation for 10 min at 95°C, followed by 45 cycles of amplification, each consisting of denaturation for 10 s at 95°C, followed by annealing for 15 s at 60°C and finishing with elongation at 72°C for 15 s.
EV type assignment and phylogenetic analysis The complete capsid gene VP1 sequence obtained in this study was compared to a database of complete sequences of most serotypes available on GenBank, in order to determine whether this sequence was genetically related to a known EV serotype. Multiple alignments were performed using the ClustalW algorithm and phylogenetic trees were constructed by the neighbor-joining method using the Kimura two-parameter model  [23] , with 10,000 generated trees based on the MEGA program (version 5. 2. 2)  [24].
Sequencing was performed with Illumina Hi-seq 2000 sequencer (Illumina) as recommended by the manufacturer. Bioinformatic and recombination event analyses. All reads were filtered according to quality (Phred score >20). Each viral read was selected using viral database and only the region that matched viral genome was considered. In order to obtain the full-length of viral genome, all reads were initially assembled to contigs with ABYSS software  [26]  with different values of k, and contigs were then assembled into a 'super assembly' with the CAP3 program  [27]. To look at potential recombination events, similarity plot and bootscanning analysis were conducted using Simplot V3. 5. 1 software  [28]. Similarity plot was done using the Kimura substitution model  [23]  and the bootscanning analysis was carried out using the neighbor-joining method  [29]  with a sliding window of 400 nt moving in steps of 20 nt.
Molecular detection and characterization of EV The goal of this work was to identify the pathogen responsible for AFP in a sick chimpanzee (IJC04). Since enteroviruses are often responsible for AFP in humans  [31]  and since an outbreak due to poliovirus occurred a year before in the human population in RC  [19] , 50 kilometers from the site where AFP was registered in a chimpanzee, we decided to first screen for the poliovirus. A real-time RT-PCR was positive for EV. Then, a nested RT-PCR allowed the acquisition of the VP1 sequence. This sequence was compared to a database of sequences containing almost all EV serotypes available in GenBank confirming that this chimpanzee was infected with an EV. Phylogenetic analysis of the complete VP1 sequences of EV species A-D showed that IJC04 isolate was closely related to the Enterovirus C species (EV-C).
EV-C99 full genome analysis Nearly complete genome was successfully assembled, with 6,648 nucleotides obtained. Despite repetitive attempts, 5'UTR (749 nt) and 3'UTR (72 nt) were not obtained (Table  1 ). The ORF (Open Reading Frame) encodes for a polyprotein of 2,210 amino acids, and is presumably cleaved in three polyproteins P1 (VP1-VP4, 883 amino acids), P2 (2A-2C, 574 amino acids) and P3 (3A-3D, 753 amino acids) (Table  1 ). Similarity plot analysis was used to evaluate nucleotide distance between IJC04, the genetically closest EV-C99 BAN00 and BAN01 strains over the genome (Fig  2 ). In the P1 and P2 coding regions IJC04 most similar to EV-C99 BAN00 (EF015008) and BAN01 (EF015009). In the P3 there was no single enterovirus sequence clearly most similar to IJC04 (including other Genbank sequences, data not shown).
Design and animals Data were collected in 2010 in three French central test stations (Le Rheu, Ille-et-Vilaine; Argentré, Mayenne; Mauron, Morbihan) on castrated males from Large White dam (LWD), Large White sire (LWS) and French Landrace dam (LR) breeds. Data were obtained in accordance with national regulations of humane care and use of animals in agriculture. The data collection has been described in  Saintilan et al. (2013). In brief, herdbook participants supplied the central test stations with 8 to 12 piglets of similar weight and age, with an objective of two piglets per litter. Rarely, 13 or 14 piglets were penned together. Animals were raised from 35 kg ± 2 (BW 1 ) to 107 ± 7 kg (BW 2 ) in pens of 12 animals equipped with single-place electronic feeders (Acema 48 in Argentré and Acema 64 in Le Rheu and Mauron) (Acemo, Pontivy).
Feed efficiency groups Groups of animals tested in 2010 were defined within breeds based either on FCR corrected with a linear model (proc GLM, SAS, 2010) including the fixed effects of the contemporary group (eight levels) and the number of pigs in the pen when the first pig ended the test (three levels), or on RFI. The 25% best animals using the RFI criterion (lowest values) were included in a RFI -(FCR -, respectively) group (89 animals), the 25% worst animals (highest values) were included in a RFI + (FCR + , respectively) group (89 animals), the remaining 50% were in a RFI0 (FCR0, respectively) group (178 animals). Individual FI and growth curves modeling, digestible lysine requirements Daily FI was available for each test day between BW 1 and BW 2. Simultaneous modelling of FI (expressed on an NE basis) and growth was carried out for each pig individually Genetics of pig feed efficiency and growth curves using the InraPorc ® software as described by  Vautier et al.