dataesr/scientific-paragraphs-categorization huggingface dataset:
(a) for the localization result. The current video frame and the closest key frame are shown in Figure 10. The localization error can be explained either by the inadequacy of the visual database in some places along the travelled path or by the occultations of nearby vehicles and the difficulty in matching points on trees which are in front of the building façades. The detection of such a failure is as follows: a. It has been experimentally found that at least 30 matched points are necessary to give an admissible result;b. The succession of the estimates of the poses must be compatible with the kinematical model (3), which can be tested with a simple Mahalanobis test; Figure9(b) illustrates another problem tied to the convergence of the optimizations involved in the localization process. In this part of the trajectory, it has been found that the localization algorithm takes too much time in processing one image.
2. 2 (a) for the localization result. The current video frame and the closest key frame are shown in Figure 10. The localization error can be explained either by the inadequacy of the visual database in some places along the travelled path or by the occultations of nearby vehicles and the difficulty in matching points on trees which are in front of the building façades. The detection of such a failure is as follows: a. It has been experimentally found that at least 30 matched points are necessary to give an admissible result;b. The succession of the estimates of the poses must be compatible with the kinematical model (3), which can be tested with a simple Mahalanobis test; Figure9(b) illustrates another problem tied to the convergence of the optimizations involved in the localization process.
All three regions share a common characteristic in presenting a significant amount of cereal crops surrounded by local landscape contexts with varying degrees of agricultural intensification. All fields were conventionally managed, with insecticides being sprayed once in May 2011 and seeds treated with a fungicide as a measure of plant disease control. Field data were collected in May and June, when both parasitoid and aphid host populations are well-established in cereal fields in those regions and secondary parasitoids (hyperparasitoids) are found at very low frequencies. In addition, a large proportion of the aphid population in cereal fields in this period are the result of aphid population growth, while during earlier months in the year the proportion of wing aphids is high, indicating that a larger part of the population is the result of recent offfield migration.
Data analysis For the analyses of parasitoid communities, relative abundance data were considered. Dissimilarity of the parasitoid communities between samples (b-diversity) was quantified using a metric based on the abundance of each parasitoid species: the Bray-Curtis distance. Bray-Curtis dissimilarities between all pairwise combinations of samples were summarized as a matrix. To ordinate the Bray-Curtis dissimilarity matrix, we v www. esajournals. org used a non-metric multidimensional scaling (nMDS), a nonparametric ordination-based method using an iterative algorithm that takes the multidimensional data of the dissimilarity matrix and presents it in minimal dimensional space. The result of nMDS ordination is a map where the position of each sample is determined by its distance from all other points in the analysis.
This method reduces ecological community data complexity and identifies meaningful relationships amongst communities. By using the matrix of Bray-Curtis dissimilarities between all pairwise combinations of parasitoid samples, an ANOVA was performed to test the effect of the geographical scale (within vs between regions) on the parasitoid community dissimilarities for each sampling year. The 'vegan' package was used to calculate Bray-Curtis dissimilarities and to perform the nMDS. For each region and each year, the centroid of each monitored field was calculated using the GIS software Quantum GIS, v. 1. 8. 0. A matrix of linear distances between centroids was then calculated. In order to assess the occurrence of spatial autocorrelations between fields, spline correlograms were performed using the geographical coordinates of those centroids and the relative abundance of each species of parasitoids.
Therefore, the parasitoids monitored considered as a whole exploited M. dirhodum at a significantly higher frequency. The aphid M. dirhodum has been considered a ''high cost'' host compared to the smaller S. avenae for the parasitoid Monoctonus paulensis Ashmead, due to its higher likelihood of behavioral defences upon facing the parasitoid, escaping or causing injury to the ovipositing female  (Chau and Mackauer 2001). On the other hand, M. dirhodum was reported to represent a higher nutritional value for the generalist linyphiid spider Erigone atra Blackwall (Bilde and Toft v www. esajournals. org 2001), thus potentially consisting of a ''high risk, high reward'' type of host. One potential explanation for the disparity of frequency of M. dirhodum among aphid mummies and living aphids is a general parasitoid exploitation preference, but this hypothesis cannot be confirmed based on field data only.
ACKNOWLEDGMENTS This study was funded by the  ANR   Landscaphid program  ( French National Research Agency ,  ANR-09-STRA-05 ) and by '' Region Bretagne ''. All field and laboratory work conducted in this study comply with French legal code requirements. We are grateful to  Valerie Briand ,  Christoph Nicolai ,  Delphine Eoche-Bosy ,  Simon Chicher ,  Cecile Gerardin, Helene Deraison, Helene Mahe, Jerôme Yvernault ,  Lucie Raymond ,  Ludmilla Martin  and  Virginie Guyot  for the technical support provided. We would like to thank  Jacques Brodeur  for his comments and advice on previous versions of the manuscript.
To generate the most diverse phylogenetic dataset for the flaviviruses to date, we determined the genomic sequences and phylogenetic relationships of 14 flaviviruses, of which 10 are primarily associated with Culex spp. mosquitoes. We analyze these data, in conjunction with a comprehensive collection of flavivirus genomes, to characterize flavivirus evolutionary and biogeographic history in unprecedented detail and breadth. Based on the presumed introduction of yellow fever virus into the Americas via the transatlantic slave trade, we extrapolated a timescale for a relevant subset of flaviviruses whose evolutionary history, shows that different Culex-spp. associated flaviviruses have been introduced from the Old World to the New World on at least five separate occasions, with 2 different sets of factors likely to have contributed to the dispersal of the different viruses.
These relationships were then corroborated and extended by the inclusion of the mosquito-borne and non-vectored flaviviruses  [1]  but analyses were still based on a limited number of recognised flaviviruses and only partial gene sequence data (44 species based on the envelope gene). Subsequent analyses  [3, 8, 10, 11] , using more extensive datasets improved our understanding of these virus-vector-host relationships in the context of their evolution and dispersal  [2, 12]. Additional flaviviruses including Lammi virus  [13] , N'goye virus  [14] , Alkhumra haemorrhagic fever virus  [15] , Usutu virus  [16] , New Mapoon virus  [17] , and Marisma mosquito virus  [18]  have subsequently been discovered. Together with the increasing numbers of documented species and strains of ISFV, that do not appear to be arboviruses  [19] [20] [21] [22] [23] , these discoveries have shed new light on our perception of the evolution and taxonomy of this complex genus.
Recently, another highly divergent lineage, Mogiana tick virus [MGTV], was isolated in Brazil  [24]. Whilst early interpretations of the evolutionary and taxonomic relationships within the genus Flavivirus have proved informative, they were restricted to some extent by the lack of complete genomic sequence data, and robust analytical methods. As a result, it has not yet proven possible to resolve the issue that phylogenies based on complete genomes and, separately, the NS3 gene show different branching characteristics from those based on the NS5 gene, despite a lack of evidence for recombination within the respective data sets  [10, 11, 25]. In this manuscript we report the genomic sequences of fourteen flaviviruses, for which previously only limited data were available. Based on these more comprehensive datasets, we attempt to resolve hitherto unanswered questions relating to the flaviviruses, and explore frame shift characteristics.
Sequence analysis Sequences were refined using Sequencher 4. 8 (Gene Codes, Ann Arbor, MI) and combined with other flavivirus sequences available in the Genbank database, to obtain a dataset including a representative of at least one sequence for each species available as full polyprotein ORF for the genus Flavivirus. Genbank accession numbers of sequences used for the analysis are noted after each virus abbreviation on Fig. 1  (tree). Complete polyprotein ORF amino acid alignments were generated using both Clustal W2  [32, 33]  and MUSCLE  [34]  available at the EMBL server (http://www. ebi. ac. uk/Tools/) and refined manually, for comparison. Nucleotide alignments were then deduced using amino acid (AA) alignments as a template using the TranAlign software available via the EMBOSS server (http://emboss.
Bayesian inference of a time-measured evolutionary history A second data set of polyprotein ORF flaviviruses was compiled by excluding the highly divergent sequences of all ISFVs and including additional sequences of YFV that were isolated from either the New World or the Old World. An amino acid alignment was produced using Clustal W2 and regions of ambiguous alignment were removed using the GBlocks algorithm with standard parameters. A time-measured evolutionary history was inferred using MCMC analysis implemented in BEAST  [40]. Based on model testing using Prottest, we used the LG substitution model  [41]  with gamma distributed rate variation among sites in conjunction with a relaxed uncorrelated lognormal molecular clock model  [42]  and a Bayesian skygrid tree-prior  [43]. Time-calibration of the evolutionary history was based on the recognised slave-trade introduction of YFV to Brazil  [12, 44, 45].
Biogeographical data Available ecological data, geographical dispersal patterns, host association and pathogenicity for all mosquito-borne flaviviruses were retrieved from the CRORA viral database (Centre collaborateur OMS de Reference et de Recherche sur les Arbovirus, Institut Pasteur de Dakar, Africa http://www. pasteur. fr/recherche/banques/CRORA/) and the International Catalogue of Arboviruses  [48]. Three viruses tentatively assigned to the genus Flavivirus, TABV  [11] , Ngoye virus  [14]  and Mogiana tick  [24]  virus were not included in analyses because they are genetically too divergent to be incorporated without ambiguities using currently-available methods  [10].
MBFVs Using partial genome sequence-based phylogenies, the MBFVs were previously divided into 2 major groups reflecting their vector associations (i. e. , Aedes-and Culex-associated groups), the principal vertebrate host and associated diseases  [1]. Our analysis, based on complete ORF sequence data, confirmed this division of MBFVs into 2 major epidemiologically distinct vector groups, i. e. , those primarily associated either with Culex spp. or Aedes spp mosquitoes. However, additional ISFV-"like" MBFVs became available for phylogenetic analysis. Lammi virus [LAMV] was isolated from A. cinereus mosquitoes in Finland  [13] , Ilomantsie virus [ILOV] was isolated from Ochlerotatus mosquitoes in Finland (Huhtamo et al. , submitted paper), Marisma mosquito virus [MMV] from O. caspius in Spain  [18] , Donggang virus [DGV] from Aedes mosquitoes in China (Unpublished data, GenBank acc.
Number: NC_016997), Chaoyang virus [CHAOV] from A. vexans nipponii in Korea  [56]  and in China (Article published in Chinese, GenBank acc. Number: FJ883471), Nounané virus [NOUV] from Uranotaenia spp. mosquitoes in Ivory Coast  [57]  and Barkedji virus [BJV] from Culex perexiguus in Israel  [58]  and Senegal (Unpublished data, GenBank acc. Number: EU078325). The mosquito vector was originally unknown for CHAOV (China) and BJV (Senegal) but these viruses have also been recently described in other locations  [58]. Thus, based on this more recent evidence the probable vectors for CHAOV and BJV are Aedes and Culex species respectively. These viruses form two distinct groups (Fig. 1 ) that diverge from the two previously recognised groups Aedes spp. -associated and Culex spp. -associated MBFV.
The sequence presented in our analysis is an isolate from 1959, included in the clade of "old isolates" (Fig. 1 ) and is 6% divergent at the nucleotide level from all other ITV and BAGV sequences. TMUV, STWV and DEDSV TMUV, STWV and the recently described duck egg drop syndrome virus [DEDSV]  [51]  and layer flavivirus (unpublished data, Genbank acc nb. : JF926699) are also closely related southern Asian strains, mainly isolated in Thailand, China and Korea, but they are phylogenetically distinct from ITV and BAGV  [71] [72] [73]. They also cause severe disease pathologies in domestic birds (chicken, duck, etc. ) but have not been associated with human disease. NTAV NTAV was originally isolated in Uganda. During the preparation of this manuscript, the sequence of another strain of Ntaya virus was reported  [74].
Many more ISFV sequences are now available, and the overlapping ORF is conserved in all except for the cell culture adapted original isolate of CFAV (GenBank acc. M91671)  [23]. The overlapping ORF ranges from 270 to 293 codons in CxFV, QBV, PCV, NAKV and Cx theileri flavivirus, and 253 to 257 codons in KRV, CFAV, HANKV, AEFV and Ochlerotatus caspius flavivirus. The frameshift site generally appears to be G_GAU_UUY (Y = U or C), with notable exceptions appearing to be G_UUU_UUU in NAKV and A_AAU_UUU_UUC (potential tandem shift sites) in PCV. In the CHAOV-LAMV-DGV-ILOV clade enhanced synonymous site conservation is apparent in the region encoding NS2B. This is associated with a conserved G_GAU_UUU slippery heptanucleotide and a 3'-adjacent predicted stem-loop structure that stimulates-1 PRF in dual reporter assays and whose functionality is supported by compensatory substitutions (i.
Funding: AEF is supported by  Wellcome Trust  grant  088789. This work was supported by  Aix-Marseille University, IRD ,  EHESP , the project  European Virus Archive  (under  EU  grant agreement  n°228292 ), the  European Union Seventh Framework Programmeprojects SILVER  and  PREDEMICS , under grant agreements  260644  and 278433 respectively. This study was also partially funded by  EU  grant  FP7-261504  EDENext and is catalogued by the EDENext Steering Committee as EDENext299 (http://www. edenext. eu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
We report for the first time the occurrence of Obama marmorata in the Iberian Peninsula as an introduced species from the Neotropical Region. The species is also reported for the first time in Argentina. The identification was made on the basis of morphological evidence. The divergence levels of a fragment of the mitochondrial cytochrome c oxidase I gene from Argentinean and Iberian samples were studied. The morphology of samples from the two regions was the same and matched the original description of the species. A DNA barcoding matrix was constructed using new sequences from O. marmorata and sequences of related species taken from GenBank. Among the Geoplanidae, interspecific divergence ranged between 3. 3 and 14. 4%, while intraspecific divergence percentages were 0-1. 2%, signalling the presence of a DNA barcoding gap.
Amplification products (324 bp) were purified using ExoSAP-IT (Affymetrix, OH) before sequencing both strands on an ABI Prism 3730. DNA sequence data were edited and aligned with Sequencher (Gene Codes Corporation) (Sequencher ® 5. 2 sequence analysis software, Gene Codes Corporation, Ann Arbor, MI, USA: http://www. genecodes. com). The sequences of the mitochondrial COI gene reported in this paper have been deposited in the EMBL/GenBank data libraries under accession numbers KM053208-KM053227.
Phylogenetic analysis Phylogenetic analysis included the newly determined nucleotide COI sequences of the 20 individuals collected both in their likely native (Argentina, South America) and introduced (Spain, Europe) distribution ranges, as well as additional sequences of several representatives of the genus Geoplana (sensu lato, recently revised and subdivided into more genera by  Carbayo et al. (2013) , whose nomenclature is adopted here), available from GenBank. Five species of the subfamily Rhynchodeminae, the sister group of Geoplaninae  (Álvarez-Presas et al. 2008 , Riutort et al. 2012 , Carbayo et al. 2013) , were selected as outgroups for the phylogenetic analyses. jModelTest 2. 1. 4 (Darriba et al. 2012 ) was used to estimate the evolutionary model that best fit the nucleotide dataset, which according to the Akaike Information Criterion (AIC: Akaike 1974) was TPM3uf+I+G.
The final alignment, including 69 terminal specimens, was subjected to the coalescent-based gene tree reconstruction method implemented in BEAST 1. 8. 0  (Rambaut and Drummond 2007)  to estimate phylogenetic relationships among taxa in our dataset. The model of substitution used in this analysis was HKY+I+G, which was the best model of those directly available in BEAUti (ranked third in jModelltest analyses under the AIC). The birth-death process was chosen as the coalescent prior and a strict clock was assumed. The analysis was run for 100 million generations, sampling every 10 000 generations. Results were visualised in Tracer 1. 5  (Rambaut and Drummond 2007)  to check for convergence and adequate effective sample sizes of parameters in the model. Uncorrected (p-distance) genetic distances between and within species (excluding the outgroup taxa) were calculated with MEGA 6  (Tamura et al.
2013). The specific labels employed here were defined according to the taxonomic labels defined by  Carbayo et al. (2013). Four of the species (Matuxia tuxaua, Geoplana vaginuloides, Obama carinata and Imbira marcusi) showed more similar intraspecific distances than those found at an interspecific level between other species of the dataset. Therefore, each haplotype of these four species was considered a different Parque da Previdência, São Paulo, SP (Brazil) KC608247 Imbira marcusi  (Carbayo et al. , 2013 ) (OTU1) São Sebastião, SP (Brazil) KC608241 Imbira marcusi  (Carbayo et al. , 2013) (OTU2) Parque Nacional Serra da Bocaina, SP (Brazil) KC608291 Matuxia matuta  (Froehlich, 1955)  Parque Estadual do Desengano, RJ (Brazil) KC608277 Matuxia tuxaua  (Froehlich, 1955) (OTU1) Parque Nacional da Serra dos Órgãos, RJ (Brazil) KC608253 Matuxia tuxaua  (Froehlich, 1955) (OTU2) Parque Estadual Serra da Cantareira, SP (Brazil) KC608302 Notogynaphallia goetschi  (Riester, 1938)  Parque Estadual Serra da Cantareira, SP (Brazil) KC608294 Obama burmeisteri  (Schultze & Müller, 1857)  Parque Ecológico do Tietê, São Paulo, SP (Brazil) KC608234 Obama burmeisteri  (Schultze & Müller, 1857)  Parque Estadual Serra da Cantareira, SP (Brazil) KC608297 Obama carinata  (Riester, 1938)  (OTU 1) Parque Estadual Intervales, SP (Brazil) KC608304 Obama carinata  (Riester, 1938) (OTU 2) Parque Estadual Intervales, SP (Brazil) KC608307 Obama josefi  (Carbayo & Leal-Zanchet, 2001)  Floresta Nacional de São Francisco de Paula, RS (Brazil).
Molecular data and phylogenetic analysis Uncorrected genetic distances across the entire dataset ranged from 0 to 1. 2% (average 0. 4%) at an intraspecific level, while divergences across species ranged between 3. 3 and 14. 4% (average 9. 4%) (Fig. 3 ). Therefore, there is a barcoding gap between 1. 2 and 3. 3% levels of divergence (Fig. 3 ). However, the proximity between the higher intraspecific and the lower interspecific values indicate that the usage of DNA barcoding in geoplanids should be undertaken with caution because recent  speciation events may have occurred. Some species, represented by more than one sequence, included highly divergent branches, with p-distance values well above mean intraspecific values reported for other species: Matuxia tuxaua  (Froehlich, 1955)  (8. 3%), Geoplana vaginuloides (Darwin, 1844) (7.
g. Ward et al. 2009; Fernández-Álvarez and Machordom 2013). Extensive molecular databases are necessary to successfully apply barcoding methods to identify specimens. Land planarians are under-represented, but recently some progress has been made  (Álvarez-Presas et al. 2012)  and our results, in accordance with the assertions of Álvarez-Presas and  Riutort (2014) , suggest that this could be a fruitful approach, especially if the studies provide a link between morphological and molecular datasets in an integrative approach to taxonomy. O. marmorata had previously been reported only in Brazil  (Schultze and Müller 1857; Froehlich 1959). As Geoplaninae are Neotropical taxa, the presence of O. marmorata in Argentina may be due to an extensive natural distribution of this species. However, the presence of O.
Acknowledgements We are deeply in debt to  Annie Machordom  for her kindness and help with molecular analyses. We thank  I. Martínez-Solano  for the help offered with the phylogenetic analyses and for comments on the manuscript. We thank  Hugo Merlo Álvarez  for collecting some Argentinean specimens. Thanks are due to  Ángel Manuel Fernández Valdés  for collecting most of the Iberian samples. We appreciate the comments of two anonymous referees, which have highly improved the quality of the manuscript. CG is currently a ' Ramón y Cajal ' postdoctoral fellow supported by the  Spanish MICINN  and the  UAM  and funded by project  CGL2011-29916  (MICINN). LN, FB and CD are financed by Project  N11/728  ( FCNyM-UNLP ) and  PIP 112-201201-00635 CO (CONICET ). We are very grateful to the staff of the greenhouses that collaborated with us.
Individual Systems' Thresholds First of all, a client requests the annotations for a text from each linker's web-service, using the services' default settings except for the confidence threshold, which is configured in our system. Annotations whose confidence is below a threshold are eliminated. All of the linkers used, except Babelfy, output confidence scores for their annotations. Cornolti et al. , (2013)  reported optimal confidence-score thresholds for all our linkers (except Babelfy). Using Cornolti's BAT Framework, we verified that the thresholds are still valid. 6 We adopted the weak-annotation match thresholds for the IITB dataset, since we consider the IITB corpus close to the task's data, in text-length and topical variety. Our thresholds were 0. 102 for Tagme, 0. 023 for Spotlight, and 0.
The reference corpora on which we pre-ranked the annotators are AIDA/CoNLL Test B  (Hoffart et al. , 2011) , and IITB  (Kulkarni et al. , 2009). These corpora are very different to each other, in terms of character length, topical variety, and regarding whether they annotate common-noun mentions or not. Moreover, some EL systems obtain opposite results when evaluated on AIDA/CoNLL B vs. IITB, as tests by  Cornolti et al. (2013)  and on the GERBIL platform 7  have shown. The heuristic's first criterion is the types of annotations needed: If the user needs annotations for common-noun mentions, the IITB ranking is used, since IITB is the only one in our reference-datasets that was annotated for such mentions. If the user does not need common noun annotations, our heuristic compares the user's corpus with our two reference corpora in terms of character length and of a measure of lexical cohesion.