dataesr/scientific-paragraphs-categorization huggingface dataset:
norrisi) from Chile, Argentina and the Falkland Islands provided by Carrasco  [119]  and Blake  [48] , and records of S. bombyx (here referred either to S. bombyx or S. cf. convexus) from Spain provided by Meißner  [8]. To link some sequences used in the molecular analysis in the present study with the corresponding data, unique numbers from the first author's database (VIR) are given to samples in the S1 Table (at the end of each record). These numbers without letters precede specific names on the phylogenetic trees (Figs  1 2 3 ). When no coordinates were provided for sampling sites in old studies, they were collected from the Google Earth map according to the original descriptions of the locations. Sampling locations of Spiophanes spp. noted in S1 Table are plotted on maps using the QGIS 3.
8. 0 Posterior probabilities are shown on the branches. Species names are followed by the names of the collecting locations. Information about numbers with letters following specific names are given in Table  1. The numbers without letters following specific names are unique numbers from the VIR database linking the individuals on the tree with the sampling data in the S1 Table. https://doi. org/10. 1371/journal. pone. 0234238. g001 software and the geodata provided by the OpenStreetMap Project (https://osmdata. openstreetmap. de). Formalin-fixed specimens of S. uschakowi were critical-point dried in carbon dioxide, coated with gold palladium, and viewed with a LEO 440 scanning electron microscope (SEM) equipped with a digital camera at the National Museum of Natural History, Smithsonian Institution, Washington, DC, USA.
Formalin-fixed specimens of Spiophanes spp. were stained with an alcohol solution of methyl green (MG), examined complete or dissected to observe internal structures, and photographed using microscopes equipped with digital cameras. Final plates were prepared using CorelDRAW12017 software. [111]. (B) Majority rule consensus tree of the Bayesian inference analysis of the combined COI (534 bp), 16S (244 bp), 18S (1656 bp), 28S (287 bp), and Histone 3 (297 bp) sequences (3018 bp in total) of Spiophanes spp. rooted with sequences of Trochochaeta multisetosa. Posterior probabilities are shown on the branches. Species names are followed by the names of the collecting locations. Information about numbers with letters following specific names are given in Table  1. The numbers without letters following specific names are unique numbers from the VIR database linking the individuals on the tree with the sampling data in the S1.
Purified PCR products were bidirectionally sequenced on an ABI Prism 3100 Genetic Analyzer (Applied Biosystems) using the BigDye Terminator v 3. 1 Cycle Sequencing Kit (Applied Biosystems) and the same primers as for PCR. The consensus sequence of each gene region of each specimen was assembled from the two complementary sequences using SeqScape v 2. 5 (Applied Biosystems). GenBank accession numbers of the obtained sequences are given in Table  1.
Phylogenetic analysis We aligned DNA sequences using the MAFFT v7. 2 software with the default settings (automatically chosen algorithms)  [127, 128]. Ambiguous positions and gaps were excluded from subsequent analysis using GBlocks  [129]. The nucleotide datasets were combined using the supermatrix approach. The number of variable and parsimony informative sites in the datasets, the uncorrected values of sequence divergence (pairwise distances, p) both within and between groups were calculated in MEGA 5. 1. We used MrBayes 3. 2. 6 via the CIPRES web portal  [130]  for the Bayesian analysis of 10,000,000 generations, four parallel chains and sample frequencies set to 500, in two separate runs. Based on the convergence of likelihood scores, 25% sampled trees were discarded as burn-in. The analysis of the combined data set was partitioned and the models of substitution were determined using Akaike Information Criterion (AIC) in Modeltest 3.
7  [131] : GTR+I+G for 16S, 28S and Histone 3, TVM+G for 18S, and HKY+I+G for COI. We also included in the analysis sequences of Spiophanes spp. obtained by Meißner & Blank  [111] , Mincks et al. [122] , Meißner & Go ¨tting  [123] , Aylagas et al. [121] , and some sequences from GenBank and BOLD (Table  1 ). We performed two analyses: the COI analysis to compare our data with those reported by previous authors, and a concatenated analysis using five genes to get better resolution of relationships among Spiophanes species. The fivegenes analysis was based on sequence data of the mitochondrial COI, 16S rDNA, nuclear 18S, 28S rDNA, and Histone 3 most of which were obtained in the present study. In this analysis, we included COI sequences obtained by other authors if they comprised more than 500 bp, and 18S sequences if they comprised more than 1600 bp.
Molecular analysis COI analysis and haplotype network. The alignment of COI sequences obtained in the present study and those from GenBank and BOLD comprised 267 bp with 106 (39. 7%) variable sites, of which 93 (34. 8%) sites were parsimony informative. The Bayesian analysis resulted in a partially resolved consensus tree (Fig  1B ). The analysis revealed two sister groups among specimens from northern Europe identified by morphology as S. bombyx: one from the North and the Norwegian seas (referred to as S. cf. bombyx), and another from Brittany, northern France, and the Bay of Biscay, northern Spain (referred to as S. cf. convexus). The p-distances among individuals of these groups ranged from 12. 73% to 14. 98%. The ingroup p-distance values ranged from 0. 00% to 1. 5% and from 0. 75% to 1.
00%) of our sequence of S. berkeleyorum from Southern California and short fragments of 18S rDNA (490 bp) of S. berkeleyorum from Northern California obtained by Meissner & Blank  [111]  (Fig 2A ). Divergence time estimation. The alignment of COI sequences obtained in the present study and those from GenBank and BOLD comprised 534 bp with 170 (31. 8%) variable sites, of which 160 (94. 1%) sites were parsimony informative. The BEAST analysis resulted in a fully resolved consensus tree (Fig  3 ) with the same topology as the tree from the five-genes Bayesian analysis (Fig  2B ). The analysis suggested that the origin of the most recent common ancestor of horned Spiophanes with metameric nuchal organs was around 11. 1 mya (95% HPD: 5. 1-19. 0 mya) and that the divergence of the North Atlantic and North Pacific lineages was around 7.
Acknowledgments Our sincere thanks are to  Peter Garwood  for organizing a field trip onboard R/V Bernicia in Northumbria;  Jane Delany  for providing generous support and working conditions at the  Dove Marine Laboratory, Cullercoats, UK; Kristine Hopland Sperre  for help in sampling in Norway, and  Marco Sigovini  for help in sampling in Venice Lagoon; Paulo da  Cunha Lana  and  Alvaro Migotto  for generous support in Brazil;  Leslie Harris  and  Christina Piotrowski  for help with museum collections. Our sincere gratitude is also to  Dorothy Norris ,  Kristin Politano ,  Dagmar Lackschewitz ,  Barbara Mikac ,  Marı ´a Martha  ( Pitu) Mendez ,  Kevin Kocot  and  Vinicius Miranda  for providing Spiophanes specimens used in this study, to  Børge Holte  and  Katrine Kongshavn  for providing Spiophanes specimens collected by the  MAREANO  Project from offshore  Norway , and to  Greg Rouse  for providing COI and 18S sequences of Trochochaeta multisetosa from  Sweden.
Financial support was provided to TVN by the  Russian Foundation for Basic Research  (https://www. rfbr. ru/rffi/engGrant  18-05-60158 ) and the  Russian Science Foundation  (http://rscf. ru/en/ Grant  16-14-10173 ), to VVP & VVM by the  Far Eastern Branch of the Russian Academy of Sciences  (http://www. febras. ru/ 2012-01-25-06-37-30. html Grant  18-4-040 ), to VIR by the Research forskningsradet. no/en/ Project  280724  "Environmental nmbaqcs. org/),and the  Canadian Museum of Nature  (https://nature. ca/en/homeScientific Training Program, 2019 Visiting Scientist Award), to SY by the  Collaborative Genome Program  of the  Korea Institute of Marine Science and Technology Promotion (KIMST)  funded by the  Ministry of Oceans and Fisheries  (https://www. mof. go. kr/eng/ index. doNo. 20180430).
Climatic limits We quantified the climatic limits of each species by summarizing climate variables across a sample of 500 occurrence records taken from vegetation plot data and other observations in the Global Biodiversity Information Facility  (GBIF, 2020). Most of our species distribution data relied on an objective grid-based sample of New Zealand's forests and shrublands  (Simpson et al. , 2016; Holdaway et al. , 2017). This sampling network consists of > 1200 permanent 0. 04 ha plots evenly spaced across mapped indigenous forests and shrublands on the intersections of an 8 km grid. This unbiased, spatially balanced sample provides the most robust data for quantifying the climate niche of each species. We randomly sampled 500 occurrences of each species from this plot network. If a species occurred on fewer than 500 of these plots, we randomly sampled the required number of occurrences without replacement from GBIF to reach our sample size of 500 for each species.
We used these occurrence records to quantify the climatic limits of each species that relate most directly to drought. Using existing spatial layers of interpolated climate data  (Leathwick et al. , 2002; Leathwick et al. , 2003)  we extracted the mean annual precipitation (MAP, mm), the annual vapor pressure deficit (VPD, kPa), the mean maximum temperature of the warmest month (T max , °C), and the precipitation-to-potential evapotranspiration ratio (P : PET, an index of aridity). Note that these climate measures address only average dryness of a region, and the frequency and intensity of drought is only partly correlated with these measures. Our 500 occurrences sample the full range of each climate variable where each species occurs, but to estimate the climatic limits of each species, we calculated the 5 th percentiles of MAP (MAP 5 ) and P : PET (P : PET 5 ), and the 95 th percentiles of T max  (T max95  ) and VPD (VPD 95 ).
Morphological traits We used mean values of leaf dry matter content (mg g À1 ) and wood density (i. e. stem-specific density; mg mm À3 ) from existing databases collected between 2002 and 2015 from forests and shrublands throughout New Zealand  (Richardson et al. , 2004; Mason et al. , 2012; Jager et al. , 2015; Simpson et al. , 2016)  following standard protocols  (P erez-Harguindeguy et al. , 2013). We focused on these two traits because wood density and specific leaf area (a trait that is inversely correlated with leaf dry matter content (LDMC)) have been shown to be predictors of droughtinduced mortality  (Greenwood et al. , 2017).
, 2010). The bark was removed from conifer branches to prevent resin filling the cavitron reservoirs  (Delzon et al. , 2010) , and all branches were recut with a razor blade, under water, to a standard length of 27 cm. Samples were infiltrated with a reference ionic solution of 10 mM KCl and 1 mM CaCl 2 in deionized ultrapure water. Centrifugal force was used to generate negative pressure into the xylem and induce embolism. This method allows measurement of xylem conductance under negative pressure using the custom software CAVISOFT 4. 0 (Univ. Bordeaux, Pessac, France). Initially, the maximum stem conductance (K max , in m 2 MPa À1 s À1 ) was calculated under low xylem pressures. The percentage loss of conductance (PLC) of the stems was calculated at different xylem pressures (P i ) from À0.
8 to À12 MPa with the following equation: PLC ¼ 100 1 À K K max Eqn 1 We obtained one vulnerability curve per tree showing the percentage loss of xylem conductance as a function of xylem pressure  (Delzon et al. , 2010). For each branch, the relationship between PLC and xylem water pressure was fitted with the following sigmoidal equation  (Pammenter & Van der Willigen, 1998) : PLC ¼ 100 1 þ exp S 25 P i À P50 ð Þ Eqn 2 where P50 (MPa) is the xylem pressure inducing a 50% loss of conductivity and S (% MPa À1 ) is the slope of the vulnerability curve at the inflection point. All sigmoidal functions were significant and fitted with the NLIN procedure in SAS (v. 9. 4; SAS Institute, Cary, NC, USA). The xylem-specific hydraulic conductivity (K s , kg m -1 MPa À1 s À1 ) was calculated by dividing the hydraulic conductivity measured at low speed by the sapwood area of the sample.
Statistical analyses To answer our first question, we determined the range of variation in hydraulic traits by comparing the minimum and maximum trait values among the angiosperms and conifers. To determine how much of this variation could be attributed to interspecific vs intraspecific variation we used variance partitioning. We fitted random effects models using the lme function in the R package NLME  (Pinheiro et al. , 2011)  where the trait was a function of a global intercept and random intercepts for each species. For the leaf hydraulic trait, two leaf disks were measured per individual, so we included an intercept for individual nested within species. HSM was computed at the species level so we could not estimate intraspecific variation in this trait. We used the varcomp function in the APE R package  (Paradis et al.
, 2004)  to decompose the variation between vs within species. New  Phytologist (2020) 226: 727-740  Ó 2020 The Authors New Phytologist Ó 2020 New Phytologist Trust www. newphytologist. com Before addressing our second and third questions, we determined the strength of phylogenetic signals in the traits using Pagel's k  (Freckleton et al. , 2002)  with the phylosig function in the PHYTOOLS R package  (Revell, 2012). Given the strength of the phylogenetic signals (see Results), we applied phylogenetic generalized least squares (PGLS) using the pgls function in the CAPER R package  (Orme et al. , 2018)  to answer our second and third questions. We used PGLS in all analysis that tested for the strength of covariation among traits (second question) and the strength of association between traits and climatic limits (third question).
Acknowledgements We thank  Gaelle Capdeville ,  Marie Harel ,  Anne-Isabelle Gravel ,  Claire Francioni ,  R egis Burlett ,  Kara Laughlin  and  Chris Morse  for contributing to the vulnerability curve measurements and  Joana Unteregger  for the leaf osmotic potential measurements. We acknowledge the use of data drawn from the Natural Forest plot data collected between January 2002 and March 2007 by the  LUCAS program  for the  New Zealand Ministry  for the Environment. This study was funded in part by the  'Investments for the Future' program  (grant no. ANR-10-EQPX-16 , XYLOFOREST) from the  French National Agency for Research and the Cluster of Excellence COTE  ( ANR-10-LABX-45 , within the  DEFI  project) to SD, and in part by the  Strategic Science Investment Fund of the New Zealand Ministry of Business, Innovation and Employment's Science and Innovation Group  to PJB and SJR.
35 In the EACH2 registry, the only parameter that differed between patients who responded to treatment and those who did not was a delay in time to treatment. 8 he decision to initiate treatment is guided by the clini-cal relevance of acute bleeds. Overall, approximately 70% of patients with AHA need hemostatic treatment. According to data from the UK and the EACH2 registry, approximately 30% of patients were untreated, 2,8 apparently because they had no bleeds or only non-severe subcutaneous bleeds. However, close observation may be warranted because even fatal bleeding can occur up to 5 months after first presentation in patients with persistent inhibitors. 2  A lack of correlation between FVIII:C or inhibitor titer and bleeding phenotype in AHA has been described in many studies. 2, 3, 36 Inhibitor titer and FVIII:C should not therefore influence the decision to initiate treatment for clinically relevant bleeding.
Choice of first-and second-line treatment for acute bleeds Parallel-group, comparative-treatment studies are not available in AHA. Propensity score-matched analysis of registry data on bypassing agents, including recombinant activated factor VII (rFVIIa; NovoSeven ® ) and activated prothrombin concentrate complex (APCC; FEIBA ® ), as well as a single-arm clinical trial on rpFVIII did not show a clear efficacy or safety benefit of one drug over the others. 8, 15, 37 A similar analysis showed that the efficacy of human FVIII concentrates and desmopressin was clearly lower than that of bypassing agents in EACH2. 8 herefore, APCC, rFVIIa and rpFVIII can all be considered appropriate first-line treatments (Figure  2 ). The final choice will be influenced mostly by the anti-porcine titer, as well as availability, cost and ability to monitor rpFVIII.
Recombinant activated factor VII The efficacy of rFVIIa [eptacog alfa (activated)] in AHA was recently addressed in a systematic literature review. 37  total of 12 studies, reporting on 671 patients and 1,063 Diagnosis and treatment of acquired hemophilia A haematologica | 2020; 105 (7) bleeds treated with rFVIIa, were analyzed. The reported median initial rFVIIa dose was 90-105 μg/kg body weight, with ranges between 25-181 μg/kg in individual studies. Doses were repeated mostly every 2-3 h, with the median total number of doses being 10-28. rFVIIa was used as first-line treatment in the majority of cases, and 39-90% of treated bleeds were severe. There was considerable variability across the 12 studies in terms of how hemostatic effectiveness was defined. The only effectiveness outcome that provided sufficient data was defined as 'complete' or 'partial response', available for six studies.
Activated prothrombin complex concentrate APCC is used for the treatment and prevention of bleeds in patients with congenital hemophilia with inhibitors,  [40] [41] [42]  and is widely used for AHA, although no systematic reviews are available. The recommended dose is 50-100 U/kg every 8-12 h, up to a maximum of 200 U/kg/day. 1 In the EACH2 registry, propensity scorematched analysis indicated indistinguishable efficacy for APCC compared with rFVIIa, with >90% bleed control rates when used as first-line treatment. 8 An earlier study collected data from 34 cases in three centers in the USA over 10 years. 43 A total of 55 bleeding events were observed and the response rate was 76% and 100% for patients with severe and moderate bleeds, respectively. 43 PCC has also been used for secondary prophylaxis.
General strategy and prognostic factors The 2009 international AHA guidelines recommended starting IST in all patients with AHA immediately following diagnosis. 1 This recommendation was mainly based on the high bleed-related mortality in earlier studies and the observation that the initial bleeding tendency was not predictive of later major or even fatal bleeding. 61 Initial treatment with corticosteroids alone or in combination with cyclophosphamide was recommended for up to 6 weeks, while second-line therapy with rituximab was suggested if first-line IST failed or was contraindicated (Figure  3 ). The GTH-AH 01/2010 study protocol was designed as a variant of this recommendation and was the first IST protocol investigated prospectively. 10 Patients were enrolled ≤7 days after starting any IST, and follow-up data were collected weekly until complete remission was achieved.
We recommend IST in all patients with AHA. However, particular caution should be exercised in frail patients (GRADE 1B). The success of IST, in particular the time to achieve remission, varies largely among patients. In the GTH study, 85/102 (83%) patients achieved a partial remission after a median time of 5 weeks (range, 1-52 weeks). 10 VIII:C at presentation was the most important prognostic factor; patients with FVIII <1% achieved partial remission less often compared with other patients (77 vs. 89%, respectively) and after a significantly longer time on IST (43 vs. 24 days, respectively). Anti-FVIII IgA autoantibodies were predictors of relapse as observed in 45% of patients with anti-FVIII IgA titers >1:80. These data suggest that IST should be individualized in patients with AHA according to baseline characteristics, although interventional studies with stratified protocols have not been performed.
We suggest using prognostic markers (FVIII activity, inhibitor titer, if available) to individualize IST (GRADE 2B). The benefit of combining corticosteroids with other immunosuppressants for first-line therapy is uncertain and cannot be concluded from the published observational studies. Combination therapy shortened the time to remission in the EACH2 registry  7  but not in the UK surveillance study. 2  GTH data indicated that achieving partial remission within 21 days of steroid therapy was unlikely (negative predictive value, 84%) if patients had FVIII <1% or an inhibitor titer >20 BU. 10  We, therefore, suggest combination therapy in these patients. In all other patients (i. e. , those with FVIII ≥1% and inhibitor ≤20 BU), we suggest using steroids alone, because the benefit of more intense regimens is uncertain, and the risk of infectious complications currently exceeds the risk of bleeding.
The Australian Productivity Commission made a first attempt at cataloguing and quantifying services trade restrictions across countries and sectors in the mid-1990s. Their restrictiveness indices covered eight services sectors and between 35 and 135 countries depending on the sector (Findlay & Warren, 2000). A second set of services trade restrictiveness indices with a global coverage was developed by the World Bank in the late 2000s. Their survey covers 103 countries and five broad sectors for the year 2008, with an update of 77 countries in 2016, using a survey for 34 of them and the OECD STRI database for the rest. 1  This paper presents the database and services trade restrictiveness indices, hereafter STRI, developed by the OECD. It currently covers 46 countries, 22 sectors and 6 years.
Like the two predecessors, it collects qualitative information on trade policy measures, which are scored and weighted to create composite indices. Unlike the predecessors, the qualitative policy information constitutes a database of its own with factual and documented information on de jure regulation. And unlike the predecessors, the information is updated each year since its launch in 2014, currently covering a time series of 6 years (2014-2019). The OECD project started in 2007 with a pilot phase covering the OECD countries and seven sectors (computer services, construction, four professional services and telecommunications). After a period of testing and revision, the sector and country coverage was extended and the first database and indicators were released to the general public in 2014.
| Construction of the database Creating a regulatory database and composite indices involves a number of decisions. The first step is to develop the list of measures to include in the database. Drawing up such a list involves a trade-off between making the data comparable across sectors and capturing sector-specific features and idiosyncrasies. For example, telecommunications and transport are subject to network effects and sectorspecific pro-competitive regulation. Asymmetric information and systemic risks are considerations that govern trade policy as well as domestic regulation in financial services. Finally, regulation of professional services is typically delegated to professional bodies such as the bar association. To balance such trade-offs, the STRI database contains a set of core measures common to all 22 sectors and sector-specific measures that differ in number and complexity across sectors.