dataesr/scientific-paragraphs-categorization huggingface dataset:
Means and variances Leaf mass per area (dry mass [g]/fresh area [m 2 ]) was calculated on a whole-leaf basis, including both laminas and petioles. In cases where dry petioles had a mass of zero (due to a balance with limited precision), the dry masses were corrected by the site-level ratio of fresh mass/dry mass of the petiole. For the statistical analyses, leaf areas from images with folded leaves were not included. Leaves that caused the tree to have variances >2000 g 2 Ám À4 for LMA were also not included (i. e. , single leaves from groups of five leaves were removed as outliers) when investigation of raw data strongly suggested measurement error. Leaf mass per area was calculated separately for each leaf before calculating the mean LMA per individual tree. At the species and plot levels, LMA was calculated from individual tree (and not leaf) values.
As proposed by  Messier et al. (2010) , we used a restricted maximum-likelihood method to decompose the variance of LMA on different levels: leaf, tree, species, site, and country. The lme and varcomp functions (R packages nlme and ape) were used to successively perform a nested ANOVA with random effects and apply a VC analysis. The R code used to calculate the variance partitioning on the whole dataset is: VC ¼ varcompðlmeðLMA $ 1; random ¼ $ 1jSite=Family=Genus=Species=Tree; data ¼ d; na. action ¼ na. omitÞÞ: Next, to account for species turnover along the gradients of dissimilarity, we calculated the Sorensen index (R package betapart, function beta. pair). The obtained distance matrix was then compared with a distance matrix of the main quantifiable environmental parameters (elevation in Peru and LAI in Brazil).
Acknowledgments UK  Natural Environment Research Council  (Grant  NE/ J023418/1 ), and in both Peru and Brazil from a  European Research Council Advanced Investigator  grant  GEM-TRAITS (321131 ). G. P. Asner  and the Carnegie team were supported by the endowment of the  Carnegie Institution for Science  and a grant from the  National Science Foundation  ( DEB-1146206 ). S. D ıaz, was partially supported by a  Visiting Professorship Grant  from the  Leverhulme Trust, UK. I. Oliveras, was supported by a  Marie Curie Fellowship ,  L. P. Bentley  was partially supported by a  John Fell Fellowship  from the  University of Oxford , and  L. P. Bentley ,  G. P. Asner , and B. J. Enquist were partially supported by a  National Science Foundation  Grant ( DEB-1457804 ). We thank the  Servicio Nacional de Areas Naturales Protegidas por el Estado (SERNANP)  and personnel of Manu and  Tambopata National Parks  for logistical assistance and permission to work in the protected areas in Peru.
This is true for gene lists obtained when comparing gene expression by CD8 T cells in homeostatic conditions (H) or following re-stimulation (R). To assess the conserved expression of these memory gene signatures, we performed a meta-analysis of 8 datasets comparing naive and memory CD8 T cells gene-expression-profiles in homeostatic conditions (Supplementary Tables  S9-11 ). Memory CD8 T cells, in these models, were generated using 4 different pathogens (vaccinia virus, Listeria monocytogenes, Vesicular Stomatitis Virus and Lymphocytic Choriomeningitis Virus) and 3 different TCR transgenic mice (P14, F5 and OT1). The majority of genes in the P2 and P3 clusters are present in the meta-analysis i. e. are differentially expressed by memory cells compared to naive cells when all these different models are analysed with Rankprod (Table  1  and Supplementary Tables S3-5 and S 9).
Discussion Using transcriptome approaches applied to different qualities of CD8 T cells, we have identified unique gene expression signatures that are associated with the capacity of memory cells to protect against a lethal influenza infection. We could show that these immune signatures were conserved, as they were induced by 2 other pathogens (vaccinia virus and Listeria monocytogenes) and also based on meta-analysis of memory CD8 T cell datasets obtained using 3 different TCR transgenic CD8 T cells. We identified a gene expression signature (HP1) associated with protective Flu-TM in homeostatic conditions, i. e. genes expressed by cells in the absence of re-stimulation, that is enriched in genes such as Ccr5 or Itga1 and Itgb1 coding for proteins that control the re-circulation of cells to the lung  24, 37, 38.
RNA quality was assessed using the Agilent Model 2100 Bioanalyzer. Samples were hybridized and loaded onto Affymetrix GeneChip Mouse 430 2. 0 arrays. Affymetrix CEL files were processed and analysed with R  49  and Bioconductor (Release 2. 10)  50  packages. The expression data were computed with the Robust MultiChip Average (RMA) method  51  implemented in the affy package  52. This pre-processing step included: background correction based on PM probes only, quantile normalization and median polish summarization  51. The log2 transformed expression data was used for all further analyses. The differential expression analysis was carried out with the Linear Models for Microarray Analysis method available in the limma package  53. For each comparison the limma p-values were adjusted for multiple testing with the Benjamini-Hochberg method for false discovery rate (FDR)  54.
Meta-analysis. To identify a homeostatic memory signature we performed a meta-analysis with 8 datasets comparing memory CD8 T cells to naive CD8 T cells (Supplementary Table  S9 ). All the datasets have been pre-processed as described above (RMA pre-processing and LIMMA analysis). We used a rank product-based meta-analysis method, available in the RankProd package  58. Rankprod method uses as input complete pre-processed expression data matrix from each experiment. All possible pair comparisons, treatment vs. control, were performed within each experiment. Suppose one has in the first experiment t treatment samples and c control samples, then t x c fold changes will be computed for each gene. Fold changes are transformed in ranks for each comparison, the largest fold change having rank = 1.
Pathway analysis. The functional analysis of gene expression data has been performed with SPIA method and R/Bioconductor package (Signalling Pathway Impact Analysis). In addition to performing classical enrichment analysis the SPIA method allows us to take into account the pathway topology and the amount of gene perturbation (FC). The KEGG information used in our analysis is the one included in the R package, and has been downloaded from the KEGG's website on 09. 07. 2012. The SPIA analysis output of an expression dataset includes for each pathway the NDE (number of genes differentially expressed for a given pathway) and its associated p-value (P NDE ), a perturbation index (tA) and its associated p-value (P PERT ). The two p-values are combined into one global probability value (P G ) that we have used for ranking and filtering the pathways.
Taqman Low Density Array (TLDA). Microarray data was validated using the Applied Biosystem TaqMan Low Density Array (TLDA) format 384, which allows the analysis of 47 gene targets in single reactions and of one mandatory endogenous control gene (HPRT). cDNA was generated using iScript cDNA Synthesis Kit (Bio-Rad) according to the manufacturer's instructions. The cDNA obtained was amplified using a pre-designed TLDA plate (Applied Biosystems) with user-defined probes. The RT-qPCR was run on the 7900 HT Applied Biosystem machine. Raw data were analyzed with the RQ Manager software. Expression values were normalized to HPRT (housekeeping gene) mRNA. Relative expression of each gene was calculated by the (delta-delta) Ct method.
Construction of the molecular dataset: regional and continental sampling Sample sizes were restricted because several Indian Ocean Orthoptera species are threatened  [23, 24] , and in view of conservation priorities, research permits restrict sampling for island endemics with small populations. Further, many species occur in treetops and are highly timeconsuming to collect. Depending on numbers of individuals available, between two and four individuals from each natural song group in the western Indian Ocean were sampled from across that group's range (be it restricted to one island, or found across many), and including at least one individual per island. Ornebius has a wide distribution across the tropics, with most described species occurring in Australasian and Oriental regions, and a minority of occurrences in the Americas and islands of the Pacific and Indian Ocean  [25].
A single species is described from Africa (Ornebius acutus from Ghana), but probably belongs to a distinct genus (S. Hugel, unpublished data). We therefore obtained Ornebius samples from Australia, French Polynesia, Borneo and Central America as potential source areas for the colonisation of the western Indian Ocean, as well as outgroup samples from two other Mogoplistinae genera (Ectatoderus and Cycloptiloides) and one other Grylloidea (Creolandreva). Each individual was vouchered and stored in Ethanol. DNA was extracted from finely sliced leg tissue using a DNeasy Blood and Tissue Kit (Qiagen Inc. , Valencia, CA, USA), and following the manufacturer's protocol. For all samples (i. e. 2-4 individuals per song group in the Indian Ocean, and 1 individual per continental species), a total of 1594 bp of sequence data were obtained from the mitochondrial COI gene, and ribosomal RNA genes 12S and 16S.
Primers used for amplification and sequencing of these three genes were LCO1490 and HCO2198  [26] , SR-J-14233 and SR-N-14588  [27] , and 16Sa and 16Sb  [28] , respectively. The polymerase chain reaction (PCR) program began with denaturation for 5 min at 94°C, followed by 35 cycles of 1 min at 94°C, 1 min at 49°C, 1 min at 72°C, and a final extension step at 72°C for 5 min. To guard against the possibility of introgression obscuring true lineage history and improve the resolution of phylogenetic relationships, the mitochondrial data were supplemented with nuclear EF1α and H3 sequences from a reduced sample set (1-3 individuals from each terminal monophyletic group in the mitochondrial dataset), providing a five-gene dataset totalling 2352 bp. Primers used for amplification and sequencing of EF1α and H3 were M51F and M53R  [29] , and 5'-ATGGCTCGTACCAAGCAGACVGC-3' and 5'-ATATCCTTRGGCA TRATRGTGAC-3'  [30] , respectively.
The PCR program began with denaturation for 4 min at 94°C, followed by 40 cycles of 30 sec at 94°C, 40 sec at 54°C, and 40 sec at 72°C, and a final extension step at 72°C for 7 min. Amplified products were purified and sequenced by Macrogen (Seoul, Korea) using the standard-seq single service. Sequences have been deposited in Genbank (Accession numbers KC494774-KC494868, KU597648-KU597710).
DNA partition, model selection and phylogenetic inference Mitochondrial data for the full sample set. The congruence of the different gene data sets was checked using the partition homogeneity test  [31]  implemented in PAUP Ã , and data from the three genes were combined for further analysis. The combined dataset excluding outgroups (Creolandreva, Ectatoderus and Cycloptiloides) was analysed in MODELTEST  [32]  and MrModeltest  [33]. The optimal model defined by MODELTEST was used to determine the maximum-likelihood (ML) distances for a ML analysis implemented in PAUP Ã. In addition, an unweighted parsimony analysis was performed with the heuristic search algorithm, holding 10 trees at each step and branch swapping on all trees. The optimal model defined by MrModeltest was used for Bayesian analysis implemented in MrBayes 3.
2. 1  [34]. Base frequencies were estimated from the data. Four Markov chains were run simultaneously for 20 million generations, and sampled every 100 generations. Variation in likelihoods was examined graphically. The trees generated prior to stationarity were discarded, and the consensus phylogeny and posterior probability of its nodes were determined from the last 150,000 trees in the chain. To check our results and guard against the possibility of multiple optima, we repeated this process four times. Nuclear & mitochondrial data for the restricted sample set. The congruence of the different gene data sets was checked using the partition homogeneity test  [31]  implemented in PAUP Ã , and data from the five genes were combined for further analysis. An unweighted parsimony analysis was performed as for the mitochondrial dataset.
In addition, the combined dataset excluding outgroup (Ectatoderus) was analysed in MODELTEST  [32]  and MrModeltest  [33]. The optimal model defined by MrModeltest was used for Bayesian analysis following the procedures for the mitochondrial dataset. The first three analyses were run for 20 million generations, and the consensus phylogeny and posterior probability of its nodes were determined from the last 150,000 trees in the chain. The final analysis was run for 50 million generations and the last 375,000 trees were used to obtain the consensus. The method of Shimodaira and Hasegawa  [35]  (SH) implemented in PAUP Ã was used to test the monophyly of Ornebius species and discriminate between alternative scenarios explaining archipelago diversity. Were all endemic taxa of an archipelago a result of a single colonisation event and in situ cladogenesis, we would expect them to be monophyletic (Scenario 1).
Biogeographic scenarios, speciation, and the zone of radiation A null hypothesis of monophyly of the two species of the Grantic Seychelles-O. elegantulus and O. validus-consistent with in situ cladogenesis (Scenario 1) can be rejected based on the SH test (P = 0. 0014; based on 5-gene dataset). Rather, their phylogenetic placement supports two independent colonisations of the Granitic Seychelles (Scenario 2), the first originating from outside the western Indian Ocean and giving rise to O. validus, and the second giving rise to O. elegantulus. By contrast, the monophyly of the Mascarene-endemic clade allows us to reject our default hypothesis of multiple colonisations (Scenario 2) to explain the origin of the six Mascarene-endemic species (O. xanthopterus, O. luteicercis, and species 7, 8, 9 and 10).
Barring unknown extinctions, all these species descend from a single colonisation of the archipelago, and only in situ cladogenesis can explain their current diversity (Scenario 1). Further, an SH test enables us to reject a scenario involving monophyly of Pandanus-associated species (P<0. 0001; based on 5-gene dataset). Rather, a minimum of two evolutionary shifts between dicot-and Pandanusassociation are required to explain the data. In the case of the Chagos archipelago, the geographic context of species origin is disputable. Unlike the Granitic Seychelles that can be inferred to have been above sea level since separation from India 64 Myr ago, the Chagos was completely submerged during the Quaternary, and likely as recently as 6,500 years ago  [38, 39]. Therefore, based on island ages, colonisation of the Chagos from the Granitic Seychelles seems more likely than colonisation in the opposite direction.
Acknowledgments We gratefully acknowledge  Laure Desutter-Grandcolas  ( MNHN ) for her help in the field, and for providing access to MNHN collections. We thank  George Beccaloni  for providing access to BMNH collections. We thank  René Hugel  for assistance in the field, and  Heather Richards ,  Nancy Bunbury ,  Thibault Ramage ,  You Ning Su ,  David Rentz  and  Sigfrid Ingrisch , for supplying material from  Aldabra, Tahiti, Australia , and Sabah. We further thank  Virginie Ravigné  for comments on the manuscript, and  David Rentz  and  Sigfrid Ingrisch  for comments on the biology of Australian and Oriental Ornebius species. We thank the  National Parks  and forestry services of  Réunion, Mauritius, Rodrigues, Seychelles, Comoros, Mayotte and Madagascar  for providing access to protected areas and for logistical support in the field.
This work was supported by the  French National Research Agency ' s biodiversity programme  ( ANR-2006-BDIV002 ) and the  European Union Seventh Framework Programme  ( 263958  and  267243 ). Additional fieldwork was supported by the  Société Entomologique de France, Cirad Reunion , the  Fondation pour la Recherche sur la Biodiversité  and self-funding by  SH. Apart from the latter, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
SmSOFb1 and SmCVFa1 were isolated from horse manure in Saint Olive and cattle manure in Versailleux, respectively. Six of the seven strains harbor the MDR phenotype (4). Only Sm32COP is susceptible to most of the antibiotics tested (Table  1 ). Genome sequencing for the seven strains was performed using an Illumina MiSeq PE 2 ϫ 300 platform at the University of Lyon (France). For each strain, between 2,827,464 and 3,703,116 paired-end reads with a mean length of about 250 bp after trim-ming were obtained, and coverage between 166ϫ and 222ϫ was generated (Table  1 ). Reads were de novo assembled using five different genome assemblers (SPAdes, Celera, Minia, Velvet, and MaSuRCA), except for SmF3 and SmF22. Contigs from these assemblers were merged using CISA  (8). For SmF3 and SmF22, reads were assembled using only the SPAdes software version 3  (9).
The new genomes described here encode eight or nine RND pumps putatively involved in MDR, with seven RND pumps conserved in all S. maltophilia strains. Interestingly, the SmeABC MDR pump is absent in three strains, unrelated to their antibiotic resistance phenotype, while some additional strain-specific RND efflux pumps were detected. Functional redundancies and/or specific regulation explain likely the variation of resistance phenotype observed in these strains and should be further studied. Accession number(s). These draft genome sequences have been deposited at DDBJ/GenBank/EMBL under accession numbers listed in Table  1. The versions described in this paper are the first versions.
Sample description Our primary data are from the Altares 2 database. We first exclude firms that do not meet the E. U. definition of an SME. The remainder of companies employ between 20 and 250 people, and generate a turnover of €2 to €50 million or have €2 to €43 million in total assets. Then, in order to assure the consistency of firms' accounting obligations in our sample, we have only retained the largest ones: those that are head of a group have to publish consolidated accounts and have their accounts certified by two different auditors. We end up with a sample of 925 SMEs: 245 PUB_SME and 680 PRIV_SMEs. Firms' accounting behaviour is observed between 2002 and 2010. After removing inconsistent data, this allows us to consider 3682 observations. Following  Marques et al. (2011) , we focus on firms' individual accounts established using local French GAAPs.
Income smoothing and discretionary accruals For H2, H3a and H3b, we use a common protocol. We regress a measure of earnings quality (an income-smoothing indicator or an estimation of discretionary accruals) on a variable called Public and a set of controls. Public takes the value of one if the SME is publicly traded and zero otherwise. The controls are the firm's size, leverage ratio, growth rate, operational performance, industry sectors and, depending on the timeframe of the explained variable, dummy years. We estimate the following specification using OLS on a cross section of aggregated data to test H2 3 and on data panel to test H3a and H3b. 12 3 4.
Subgenus Ochlerotatus Lynch Arribálzaga, 1891 This subgenus includes 187 species in the world  [241]. Only Ae. (Och. ) ambreensis is present in Madagascar. The report of Aedes dufouri as present in Madagascar in Arim dataset  [5]  is doubtful as information on collection areas is not available. De facto this information was treated as an error. Aedes dufouri was described from Réunion Island and occurs on Europa island (French island in the Mozambique Channel)  [99]. d Aedes (Ochlerotatus) ambreensis Rodhain & Boutonnier, 1983 Rodhain & Boutonnier, 1983  [193]  Endemic. Only the female was described  [193]. Occurs in the Montagne d'Ambre, in the northern domain  [85, 193]. Nocturnal, diurnal species and anthropophilic species, but also seems to feed on lemurs (Eulemur fulvus)  [85]. Found naturally infected with unclassified virus (MMP 158 virus) in specimens collected at Montagne d'Ambre  [85].
Not involved in disease transmission. Dyar, 1905 [71]  This genus includes 57 species in the world  [117]. These species represent three subgenera: Coquillettidia, Rhynchotaenia, and Austromansonia. In Madagascar, only the subgenus Coquillettidia is present and it is represented by three species. Two of them are endemic to Madagascar. Larval and pupal stages of Coquillettidia species derive their oxygen by puncture of the aerenchyma of aquatic plants. The report of Coquillettidia (Coquillettidia) aurites  (Theobald)  as present in Madagascar in Arim dataset  [5]  is doubtful as information on collection areas is not available. De facto this information was treated as an error.
Subgenus Culex Linnaeus, 1758 This subgenus includes 198 species in the world. Twentyseven species were recorded in Madagascar. Among them, Culex scottii Theobald and Cx. vansomereni Edwards were inventoried in this study and in the Arim dataset  [5]. Three species are endemic to Madagascar and two other species occur on several Indian Ocean islands. The report of Cx. sinaiticus Kirkpatrick in the Arim dataset  [5]  and Cx. thalassius Theobald in WRBU  [244]  as present in Madagascar is doubtful as information on collection areas is not available. De facto this information was treated as an error. d Culex (Culex) antennatus  (Becker, 1903)   [11]  Edwards, 1920 (as Cx. laurenti)  [75]  This species belongs to Subgroup Decens in the Group Pipiens  [115]. Larval stages are morphologically close to those of Cx.
Not involved in disease transmission. In Africa, involved in transmission of WNV, MOSV, SINV  [45] , CHIKV, BABV, and WSLV. MgV was isolated from this species  [1]. Theobald, 1907 [219]  This subgenus includes 55 species in the world. Six species occur in Madagascar, two of them are endemic species to the island. The report of Cx. semibrunneus Edwards as present in Madagascar in the Arim dataset  [5]  is doubtful as information on collection areas is not available. De facto this information was treated as an error.
Subgenus Mimomyia Theobald, 1903 The subgenus Mimomyia includes 21 species, widely distributed throughout the Ethiopian and Oriental regions and extends to northern Australia and the South Pacific. The four Malagasy species have a wide distribution on the African mainland. The report of Mi. lacustris Edwards and Mi. pallida Edwards as present in Madagascar in the Arim dataset  [5]  is doubtful as information on collection areas is not available. De facto this information was treated as an error. The species of the subgenus Mimomyia develop in a wide variety of terrestrial water accumulations (ponds, marshes, ponds, and riverbanks). d Mimomyia (Mimomyia) hispida  (Theobald, 1910)  Doucet, 1951  [66]  Eggs undescribed. In Madagascar, larval habitats are ponds and marshes containing abundant aquatic vegetation  [110] , muddy swamp water and rice fields with low vegetation  [67].
However, this number is moderately lower than that given in Internet references such as WRBU (253 species)  [244]  and Arim (245 species)  [5] , which include an enlarged area of several islands in the Mozambique Channel. The report of the genus Culiseta (Culiseta longiareolata (Macquart)) as present in Madagascar in the Arim dataset  [5]  is doubtful as information on collection areas is not available. To date, there is no conclusive evidence of the presence of this tropical species in Madagascar and this information was treated as an error. Taking into account that 3546 mosquito species are currently recognized in the world  [119] , 6. 6% of them are present in Madagascar. In addition, 28% of the 804 known species in the Ethiopian zoogeographical area are present in Madagascar  [144]. Moreover, despite decades of research, there is no doubt that new species remain to be discovered and that endemism could be higher than 60%.