dataesr/scientific-paragraphs-categorization huggingface dataset:
the authors test it on the classic Pasoh and Barro Colorado Island tropical forest datasets, and on simulated data. They make a very laudable effort in both explaining its theoretical underpinnings, and proposing a straightforward step-by-step guide to applying it to data. The core of Tovo et al's method is a simple property: the scale invariance of the Negative Binomial (NB) distribution. Subsampling from a NB gives another NB, where a single parameter has changed. Therefore, if the Species Abundance Distribution is close enough to some NB (which is flexible enough to accommodate all the data here), we can estimate how this parameter changes when going from (1) a single sample to (2) all the available samples, and from there, extrapolate to (3) the entire community. This principle was first applied by the authors in a previous study  [3]  that required abundance data in the samples, rather than just presence/absence.
Sachant que les limites du champ couvert par l'agroécologie varient fortement d'un acteur et d'un auteur à l'autre. Voir par exemple la base de données établie par la FAO sur les cadres légaux et de politiques publiques concernant l'agroécologie. http://www. fao. org/agroecology/policies-legislations/fr/, accédé le 8/3/2019.
2002)  and Hadley Centre EN4 dataset  (Good et al. 2013) ] are indicated by the vertical dashed lines. SST cooling response to ozone depletion in GFDL-ESM2Mc. Motivated by this result we here show the relationship between CMIP5 models' December-March jet-CRE indices and their year-1 SST cooling in the SAM CRF (Fig. 8a ). A positive correlation, which statistically significant (at the 95% level), can be seen. Although the R 2 value of 0. 15 is less than those in Fig. 7 , the sign of the correlation is physically intuitive. Models with a positive jet-CRE index display a shortwave warming associated with a poleward jet shift (positive SAM) that opposes the SST cooling response. Models with a negative jet-CRE index have a net shortwave cooling associated with the SAM perturbation, leading to a stronger SST cooling.
2009) , which were out of the scope of this study. The review of exploratory scenarios had two partsa formal review of peer-reviewed scenario literature using the Scopus database, and an informal review of grey literature using the knowledge of the author team (see Appendix #2 for the review protocol). Both reviews focused on environment-related scenarios from 2005 until the present. Articles were screened for ten aggregated groups of drivers (indirect drivers: demography, economy, technology, cultural and institutional; and direct drivers: climate change, land use change, natural resource extraction, pollution, and alien invasive species). Studies including only single drivers and studies with subnational spatial coverage were excluded from the review. These constraints were put in place to focus on multiple driver combinations and on spatial scales relevant to the sub-regional and regional levels.
A total of 436 scenarios in 143 studies from both the formal and informal reviews met the review criteria and were assessed. The review of modelling studies focused on integrated modelling approaches that combine modelling of multiple environmental, social and economic system components and their interactions. Such approaches provide essential support to guide planning and decision-making by highlighting critical interdependencies and potential synergies and trade-offs between NCP under different plausible futures. Similar to the scenarios review, the modelling review consisted of a formal review of the peer-reviewed literature using the Scopus database, which was complemented by extensive searches using the IPBES expert network, additional efforts by the author team to reduce gaps (i. e. for Central Asia and marine ecosystems) and suggestions to include additional studies by external reviewers (see Appendix #3 for the review protocol).
Articles were limited to those studies that included projections of future impacts of multiple drivers on multiple components of nature and NCP. As the majority of impact assessment studies still rely on single component models  (Harrison et al. 2015) , only 37 articles were found from both the formal and informal reviews that met the review criteria. Nevertheless, these 37 articles led to a total of 3,151 entries in the review database representing different combinations of integrated approaches, scenarios, regions and modelled system indicators for nature, NCP and quality of life. The final set of reviewed articles included local (a few hundred square kilometres), national, regional (EU wide, Central Asia) and global (which provided information for Europe and Central Asia) modelling studies.
The individual scenarios from the exploratory scenarios and modelling review databases were screened for multiple attributes (Table  A3. 2 and A2. 3), which were extracted for each scenario and entered in the database. Subsequently, based on the storylines of the scenarios, their underlying logic and assumptions, as well as the qualitative and quantitative values of scenario attributes, the individual scenarios were matched to the six scenario archetypes for Europe and Central Asia using the classification provided by  Hunt et al. (2012). This covered all global scenario sets and a large share of the European-scale scenarios. For those scenario sets not assigned to any of the  Hunt et al. (2012)  scenario archetypes, the qualitative or quantitative descriptions of changes in indirect and direct drivers were compared with the broad assumptions, storylines and characteristics for the archetypes as described in  van Vuuren et al.
Overview of the review database The majority of studies in the scenario and modelling reviews originated from Western Europe (64% and 57%, respectively). Central Europe had a reasonable coverage in the scenarios review (30%), but not in the modelling review (6%). Few studies were found in both reviews for Eastern Europe (5% and 6%) and Central Asia (1% and 6%). Most studies involved multiple sectors, with the agricultural sector often featuring in various combinations with water management, nature conservation, forestry, tourism and energy. Combinations between fisheries, aquaculture, water management and conservation were also observed. The six archetypes were not represented equally in the literature for Europe and Central Asia. The business-as-usual type of scenario was often used (30% of scenarios), but few of these studies developed a storyline of how indirect and direct drivers are projected to change over time (only three studies); rather they simply assumed no change in current trends.
This could be overcome in future applications of a deductive approach to archetype analysis by including the "currency" of scenarios as a classification criteria or by defining the original set of scenario archetypes with a greater emphasis on theory  (Oberlack et al. this issue). Alternatively, an inductive approach could be employed by constructing scenario archetypes from the review database, rather than predefining them. This would imply a loss of comparability with other assessments in the example of IPBES, but a better representation of the information in the database and the possibility of new archetypes and novel insights. Furthermore, as many past scenarios have been developed to be used as inputs to global Integrated Assessment Models and climate models, scenario archetypes have tended to be tailored to the temporal, spatial, and sectoral approaches most relevant to understanding greenhouse gas emissions and climate change.
ACKNOWLEDGEMENTS The authors are grateful to the  IPBES Europe and Central Asia Expert Group and Technical Support Unit  for all their input, support and collaboration over the past 3 years. Paula Harrison  and  Ian Holman  acknowledge financial support from the  UK Department of Environment, Food and Rural Affairs  and the  EU -funded  IMPRESSIONS  project (Grant Agreement  603416 ). Martin Schlaepfer  received support from  ENVIROSPACE, University of Geneva. Antoine Guisan  acknowledges additional funding from the  University of Lausanne  to support Anthony Sonrel's contribution to the assessment.
Suivi de la composition chimique de plusieurs espèces de bois tropicaux La variabilité de la composition chimique de 614 espèces est décrite dans une base de données contenant des mesures de polymères du bois (cellulose, lignine et pentosane), ainsi que de l'ensemble des composants externes (extraits éthanolbenzéne ou à l'eau chaude et cendres, en particulier la teneur en silice). Ces mesures ont été effectuées entre 1945 et 1990 selon le même protocole standard. Au total, 1 194 arbres appartenant à 614 espèces, 358 genres et 89 familles ont été mesurés. La variabilité entre les espèces (quantifiée par le coefficient de variation) était plutôt élevée pour la densité (27 %), beaucoup plus faible pour la lignine et la cellulose (14 % et 10 %) et beaucoup plus élevée pour les extractibles éthanol/benzène, les extractibles à l'eau chaude et les cendres (81 %, 60 % et 76 %).
Une valeur élevée pour tout composant externe, même dans un seul arbre, est suffisante pour classer l'espèce à l'égard de ce composant. Les bois siliceux identifiés par les cristaux de silice en anatomie ont une teneur très élevée en silice et seules ces espèces méritent une étude sur la silice. Mots-clés : composants du bois, cellulose, lignine, pentosane, éthanolbenzène, eau, cendres, silice, chimie du bois, espèces tropicales, base de données.
Survey on the chemical composition of several tropical wood species Variability in the chemical composition of 614 species is described in a database containing measurements of wood polymers (cellulose, lignin and pentosan), as well as overall extraneous components (ethanol-benzene, or hot water extracts and ash, with a focus on silica content). These measurements were taken between 1945 and 1990 using the same standard protocol. In all, 1,194 trees belonging to 614 species, 358 genera and 89 families were measured. At species level, variability (quantified by the coefficient of variation) was rather high for density (27%), much lower for lignin and cellulose (14% and 10%) and much higher for ethanol/benzene extractives, hot water extractives and ash content (81%, 60% and 76%). Considering trees with at least five different specimens, and species with at least 10 different trees, it was possible to investigate within-tree and withinspecies variability.
In order to check possible changes we look at variations of results during succeeding years. There are no significant differences between periods except for the species sampling, much larger in the first period. We have decided to open these data files to the scientific community because we trust in its quality, in terms of continuity. Mostly hardwood species (599) were measured, including a very small number of temperate hardwood species (5), with only 15 gymnosperm species being included. Seven basic parameters are discussed: hot water extracts, ethanol-benzene extracts, ashes, silica content within ashes, Klason lignin, pentosan, Kürschner cellulose.
Database and statistical methods All the informative data and metadata on the collection have been recorded in digital files since 1980  (Gérard and Narboni, 1996). In the data file associated with this paper, the botanical names have been updated and mean density values have been added at species level (unless there was a density value associated with the CTFT id in the wood collection). Basic statistical analyses were performed using XLSTAT software. The data description table includes the number of present and missing data, minimum, maximum, 1 st quartile, median, 3 rd quartile and mean (with its standard deviation) values for each parameter, as well as the coefficient of variation (CV), skew (Pearson) and kurtosis (Pearson) of the distribution. A box plot is also given for each parameter.
Discussion The total of species measured represent around 10% of species present in the CIRAD wood collection. In some cases, the choice was guided by specific forests where there was a pulp and paper manufacture project (Le  Cacheux, 1949; Pétroff, 1976; Tissot, 1989). In other cases it was guided by the necessity to have a large range of densities  (Doat, 1977). Globally the necessity to cover a wide range of wood chemical composition was taken into account  (Pétroff, 1960). The only way to predict a wide diversity of composition was to choose the widest diversity in density known from the wood collection  (Langbour et al. , 2018)  and to use trees from different countries in the tropical region. In the described data file we have only the country of nance but nothing on provenance of the trees.
Conclusion The CTFT chemical composition database for tropical woods provides a relevant view of wood variability at the level of both main and extraneous components in tropical hardwoods, given the wide range of density of species (240 to 1,310 kg/m 3 ), the large number of species (614), genera (358), and families (89) representing respectively 7%, 17% and 39% of species, genera or families present in the CIRAD wood collection. Values for main components (lignin, pentosan and cellulose) or extraneous components (AB and hot water extracts, ashes) are similar to literature data showing that temperate hardwoods values are included in the larger tropical hardwood range, in the same way as densities. Softwood species clearly differ from hardwoods for pentosan sugars that are less dominant among hemicelluloses in the softwoods.
fichiers de données sont disponibles sur le centre de stockage Dataverse DOI: 10. 18167/DVN1/D5HNOK. Pour chaque fichier, sur la première feuille (métadonnées) sont décrits et explicités codages et dénominations utilisés dans les feuilles suivantes qui correspondent chacune à un niveau d'enquête et contiennent un champ identifiant le ménage ou le restaurant étudié. Le fichier « Data_Menageres_Rebena_et_al. xlsx » regroupe les données sur l'enquête menée auprès des ménagères : niveau « ménages » : caractéristiques du ménage de l'habitat et du matériel de cuisson, quantités et types d'huile consommés, pratiques d'approvisionnement en huile rouge et plats préparés ; niveau « Details conso þ appro » : consommation en huiles végétales et approvisionnement en détail ; niveau « Plats » : plats réalisés à l'huile de palme, les types, caractéristiques et critères de choix des huiles, décrits avec les mots des ménagères.
Deux fichiers de données sont disponibles sur le centre de stockage Dataverse DOI: 10. 18167/DVN1/D5HNOK. Pour chaque fichier, sur la première feuille (métadonnées) sont décrits et explicités codages et dénominations utilisés dans les feuilles suivantes qui correspondent chacune à un niveau d'enquête et contiennent un champ identifiant le ménage ou le restaurant étudié. Le fichier « Data_Menageres_Rebena_et_al. xlsx » regroupe les données sur l'enquête menée auprès des ménagères : niveau « ménages » : caractéristiques du ménage de l'habitat et du matériel de cuisson, quantités et types d'huile consommés, pratiques d'approvisionnement en huile rouge et plats préparés ; niveau « Details conso þ appro » : consommation en huiles végétales et approvisionnement en détail ; niveau « Plats » : plats réalisés à l'huile de palme, les types, caractéristiques et critères de choix des huiles, décrits avec les mots des ménagères.
Peptides were identified with X!TandemPipeline open source software by spectrum matching approach. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD015856". The MS data were processed in order to identify specific interaction signals. Global specific spectra from samples were normalized, as described in  (40) , between replicate series. We used a cut-off of two normalized spectra as minimum MS signal for network hit validation. Normalized spectra were then averaged between replicates and referenced versus control to calculate the number of 'Referenced Spectra'. Calculation of the 'Specificity Index' score is the ratio of the averaged normalized spectra in control versus assay. The 'Specificity Index' varies from 0 to 1 (with a maximum threshold of 1) as the specificity decreases.
For the AP-MS experiments with aRNase J as bait, nuclease and nuclease-free assays were run in triplicate, whereas for ASH-Ski2 the same analyses were performed in 4 replicates. For aRNase J n = 6 for the controls and for ASH-Ski2 n = 8 for the controls. For ASH-Ski2, we took only into consideration hit proteins detected independently in both His-Tag orientations. The effect of nuclease has been identified as: Nucl. Effect = 100 × Spectra No Nuclease -Spectra Nuclease Spectra No Nuclease Diagram networks have been created using Cytoscape 3. 7. 2 software  (41).
Multiple sequence alignments and phylogenetic tree constructions The complete archaeal and bacterial genome entries were retrieved from the EBI (European Bioinformatics Institute). The collection of helicases from super-families SF1 and SF2 were identified by RPS-Blast of Pfam domains DEAD (PF00270) or Helicase C (PF00271) among a set of completely sequenced non-redundant genomes composed of 114 archaeal genomes and 1105 bacterial genomes. A total of 17 661 helicases were identified and further compared to each other using the BlastP program. Partitioning of the all-vs-all Blast results was achieved using the Markov Cluster Algorithm  (42)  and resulted in 84 clusters of >5 orthologous archaeal helicases. The archaeal sequences were collected and corresponded to occurrences with COG1202 for ASH-Ski2.
We also collected an initial set of proteins using COG profile annotations (COG1096 for Csl4 and COG0689 for Rrp41) from complete archaeal genomes. Hidden Markov model (hmm) profiles were built for each family and used with hmmsearch (HMMER package, (  43 )) to identify homologues in our archaeal proteome sample. In addition, to identify potential unannotated genes and pseudogenes, we performed tblastn searches. The archaeal phylogenetic tree was inferred from a concatenated dataset of 81 protein families obtained from COG annotation. If multiple copies occurred in a genome, all paralogues were removed. The sequence alignments for each family were created using the MUSCLE program  (44)  with the default parameters. We used the trimAl program  (45)  to remove spurious sequences and poorly aligned positions and to analyse the quality of the alignments according to gap numbers and residue conservation in the columns of the alignments.
These parsed alignments were concatenated to produce a single alignment of 17 827 residues. When a species did not have a record for a family, the missing sequence was replaced by gaps in the alignment. The maximum-likelihood tree was computed with PhyML  (46)  and the optimal combinations of parameters was selected using ProtTest3 program  (47). The LG model of sequence evolution was used and the gamma-distributed substitution rate variation was approximated by eight discrete categories with shape parameter and proportion of invariant sites estimated from the data. The statistical branch support was inferred with the parametric bootstrap. The archaeal Ski2-like helicase alignment was built by Mafft incorporating local pairwise refinement (L-INS-i) up to 2000 iteration (maxiterate 2000) (  48 ) and trimmed with trimAL as described above.
ACKNOWLEDGEMENTS We are indebted to  L. Correia  of the  Paris Sud Ouest PAPPSO proteomics core facility  (http://papso. inra. fr)which is supported by  INRA  (http://www. inra. fr), the  Ile-de-France regional council  (https://www. iledefrance. fr/education-recherche),  IBiSA  (https://www. ibisa. net)and  CNRS  (http://www. cnrs. fr)for LC/MS analyses and to L. Correia. We thank  Y. Quentin  for its expertise in taxonomic identification of archaeal Csl4 and Rrp41 members,  L. Plassart  and  J. Caumes  for technical help and  P. Vitali  and  M. Kwapisz  for helpful discussions.
FUNDING CNRS; University Paul Sabatier;  University of Western Britany; Ifremer; University of Toulouse ,  Idex-emergence program  (to B. C. O. );  French Ministère de l'Enseignement Supérieure et de la Recherche PhD Fellowship  (to D. K. P and C. E. );  French 'Agence Nationale pour la Recherche'  [ ANR-16-CE12-0016  to B. C. O];  Funding for open access charge: ANR  [ ANR-16-CE12-0016-01 ].
Remerciements Nous remercions particulièrement l' INRA, Idele, Itavi, Ifip pour le financement du travail et l'ensemble du groupe de travail « Efficience des productions animales » du GIS Élevages Demain  ( membres de l'INRA, Idele, Itavi, Ifip, CIV, Terres Univia, FranceAgriMer ) ainsi que les différents stagiaires, ingénieurs, chercheurs et autres experts des filières pour leur contribution au projet et leur apport en données indispensables. Nous remercions également les deux lecteurs critiques qui ont grandement contribué à améliorer ce manuscrit.
Biochemistry Human LSD1 (KDM1A) (lysine (K)-specific demethylase 1A) was purchased from BPS Bioscience (catalog No 50097). Monomethylated histone peptide H3K4N(CH 3 ) was purchased from Pepscan and horseradish peroxidase (HRP) from Pierce (Catalog No. 31490). The reagents for buffer preparation were purchased from Merck, Netherlands. Reactions were conducted in black 96-well flat-bottom microplates (Corning). The fluorescence measurements were carried out in a Synergy H1 Hybrid Multi-Mode Microplate Reader (BioTek, USA) and the gain setting of the instrument was adjusted to 70. GraphPad Prism 5. 0 was used for determination of the half-maximal inhibitory concentration (IC 50 ). Nonlinear regression was used for data fitting.
Homology modeling The amino acid sequence of SmLSD1 was retrieved from Uniprot  [27]  (accession number: G4VK09). Subsequently, alignment of SmLSD1 and HsLSD1 sequences was performed using MOE version 2018. 01 (Molecular Operating Environment (MOE), 2018. 01; Chemical Computing Group Inc. , Canada). Long inserts in the sequence of SmLSD1 (aa: 205-271, 324-385, 828-860, 883-910, and 965-983) were deleted and consequently not modeled. The saved alignment file was used to generate a homology model of SmLSD1 based on the cocrystal structure of hLSD1 with MC2580 (PDB ID 2XAS)  [26]  using MODELLER 9. 11  [28].
Ligand preparation Similar to the observed adduct of the analogous tranylcypromine derivative MC2584 with FAD (PDB ID 2XAQ  [29] ), an N5 adduct of MC3935 with FAD was generated in MOE using only the flavin ring of FAD. The generated adduct was then cured using LigPrep (Schro ¨dinger Release 2018-1): protonation states were assigned at pH 7±1 using Epik, tautomeric forms, as well as possible conformers were generated, and energy minimized using the OPLS03 force field. As a result, 25 low-energy conformers were generated using the bioactive search module implemented in Schro ¨dinger.
SmLSD1 mRNA quantification After treatment, the total RNA was extracted using a RiboPure kit (Ambion) followed by DNase treatment (Ambion) and cDNA synthesis (Superscript III, Invitrogen), following the manufacturer's instructions. The resulting cDNA was diluted 10-fold in water and qPCR amplification was performed with 5 μL of diluted cDNA in a total volume of 15 μL using SYBR Green Master Mix (Life Technologies) and specific primer pairs listed in S12 Table were designed for S. mansoni genes by Primer3 online software (http://www. bioinformatics. nl/cgibin/primer3plus/primer3plus. cgi). QuantStudio 3 Real-Time PCR System (Applied Biosystems) was used. The results were analyzed by the comparative Ct method, the graphs were plotted using GraphPad Prism 8 software, and statistical significance was calculated with the Student´s t-test.