dataesr/scientific-paragraphs-categorization huggingface dataset:
More recently, it has also been demonstrated that Bayesian outperforms traditional parsimony for discrete morphological characters at variable evolutionary rates, with and without missing data  [51, 52] , although with some potential loss of resolution  [52]. Additionally, Bayesian analyses allow explicit considerations regarding variations in evolutionary rates and branch lengths among characters, and between the morphological and molecular partitions of the dataset  [38, [53] [54] [55]. For the above reasons, we illustrate the result of the Bayesian inference analysis as our preferred result (based on methodological reasoning). However, for comparative purposes, we also report on the results obtained from both the MP analyses (see also the electronic supplementary material). Type species † Jeddaherdan aleadonta sp.
Phylogenetic position Jeddaherdan aleadonta and Gueragama sulamericana are based on a single fragmentary dentary specimen each. Therefore, despite the relatively well-sampled amount of mandibular characters for acrodontans in the present dataset, the strict consensus of the traditional MP analysis could not find resolution at the early divergence of acrodontans (figure  4a ). It can be determined, however, that J. aleadonta (and G. sulamericana) are nested within Acrodonta. In the IWMP analysis (figure  4b ), the early dichotomy between chamaeleonids and agamids, as obtained by Hutchinson et al. [34] , is not retrieved, nor a monophyletic Leiolepidinae sensu Frost & Etheridge  [77]. Instead, Leiolepis falls as the sister taxon to Uromastycinae (here being inclusive of Uromastyx, Jeddaherdan and Gueragama), and a clade formed by Chamaeleontidae + Agaminae sensu Frost & Etheridge  [77].
Under Bayesian inference (figure  5 ), the analysis we consider most appropriate to our dataset (see Material and methods), Jeddaherdan and Gueragama are nested with Uromastyx, as they also are in the IWMP tree (although forming a monophyletic Leiolepidinae with Leiolepis), and leiolepidines are the sister clade to Chamaeleontidae + 'agamines'. The early divergence of leiolepidines (either forming a monophyletic group or a Hennigean comb), followed by the divergence of chamaeleontids and agamines, is a similar result to the one obtained using MP of morphological data by Gauthier et al. [2] , and both ordered and unordered modified versions of that dataset in Simões et al. [78]. This overall topology was also obtained using molecular data under maximum-likelihood  [4] , and in combined dataset analyses of Wiens et al.
[7]  and Reeder et al. [3]  using MP. All these results differ from another commonly inferred hypothesis of acrodontan relationships, in which the dichotomy between chamaeleontids and all other acrodontans (Agamidae) occurs early in acrodontan evolution, as previously inferred using both morphological and/or molecular data, under multiple tree inference methods  [3, 6, [79] [80] [81] [82] [83] [84] [85] , including the analysis of the present dataset without Jeddaherdan and Gueragama  [34]. Importantly, under all of the phylogenetic analyses just discussed (and regardless of the position of chamaeleonids), the lineage leading to Uromastyx is always found as one of the earliest diverging ones in the phylogenetic history of acrodontans whenever Uromastyx or other uromastycines are included  [1] [2] [3] [4] 6, 7, [79] [80] [81] [82] [83] [84] [85].
Nevertheless, the result for G. sulamericana could be affected by the reduced number of non-acrodontan iguanians in the dataset used herein, and thus increasing the sampling of the latter could help to better assess the transition between acrodontans and other iguanians. A future updated morphological dataset of acrodontan iguanians containing a diverse sample of well-constructed morphological characters (and with a more complete sampling of non-acrodontan iguanians) shall provide important insights into early acrodontan evolution, and the position of Gueragama within the group. One important consideration in every phylogenetic analysis of very fragmentary fossil taxa is the potential effects of missing data upon their placement on the tree, which may cause fossils to be found more rootward on the tree  [89] [90] [91].
Acknowledgements. We thank  Philippe Loubry  ( MNHN ) for taking the photographs of the holotype of Jeddaherdan. We thank  Elizabeth Glynne  for English corrections. We thank  Ronan Allain  (MNHN),  Alan Resetar  (FMNH),  Lauren Vonnahme ,  Margareth Arnold ,  David Kizirian  and  Christopher Raxworthy  (AMNH),  Jonathan Losos  and  José Rosado  ( MCZ ) for specimen access. We thank  Noureddine Jalil  and  Mehdi Mesmoudi Padinha  for discussions on the etymology of new species name. We appreciate the information shared by the colleagues of one of the authors (J. C. R. ) from  Montpellier, Tlemcen, Oran  and Tunis which permitted us to cite the unpublished presence of acrodontans in the  Eocene of Africa. We thank the  Willi Hennig Society  for the free availability of the software TNT. The fossil specimen under study herein is currently housed at the  Muséum National d'Histoire Naturelle, Paris, France.
Acknowledgements Y. T. and G. S. contributed equally to this work. The authors acknowledge funding support from the  Walloon Region  ( WCS  Project  N° 1117306 ), from the  European Commission / Walloon Region (FEDER -Smartfi  lm  RF  project), from the  Interuniversity Attraction Pole program of the Belgian Federal Science Policy Offi ce  ( PAI 7/05 ), from the  Programme d'Excellence de la Région Wallonne  ( OPTI2MAT  project), from the  Belgian National Fund for Scientifi c Research (FNRS - Project  N° 2. 4565. 11 ),from a concerted research action of the  French Community of Belgium  ( ARC  Project  N° 20061 ), from a  Marie Curie IIF Scheme  of the 7th  EU Framework Program  for the  DISCO-project  (Grant No. 298319 ), from a  Grant-in-Aid for Scientifi c Research  (Grant Nos. 26620104  and  26102001 ) by the  Japan Society for the Promotion of Science (JSPS) , from  Shorai Foundation for Science and Technology , from The  Murata Science Foundation  and the  ERC  project  SUPRAFUNCTION  ( GA-257305 ).
Y. G. has benefi ted from a mandate of  Francqui Research Professor. G. S. kindly acknowledges postdoctoral fellowship support from the  Wiener-Anspach Foundation. P. S. acknowledges also the  Agence Nationale de la Recherche  through the  LabEx CSC  ( ANR-10-LABX-0026_CSC ) and the  International Center for Frontier Research in Chemistry (icFRC). D. B. and J. C. are FNRS Research fellows. Crystallographic data for isomer 3 were measured at the DIAMOND light source by the  UK National Crystallography Service.
Acknowledgements Research culminating in the derivation of this line was funded by a grant ( PM07321 ) from  Scottish Enterprise Economic Development Agency  to PDS, MB and AC. Images of embroid body staining were kindly provided by  S. Greenhough  and  J. Gardner ,  Roslin Cellab Ltd. The oocyte activation protocol was developed with the assistance and guidance of  Dr. A. Bos-Mikich.
These data suggested that the sop mutations affect the production or the stability of specific mRNA isoforms generated from the pas2-1 locus. To understand the splicing defects present in pas2-1 mutants, we cloned and sequenced the PAS2-1 RT-PCR products. Four different isoforms were identified (for sequence detail see S3 Fig). The longest isoform (PAS2-1 LONG ) corresponded to an incompletely spliced PAS2 mRNA, which retained the 8th intron leading to the production of an mRNA with a premature termination codon (PTC). The shortest (PAS2-1 SHORT ) PCR product lacked the 8th exon resulting in a direct fusion of Exon 7 to Exon 9, which results in a frame shift leading to the loss of the stop codon. The band with a size similar to wild type corresponded to a mix of two isoforms. One corresponded to a mispliced isoform (PAS2-1 MIDb ) that used a cryptic splicing donor site (GT) seven nucleotides upstream of the pas2-1 mutation, and also resulted in the loss of a stop codon.
Genomic DNA sequencing and SNP determination Total genomic DNA isolated from whole 12 day old seedlings was extracted using the DNeasy Plant mini kit (Qiagen) according to the manufacturer's instructions. For genome sequencing of sop1-1, DNA was prepared into indexed fragment libraries with amplification and sequenced on an Illumina GAIIx instrument to a minimum of 30 M reads per sample, each with 76 nt read length. Using a custom Perl script, reads were trimmed to 65 nts to remove ends of biased composition and low quality. Reads were mapped to the TAIR10 genomic reference (www. arabidopsis. org) using GenomeMapper in the SHORE software suite  [63]. Single nucleotide polymorphism (SNP) variants were determined using SHORE version 0. 6 using a consensus minimum coverage of 3 reads. Overlap of SNPs with known genomic features, and functional consequences of SNPs were computed and summarized using FEATnotator  [64].
0. 5  [66] , with only uniquely mapped reads retained for further analysis. Read number aligned to annotated exon regions (TAIR10) for each annotated gene was computed using a custom Perl script. For genes with multiple isoforms, exons from the representative gene model (TAIR10) were used. Differential expression between samples was analyzed pairwise using NOISeq ver. 2. 0. 0  [67] , an R bioconductor package that uses read count data as input. NOISeq was used to simulate 5 samples within each condition (nss parameter), permitting 0. 2% of total reads in each condition for each simulated sample (pnr parameter) and a variability (v parameter) of 0. 02 in total sequencing depth of simulated samples. Normalization (norm parameter) was according to the RPKM calculation, and for genes with zero read counts, a pseudo count of 0.
5 was used (k parameter) for computing RPKM. Correction factor for length normalization (lc parameter) was set to 1, indicating counts to be divided by a single order of length. The NOISeq pipeline was repeated for exons alone, and for full length genes (both exons and introns included). RNAseq reads have been deposited in the NCBI short read archive (SRA) under the accession numbers listed in the BioProject PRJNA293799.
Acknowledgments We are very grateful to  Mathilde Séguéla-Arnaud  and  Raphaël Mercier  for their help during the genome sequencing of sop2 and sop3. We thank  Martine Pastuglia  and  David Bouchez  for the ton2-12 allele;  Emilio Martinez de Alba  and  Allison Mallory  for the upf1-5 and upf3-1;  Florent Bardou  and  Martin Crespi  for the RRP4-GFP construct and  Magali Goussot  for the BAC containing SOP1. We thank  Christopher Lima  for sharing his point of view on the possible effect of sop2-1 mutation on the exosome structure. We thank  James Ford  and  Zach Smith  for sequencing laboratory work,  Greg Zynda  for assistance with sequence data processing (IU CGB) and to  Le-Shin Wu  ( IU CGB ) and  Bruno Wauthier-Wurmser  ( INRA Jouy ) for their help in setting up the Jbrowse website. We are grateful to  H.
The pellet was then transferred by resuspension to an autoclaved tube and freeze-dried. A tube of unused sampling liquid was treated in the same way and used as a negative control. Total DNA was extracted from each leaf and airborne sample with the DNeasy 96 Plant Kit (QIAGEN). Foliar DNA samples from the same tree were pooled, as were foliar DNA samples from the three adjacent grapevine stocks. Fungal Internal Transcribed Spacer 2 (ITS2) was amplified with the fITS7 (forward) and ITS4 (reverse) primers  (Ihrmark et al. , 2012). Paired-end sequencing (300 bp) was then performed in a single run of an Illumina MiSeq sequencer, on the basis of V3 chemistry. Polymerase Chain Reaction (PCR) amplification, barcodes and MiSeq adapters addition, library sequencing and data preprocessing were carried out by the LGC Genomics sequencing service (Berlin, Germany).
, 2010). All the sequences were then concatenated into a single fasta file, after adding the sample code in the label of each sequence. The sequences were dereplicated, sorted and singletons were discarded with VSEARCH (https://github. com/torognes/ vsearch). The sequences were then clustered into molecular operational taxonomic units (OTUs) with the UPARSE algorithm implemented in USEARCH v8  (Edgar, 2013) , with a minimum identity threshold of 97%. Additional chimera detection was performed against the UNITE database (Ko ˜ljalg et al. , 2013), with the UCHIME algorithm implemented in USEARCH v8  (Edgar et al. , 2011). The OTU table, giving the number of sequences of each OTU for each sample, was created with USEARCH v8. OTUs were taxonomically assigned using the online BLAST web interface  (Madden, 2013)  against the GenBank database, by excluding environmental and metagenome sequences.
, 2016). It is highly probable that OTUs assigned to Erysiphe alphitoides, the agent responsible for the oak powdery mildew (1. 5% of the negative control sequences;  Jakuschkin et al. , 2016)  or Botrytis cinerea, responsible for the grey mold on grapes (1. 2%;  Jaspers et al. , 2016)  are likely crosscontaminations because they are strongly related to a specific host. Moreover, the removal of very abundant OTUs strongly altered the taxonomic composition of the samples, and removed some species known to be abundant on leaves such as Aureobasidium pullulans, known as very abundant on grapevine  (Pinto & Gomes, 2016). We thus decided to retain all these OTUs in the dataset. Two samples containing very few sequences (< 300 sequences) were removed. These samples corresponded to grapevine leaves collected at the Couhins site, in May.
Taxonomic assignment of the 10 most abundant OTUs by the online BLAST analysis against the GenBank database. The environmental and metagenome sequences were excluded. Identity is the percentage identity between the OTU representative sequence and the closest matching sequence in GenBank. Taxa shown as unassigned at the species level (sp. ) indicate OTUs assigned to at least two species of the same genus with identical e-value. Relative abundance are percentage of abundance of each data subset and brackets contain the rank of the OTU in each data subset.
ACKNOWLEDGEMENTS We thank the vineyard managers for allowing us to carrying out these experiments in their domains:  Nicolas Lesaint  in  Chateau Reignac, Mathieu Arroyo in Chateau Couhins , and  Antoine Le Grix de la Salle  in Chateau Grand-Verdus. We thank  Morgane Petitgenet  for assistance with sample collection, and  Olivier Fabreguettes  and  Jessica Vallance  for providing help and advice for DNA extraction and bioinformatic analyses. We thank the entire  LGC  genomics team for assistance and advice concerning sequencing.
Sources permitting to gauge the financial aspects of literary and artistic reviews are hard to come by; our data, mainly based on the review itself and La Plume's unpublished correspondence, may well be less objective than if collected from an independent source. In order to promote their journal, editors are known to have exaggerated their print run or financial figures. With this in mind, our data was tested data for congruity through comparison of different sets in order to extract reasonably convincing numbers. Nonetheless, there remains a risk of unreliability in the statements made by the journal. In its first period, La Plume attracted its readership by a double strategy. Not only did the journal open its pages to aspiring writers, it also promoted their work and their names amongst confirmed authors and Parisian celebrities, the latter receiving free copies of the review.
Crisis Although La Plume started out as a periodical by writers for writers, this was not the kind of long-term venture Deschamps was aiming for. 29 The restricted number and spending capacity of young writers were indeed limiting factors for the prosperous business model he appears to have picked up from practices of the time. Thus, in July 1891, only two years after its inception, Deschamps asserted that the development of his review in its present form had reached its peak, given that every writer and poet in Paris had subscribed to it. 30 Although we doubt this to be true, the financial figures of the review confirm that the circulation had not increased in the previous eighteen months. 31 It must be noted that the financial data come from the review itself and are only available for certain years, as La Plume did not reveal its finances on a regular basis.
In 1890 the review ran 1,100 copies per issue, in 1891 between 1,200 and 1,800. 32 However, Deschamps never mentioned the actual sales. We have deduced them from the financial figures collected from various sources. The receipt for Verlaine's Dédicaces provides us with precious insight into La Plume's printing costs. 33 This document, reproduced on the cover of the review's twentyfifth issue, reveals that printing of the review's eight pages including the paper cover and graphic supplement amounted to five centimes per copy. As for its financial figures of La Plume, they may have been falsified by Deschamps. However, an analysis of printing costs throughout France at the end of the nineteenth century is consistent with the figures published in La Plume, and confirms the data we collected for 1890.
Through twin experiments, the assimilation of synthetic spectral reflectances matching the MODerate resolution Imaging Spectroradiometer (MODIS) spectral bands is examined over five seasons at the Col du Lautaret, located in the French Alps. Overall, the assimilation of MODIS-like data reduces by 45 % the root mean square errors (RMSE) on snow depth and snow water equivalent. At this study site, the lack of MODIS data on cloudy days does not affect the assimilation performance significantly. The combined assimilation of MODIS-like reflectances and a few snow depth measurements throughout the 2010/2011 season further reduces RMSEs by roughly 70 %. This work suggests that the assimilation of optical reflectances has the potential to become an essential component of spatialized snowpack simu-lation and forecast systems.
, 2009). In particular, the MODIS sensor, onboard the TERRA and AQUA satellites, offers a daily coverage and provides reflectance measurements in seven bands distributed in the visible (at 250 to 500 m spatial resolution), near and shortwave infrared wavelengths. Surface bi-hemispherical reflectances corrected from complex topographic effects in mountainous areas can be computed  (Sirguey et al. , 2009)  and have been evaluated and used in several rugged areas  (Dumont et al. , 2012; Brun et al. , 2015). The work presented in this article examines the possibility, the relevance and the limitations of assimilating visible and near-infrared satellite reflectances into a multilayer snowpack model. A convenient approach, known as twin experiment, uses synthetic data in the same spectral bands than the real data, to examine the content of information of the observations, and the impacts we can expect from their assimilation.
In twin experiments, the model used to create the synthetic data is the same as the model used for the assimilation. The synthetic observations are extracted from a member of the ensemble considered as the true state. Twin experiments are preferred in this first study in order to focus on the information content of the observations and to avoid the problem of observational biases. Data assimilation is performed with a particle filter and a Sequential Importance Resampling (SIR) algorithm  (Gordon et al. , 1993; Van Leeuwen, 2009 , 2014). The particle filter is easy to implement, free of hypotheses about the nature of the model and the observations, and provides uncertainties in the estimation of the snowpack state. For a comprehensive snow simulation evaluation, as recommended by  Essery et al.
General settings and diagnostics The assimilation experiments are twin, meaning that the observations are synthetics and come from a single model simulation. They are performed over five winter seasons at the CdL area. A synthetic truth simulation is first obtained by running Crocus, through the use of the radiative transfer model TARTES, forced by one perturbed meteorological forcing, as detailed in Sect. 3. 3. The synthetic observations used in all the assimilation experiments reported in Sects. 5 and 6 are extracted from this synthetic truth simulation. The synthetic truth simulation is also considered as the truth to evaluate the performance of data assimilation in terms of SD and SWE variables. Data assimilation performances are evaluated by comparing RMSE for ensembles with and without assimilation, and by comparing the synthetic true simulation to the 33rd, 50th, and 67th quantiles from the ensembles with assimilation.
Assimilation of MODIS-like reflectances In this section, we assess to what extent the assimilation of the available MODIS-like reflectance observations allows the accurate estimation of snowpack properties throughout the season. This experiment will be considered as our baseline experiment. Data assimilation results for the 640 and 1240 nm reflectance (first and fifth MODIS bands) and for SD and SWE over the hydrological season 2010/2011 are shown in Fig. 3. To mimic real cloud conditions, reflectances are assimilated at 34 clear sky days of the season. We define a clear sky date according to the real cloud mask from MODIS data computed with the method of  Sirguey et al. (2009). The corresponding 640 and 1240 nm synthetic reflectance observations are shown by the red dots in Fig. 3a  and b.
This algorithm uses a first-order autoregressive model to account for the temporal correlations in the meteorological forcing uncertainties. This ensemble of meteorological forcings is then applied to generate the ensemble of snowpack simulations for the assimilation. Twin experiments are conducted at one point in the French Alps, the Col du Lautaret, over five hydrological years. The assimilated reflectance data corresponds to the first seven spectral bands of the MODIS sensors. Reflectance assimilation using only data from clearsky days reduces the SD and SWE seasonal RMSE by a factor close to 2. The uncertainty range on the snow meltout date drops to 9 days compared to 24 without assimilation. Additional assimilation tests using different time distributions of the observations show that (i) reflectance assimilation greatly improves snowpack estimates if the observation comes after an extended period without precipitation, (ii) the assimilation has almost no impact if it comes right after a snowfall, and (iii) using only a few observations with the appropriate timing, i.
Acknowledgements. We wish to thank the two anonymous reviewers for their detailed comments. We gratefully acknowledge funding from  Labex OSUG@2020  (Investissements d'avenir - ANR10 LABX56 ) and  Fondation Eau Neige et Glace. This work has also been supported by the  INSU/LEFE/MANU program. The development of the radiative model TARTES has been funded by the  French ANR   MONISNOW  project, number  ANR-11-JS56-0005. Edited by:  X. Fettweis.
www. the-cryosphere. net/10/1021/2016/ The Cryosphere, 10, 1021-1038, 2016 of satellite observations data such as MODIS data. This model, named TARTES (Two-streAm Radiative TransfEr in Snow, To this end, a new radiative transfer model was recently implemented in Crocus to calculate spectral reflectances that can be used for the comparison and the assimilation.