dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We are deeply indebted to Aixa and Lluı ´s Tosal for the discovery of the  Tossal de Pollerini (Erillcastell)  locality and guidance to the tracksites. We acknowledge advices and suggestions of  Agustina Leucona. We thank  Ruben Garcia-Artigas ,  Mireia Plà ,  Pablo Rodrı ´guez-Salgado  and  Montse Vilalta  for making the fieldwork possible and  Xènia Aymerich  ( ICP ) for assistance in lab preparation of trackways molds and casts. Agustı ´Lopez,  Jordi Palau ,  Marc Garriga ,  Marc Cortina  are acknowledged for logistic facilities during fieldwork. Comments of  Hendrik Klein  and anonymous reviewers improved a previous version of the manuscript. We acknowledge.
Samples were washed three times by TBST and imaged using a Zeiss AxioObserver microscope equipped with Axiovision software with "shuttle & find" to mark cell locations. After fluorescence imaging, samples were fixed with 2. 5% glutaraldehyde, dehydrated in ethanol, critical point dried (Tousimis Samdri 790), and coated with chromium (EMS 150T-ES). The same cells were automatically located in the Zeiss Supra 40 Field Emission Scanning Electron Microscope and imaged with a secondary electron detector. Fluorescence and SEM images were correlated with Zeiss AxioVision.
Briefly, excised gel bands were reduced, alkylated and digested with trypsin. LC-ESI-MS/MS (liquid chromatography electrospray ionization mass spectrometry) analysis of the peptide digests was then done by C18-Reversed Phase (RP) chromatography using an Ultimate 3000 RSLCnano System (ThermoFisher Scientific) equipped with an Acclaim Pep-Map RSLC C18 column (2 μm, 100 Å, 75 μm x 15 cm, ThermoScientific, USA). The UPLC was connected to a TriVersa NanoMate nanoelectrospray source (Advion) and a linear ion trap LTQ-XL (ThermoFisher Scientific) mass spectrometer with ESI source operated in the positive ionization mode. MGF files generated from the raw LC-ESI-MS/MS data were searched by Mascot (version 2. 5. 1, Matrix Science, USA) against NCBInr90_20141124 database (25,782,812 protein sequences) with the following search parameters: trypsin; two missed cleavages; peptide charges of +2 and +3; peptide tolerance of 1.
5 Da; MS/MS tolerance of 0. 5 Da; carbamidomethylation (Cys) for fixed modification; deamidation (Asn and Gln) and oxidation (Met) for variable modifications. An appropriate decoy database search was utilized to measure the false discovery rate. The immunoprecipitation was also repeated using with MAb-EhPTP4, briefly 50 μl of Protein G sepharose beads in PBS was incubated with 20 μl of MAb-EhPTP4 or mouse negative IgG at 4˚C for 1hr. The protein G sepharose beads conjugates were washed three times with PBS and resuspended in a final volume of 500 μl cell lyses collected above. Samples were incubated at 4˚C for 2hrs with gentle shaking, then centrifuged, and the pellets were washed three times with PBS. Fifty μl of 2X protein sample buffer was ere added to each sample and the samples were then boiled for 5 min.
, 1999; Schneebeli, 2004; Kaempfer et al. , 2005; Flin and Brzoska, 2008; Chen and Baker, 2010;  Published by Copernicus Publications on behalf of the European Geosciences Union. A. Wautier et al. :  Numerical homogenization of the viscoplastic behavior of snow  Srivastava et al. , 2010; Pinzer et al. , 2012; Wang and Baker, 2013; Adams and Walters, 2014; Calonne et al. , 2015)  good databases of 3-D images for the main snow types reported in the international classification  (Fierz et al. , 2009)  are now available  (Calonne et al. , 2012; Löwe et al. , 2013). Given these extensive geometrical descriptions of snow, its corresponding macroscopic behavior can be upscaled in a more systematic way thanks to the use of techniques derived from the homogenization theory  (Dormieux and Bourgeois, 2002; Auriault et al.
(2015)  is used in this paper and easily adapted to the study of the elasto-viscoplastic behavior of snow. It consists in the four steps recalled in Fig. 1. The first two steps remain unchanged and consist in (i) meshing the 3-D microtomographic images (Step 1) and (ii) defining the kinematic relation u = E • x between the homogeneous macroscopic strain E and the displacement field u on the boundary (Step 2). Step 1 requires the use of the MATLAB open-source toolbox iso2mesh  (Fang and Boas, 2009)  while Step 2 is achieved thanks to the use of the plugin Homtools  (Lejeunes and Bourgeois, 2011). More details can be found in  Wautier et al. (2015). The next two steps (steps 3 and 4) are modified in order to take into account the change in the constitutive modeling of ice.
HomTools Step 4 Step 3 where e 2 is the second invariant of the deviatoric part of εv. If p v stands for the volumetric mechanical dissipation, the equivalent stress and the equivalent strain rate verify p v = σ : εv = s 2 e 2 = εeq σ eq = Aσ (n+1) eq. (6) At the microscopic scale, the viscoplastic deformation of ice is incompressible. Consequently the equivalent stress (or the equivalent strain rate) depends only on the second invariant s 2 of σ (or the second invariant e 2 of εv ). Overall, the ice matrix is thus modeled as an isotropic elasto-viscoplastic material in the finite element commercial software Abaqus. The values of the material constants used in this constitutive modeling, namely A, n, E and ν, are given in Table  1. It should be underlined that even if the most common values used for E and n are E = 9 GPa and n = 3, the Young modulus values of ice found in the literature range from 0.
Finally, to be consistent with the isotropy hypothesis, numerical simulations have been performed on the most isotropic snow samples with respect to their elastic behavior from the snow database used in  Wautier et al. (2015). With reference to the supporting information of the cited paper  (Wautier et al. , 2015) , the name and the principal characteristics of each sample are recalled in Table  2. The porosities of the selected samples vary from 0. 43 to 0. 87, which covers almost the entire range of porosity of seasonal snow. Each sample presents similar correlation lengths ( 1 , 2 , 3 )  (Löwe et al. , 2013; Calonne et al. , 2014)  in the three space directions. All the simulations have been performed on volumes extracted from the 3-D images sufficiently large to be considered as REV, as in  Wautier et al.
Results and discussion The homogenization and the post-processing procedure presented in the previous sections are applied to six isotropic snow samples of various densities chosen in the same database as  Wautier et al. (2015)  and already introduced in Table  2. In Fig. 4 , the seven points (S • 1 /3, S • 2 ) corresponding to the strain rates of Eq. (  21 ) are represented for these six snow samples in the plane of the two first stress invariants for n = 4. 5. Similar results have been obtained for the other values of n, as shown in Figure  5. The corresponding strain flow vectors (E • 1 , E • 2 ) are shown by solid arrows and iso-dissipation curves corresponding to fitted Abouaf models are represented by solid lines. Optimal values for f and c obtained for each snow type are presented in Fig.
Acknowledgements. We thank  Stéphane Lejeunes  and  Stéphane Bourgeois  from the LMA for sharing with us the code of their plug-in Homtools and for helping us to use it in our scripts. Tomographic images have been acquired at  ESRF  ( ID19 ) and 3SR Lab. CNRM/CEN is part of the  LabEx OSUG@2020  ( ANR10 LABX56 ). 3SR lab is part of the  LabEx Tec 21  ( Investissements d'Avenir -grant  agreement  ANR11 LABX0030 ). The authors gratefully acknowledge the anonymous reviewers,  Andrew Hansen  and  Maurine Montagnat  for their comments and advice, which helped improve the quality of the final paper. Edited by:  Martin Schneebeli Reviewed  by:  Andrew C. Hansen  and two anonymous referees.
Data availability. The original 3-D images used in this study are further described in the Supplement of Calonne et al. (2012)  and Wautier et al. (2015). They can be obtained on request (frederic. flin@meteo. fr) after signing an agreement with Météo-France. More details on the numerical tools used to convert binary images into meshes can be found in  Fang and Boas (2009)  and they can be downloaded at http://iso2mesh. sourceforge. net/cgi-bin/ index. cgi. More details on the plug-in used to performed the homogenization test (KUBC) can be found in  Lejeunes and Bourgeois (2011)  and they can be downloaded at http://www. lma. cnrs-mrs. fr/ spip. php?article171.
In particular, ethics boards often only try to minimize the risk to subjects when we are also obliged to maximize the benefit of our research to science and society, so as to honor the contribution of our subjects  12. The future value of shared data must be considered in ethical decision making. While studies lacking shared data and having opaque methodological detail are typical, some authors have embraced the challenges of sharing data and analysis methodology. Some recent examples that are particularly thorough and elegant include Waskom et al. 13  and Whitaker et al. 14  , each of which published a complete array of analysis scripts for generating all figures and results in the paper (https://github. com/mwaskom/Waskom_JNeurosci_2014 and https://github. com/KirstieJane/NSPN_WhitakerVertes_PNAS2016, respectively), and Pernet et al.
Only with user experience and reproducibility comparisons will the field be able to identify what are the preferred analytical approaches. There is a particular embrace of data sharing in the resting-state fMRI community. Since resting-state analyses methods remain in flux, sharing of this data has particular value as it allows future improvements in methods to be assessed and benchmarked relative to previous analyses. For resting and task fMRI and structural MRI, there are a number of projects that have led the way in this area, including the sibling projects FCON1000 and INDI (http:// fcon_1000. projects. nitrc. org, ref. 17), and the Alzheimer's Disease Neuroimaging Initiative (ADNI; http://www. adni-info. org). The freely available data from these studies have become invaluable resources for methodologists evaluating novel image processing algorithms, not to mention the value of the primary scientific outputs from these projects.
The BIDS apps mentioned above rely on such containers, encapsulating software packages large and small that alleviate installation of a myriad of software dependencies. Open science tools are gaining traction. For example, the CBRAIN web-based analysis service (http://www. cbrain. mcgill. ca) supports over 260 collaborators in 20 countries; the COINS service (http://coins. mrn. org) currently hosts data on over 40,000 subjects for 643 studies; the LONI Pipeline (http://pipeline. loni. usc. edu) has an average of 100,000 daily jobs from 200 different analysis workflows; the Neurovault repository (http://neurovault. org) hosts 450 public collections; and the FCP/INDI openly shares over 15,000 resting fMRI and structural MRI data sets.
Acknowledgments T. E. N. is supported by the  Wellcome Trust  ( 100309/Z/12/Z ) and  NIH  ( R01 NS075066-01A1 ,  R01 EB015611-01 ). B. T. T. Y. is supported by  Singapore   MOE Tier 2  ( MOE2014-T2-2-016 ),  NUS  ( DPRT/944/09/14 ,  R185000271720 ),  NMRC  ( CBRG14nov007 ) and the  NUS YIA. S. B. E. is supported by the  Deutsche Forschungsgemeinschaft (DFG ,  EI 816/4-1 ,  LA 3071/3-1 ;  EI 816/6-1 ), the  National Institute of Mental Health  ( R01-MH074457 ), the  Helmholtz Portfolio Theme 'Supercomputing and Modeling for the Human Brain'  and the  European Union Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 604102 ). M. H. was supported by funds from the  German federal state of Saxony-Anhalt  and the  European Regional Development Fund (ERDF) , project:  Center for Behavioral Brain Sciences , and  CRCNS BMBF/NSF  ( 01GQ1411/1429999 ).
present, ii. absent], (9) reticulated dorsal pattern (which consists of a fine network of white or yellow lines on the dorsal region, sides of the head and body with a dark brown to brown background) [i. present, ii. absent],  (10)  ventral coloration, and  (11)  iris coloration. Coloration in life was obtained from digital color photographs. Calls recorded by us were obtained with a Sennheiser K6-ME67 directional microphone and an Olympus LS-10 digital recorder. Calls described by Duellman and Pyles  [27] , Lougheed et al. [19] , and Jansen et al. [4]  were also included and reanalyzed. Spectrograms were generated with Raven 1. 5 software  [28]  using a Fast Fourier Transformation (FFT) from a sample of 1024 points and a frequency resolution of 43. 1 Hz. Calls of the members of the D. leucophyllatus-triangulum complex consist of two components, the first note (Type I) is a pulsed trill and the second note (Type II) is similar to Type I but shorter  [19].
Temperature can influence quantitative parameters of frog calls including dominant frequency, pulse rate, and call length  [31]. However, variation in recording temperature was relatively low (< 3 C˚) with the exception of clade A (range variation of 6. 8 C˚). Thus, temperature should not significantly influence our comparisons. Original recordings (see S1 Table ) are deposited in the audio archive of the QCAZ (available at the AmphibiaWebEcuador website, http://zoologia. puce. edu. ec/Vertebrados/anfibios/), the Fonoteca Zoologica of MNCN (http://www. fonozoo. com/) and the Macaulay Library at the Cornell Lab of Ornithology (http://macaulaylibrary. org/). We also assessed the Red List status of each species according to the IUCN Red List criteria (IUCN 2001). Geographic ranges were estimated using minimum convex polygons in software ArcMap 10  [32].
Phylogenetic analyses To determine phylogenetic relationships between species of the Dendropsophus leucophyllatus species group we used the DNA sequences including sequences from GenBank. For the outgroup, we added samples of Dendropsophus brevifrons, D. carnifex, D. parviceps and D. rhodopeplus (based on Pyron and Wiens  [16] ). All samples used are listed in S3   [35] ) and the alignment was adjusted by hand. Because it is likely that variation in each of our sampled genes (or codon positions within protein coding genes) were shaped by different evolutionary processes, we partitioned the data according to gene and codon position to analyze each partition under separate models of evolution. We used software PartitionFinder v. 1. 1. 1 [36]  to simultaneously estimate both the best-fit model for each partition and the best partition strategy for our data.
05 between runs. Tracer software version 1. 5  [37]  was used to confirm convergence and stationarity of the parameter estimates using an ESS threshold of 200. Phylogenetic analyses were carried out in MrBayes 3. 2  [38]. Maximum likelihood analyses were conducted using GARLI 2. 0  [39]  with default settings. Analyses were terminated after 10 000 generations without an improvement in tree topology. We ran a total of 20 independent searches and used random starting addition (streefname = random) to reduce the probability of inferring a suboptimal likelihood solution. Support was evaluated using 100 bootstrap replicates with each replicate terminated after 5000 replications without improvement in topology. Uncorrected mean between-species genetic distances were calculated in MEGA 5  [40]  for gene 16S given that this is generally used to compare divergence among Amphibian species (e.
Species delineation Species limits among populations of Dendropsophus leucophyllatus-triangulum were evaluated using three independent character sets: genetic, bioacoustic, and morphological. Following Fouquet et al. [3] , we classified pairwise genetic uncorrected p-distances in the 16S rRNA gene as follows: low divergence, below 3%; moderate divergence, 3-5%; high divergence, above 5%; very high divergence, above 7%. We used the predefined 3% threshold for species delimitation (i. e. , groups with distances > 3. 0% were considered candidate species  [3] ). This is a conservative threshold because various studies have shown that sister species among hylids are frequently separated by lower distances (e. g. [8, [41] [42] [43] ). We classified genetic lineages into the following categories: (1) Confirmed Candidate Species (CCS) when there was covariation between genetic and bioacoustic or morphological data sets, (2) Deep Conspecific Lineages (DCL) when such covariation was not found, and (3) Unconfirmed Candidate Species (UCS) when bioacoustic and morphological data were unavailable.
Acknowledgments Patricia Herrera  and  Kathia Rivero  ( Museo Noel Kempff Mercado ,  Santa Cruz de la Sierra ) provided valuable assistance to obtain collecting permits in Bolivia. William E. Duellman  ( Natural History Museum, University of Kansas ),  I. De la Riva  (MNCN),  S. Reichle  (The  Nature Conservancy, Southern Andes Conservation Program ),  P. Gaucher  ( French National Centre for Scientific Research ) and The  Cornell Lab of Ornithology  provided call recordings from  Ecuador, Bolivia, Peru and French Guiana. For providing access to herpetological collections we thank  M. Calvo  (MNCN),  R. McDiarmid  (USNM), and  R. Sosa  (MNK). Liliana Jaramillo , Sebastian  Espinoza Ulloa  and  Gabriela Castillo  helped with laboratory work. We are particularly thankful to Paul and  Diana Szekely , who provided photos of the syntypes of Hyla membranacea.
This work was supported by  BIOPAT. Field and laboratory work were funded by grants from the  Secretarı ´a Nacional de Educacion Superior, Ciencia, Tecnologı ´a e Innovacion del Ecuador SENESCYT  ( Arca de Noe  ´initiative; SRR principal investigator), and a grant from  Pontificia Universidad Catolica del Ecuador of the Direccion General Academica (DGA)  department for SRR. AF's contribution to this work has benefited from an " Investissement d'Avenir " grant managed by  Agence Nationale de la Recherche  (CEBA, ref. ANR-10-LABX-25-01 ),  France. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The cover glasses was precoated for 1. 5 h with protein concanavalin A, 0. 5 mg ml À 1 in 0. 01 M PBS, to immobilize yeast cells on the surface. The coating did not induce any stress response. By combining neutral density filters, the illumination intensity was in most experiments set to 115 mW in the microscope field of view, unless otherwise noted. GFP fluorescence imaging was accomplished with a mercury lamp, an excitation filter (470 ± 20 nm), a dichroic mirror (505 nm) and an emission filter (515 ± 15 nm) (Chroma Technology) using the Nikon microscope. On the Olympus microscope, GFP was imaged using a quadruple emission filter at 521 ± 17 nm and an excitation bandpass filter at 485 ± 10 nm. The microscope setups were controlled with the NIS-Elements software (Nikon) and the Xcellence software (Olympus), respectively.
HyPerRedSc fluorescent imaging was accomplished in the Olympus system using a quadruple filter set with 606 ± 25 nm for detection and an excitation bandpass filter at 560±12. 5 nm was used for imaging. Illumination of cells. Illumination of cells was accomplished simultaneously with GFP excitation as previously described  14. Cells were continuously illuminated with blue light (450-490 nm) and fluorescence images were typically acquired every 4 s. Bright-field images acquired once every 60 s with a small focus offset were used to identify cells in the CellStat software  14. After each Msn2-GFP imaging experiment, non-illuminated cells were imaged to ensure that only cells that had been exposed to light exhibited nuclear Msn2p localization. H 2 O 2 treatment. Growth medium containing H 2 O 2 at the desired concentration was injected into the perfusion chamber at the start of the experiment.
Bright-field and fluorescence images were captured every 30 s at a low intensity (26 mW) to avoid light-induced stress (Supplementary Fig. 1c ). The H 2 O 2 solution was made fresh before the start of each experiment. Image and signal analysis. Image and signal analysis was performed using the CellStat software  14. To quantify the degree of Msn2 nuclear localization, the signal intensity in the nucleus was compared with that in the cytosol  14. Signal analysis was implemented using routine MATLAB commands. The nucleocytoplasmic localization trajectories were ordered in MATLAB by means of non-metric multidimensional scaling from low responders to high responders  65. Cytosolic H 2 O 2 determination by HyPerRed. Median HyPerRedSc and HyPerRedScC199S fluorescence values for each cell and time point was exported from CellStat following cell recognition as for Msn2 signal analysis.
Acknowledgements Christoph Schu ¨ller and  Thomas Nystro  ¨m are acknowledged for comments on the manuscript and we thank  Anders Blomberg  and  Gustav Ammerer  for support throughout this study. We are also grateful to  Dorothea Anrather  and  David Hollenstein  for help with MS analyses;  Marija Cvijovic  for help with statistical analyses;  Frederik Eisele ,  Takahashi Tatsuta ,  Thomas Langer ,  Joseph Heitman  and  Joakim Norbeck  for providing reagents, and the  Centre of Cellular Imaging, Sahlgrenska Academy , for the use of imaging equipment and support from the staff. The Olympus Cell^R microscope was purchased with support from  Ingabritt och Arne Lundbergs stiftelse. This work was supported by grants from the  Swedish Research Council  (to M. M. ), by the foundations of Olle Engkvist Byggma ¨stare and  Carl Trygger  (to M.
2a ). Since predicted binding sites for AP2-exp are enriched in upstream regions of var genes, we investigated transcript levels of the var gene family by quantitative real-time PCR (qRT-PCR), on cDNA prepared from 14 hours post-invasion (hpi) ring stages. The analysis of two mutant clones called MT6 and MT20 and 3D7 wild-type (G7 clone), demonstrated that only one major var gene was expressed, indicating that the mutually exclusive var gene expression was not disrupted in AP2-exp mutant parasites (Fig. 2b ). Moreover, var gene expression decreased similarly in late stages of mutants and wild-type G7 (data not shown), ruling out a major role of this AP2 protein on stage-specific and monoallellic var expression. Though var genes are the main players in P. falciparum cytoadherence, other exported clonally variant families such as rif, stevor and pfmc-2tm are expressed at late asexual blood stages (trophozoite-schizont stage) at the erythrocyte membrane at the time AP2-exp is expressed.
Next generation sequencing and data analysis. After initial quality control using FastQC software (http://www. bioinformatics. babraham. ac. uk/projects/fastqc/), reads were mapped to the Plasmodium falciparum 3D7 genome (v3, PlasmoDB) using the BWA MEM software 54 at default settings. The edgeR library  55  in the R statistical environment was used to normalize, explore, and estimate significantly differentially expressed (DEX) genes from the RNA expression data.
Acknowledgements We thank  Mehdi Ghorbal  for help with the FACS cell-cycle experiment and the  Institut Pasteur's Cytometry Platform (PFC) ; the  Institut Pasteur's imaging platform Imagopole  and  Jose-Juan Lopez-Rubio  for critically reading the manuscript. This work was supported by a  European Research Council   Advanced Grant  ( PlasmoSilencing 670301 ) and the  French Parasitology consortium ParaFrap  ( ANR-11-LABX0024 ) and the  Singapore A*Star-UK MRC joint Grant  ( A*Star  reference  10/1/22/24/630 ) and  MOE   Tier 1 Grant  ( RG 20/12 ).