dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analyses Except for the ranking between the film posters and children's survey, all other rankings were correlated with each other (S1 Table ). We combined all scores (i. e. , number of survey votes and number of mentions for zoos and film posters) for each species into an overall score, thus giving us the final rank of the most charismatic species. All of the following analyses were conducted using the online survey results alone. We used the chi-square test of homogeneity to assess whether the sociocultural categories (age, education level, language, and gender) were homogeneous. First, we removed from the dataset the responses with missing sociocultural information, thus resulting in a total number of 4,520 respondents. To assess any redundancy between the three main pairs of traits ("Rare/Endangered", "Beautiful/Cute", "Dangerous/Impressive"), we used McNemar's test to assess any correlations among them.
We assessed whether the 20 most charismatic species were associated with any sociocultural category. Sociocultural categories (age, education level, language, and gender) were nominal data with 2 to 5 levels (study level = 5, age = 4, language = 3, gender = 2). We conducted multiple correspondence analyses (MCA) with a data matrix formed by the frequency of each animal for each level of a given sociocultural category. In addition, we examined the association between species traits and sociocultural categories using MCA, which included the frequency of species traits for each sociocultural category. All statistical analyses were conducted with R software  [30] , using "lme4"  [31]  and "ade4" packages  [32].
Acknowledgments We would like to thank the students who worked on this project ( Frederic Ducarme ,  Marine Turpin , and  Aurelie Wibaux) , the participating school teachers in France, Spain, and the  UK , and the many respondents of the online surveys. We wish to thank  Morgane Barbet-Massin ,  Guillaume Marie , and  Marine Pasturel  for their help with the modelling analyses. We are also very grateful to  Ivan Jarvic  and  Elena Angulo  for their insightful comments on the earlier drafts of this manuscript, as well as the members of the  Biodiversity Dynamics Group  for the helpful discussions and feedback. This work was supported by the  Invacost grant  ( ANR, Foundation BNP-Paribas ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Different options for shapers and ADC, such as an 11-bit SAR-ADC, were studied in the TV2. A first implementation of a 32×512 RAM designed at CERN was successfully tested. HGCROC A first version of the final ASIC HGCROCv1 was submitted mid 2017 and is expected to become available for tests towards the end of the year. The number of channels of this ASIC was reduced to 32 instead of the anticipated 72 for development and cost reasons. The chip features most of the analogue and mixed analogue-digital blocks, while some of the missing digital parts are foreseen to be incorporated in the next version. The HGCROCv1 includes a TOA circuit and two variants of TOT circuits. The 11-bit SAR-ADC operates at 40 MHz and the data are read out at 320 MHz. A shift register with triple voting similar to the SKIROC2cms is implemented for the slow control configuration.
Trigger Primitive Generation As mentioned in section 1, the upgraded L1 Trigger will operate at rates exceeding 750 kHz. Given the high number of readout channels and large data size, a raw data flow of about 8 Pbit/s is generated. Since this amount of data is incompatible with cost and link placement, a drastic data reduction has to be performed from the detector front-end to the back-end. The maximum allowed trigger latency is 12. 5 µs. The trigger primitive (TP) generation starts in the HGCROC with the linearization of the ADC and TOT signals for each channel. A combination of channels into trigger cells (TC) according to their geometrical alignment (figure  4 , left) allows for a further reduction of the data size. Each sensor comprises 48 TCs. The concentrator ASIC on the motherboard selects a fraction of these TCs depending either on an individual threshold or selecting a fixed number of the highest energy TCs.
8 and 173°for ζ-potential and DLS, respectively. The t-CNC solutions were diluted to 0. 2 g L -1 without the addition of salt and filtered by 5 μm. The pH of the t-CNC solutions was 5 in all the cases. The hydrodynamic diameter was obtained from the analysis of the correlation function using Malvern DTS software. Conductometry. The quantity of charges on the t-CNC surface charge was measured by conductometric titration with a 0. 001 M NaOH solution by a TIM900 titration manager and a CDM230 conductimeter equipped with a CDC749 conductivity cell. Quartz Crystal Microbalance with Dissipation (QCM-D). The QCM-D measurements were performed with a Q-Sense E4 instrument (AB, Sweden) using a piezoelectric ATcut quartz crystal coated with gold electrodes on each side (QSX301, Q-Sense). All the measurements were carried out at 20 °C using the QCM flow cell modules.
Images were collected by an Innova AFM (Bruker) in tapping mode under ambient air conditions (temperature and relative humidity) using a monolithic silicon tip (TESPA, Bruker; spring constant k = 42 N m -1 ; frequency f 0 = 320 kHz). Image processing was performed with the WSxM 5. 0 software. Transmission Electron Microscopy (TEM). The t-CNC suspensions in water were deposited on freshly glowdischarged carbon-coated electron microscope grids (200 mesh, Delta Microscopies, France) and the excess water was removed by blotting. The sample was then immediately negatively stained with phosphotungstic acid solution (1%, w/ v) for 2 min and dried after blotting at room temperature just before observation. The grids were observed with a Jeol JEM 1230 TEM at 80 kV. The length of the nanocrystals was determined by the analysis of TEM images (15 images) using ImageJ software.
■ ACKNOWLEDGMENTS The authors gratefully acknowledge the  French National Research Agency  (Project  Cellmach ,  ANR-17-CE07-0010-01 ) and the  Region Pays de la Loire  ( Project Nanomach ,  Etoiles Montantes   2017-10691 ) for financial support. We greatly thank  Dr HervéBizot  for the preparation of tunicate nanocrystals and fruitful discussions. The authors acknowledge the  BIBS platform of INRA Angers-Nantes  for access to infrared spectroscopy (Sylvie Durand), elemental analysis ( Veŕonique Soléand Brigitte Laillet ), atomic force microscopy, and transmission electron microscopy ( Emilie Perrin ).
Background: Hepatitis B causes death mainly due to liver disease worldwide. Human immunodeficiency virus increases the pathological effect of hepatitis viruses and potentiates re-activation of latent hepatitis infections as a result of reduced immunity. Because of the same modes of transmission shared by the two infections, HBV represents an important cause of co-morbidity and mortality among people living with HIV; hence, the aim of this review is to determine the prevalence of HBV among people living with HIV. Methods: This systematic review and meta-analysis will include cross-sectional, case-control, and cohort studies of patients positive for HBV and HIV irrespective of their countries. All pertinent articles published on hepatitis B in people living with HIV from January 1, 1990, to July 31, 2017, without any language restriction will be searched in PubMed/MEDLINE, Global Index Medicus Web of Science, and Excerpta Medica Database.
Two review authors will independently assess the relevance of all titles and abstracts identified from the electronic searches. The studyspecific estimates will be pooled through a random-effects meta-analysis model to obtain an overall summary estimate of the prevalence of HBV across studies. We will assess statistical heterogeneity and pool clinically homogeneous studies. On the other hand, we will evaluate statistical heterogeneity by the chi-squared test on Cochrane's Q statistic. Symmetry of funnel plots and Egger's test will be used to detect the presence of publication and selective reporting bias. In the case of publication bias, we will report estimates after adjustment on publication bias using the trim-and-fill method. We will assess inter-rater agreement between investigators for study inclusion, data extraction, and methodological quality assessment using Kappa Cohen's coefficient.
Electronic search PubMed/MEDLINE, Global Index Medicus Web of Science, and Excerpta Medica Database will be searched to identify all relevant articles published on hepatitis B among people living with HIV from January 1, 1990, to July 31, 2017, without any language restriction. A search strategy based on the combination of relevant terms will be applied. Medical subject headings and other search words or their variants will include the following: "hepatitis B", "HIV", and "AIDS".
Two investigators will extract data pertaining to Author details: name of first author and publication year. Study characteristics: country, study design, setting, data source, sampling method, data collection period, response rate, timing of data collection, and diagnostic method for HBV. World Health Organization (WHO) region and level of income will be assigned depending on countries of recruitment. Participants' characteristics: inclusion criteria, mean and/or median age, age range, proportion of male, specific profile of the study population including pregnant women, injecting drug users, male who have sex with male, transgender, female/male sex workers, and prisoners. HIV-related data: mean and/or median time since diagnosis of HIV infection, mean and/median CD4 cell count, and proportion of patients on ART.
HBV characteristics: diagnostic method used, prevalence, number of participants tested, and diagnosed with HBV. Where only primary data (sample size and number of outcomes) will be provided, these data will be used to calculate the prevalence. Data will be extracted using a preconceived, piloted, and standardized data abstraction form. Disagreements between review investigators will be reconciled through discussion and consensus, or arbitration by a third review investigator whenever necessary. In case of multinational studies, the results will be separated to show the estimate within individual countries. When it will not be possible to disaggregate the data by country, the study will be presented as one and the countries in which the study was done will be shown.
Data synthesis including assessment of heterogeneity Data will be analyzed using Stata software (Stata Corp V. 13, Texas, USA). Unadjusted prevalence and standard errors will be recalculated based on the information of crude numerators and denominators provided by individual studies. To keep the effect of studies with extremely small or extremely large prevalence estimates on the overall estimate to a minimum, the variance of the study-specific prevalence will be stabilized with the Freeman-Tukey single arc-sine transformation before pooling the data with the random-effects meta-analysis model  [10]. Heterogeneity will be evaluated by the chi-squared test on Cochrane's Q statistic  [11] , which will be quantified by I-squared values, assuming that I-squared values of 25%, 50%, and 75% being representative of low, medium and high heterogeneity respectively  [12].
When substantial heterogeneity will be detected, subgroup analysis and meta-regression will be performed to investigate the possible sources of heterogeneity using the following variables: age, sex, study design, sampling method, data collection period, timing of data collection, diagnostic method for HBV, study setting, WHO region, level of income, ART regimens, and study methodological quality. Symmetry of funnel plots and Egger's test will be done to assess the presence of publication and selective reporting bias  [13]. A p value < 0. 10 will be considered indicative of statistically significant publication bias. In the case of publication bias, we will report estimates after adjustment on publication bias using the trim-and-fill method  [14]. We will assess inter-rater agreement between investigators for study inclusion, data extraction, and methodological quality assessment using Kappa Cohen's coefficient  [15].
The system was run on a Dell Precision T7500 computer system (Dell Inc. , Round Rock, TX) using the SlideBook software (Intelligent Imaging Innovations). Acquisitions were made at ZT5, ZT9 or ZT13 and neutrophils were stained with an AF647-conjugated anti-Ly6G antibody (clone 1A8, BioXcell), while blood vessels were visualized using red fluorescent Dextran (Molecular Probes). In some groups, anti-P and E-selectin antibodies or Rat IgG control antibody (25 μg/mouse) were injected 2h before imaging. Quantification was done using the ImageJ (NIH, Bethesda, MD). Cells were considered adhered if they remained stationary on the venule for over 30 seconds. Vessel diameters were measured using the ImageJ software  (Schindelin et al. , 2015)  to normalize the number of adherent cells.
Intravital microscopy of the cremaster muscle Intravital microscopy of the cremaster muscle after TNFα stimulation (R&D Systems, 0. 5μg intrascrotal injection) was performed as previously reported  (Hidalgo et al. , 2009 ) using the VIVO system indicated above. For confocal IVM, we used laser stacks for 488, 561 and 640nm beams coupled with a confocal scanner (Yokogawa CSUX-A1; Yokogawa, Japan) and images were acquired with 0. 5μm Z-intervals. The SlideBook software was used for acquisition and analysis. Ten to twenty venules segments per mouse were analysed 150 to 210 min after TNF-α treatment in multiple fluorescence channels (Cy3/561 for PE, FITC/488 for FITC and Cy5/640 for APC) and bright-field images with 1x1 or 2×2 binning with 3 second interval for 2 min on each field of view. For double staining with PE-and FITC-conjugated antibodies, acquisition was facilitated in single (FITC) and quadrant (PE) filters in order to avoid bleed-through of fluorescent signals between channels.
For the visualization of leukocytes, fluorescently labelled anti-Ly6G-APC, anti-Ly6C-FITC and anti-CD62L-APC antibodies were injected intravenously at 1 g/mouse. For analysis of rolling and adhered cells to the inflamed endothelium we used the SlideBook software. Counts of rolling or adhered cells in 2 minute captures (captured at 3 second intervals) were normalized using the width of the vessel to allow comparison among all vessels. For adhesion or rolling efficiency indices, this data was compared with the frequency of free-flowing WT and experimental cells in the blood for each mouse, which was obtained from cytometric analysis of blood neutrophils for each parabiont or BM chimeric mouse. Kinetic parameters for crawling neutrophils were calculated using ImageJ, with the help of the Manual Tracking plugin (Fabrice Cordelières, Institut Curie, France) and the Chemotaxis and Migration Tool (Gerhard Trapp and Elias Horn, ibidi GmbH, Germany).
All the groups were performed and quantified in a randomized fashion by investigators blinded to groups. Physiological parameters were not significantly different among the different groups studied. Infarct size was determined by magnetic resonance imaging 48 hours after MCAO using a BIOSPEC BMT 47/40 (Bruker, Ettlingen, Germany). Infarct volume was calculated using the ImageJ software (NIH, USA) from the T2-weighted images. With the observer masked to the experimental conditions, the areas of the infarcted tissue (InfArea), the whole ipsilesional hemisphere (IpsArea) and the whole contralesional hemisphere (ContrArea) were delineated for each slice. Then, infarct volume, expressed as percentage of the hemisphere that is infarcted (%IH) was calculated using the formula: %IH = InfVol/ContrVol*100 where InfVol (Infarcted Tissue Volume) = ΣInfAreai / SwellingIndexi, ContrVol (Contralesional Hemisphere Volume) = ΣContrAreai and SwellingIndexi = IpsAreai/ContrAreai.
Neutrophil quantification in brains was performed 48h after surgery. The ipsilateral cortex was dissected, placed in ice-cold PBS and dissociated into a single cell suspension by mechanical dissociation. Cell suspensions were filtered on 70-μm nylon mesh strainers and centrifuged at 300g for 10 min at room temperature. Pellets were resuspended in 8 mL of 35% Percoll and overlaid on the top of 5 ml HBSS. The gradient was centrifuged at 800g for 40 minutes at 4ºC and cell pellets resuspended for staining with anti-CD11b-FITC and anti-Ly-6G-PE antibodies (BD Bioscence). Stained cells were analysed in a FACSCalibur flow cytometer with CellQuest software (BD Pharmingen, San Jose, CA) and data was analysed using FlowJo software (Tree Star Inc, Ashland, OR).
Multiplex cytokine assay. Mice were i. p. injected with Zymosan as indicated above. After 2 hours peritoneal lavages were collected and neutrophils stained for FACS sorting. One million sorted neutrophils were incubated for 3h in RPMI containing 0. 5% BSA and 100,000 heat-killed C. albicans conidia. Supernatants were collected and frozen at -80ºC until cytokine quantification was performed. CXCL1, IL-10, IL-1β, IL-12, TNFα, G-CSF, IL-23, CXCL2, IL-6 and CCL2 were measured in neutrophil supernatants using the Mouse ProcartaPlex™ Multiplex Immunoassay (PPX-10-MXTZ766), following the manufacturer's protocol (Thermo Scientific, Waltham, USA). For TGF-β1 detection, samples were activated with HCl and measured using commercial TGF beta-1 Mouse ProcartaPlex™ Simplex Kit (EPX01A-20608-901). Data acquisition was performed on a MagPix instrument (Luminex Inc, Houston, TX) using xPONENT v4.
Acknowledgments: We thank all members of the  Hidalgo Lab  for discussion and insightful comments;  J. M. Ligos ,  R. Nieto  and  M. Vitón  for help with sorting and cytometric analyses;  I. Ortega  and  E. Santos  for animal husbandry;  D. Rico ,  M. J. Gómez ,  C. Torroja  and  F. Sanchez-Cabo  for insightful comments and help with transcriptomic analyses;  V. Labrador ,  E. Arza ,  A. M. Santos  and the  Microscopy Unit of the CNIC  for help with microscopy;  S. Aznar-Benitah ,  U. Albrecht ,  Q-J. Meng ,  B. Staels  and  H. Duez  for the generous gift of mice;  J. A. Enriquez  and  J. Ávila  for scientific insights and  J. M. García  and  A. Diez de la Cortina  for art. The data is presented in the main manuscript and in the supplementary materials. RNA-seq data are deposited in the Genome Expression Omnibus under accession number  GSE86619.
This study was supported by  Intramural grants  from  A*STAR  to L. G. N. ;  BES-2013-065550  to J. M. A. ,  BES-2010-032828  to M. C-A and  JCI-2012-14147  to L. A. W (all from  Ministerio de Economía, Industria y Competitividad ; MEIC). SAF2014-61993-EXP to C. L-R. , SAF2015-68632-R to M. A. M. ,  SAF-2013-42920R  and  SAF2016-79040R  (all from MEIC),  635122-PROCROP H2020  from the  European Commission  and  ERC CoG 725091  from the  European Research Council (ERC)  to D. S. ERC AdG 692511 PROVASC from the  ERC  and  SFB1123-A1  from the  Deutsche Forschungsgemeinschaft  to C. W. ;  MHA VD1. 2/81Z1600212  from the  German Center for Cardiovascular Research (DZHK)  to C. W. and O. S. ;  SFB1123-A6  to O. S. and  SFB914-B08  to O. S. and C. W. ;  INST 211/604-2 ,  ZA 428/12-1 , and  ZA 428/13-1  to A.
DATA AND SOFTWARE AVAILABILITY Raw data for the RNA sequencing analyses can be publicly accessed at the Gene Expression Omnibus (GEO, NCBI) with GEO Accession Number GSE102310 (for reviewers: https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE102310; password for reviewers: knkzmwsenvannir). Any other pieces of data are available on request.
SEVIRI has lower spatial resolution than MODIS; the observing pixel size at nadir is 3000 m against the 1000 m of MODIS for the channels that are used in the FRP calculations. This broad spatial resolution makes small fire mappings challenging with the exclusive use of SEVIRI. Nevertheless, the high sampling frequency means fire observations can occur during brief cloud-free spells in otherwise mostly cloudy regions. In addition it covers higher latitudes than the MODIS fire products since snow and ice pixels are being processed. Despite these advantages the FRP product from SE-VIRI does not provide global coverage since it only covers a geographical disc comprising Europe and Africa. Moreover, the SEVIRI FRP level 2 products undergo a different calibration procedure from that of MODIS, and the merging of the two datasets has proven to be a challenge  (Roberts et al.
, 1989). The new model based on the FWI has been implemented in GFAS to account for missing observations in the MODIS FRP. Improvements in the prediction of biomass-burning emissions have been assessed for a collection of 5-day forecasts initialized on a daily basis during 3 months spanning June-August 2013. Fire radiative power is the radiant heat power emitted by fires and it can be related to the energy released during the combustion process, whereby carbon-based fuel is oxidized to CO 2  (Wooster et al. , 2005). Measurements of FRP are proportional to the total biomass combustion and thus to emissions  (van der Werf et al. , 2006; Kaiser et al. , 2012). The FRP (ρ) observations from MODIS used in this study are available at 1 km resolution from the MOD14 product of MODIS Collection 6. This dataset also provides a pixel classification attribute to flag missing observations (mostly because of cloud cover) and low confidence measurements, which are disregarded by the GFAS.
The impact on the AOD forecasts during a large fire event in Canada in summer 2013 is large close to the fires and negligible elsewhere. One of the advantages of the new approach is that the concept of modelling the likelihood of fire persistence as a function of weather parameters can also be extended to modulate the contribution of fire emission during the model integration. This is investigated in Di  Giuseppe et al. (2017). Data availability. All operational GFAS data are available from the ECMWF web application (http://apps. ecmwf. int/datasets/data/ cams-gfas/, CAMS, 2015). The data from the modified GFAS experiments described in this paper are instead stored under experiment identification "gdpd" and "gdpe" in the operational ECMWF MARS archive. They are accessible upon request to the corresponding author or through direct download if one is a registered user of ECMWF.
Figure1ademonstrates the more obvious consequence of the persistence assumption -the increase in mean fire duration. It shows the difference in fire duration between MODIS and the GFAS. The density plot takes into account all fires detected by MODIS instruments on board the Terra and Aqua platforms during the verification period in summer 2013. Fire duration for MODIS is defined by the number of continuous days for which FRP is available and larger than zero. Fire duration in the GFAS extends also during observation blackout periods until a valid observation confirms the end of the event. The observed global average fire duration in the MODIS dataset is 4. 2 days, and by assuming persistence the.
Acknowledgements. This work was funded by the  EU  Project  ANYWHERE  (contract  700099 ) and the Global Fire Contract 389730 between the  Joint Research Centre  and the  ECMWF. Angela Benedetti  is thanked for the fruitful discussions concerning the interpretation of the MOPITT comparison. We would like to thank  NASA  and the  MOPITT team  for the ease of access to their data. Luke Jones  is acknowledged for his support in creating Fig. 7. Rebecca Emerton  and  Sue Dunning  kindly read the manuscript before submission. Edited by: Dominick Spracklen Reviewed by: two anonymous referees.