dataesr/scientific-paragraphs-categorization huggingface dataset:
Results Characteristics of the sample 770 stable SZ outpatients (mean age 32 years, 74% male) were included in the FACE-SZ cohort. Among the 770 patients assessed at the initial visit, 325 were evaluated at one-year. There were no significant differences between patients seen at the beginning of the study and those lost during follow-up in regard to our variables of interest (severity of the disease, level of functioning, number of lifetime episode, cognitive abilities) (all p>0. 05, data not shown). Of the 325 patients with two assessments at one year interval, 297 had sufficient information available to allow clinical stage assessment.
Acknowledgments We thank the  FondaMental Foundation  (www-fondation-fondamental. org) which is a nonprofit foundation supporting research in psychiatry in France and coordinating the infrastructure of Bipolar Expert Centers. We express all our thanks to the patients who have accepted to be included in the present study. We thank the team of FondaMental foundation,  Hakim Laouamri  and his team ( Seif Ben Salem ,  Karmène Souyris , Victor Barteau  and  Mohamed Laaidi ) for the development of the FACE-SZ computer interface, data management, quality control and regulatory aspects.
Funding sources This work was funded by  AP-HP  ( Assistance Publique des Hôpitaux de Paris ),  Fondation FondaMental  ( RTRS Santé Mentale ), by the  Investissements d'Avenir program  managed by the  ANR  under reference  ANR-11-IDEX-0004-02  and  ANR-10-COHO-10-01 , and by  INSERM (Institut National de la Santé et de la Recherche Médicale). This funding source had no role in the study design, data collection, analysis, preparation of the manuscript, or decision to submit the manuscript for publication. O Godin had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors have approved the manuscript and have nothing to disclose.
borchii genome  (Murat et al. , 2018). Tri-, tetra-, pentaand hexanucleotide satellites with at least six repetitions and excluding composite SSRs were selected as search parameter. Subsequently, primer pairs were designed based on the sequences flanking the selected SSRs using Primer 3 software  (Rozen and Skaletsky, 2000). The functionality of the designed primers was tested using AmplifX software (http://crn2m. univ-mrs. fr/pub/amplifx-dist). After in silico analyses, a total of 31 primer pairs were designed and tested in PCR and visualized in 4% agarose gel. Among then 14 were retained since they produced only one band per sample and showed polymorphisms. They were used to search for polymorphisms on 50 ascomata from Italy and Hungary (Supporting Information Tables  S1  and S4 ). The genotyping was realized in the Gentyane platform  (INRA, Clermont-Ferrand, France).
PCR products were run on 4% agarose gel. Genomic DNA was analysed using an ABI 3730XL sequencer (Applied Biosystems, Foster City, CA) from 'Plateforme de Génotypage GENTYANE'  (Clermont-Ferrand, France). The size of the alleles was analysed with the Peak scanner software v. 1. 0. SSR analyses were carried out only on ascomata because, when the genome sequencing of T. borchii  (Murat et al. , 2018)  made possible to select the SSR markers, the mycorrhizas were already analysed for mating type characterization by using direct PCR and successively disrupted (see above).
51. b2. In this analysis, only the nine polymorphic SSR in this population were used. The significant departure from F IS = 0 was estimated using the R script developed by  Taschen et al. (2016) ; script available at https://doi. org/10. 5061/dryad. vm11r. MLG analysis of the inoculated mycelia, and the maternal (gleba) and paternal (spores) ascoma tissues harvested in Cadriano was realized using the 14 polymorphic SSR markers combined with the mating type gene. MLGsim 2. 0  (Stenberg et al. , 2003)  was used for MLG identification and the calculation of the likelihood (PSex) that copies of MLGs result from sexual reproduction or clonal spread. The threshold value (< 0. 05) for testing the significance of the PSex for each genotype was estimated using 1000 simulations. When the PSex values fell below the threshold value, it was concluded that identical genotypes originated from clonal multiplication.
Acknowledgements UMR 1136 is financed by the  French National Research Agency (ANR)  as part of the  'Investissements d'Avenir' program  ( ANR-11-LABX-0002-01 ,  Lab of Excellence ARBRE ) and CM benefits of the project CulturTruf financed by  FranceAgriMer (CASDAR). We are grateful to  Dr Fabien Halkett  for population genetic critical discussions. We also thank to  Susan West  for her professional revision of the English.
Study population The TB isolates used in this study were collected during the first national TB prevalence survey in Lao PDR (July 2010-December 2011). The survey design and sample size were determined according to the WHO recommendations and has been described in  Law et al. (2015). During this survey that covered the 17 provinces of Lao PDR (organized in three main regions, North (1-9), Center  (10) (11) (12) (13)  and South  (14) (15) (16) (17) , see Fig. 1 ), at least one sputum specimen was collected from 6290 (99. 1%) of the 6346 participants suspected to have TB on the basis of clinical data (chronic cough and/or hemoptysis and/or chest X-ray abnormalities). Finally, TB was confirmed in 237 participants, according to the study case definition  [3]. Among these 237 patients, 94 had at least one smear-positive sputum and culture-confirmed M.
Colonies were scraped from the medium slopes and resuspended in 300 μL of distilled water, heated at 95 °C for 20 min, and centrifuged at 13000 g for 5 min. Then, the DNA-containing supernatant was transferred into a new tube and stored at -80 °C. The patients' demographic, epidemiologic, and clinical data were collected using a questionnaire, including residence, sex, age, TB history, TB symptoms, and CXR findings.
Spacer oligonucleotide typing (spoligotyping) Spoligotyping (the classical 43-spacer format) was performed as previously described  [14, 15]. DNA samples of the M. tuberculosis H37Rv and Mycobacterium bovis BCG strains were included as positive controls. Molecular biology-grade water was used as a negative control. The spoligotypes were then recorded in 43-digit binary format and compared with those recorded in the SpolDB4 database (http://www. pasteur-guadeloupe. fr:8081/ SITVIT_ON-LINE/) to identify the Spoligotype International Type (SIT) and family  [16]. For the spoligotypes that matched the SITs, but could not be related to any family (i. e. , unknown), and for the spoligotypes that were not present in the SpolDB4 database (i. e. , orphan), the SPOTCLUST program, which was built from the spolDB3 database (http://tbinsight.
Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing MIRU-VNTR typing was performed as previously described  [18, 19]  and the full set of 24 MIRU-VNTR loci was used for isolate characterization. The patterns obtained for the 24 loci were used to create a 24-digit allelic profile for each isolate. The MIRU-VNTR typing results were analyzed using MIRU-VNTRplus (http:// www. miru-vntrplus. org), a freely accessible web-based program  [20]. A Neighbor-Joining (NJ) tree based on categorical distances was built by combining the spoligotyping and MIRU-VNTR results. The final designation of family/subfamily was revised using the MIRU-VNTRplus website (MIRU-VNTRplus. org) based on the family results for each isolate and the MIRU-VNTR/spoligotyping phylogenetic tree.
Identification of the M. tuberculosis families/subfamilies Spoligotyping and 24-locus MIRU-VNTR typing were performed on 206 of the 222 isolates (Table  1 , Additional file 1: Figure  S1 ). The M. tuberculosis family/subfamily identifications were determined using SITVITWEB (SpolDB4 database), SPOTCLUST and MIRU-VNTRplus. The patterns of four isolates reflected either clonal variants (with double alleles at a single MIRU-VNTR locus) or mixed infections (with double alleles at two MIRU-VNTR loci)  [22]  (Additional file 2: Table  S1 ). These four isolates were removed from the analysis to avoid incorrect designation. The other 202 isolates had 58 different spoligotype profiles among which 41 spoligotypes were unique and 17 patterns allowed the clustering of 161 isolates. Each cluster contained 2 to 40 isolates (average = 9).
Moreover, 165 isolates (81. 68% of 202) were assigned to 29 SITs and seven families present in the SpoIDB4 database; two (1. 0%) were unknown; and 35 (17. 3%) were orphans. The 35 orphan and the two unknown isolates were then compared using SPOTCLUST. Finally, isolates could be classified in seven M. tuberculosis families and ten subfamilies (Table  1 ). EAI was the predominant family (76. 7%, n = 155 isolates), followed by Beijing (14. 4%, n = 29) and T (5. 5%, n = 11). Five isolates (2. 5%) belonged to other families, such as Haarlem (H), Central Asian Strain (CAS), Latin American-Mediterranean (LAM), and Manu. Only one orphan and one unknown isolate could not be identified. Within the EAI family, the most frequent subfamily was EAI5 (53. 0%, n = 107), followed by EAI1-SOM (8. 9%, n = 18) and EAI2-Nonthaburi (6.
Acknowledgments We thank the  Center for Infectiology Lao-Christophe Mérieux , the  Institut de Recherche pour le Dévelopement (IRD), France , the  Fondation Mérieux/ Laboratoire des Pathogènes Emergents (LPE) ,  France , and The  National Institute of Hygiene and Epidemiology (NIHE), Vietnam , for their support. We are also grateful to the  Ministry of Health , the  National TB Control Program , the  National reference laboratory , the survey teams, the experts for technical validation, all participants and funders of the first National TB prevalence survey of Lao PDR. We thank  Elisabetta Andermarcher  for assistance in preparing and editing the manuscript. This research was carried out in the framework of the  JEAI "Mycobaterium tuberculosis in Southeast Asia (MySA)  and the  LMI "Drug Resistance in South East Asia" (DRISA)  projects.
Imagery techniques. Global views of the holotype and paratype of Voulteryon parvulus were done using a cross-polarized light setup  97, 98  ) coupled to image stacking. Colour detailed views of the epibionts and eyes on the holotype were obtained with a 24 × 36 mm digital SLR equipped with a x10 microscope objective. The holotype was micrographed using a Hitachi Analytical Table Top Scanning Electron Microscope. The paratype was micrographed using a Tescan SEM (VEGA II LSU) linked to an X-ray detector SD3 (Bruker) (Direction des Collections, MNHN, Paris). Additionally, we used the virtual slices and the reconstruction of the ventral surface of the holotype by Jauvion et al. 28  , reconstructed using the VG-Studio MAX 2. 2 (© Volume Graphics) software on X-Ray Tomography (XTM, CT-Scan) data (voxel size = 9.
Acknowledgements This scientific collaboration was made possible following the 6 th  Symposium on Mesozoic and Cenozoic Decapod Crustaceans (June 2016, Normandy, France). We acknowledge  Jean-Michel Pacaud  ( MNHN ) for providing the access to the material as well as  Sylvain Pont  ( MNHN ) for attending us at environmental SEM imaging. JTH was kindly funded by the  German Research Foundation (DFG)  under  Ha 6300/3-1  and is currently supported by the  Volkswagen Foundation  with a Lichtenberg Professorship. JL acknowledges the  Izaak Walton Killam Memorial Scholarship (Canada)  and a  Natural Science and Engineering Research Council of Canada (NSERC)   Postdoctoral Fellowship. DA research was supported by the  China Postdoctoral Science Foundation ,  Yunnan Province Postdoctoral Science Foundation ,  NSFC  grant  41861134032 , and Yunnan Provincial Research Grants  2018FA025  and  2018IA073.
, 2013; Masson et al. , 2003) , involving that only the CO 2 effect on stomatal closure is represented (called the "antitranspiration" effect of CO 2 ). There are no land cover changes in CNRM-CM6-1, and the land cover distribution is fixed in time according to the ECOCLIMAP database (Table  2 ). This database includes climatological observations at high resolution over the 2000s, such as LAI, vegetation roughness length, snow-free land surface albedo  (Carrer et al. , 2014) , or soil textural properties, from the Harmonized World Soil Database at a 1-km resolution  (HWSD, 2012). More details on the physical processes represented in the ISBA-CTRIP system can be found in  Decharme et al. (2019). The ocean component of CNRM-ESM2-1 is the Nucleus for European Models of the Ocean (NEMO) Version 3.
Coupling and Outputs CNRM-ESM2-1 exploits the full capabilities of the OASIS3-MCT software  (Craig et al. , 2017) , which allows the exchange of 31 physical and 4 biogeochemical fields across the various model components (Figure  1 ). In the CNRM-CERFACS climate models such as CNRM-ESM2-1, the coupling is implemented in SURFEX, NEMO, and CTRIP. The generic coupling interface implemented in SURFEX is detailed in  Voldoire et al. (2017). CNRM-ESM2-1 is also interfaced with XIOS  (Meurdesoif, 2018)  which is an Input/Output parallel server software allowing for a declarative description of output files content and for the realization of online calculation on geophysical fields.
Tropospheric Aerosols CNRM-ESM2-1 includes an interactive tropospheric aerosol scheme included in the atmospheric component ARPEGE-Climat. This aerosol scheme, named Tropospheric Aerosols for ClimaTe In CNRM (TACTIC_v2), represents the main anthropogenic and natural aerosol species of the troposphere. Originally developed in the European Centre for Medium-Range Weather Forecast Integrated Forecasting System as presented in  Morcrette et al. (2009) , this scheme has been adapted to the ARPEGE/ALADINclimat code  (Michou et al. , 2015; Nabat et al. , 2015). It is based on a sectional representation of desert dust (three size bins whose limits are 0. 01, 1. 0, 2. 5, and 20 μm), sea-salt (three bins whose limits are 0. 03, 0. 5, 5. 0, and 20. 0 μm), sulfate (one bin), organic matter (two bins), and black carbon (two bins).
Compared to the version used in CNRM-ESM 1, key improvements have been done in ISBA as used in CNRM-ESM2-1; they relate to the assimilation and autotrophic respiration processes used in the vegetation physiology scheme. In particular, the structural parameters of the photosynthetic scheme such as the mesophyll conductance, the maximum photosynthetic rate, and the leaf carbon-to-nitrogen ratio have been calibrated on the TRY database  (Kattge et al. , 2011). The autotrophic respiration scheme has been revised following  Joetzjer et al. (2015)  which scale leaf to canopy respiration by using a vertical exponential profile of leaf nitrogen as suggested by  Bonan et al. (2012). Finally, in the absence of nitrogen cycling within the vegetation, an implicit nitrogen limitation scheme has been implemented in ISBA following the metaanalysis of  Yin (2002).
Journal of Advances in Modeling Earth Systems From these initial conditions, CNRM-ESM2-1 was spun-up as follows. The land surfaces were spun-up using a sequential approach where SURFEXv8. 0 was first run offline during 1000 years using the atmospheric fields taken from a preindustrial atmosphere-alone simulation with ARPEGE-Climat. For the atmospheric forcing, a sequence of 10 years is repeated continuously. The spinup for land carbon reservoirs employs an acceleration scheme updating the wood growth, the litter, and soil carbon modules several times per model time step with constant incoming carbon fluxes and physical conditions, allowing the various reservoirs of carbon to fill up much faster. Consequently, soil carbon and wood reservoirs were respectively spun-up for 21800 and 1200 years.
Concerning smoke aerosols emitted over the tropical region (Amazonia, Indonesia, and Central Africa), results confirm  Petrenko et al. 's (2017)  findings suggesting an underestimation of biomass burning emissions in the current emission database. Besides, our analyses suggest that biases in precipitation impact the partition between dry and wet deposition of aerosols in several regions. This is the case over the Saharan Air Layer where the positive bias in JJAS precipitation in both models (Figure  4 ) enhances the wet deposition of dust through below-clouds scavenging. Similar conclusions were obtained over the Southeast Atlantic where the transport of significant smoke aerosol concentrations occurs  (Zuidema et al. , 2016). It should also be reminded that the differences observed in AOD could be due to uncertainties in the MODIS AOD retrievals  (Gupta et al.
We take the opportunity to stress here that a specific effort has been made to contribute to the entire matrix of ScenarioMIP Shared Socioeconomic Pathways with CNRM-ESM2-1 future climate projections. Ongoing developments led at CNRM-CERFACS on Earth system components aim to improve model-data comparison. They concern, for example, a better representation of the land cover-aerosol interactions but also the coupling between the air-sea exchange of trace gases and particles emitted by the ocean (e. g. , DMS or organic matter) with the aerosol scheme. Future developments of CNRM-ESM will aim at better representing climate-relevant processes. For example, the inclusion of a permafrost carbon module  (Morel et al. , 2019)  is expected to improve the representation of the soil carbon and associated CO 2 and CH 4 emissions in high latitude biomes.
Data Availability Statement All of the CNRM-ESM2-1 and CNRM-CM6-1 model outputs are available for download on ESGF under CMIP6 projects. The SURFEX-CTRIP code is available (Open-SURFEX) using a CECILL-C Licence (http://www. cecill. info/licences/Licence_CeCILL-C_V1-en. txt) at the SURFEX website (http://www. umrcnrm. fr/surfex). NEMO-GELATO-PISCESv2-gas is also available at https://opensource. umr-cnrm. fr/; the access to the Git repository is granted upon request to the corresponding author. OASIS3-MCT can be downloaded at this website (https://verc. enes. org/oasis/download). XIOS can be downloaded at the XIOS website (https://forge. ipsl. jussieu. fr/ioserver). For the ARPEGE-Climat_v6. 3 code and exact version applied to each component, please contact the authors. Finally, a number of analyzing tools developed at CNRM, or in collaboration with CNRM scientists, is available on as Open Source code (see https://opensource.
Anthropometric and body composition parameters Age, gender, height and body weight were recorded, and BMI was calculated. Total body fat and lean masses were measured by dual-energy X-ray absorptiometry (DXA; Lunar DPX-IQ, GE Healthcare, Waukesha, WI, USA). Total and intra-abdominal adipose tissue surface areas to allow assessment of subcutaneous and visceral fat were calculated at the same radiological centre, using 1cm reconstructed slices of abdominal L4 magnetic resonance imaging (MRI) scans and Extended Brilliance Workspace (EBW) version 3. 5 software (Philips Medical Systems, Eindhoven, The Netherlands). Fat and lean body mass measurements in grammes and percentages were used to derive ratios of total fat/height 2 (body fat mass index) and lean mass/height 2 (body lean mass index), total and intra-abdominal fat surface areas, and intra-abdominal/total abdominal fat surface areas.
Statistical analysis Quantitative variables were expressed as medians, first and third quartiles or means ± standard deviation (SD). Between-group comparisons were performed using Kruskal-Wallis or Mann-Whitney tests. Qualitative values were expressed as proportions, and compared between groups using chisquared or Fisher's exact tests, according to validity conditions. Confidence intervals (CIs) for proportions were computed using a binomial law. Correlations were assessed by Spearman's rank correlation coefficient and related tests. All tests were two-sided, and a P value < 0. 05 was considered statistically significant. All statistical analyses were performed with the ROCR software package (R Foundation for Statistical Computing, Vienna, Austria). Finally, an arbitrarily developed score was used to distinguish FPLD2 patients from other patients (OND vs HC), defined by the following equation: FPLD2 score = irisin -[12.
ACKNOWLEDGEMENTS This study was supported by the  French Ministry of Health  (PHRC 2009; Clinical Trial Registration Number: Clin. gov2009-AO- 1169-48 ). In addition, the authors are indebted to  Hélène Verstavel  and  Anne-Sophie Vanceulebroek  (clinical research nurses),  Mr Patrick Gelé  of the  Center of Research Biology (CRB) , the staff of the  Department of Endocrinology, Diabetology and Metabolism, Department of Clinical Research and Délégation à la Recherche Clinique of Lille University Hospital. We also thank the endocrinologists of the Diamenord-AEDNL regional network. Our team is part of the  European Consortium of Lipodystrophies (ECLIP)  and  French Rare Diseases Healthcare Network (FIRENDO) Rare Pathologies of Insulino-Resistance and Insulin Secretion (PRISIS).
In this work, PAPIFY toolbox is presented as a tool to perform automatic PAPI-based instrumentation of dynamic dataflow applications. It combines PAPIFY with a dataflow Y-chart based design framework, which is called PREESM, and its companion run-time reconfiguration manager, which is called Synchronous Parameterized and Interfaced Dataflow Embedded Runtime (SPiDER). PAPIFY toolbox accounts for an automatic code generator for static and dynamic applications, a dedicated library to manage the monitoring at run-time and two User Interfaces (UIs) to ease both the configuration and the analysis of the captured run-time information. Additionally, its main advantages are 1) its capability of adapting the monitoring according to the system status and 2) adaptation of the monitoring accordingly to application workload redistribution in run-time.
This new functionality makes PAPIFY detect the workload redistribution performed by SPiDER and, consequently, it is able to modify the monitored data accordingly. Furthermore, transparently to the user, PAPIFY now adapts different strategies according to the monitoring status to minimize its overhead. To sum up, this paper presents the following contributions: • Design time: Y-chart based monitoring configuration. Application monitoring configuration and platform supported monitors are completely isolated from each other • Run-time: dynamic monitoring of application performance execution that feeds a run-time manager like SPiDER. The user-defined monitoring follows the actor even after application reconfigurations • PAPIFY-VIEWER: a graphical display showing collected hardware information for improved data analysis • Thorough overhead toolbox characterization.
PiSDF extends SDF by introducing consistent graph hierarchy using interfaces, parameterized FIFO sizes and run-time reconfiguration  [9]. Likewise, S-LAM  [4]  describes parallel architectures as a set of PEs transmitting data through a set of communication nodes and data links. By doing so, it supports the definition of SW, HW or heterogeneous platforms  [17]  connected through different levels of granularity (i. e. , Ethernet, shared memory, etc). The joint node of the Y-chart design flow is the scenario. It relates both the application (PiSDF) and the architecture (S-LAM). Additionally, it provides user defined information to drive the automatic steps of the flow, e. g. , actor timing information or actor ↔ PE affinity. Using this information, PREESM schedules, maps and simulates the execution of the application and generates a compilable code in a language supported by the architecture, thus providing both metrics for system design and a prototype for testing.