dataesr/scientific-paragraphs-categorization huggingface dataset:
Neurosynth meta-analysis. We used the neurosynth meta-analytic database (https ://www. neuro synth. org) to assess topic terms associated with the functional connectivity profile and significant cortical thickness regions. For each region of interest map, the output of the analysis was a z statistic associated with the feature term. The terms were then visualised as word clouds. Feature terms were derived from the 50 topic term-based meta-analysis (v4; https ://raw. githu buser conte nt. com/neuro synth /neuro synth -web/maste r/data/topic s/keys/ v4-topic s-50. txt). The analysis method can be found on the official website (https ://neuro synth. org/analy ses/ terms /). Of the 50, 25 were removed as "noise" terms or experiment paradigm related information, because they did not capture any coherent cognitive function, leaving 24 topic terms (see https ://githu b.
Acknowledgements This study was supported by the  European Research Council  (Project ID:  646927 ) awarded to JS, supporting NSPH. HTW is part of the  Sackler Centre for Consciousness Science  which is supported via a donation from the  Dr. Mortimer and Theresa Sackler Foundation. DB is supported by the  Healthy Brains Healthy Lives initiative (Canada First Research Excellence  fund), and by the  CIFAR  Artificial Intelligence Chairs program.
Mass spectrum of cationic products resulting from the interaction between XUV pulses and neutral adamantane molecules (purple). The dashed gray lines correspond to the mass spectrum obtained by electron impact at 70 eV  36. The main ingredients of the M3C simulations, i. e. structures, energies, and vibrational frequencies of the fragments, are those obtained in the PES exploration at the B3LYP/6-31G(d) level. In total, 148 molecules are included in the fragmentation model (see SI for details). Geometries are available as an additional file in the SI and in the M3C-store project database  35. The statistical simulations have been carried out such that the sum of angular momenta from all fragments exactly compensates the orbital momentum resulting in a total angular momentum equal to zero. We set the radius of the system to 30.
Acknowledgements A special thanks is given to  A. Persson  for his support for the high-power laser and to  M. Gisselbrecht  for critical reading of the manuscript. This research was supported by the  Swedish Research Council , the  Swedish Foundation for Strategic Research  and the  Crafoord Foundation. This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Sklodowska-Curie Grant  Agreement No. 641789   MEDEA  and under grant agreement no 654148  Laserlab-Europe. The research was conducted in the framework of the  International Associated Laboratory (LIA) Fragmentation DYNAmics of complex MOlecular systems -DYNAMO , funded by the  Centre National de la Recherche Scientifique (CNRS). The authors acknowledge the generous allocation of computer time at the  Centro de Computación Científica at the Universidad Autónoma de Madrid (CCC-UAM ).
This product classifies major cloud classes: fractional clouds; semitransparent clouds; and high, medium and low opaque clouds. More details on the retrieval algorithm can be found in  Stengel et al. (2014 ), Finkensieper et al. (2016)  and the Algorithm Theoretical Basis Document (ATBD) Meteo-France (  2016 ) document (http://www. nwcsaf. org, last access: 13 November 2019). A comparison of the SAF-NWC product with spaceborne active lidar measurements can be found in  Sèze et al. (2015). Here we use a specific version of the product where the ancillary data are taken from ERA5 at hourly resolution. For the scope of our analysis, we selected the highest and opaque cloud classes (high opaque clouds, very high opaque clouds and very high semi-transparent thick clouds) that are representative of the deep-convective events as classified in the cloud type (CT) product.
, 2012). At the same time, previous studies based on ERA-Interim wind fields and heating rates in the AMA region suggested a higher reliability of the diabatic heating rates for convective transport to the TTL  (Ploeger et al. , 2011; Bergman et al. , 2015)  as well as higher vertical motion in the inner tropical pipe region  (Hoppe et al. , 2016). In order to evaluate the sensitivities and estimate the uncertainties associated with vertical velocities, we compare kinematic and diabatic trajectories. Moreover, we test both ERA-Interim (1 • ×1 • horizontal resolution, 3 h temporal resolution and 60 vertical levels) and the newer ERA5 dataset at higher spatial and temporal resolution (0. 25 • × 0. 25 • horizontal resolution, 137 vertical levels and 1 h temporal resolution). In both cases the vertical velocities are taken as an instantaneous field for the kinematic computation, while for the diabatic computation, the heating rates are only available as averages of the reanalysis time step.
To take into account the spatial heterogeneity in emission intensity, we multiplied the convective distribution by the CO fluxes from an emissions database. We used here the 2010 monthly emissions from the MIX v1. 1 gridded emissions database (M. Li et al. , 2017)  based on a harmonization of different up-to-date Asian regional emission inventories. The quantity we obtain (δCO Trac (z(t))) is therefore indicative of the CO mass potentially transported from the BL up to the flight position, hence the enhancement of CO with respect to the background. With our diagnostic, it is not possible to pursue a rigorous computation of the CO mixing ratio since the simulation does not take into account all the processes of microphysics and chemistry. We therefore adopted an empirical rescaling as explained in the following.
In the ERA-Interim version (Fig. 5f ) the relative enhancement between outside and inside the plume is damped, and the timing is not consistent with the observations. This is particularly visible in the kinematic computation (that has in fact the lowest correlation coefficient, 49. 4 %), while the diabatic one looks closer to the COLD2 measurements (with a correlation of 56. 4 %). The results of the statistics are shown in Table  S1  of the Supplement for each single flight and in Table  1  for the whole campaign average. The correlation analysis confirms that ERA5 performs better than ERA-Interim in reproducing the trace gas transport to the UTLS (R of around 60 % vs. 50 %). In both EA and EI, the diabatic vertical transport better reproduces the variability observed in the CO measurements, with a slight enhancement in the correlation with data with respect to the kinematic simulations.
Discussion and conclusions The StratoClim campaign offered, for the first time, a comprehensive dataset of in situ measurements in the UTLS inside the summer AMA. It represented a unique occasion to investigate the details of deep-convective transport into the low stratosphere and a useful reference dataset to evaluate transport model performance over this region. We therefore tested the quality of the TRACZILLA dispersion model fed with different reanalyses (ERA5 vs. ERA-Interim) and vertical-motion settings (diabatic vs. kinematic) against the measurements of the CO species. We found that ERA-Interim, with respect to ERA5, generally recognized more  sources over the maritime regions (i. e. Pacific Ocean, Bay of Bengal) and northern China and less from the Tibetan Plateau. The comparison with the CO measurements shows that the transport in the AMA region is better represented by the ERA5 winds.
Acknowledgements. This work was supported by the  StratoClim  project by the  European Community 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 603557 ,  CEFIPRA5607-1  and the  TTL-Xing   ANR-17-CE01-0015  projects. We thank the whole  StratoClim Team  for having made this successful campaign possible. Meteorological analysis data are provided by the  European Centre for Medium-Range Weather Forecasts. ERA-5 trajectory computations are generated using  Copernicus Climate Change Service Information. We also thank the AERIS data and service centre for providing access to the MSG1 and Himawari data. Financial support. This research has been supported by the  European Community 's  Seventh Framework Programme  (FP7/2007-2013; grant no. 603557 ),  CEFIPRA  (grant no.
Data availability. Data will be available at https://halo-db. pa. op. dlr. de/mission/101 (Leibnitz Institut für Troposphärenforschung, 2020) when the database is freely released. Meanwhile, they will be available upon request from the authors. Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/acp-20-12193-2020-supplement.
By performing high-quality sequence clustering, Operational Taxonomic Units (OTUs) were retrieved and taxonomic assignments were performed comparing OTUs representative sequences against dedicated reference databases from SILVA  [120]. The cleaned data set is available on the European Nucleotide Archive database system under the project accession number PRJEB36457. Soil samples accession numbers range from ERR3842608 to ERR3842625 for 16S and 18S rDNA. The alpha diversity of the communities was analyzed. To compare bacterial or fungal composition among three soil preparations, the richness of these communities was characterized by the number of OTUs found in each soil. As metric of taxonomy diversity, the Shannon diversity index was also determined (package 'vegan'  [121] ). Since values were conformed to normality assumptions, linear models LMM function 'lmer', package 'lme4'  [122] ) were used to examine differences between soil preparation for these measures.
Episodic memory. Verbal episodic memory was investigated through a modified version of the Free and Cued Selective Reminding Test (FCSRT;  Grober & Buschke, 1987; Grober, Ocepek-Welikson, & Teresi, 2009). In the original task, participants are asked to learn 16 words belonging to 16 different semantic categories presented in groups of four cards. Although this task is well suited to investigating memory processes, it is too easy for nonclinical young adults. For this reason, we decided to make it more difficult by adding items. Hence, our modified version was composed of 24 target words belonging to 24 different semantic categories, together with 24 semantic distractors and 24 neutral distractors (i. e. , not semantically related to the target words; see Supplemental Table  1 ). We selected items characterized by their low lexical frequency and their low typicality in the corresponding semantic category  (Rosch & Mervis, 1975)  from the OpenLexicon database  (Pallier & New, 2019).
Data analysis plan First, we assessed differences between the BD and SD groups on background and verbal memory measures. Chi-square tests were used for categorical variables, and independent t tests for numerical variables. Nonparametric Mann-Whitney U tests were used for numerical variables if the normality assumption was violated, according to the Shapiro-Wilk test. Next, to investigate the effect of learning across groups we conducted mixed model analyses on the numbers of free and total recall trials of the FCSRT. We first conducted a linear mixed model analysis on free recall performance, with group and trial (1, 2 and 3) as fixed effects, and participant as a random effect. As there was a ceiling effect for the three total recall trials, the assumption of normality was violated. We therefore carried out a generalized logistic mixed model on this variable, with group and trial as fixed effects, and participant as a random effect.
Data were dummy-coded according to whether the entire list of words was correctly recalled (=1) or not (=0). Pairwise comparisons were conducted using t tests adjusted for multiple comparisons using the Holm-Bonferroni method. Mixed models were conducted using the lme4 package  (Bates, Mächler, Bolker, & Walker, 2015)  in the R environment  (R Core Team, 2020). Finally, the relationships between background variables and verbal memory measures were examined with Spearman correlation coefficients, according to normality violation. Correction for multiple comparisons was done using the false discovery rate implemented in the ppcor package  (Kim, 2015). The significance level was set at 0. 05.
, 2014). Moreover, on a clinical level, binge drinking has been associated with blackouts  (Hingson, Zha, Simons-Morton, & White, 2016) , which are manifestations of damage to the hippocampal system  (Hermens & Lagopoulos, 2018). Finally, in a preclinical study, alterations in the basic cellular mechanisms of learning (i. e. , long-term depression) were found in the hippocampus of adolescent rats after only two binge drinking episodes (Silvestre de  Ferron et al. , 2015). Finally, we counted a large number of perseverations during recall among BDs. This result, in line with previous data  (Sanhueza et al. , 2011) , suggests that BDs had difficulty monitoring the task. They seemed to have problems knowing precisely what information had or had not already been given. Impairment of monitoring processes in BDs has already been highlighted in electrophysiological and behavioral studies of executive function  (Lannoy et al.
Acknowledgements We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. ABCFS thank  Maggie Angelakos ,  Judi Maskiell ,  Gillian Dite. ABCS thanks the  Blood bank Sanquin , The Netherlands. ABCTB samples are made available to researchers on a non-exclusive basis. The ACP study wishes to thank the participants in the Thai Breast Cancer study. Special thanks also go to the  Thai Ministry of Public Health (MOPH) , doctors and nurses who helped with the data collection process. Finally, the study would like to thank  Dr. Prat Boonyawongviroj , the former Permanent Secretary of MOPH and  Dr. Pornthep Siriwanarungsan , the former Department Director-General of Disease Control who have supported the study throughout.
UCIBCS thanks  Institutes of Health  ( R01 CA77398 ,  UM1 CA164917 , and  U01 CA199277 ). Collection of cancer incidence data was supported by the  California Department of Public Health  as part of the statewide cancer reporting program mandated by  California Health and Safety Code Section 103885. HAC receives support from the  Lon V Smith Foundation  ( LVS39420 ). The University of Westminster curates the DietCompLyf database funded by  Against Breast Cancer Registered Charity  No. 1121258  and the  NCRN. The coordination of EPIC is financially supported by the  European Commission (DG-SANCO)  and the  International Agency for Research on Cancer. The national cohorts are supported by:  Ligue Contre le Cancer ,  Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale ,  Institut National de la Santé et de la Recherche Médicale (INSERM) (France) ;  German Cancer Aid ,  German Cancer Research Center (DKFZ) ,  Federal Ministry of Education and Research (BMBF) (Germany) ; the  Hellenic Health Foundation , the  Stavros Niarchos Foundation (Greece) ;  Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy) ;  Dutch Ministry of Public Health, Welfare and Sports (VWS) ,  Netherlands Cancer Registry (NKR) ,  LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland) ,  World Cancer Research Fund (WCRF) ,  Statistics Netherlands  (The Netherlands);  Health Research Fund (FIS) ,  PI13/00061  to Granada,  PI13/01162  to  EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC  ( RD06/0020 ) (Spain);  Cancer Research UK  ( 14136  to  EPIC-Norfolk ;  C570/A16491  and  C8221/A19170  to  EPIC-Oxford ),  Medical Research Council  ( 1000143  to  EPIC-Norfolk ,  MR/M012190/1  to  EPIC-Oxford) (United Kingdom ).
The ESTHER study was supported by a grant from the  Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the  German Cancer Aid (Deutsche Krebshilfe ). The  GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer)  is supported by the  German Cancer Aid  (grant no  110837 , coordinator:  Rita K. Schmutzler , Cologne). This work was also funded by the  European Regional Development Fund and Free State of Saxony, Germany (LIFE -Leipzig Research Centre for Civilization Diseases , project numbers  713-241202 ,  713-241202 ,  14505/2470 ,  14575/2470 ). The GENICA was funded by the  Federal Ministry of Education and Research (BMBF)   Germany grants   01KW9975/5 ,  01KW9976/8 ,  01KW9977/0  and  01KW0114 , the  Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ) ,  Heidelberg , the  Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA) ,  Bochum , as well as the  Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany.
The GEPARSIXTO study was conducted by the  German Breast Group GmbH. The GESBC was supported by the  Deutsche Krebshilfe  e. V. [70492] and the  German Cancer Research Center (DKFZ). The HABCS study was supported by the  Claudia von Schilling Foundation for Breast Cancer Research , by the  Lower Saxonian Cancer Society , and by the  Rudolf Bartling Foundation. The HEBCS was financially supported by the  Helsinki University Hospital Research Fund , the  Finnish Cancer Society , and the  Sigrid Juselius Foundation. The HERPACC was supported by  MEXT Kakenhi  (No. 170150181  and  26253041 ) from the  Ministry of Education, Science, Sports, Culture and Technology of Japan , by a  Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control  from  Ministry Health, Labour and Welfare of Japan , by  Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan , by  National Cancer Center Research and Development Fund, and "Practical Research for Innovative Cancer Control  ( 15ck0106177h0001 )" from  Japan Agency for Medical Research and development, AMED , and  Cancer Bio Bank Aichi.
The HMBCS was supported by a grant from the  Friends of Hannover Medical School  and by the  Rudolf Bartling Foundation. The HUBCS was supported by a grant from the  German Federal Ministry of Research and Education  ( RUS08/017 ), B. M. was supported by grant  17-44-020498 ,  17-29-06014  of the  Russian Foundation for Basic Research , D. P. was supported by grant  18-29-09129  of the  Russian Foundation for Basic Research , E. K was supported by the program for support the bioresource collections  №007-030164/2 , and the study was performed as part of the assignment of the  Ministry of Science and Higher Education of the Russian Federation  ( №АААА-А16-116020350032-1 ). Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between  Stockholm County Council and Karolinska Institutet , the  Swedish Cancer Society , The Gustav V Jubilee foundation and Bert von Kantzows foundation.
The KARMA study was supported by  Märit and Hans Rausings Initiative Against Breast Cancer. The KBCP was financially supported by the special Government Funding (EVO) of  Kuopio University Hospital  grants,  Cancer Fund of North Savo , the  Finnish Cancer Organizations , and by the strategic funding of the  University of Eastern Finland. The KOHBRA study was partially supported by a grant from the  Korea Health Technology R&D Project  through the  Korea Health Industry Development Institute (KHIDI) , and the  National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea  ( HI16C1127 ;  1020350 ;  1420190 ). LMBC is supported by the 'Stichting tegen Kanker'. DL is supported by the  FWO. The MABCS study is funded by the  Research Centre for Genetic Engineering and Biotechnology "Georgi D.
and Margaret T. Grohne Family Foundation. The Melbourne Collaborative Cohort Study (MCCS) cohort recruitment was funded by  VicHealth  and  Cancer Council Victoria. The MCCS was further augmented by  Australian National Health and Medical Research Council  grants  209057 ,  396414  and  1074383  and by infrastructure provided by  Cancer Council Victoria. Cases and their vital status were ascertained through the  Victorian Cancer Registry  and the  Australian Institute of Health and Welfare , including the  National Death Index Research Centre. The WAABCS study was supported by grants from the  National Cancer Institute of the National Institutes of Health  ( R01 CA89085  and  P50 CA125183  and the  D43 TW009112  grant),  Susan G. Komen  ( SAC110026 ), the  Dr. Ralph and Marian Falk Medical Research Trust , and the  Avon Foundation for Women.
The Prostate cancer genome-wide association analyses are supported by the  Canadian Institutes of Health Research , Eu rop e an C om m iss i on's S e ve nt h Fr ame work Pro g r am me g r ant ag re e me nt n  ° 2 2 3 1 7 5 (HEALTH-F2-2009-223175 ),  Cancer Research UK  Grants  C5047/A7357 ,  C1287/A10118 ,  C1287/A16563 ,  C5047/A3354 ,  C5047/A10692 ,  C16913/A6135 , and The  National Institute of Health (NIH) Cancer Post-Cancer GWAS  initiative grant: No. 1 U19 CA 148537-01  (the  GAME-ON initiative ). Genotyping of the OncoArray was funded by the  US National Institutes of Health (NIH)  [ U19   CA 148537 for ELucidating Loci Involved in Prostate cancer SuscEptibility (ELLIPSE)  project and  X01HG007492  to the  Center for Inherited Disease Research (CIDR)  under contract number  HHSN268201200008I ] and by  Cancer Research UK  grant  A8197/A16565.
Irene Masunaka. UKBGS  thanks  Breast Cancer Now  and the  Institute of Cancer Research for support and funding of the Breakthrough Generations Study , and the study participants, study staff, and the doctors, nurses and other health care providers and health information sources who have contributed to the study. We acknowledge NHS funding to the  Royal Marsden/ICR NIHR Biomedical Research Centre. We acknowledge funding to the  Manchester NIHR Biomedical Research Centre  ( IS-BRC-1215-20007 ). We thank the UKOPS participants who donated their samples and data and all the researchers, especially  Andy Ryan ,  Simon Gayther  and  Ian Jacobs. Finally , we thank the  PRACTICAL consortium. J. Liu  received a scholarship from the  China Scholarship Council (Beijing, China). BCAC is funded by  Cancer Research UK  [ C1287/A16563 ,  C1287/A10118 ], the  European Union 's  Horizon 2020 Research and Innovation Programme  (grant numbers  634935  and  633784  for BRIDGES and B-CAST respectively), and by the  European Community´s Seventh Framework Programme  under grant agreement number  223175  (grant number  HEALTH-F2-2009-223175 ) (COGS).
The  EU Horizon 2020 Research and Innovation Programme  funding source had no role in study design, data collection, data analysis, data interpretation or writing of the report. Genotyping of the OncoArray was funded by the  NIH  Grant  U19 CA148065 , and  Cancer UK  Grant  C1287/A16563  and the  PERSPECTIVE  project supported by the  Government of Canada through Genome Canada  and the  Canadian Institutes of Health Research  (grant  GPH-129344 ) and, the  Ministère de l'Économie, Science et Innovation du Québec through Genome Québec  and the  PSRSIIRI-701  grant, and the  Quebec Breast Cancer Foundation. Funding for the iCOGS infrastructure came from: the  European Community 's  Seventh Framework Programme  under grant agreement n°  223175  ( HEALTH-F2-2009-223175 ) (COGS),  Cancer Research UK  ( C1287/A10118 ,  C1287/A10710 ,  C12292/A11174 ,  C1281/A12014 ,  C5047/A8384 ,  C5047/A15007 ,  C5047/A10692 ,  C8197/A16565 ), the  National Institutes of Health  ( CA128978 ) and  Post-Cancer GWAS initiative  ( 1U19 CA148537 ,  1U19 CA148065  and  1U19 CA148112  -the  GAME-ON initiative ), the  Department of Defence  ( W81XWH-10-1-0341 ), the  Canadian Institutes of Health Research (CIHR)  for the  CIHR Team in Familial Risks of Breast Cancer , and  Komen Foundation  for the Cure, the  Breast Cancer Research Foundation , and the  Ovarian Cancer Research Fund.