dataesr/scientific-paragraphs-categorization huggingface dataset:
Understanding how terrestrial biogeochemical processes contribute to the emergent response of ecosystems to warming and drying during El Nin ˜o events is crucial to comprehend the vulnerability of land ecosystems to future changes in climate in the tropics and other sensitive regions. Data accessibility. CO 2 fluxes from the CAMS atmospheric inversion are freely available at http://atmosphere. copernicus. eu/. CarboScope datasets are available at http://www. bgc-jena. mpg. de/Carbo-Scope/. The monthly time series of global and tropical CO 2 fluxes are provided for each inversion in electronic supplementary material. Outputs from land surface models from the TRENDYv6 project used in this study are provided in electronic supplementary material. These are the time series of global/tropical average monthly NBP, GPP, TER and fire emissions from each individual model, as well as the annual and seasonal gridded anomalies of the MMEM NBP, GPP, TER and LAI.
Annual and seasonal anomaly NBP maps from inversions, and annual NBP maps from individual models are also provided. The full TRENDYv6 dataset including other outputs is available, subject to the individual modelling groups' agreement, via a request to S. Sitch (s. a. sitch@exeter. ac. uk). The results from the Global Carbon Budget 2017 are available for download at http:// www. globalcarbonproject. org/carbonbudget/17/data. htm. Annual anomalies of WUE-GPP are provided in electronic supplementary material. The GFED4. 1s fire emission database is publicly available at http://www. globalfiredata. org/data. html. MODIS data are freely available at https://lpdaac. usgs. gov/dataset_discovery/ modis/modis_products_table. The L-VOD data can be accessed at the Centre Aval de Traitement des Donnees SMOS (CATDS): ftp://ext-catds-cecsm:catds2010@ftp.
Agency Climate Change Initiative ESA-RECCAP2  project ( ESRIN/ 4000123002/18/I-NB ). F. C is funded by the  Copernicus Atmosphere Monitoring Service , implemented by the  European Centre for Medium-Range Weather Forecasts (ECMWF)  on behalf of the  European Commission. A. K. J. is funded by the  US National Science Foundation  ( NSF-AGS-12-43071 ). A. W. was supported by the  Newton Fund  through the  Met Office Climate Science for Service Partnership Brazil (CSSP Brazil ). P. C is funded by the  European Research Council Synergy  [grant no. ERC-2013-SyG-610028 IMBAL-ANCE-P]. P. F. is supported by the  EC H2020  project  CRESCENDO  (grant no. 641816 ). V. H. , P. R. B. and P. C. are supported by the  Earth Systems and Climate Change Hub , funded by the  Australian Government 's  National Environmental Science Program.
S. Z. is supported by the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme (QUINCY ; grant no. 647204 ). J. P. and J. E. M. S. N. are supported by the  German Research Foundation 's  Emmy Noether Program. S. L. and F. J. acknowledge the support by the  Swiss National Science Foundation  (# 200020_172476 ). J. -P. W. and A. M. were supported by funding programmes of the  Centre National d'Etudes Spatiales (CNES)  and the  European Space Agency (ESA). L. C. is funded by the  National Natural Science Foundation of China  ( 51861125102 ) and by the  National Key Research and Development Program of China  ( 2017YFC1502503 ). C. v. E. was funded by the  Belgian Science Policy Office (BELSPO)  in the framework of the  STEREO III  programme, project  SAT-EX  ( SR/00/306 ).
The worse partner's improvement came at no cost to the better partner's performance. Next, we examined how the partners' effort was affected by the coupling dynamics. The effort was measured from the mean absolute value of the electromyography signals from a wrist flexor-extensor muscle pair of each partner normalized to their torque-equivalent values (see Experiments for calibration procedure). We computed the interaction effort, α c /α -1, as the difference between the effort in the connected trial α c and the effort in the proceeding solo trial α. This interaction effort is plotted, in Fig 2B, as a function of the relative error for the hard (red), medium (blue) and soft interactions (green), where the lines are the fits to the data using a linear mixed-effects model with the interaction effort as the dependent variable and Results of physical interaction between humans through different coupling dynamics.
Surface electromyography (EMG) was used to collect data from the flexor carpi radialis (FCR) and extensor carpi radialis longus (ECRL) muscles. Subjects were asked to flex or extend their wrist while the device kept their wrist locked at 0 degrees, the subject's most comfortable position. The subject was asked to produce flexion and extension torques of 1, 2, 3 and 4 Nm for 2 seconds, first flexion then extension, with a rest period of 5 seconds between each activation to prevent fatigue. This EMG data was linearly regressed versus torque to estimate the relationship between muscular activity and torque. The effort measure used in this study uses these estimated torques values. Another 8 subjects were recruited individually to carry out a haptic tracking control experiment. The target movement was the same as in Eq (1) and the cursor was visible but the target was invisible through the trial.
Funding was provided by ICT-231554 HUMOUR (AT, EB), ICT-601003 BALANCE (EB), ICT-611626 SYMBITRON (EB),  EU-H2020 ICT-644727  COGIMON (AT, EB),  UK EPSRC MOTION  grant  EP/NO29003/1  (EB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Methods This 8 week, open-label study (registered at ClinicalTrials. gov, NCT01130597) was conducted at 13 centres in Georgia and Slovenia between May 2010 and September 2010. All participating sites received approval from their nationally or locally appointed Independent Ethics Committee, and all patients provided written informed consent. The study was performed in accordance with the Declaration of Helsinki, current local and national regulations, the International Conference on Harmonization, and Good Clinical Practice guidelines and fulfilled other applicable requirements governing the conduct of human clinical trials.
Statistical analysis A total of 63 patients were enrolled to ensure that at least 50 patients would receive patiromer and provide efficacy data for analysis. The sample size was based on the patiromer response predicted from the PEARL-HF study. 16 For the primary efficacy endpoint, the proportion of patients with serum K + 3. 5-5. 5 mEq/L at the end of the study treatment was summarized along with 95% confidence intervals (CIs). The analysis population for the primary and secondary efficacy endpoints, and for assessment of safety, was the intent-to-treat population (i. e. , all enrolled patients). Baseline values were obtained from the last available measurement prior to the start of patiromer. For categorical secondary endpoints, the proportion of patients and 95% CIs were summarized. AEs were summarized descriptively.
Although available data, specifically those collected during the past decade, show an increased frequency of anaphylaxis, there are still challenges in interpreting these informations  [6, 7]  and its global applicability. The most widely discussed issues in the epidemiology of anaphylaxis filed over the last 10 years are: (I) regional variations in concepts and definitions (Fig. 1 )  [1] [2] [3] [8] [9] [10] , (II) whether prevalence or incidence is the best measure of the frequency of anaphylaxis in the general population, (III) whether the frequency of anaphylaxis is higher than previously thought, and (IV) whether the increasing incidence published is real or reflects different methodologies and definitions used. Over the last several years, an increasing number of clinical databases have been developed to capture reliable anaphylaxis epidemiological data at both national and regional levels (Fig.
Generally speaking, population-based studies have adopted the World Health Organization (WHO) International Classification of Diseases (ICD) as the main tool to capture the proposed outcomes. These studies have been especially useful in detailing timerelated trends, capturing clinical practice and principal discharge diagnosis coding statistics, and in providing broader morbidity and mortality statistics (MMS). However, anaphylaxis has never been well classified under the ICD context, either for morbidity  [11]  (Table  1 ) or for mortality data  [12]. This is exemplified by the undernotification of anaphylaxis deaths using the Brazilian national mortality database  [12]. An important reason for this is the difficulty of coding anaphylaxis fatalities under the WHO ICD system. In most countries, mortality statistics are routinely compiled according to regulations and recommendations adopted by the World Health Assembly (WHA).
Causes of deaths are classified and grouped according to the ICD edition in use at the time and the information on death certificates is collected using the international form recommended by the WHO. However, a limited number of ICD-10 codes are considered to be valid for representing underlying causes of death on the current death certificates, and with regard to anaphylaxis as such, there are simply no valid codes  [12]. Taking the opportunity presented by the ongoing ICD-11 revision, the under-notification of death data  [12]  triggered a cascade of strategic international actions supported by the Joint Allergy Academies and the ICD WHO governance  [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23]  to update the classifications of allergic conditions for the new ICD edition.
Lessons from population-based anaphylaxis morbidity epidemiology publications From 19th to 26th October 2016, 1896 manuscripts were selected using PubMed Mesh terms "anaphylaxis epidemiology", "epidemiology of anaphylaxis" or "anaphylaxis epidemiology population-based studies". After removing those published before 2011 and those not published in English, there were 532 papers published in the last 5 years. We did not include case reports, studies in animal models, quality of life studies, fatality studies, guidelines or reviews (Fig. 4 ). All publications were independently evaluated by two co-authors and disagreements related to the inclusion into the analysis were resolved through open discussion and consensus. We analyzed methodological aspects, main outcomes and databases used in the remaining 15 publications selected as eligible according to the selection criteria (Fig.
4 ) from different countries. The methods used and the definitions taken varied among the publications; however, 67% focused on rates of hospitalization or emergency department admissions. National databases were used in 67% of the studies. Overall, 40% were large population-based studies and 100% of these documents used the ICD definition as the starting point of the analysis (Table  2 ). Based on ICD registries, regardless of the ICD version used, 71% of all the studies had to utilize secondary data in order to capture the anaphylaxis data, meaning that the data have been affected by the misclassification of anaphylaxis in the previous versions of the ICD. Most of the studies (60%) did not address the possibility of recurrence of episodes, and, therefore, of cumulative incidence. This highlights the need to distinguish the number of patients with anaphylaxis per year from the number of episodes per year.
The Orphanet, lead by the French National Institution of Health and Medical Research (INSERM) and the French Ministry of Health, is responsible for developing an inventory of rare diseases and a classification system which could serve as a template to update International terminologies. When the WHO launched the revision process of the ICD, a rare diseases Topic Advisory Group was established. So far 5400 rare diseases listed in the Orphanet database have an endorsed representation in the foundation layer of  28] , but severe anaphylaxis is not yet included on the list. In addition to all the benefits expected by the actions to update terminology, definitions and classification of allergic and hypersensitivity conditions through the ICD-11 revision, we strongly believe that anaphylaxis is a public health priority, therefore in order to strengthen awareness and quality clinical management of patients it should therefore be formally added to the list of rare diseases.
The ICD-11 intends will be presented to the WHA in 2018. A known issue regarding accurate epidemiological data and miscoding is the lack of training regarding how disorders should be classified and coded in administrative and institutional databases. For this reason, the core ALLERGY in ICD-11 operational team (LKT, PD) in collaboration with the WHO and with the support of our international academies network, intends to implement education tools to support the allergy community in the transition process, preparing health professionals and stakeholders for the new logic of the ICD-11, when it is launched. Educational efforts will also help to decrease the under-recognition of anaphylaxis by patients, caregivers, and health professionals, health authorities and governments and have been the main aim of allergy academies by promoting education programs and publications in the field.
Acknowledgements We are extremely grateful to all the representatives of the ICD-11  Revision  Project with whom we have been carrying on fruitful discussions, helping us to refine the classification presented here:  Robert Jakob ,  Linda Best ,  Nenad Kostanjsek ,  Robert J. G. Chalmers ,  Jeffrey Linzer ,  Linda Edwards ,  Ségolène Ayme ,  Bertrand Bellet ,  Rodney Franklin ,  Matthew Helbert ,  August Colenbrander ,  Satoshi Kashii ,  Paulo E. C. Dantas ,  Christine Graham ,  Ashley Behrens ,  Julie Rust ,  Megan Cumerlato ,  Tsutomu Suzuki ,  Mitsuko Kondo ,  Hajime Takizawa ,  Nobuoki Kohno ,  Soichiro Miura ,  Nan Tajima  and  Toshio Ogawa.
5 per 100,000 Incidence of anaphylaxis: 12. 0 per 100,000 person- years Prevalence of anaphylaxis: 582 Patients needing more than 1 dose of epineph- rine: 8% Incidence admissions for anaphylaxis: 11. 05 per 100,000 person-years Paediatric admissions with anaphylaxis: 6-23/year Adult admissions with anaphylaxis: 183-331/ year Emergency department visits for anaphylaxis: 23. 2 per 100,000 person- years Incidence of anaphylaxis: 7. 5 per 100,000 person- years Self-reported cases from the general population based on survey ques- tionnaire Retrospective observa- tional study based on search terms consider- ing the WAO anaphylaxis definition [7] Historic-prospective observational cohort study with analysis of medical records based on the NIAID/FAAN diagnostic criteria for anaphylaxis [1] Search for ICD-10 ana- phylaxis and secondary codes as primary cause of hospitalization Retrospective analysis of all physician-diagnosed cases in national audit data from critical care units considering NIAID/ FAAN anaphylaxis definition [1] as first or secondary cause of admission Retrospective cohort study with dichoto- mized algorithm for "anaphylaxis" consider- ing the WAO definition for anaphylaxis [7] Population-based epide- miologic study using national database and selected ICD codes Beyer et al.
6 per 1,000,000 person-years % Anaphylaxis among all calls: 0. 31 % Anaphylaxis among calls requiring transport: 0. 44 Incidence rate of anaphy- laxis was 42 per 100,000 person-years Increase in overall ana- phylaxis admission rates: 1. 5-fold/7 years Anaphylaxis admissions in the general population: 1. 35-2. 38 per 100,000 person-years Prevalence of anaphylaxis in the general popula- tion: 1. 6% Number of anaphylaxis cases: 3333 Recurrence: 34. 2% Number of hospital admissions for anaphy- laxis: 1. 0-7. 0 cases per 100,000 population per annum Population-based cohort study using national database and selected ICD codes Software program applied to prospectively record characters of anaphy- laxis cases taking the WAO definition of anaphylaxis [7] Population-based inci- dence study selected by ICD codes Population-based epide- miologic study using national database and selected ICD codes Population-based epide- miologic study using national database and selected ICD codes Self-reported cases from the general population based on survey ques- tionnaire considering the main anaphylaxis definitions [1, 3, 6, 7] Data collection from specialized European countries by online questionnaire consider- ing the EAACI-WAO revised nomenclature [45] Population-based epide- miologic study using hospital admission data and selected ICD codes Denmark Canada United States of America Australia Spain United States of America European countries (Aus- tria, Bulgaria, France, Ger- many, Greece, Ireland, Italy, Poland, Spain and Switzerland) United Kingdom Jeppesen et al.
, 2011)  and heat and freshwater fluxes from the COADS data set  (da Silva et al. , 1994). The model forcing also includes a 23,000 m 3 /s discharge from La Plata River and the principal semidiurnal tidal constituent (M 2 ). For vertical mixing, the model uses a K-Profile Parameterization scheme  (Large et al. , 1994)  and a quadratic friction law with a friction parameter α = 0. 045. No explicit horizontal diffusion and viscosity have been added. More detailed technical description of the model configuration can be found in  Combes and Matano (2014a). For the present study, we used a climatological average of the last 10 years of the model run.
Characterization of the STSF To characterize the STSF, we construct T-S and quantitative T-S diagrams employing the model's output data. The data were averaged for each season, and only subsurface data (z < À50 m) located between the 50 and 200 m isobath were used to construct the T-S diagrams. The thermohaline indexes used to describe the main 10. 1029/2018JC013824 Journal of Geophysical Research: Oceans shelf water masses (SASW and STSW) seen in Figure  2  followed  Piola et al. (2000). To validate the model output, we employed historical hydrographic data collected along the shelf (z > À200 m) between 20°S and 40°S and from 1960 to 1990  (Piola et al. , 2000). This large database is likely to characterize climatological conditions, and therefore, we believe that is suitable for the validation of the model's performance in representing the STSF.
Study design and data collection A national, multicentre, noninterventional, longitudinal epidemiological study was conducted in France, in a representative population of men treated with a GnRH analogue for locally advanced or metastatic PCa, conducted under the aegis of the Association Française d'Urologie. The study ran from September 2011 to January 2015. Assessments were made at consultations scheduled by the participating physicians as part of the standard follow up for patients (usually every 6 months). All prescribed medications and medication changes were at the sole discretion of the physician and the patient. Data available in the patients' medical records and data collected for 24 months following inclusion as part of the routine management of their disease were used in the analysis.
For the initial selection of variables, the level of significance was 20%. The stepwise selection of variables for the multivariate analysis was made at a significance level of 5%. Statistical analyses were performed using SAS ® software, version 9. 1 or later (SAS Institute, NC, USA). Since percentages were calculated from the answers provided on the CRF (excluding missing data), the figures do not always add up to 100%. Multiple responses to a single element of the CRF have produced percentages over 100%.
ACKNOWLEDGEMENTS We would like to thank the members of  Animaleries Lyon Est Conventionnelle et SPF (ALECS, Université Lyon 1, SFR Santé Lyon Est)  for the animal care, the members of the  CIQLE platform (Université Lyon 1, SFR Santé Lyon Est ) for the TEM observations and the members of the Anipath platform for the histology experiments (Université Lyon 1). We thank  Dr. Catherine Postic  for constructive discussions. This work was supported by research grants from the  Agence Nationale de la Recherche  ( ANR-15-CE14-0026-03  and  ANR16-CE14-0022-02 ), the  Association Francophone des Glycogénoses , and the Ligue régionale contre le cancer. LM and MG are recipients of funding of the  Fondation pour la Recherche Médicale  (FRM grant number  ECO20160736048 ) and the Ligue nationale contre le cancer, respectively.
MG with anti-LRP4 antibodies The LRP4 protein belongs to a family of proteins that has been recently identified as the receptor for the neural agrin that can activate MuSK  [17]. Patients with anti-LRP4 antibodies were only described in 2011  [3, 18]  (Table  1 ). A study has investigated a large number LRP4-MG patients  [19]. The clinical data collected for LRP4-MG patients showed that at disease onset, symptoms are mild with some identified thymic changes (32% with follicular hyperplasia, none with thymoma). These patients are predominantly of the IgG1 and IgG2 subtypes that can activate the complement cascade. In the LRP4 induced-mouse model, alterations of the NMJ is observed  [20]. Overall, the response of LRP4-MG patients to treatment seems more similar to that of AChR-MG than of MuSK-MG patients  [19].
The final per protocol (PP) study sample was 80 women and 86 men (N ¼ 166). Fig. S1  in supplementary data, gives the flow diagram of the recruitment and participation through the phases of the study. All participants signed an informed consent form and were informed of their right to withdraw from the study at any time. The protocol was approved by the Institutional review Board (CPP of Lyon Sud-Est III, September 16, 2014), registered and authorized by the French competent health authorities  (ANSM, June 19, 2014 , N ID RCB: 2014-A01024-43). The study was registered in the Protocol Results registration System (PRS) at ClinicalTrial. gov (Identifier: NCT02297880). The first participant was enrolled on October 14, 2014 and the experimental procedure ended on March 14, 2016.
A registered dietician instructed each participant about weighing all the food they consumed on the next day (using a portable household scale lent by the research center) and to reporting the quantity (leftovers deducted) in a food diary. Energy and nutrient intakes were computed using the validated Nutri-7 ® software  (Fantino & Gourmet, 2008; Ghisolfi, Fantino, Turck, de Courcy, & Vidailhet, 2013)  based on the food composition indicated by the producers or on the CIQUAL French food composition table of the French Food Safety Agency (ANSES) (https://pro. anses. fr/tableciqual/). Appetite ratings were obtained during the laboratory session. At 1 h intervals between 08:00 h and 22:00 h, and after each meal, participants rated their sensations of hunger, fullness, and desireto-eat using digital Visual Analogue Scales (touch screen VAS).
Statistical analysis The hypothesis was the "non inferiority" of LCS beverages compared to water for their effects on food intake behavior prior to and after a 5-wk habituation. The sample size was computed using NQuery 7. 0 software separately for males and females, considering the non-inferiority margin (i. e. the maximum value over which two daily TEI can be considered equal) as 15% with a 2-sided 5% type 1 error and a statistical power of 80%. The non-inferiority margin was determined according to the method prescribed by the Food and Drug Administration (FDA, 2016) and European Medicines Agency  (EMA, 2005). Since there was no-drop out after the first measurement week, a single analysis population was used including all randomized participants (80 women and 86 men). The primary objective was the demonstration of the "non inferiority" of the daily TEI associated with LCS versus water during the cross-over pre-habituation measurement (sessions 2 and 3).