dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements A. C. and P. W. are very grateful to  Thomas Zacharias ,  Aggelos Kiayias  and especially  Yiannis Tselekounis  for many useful discussions about the security proofs. L. C. also thanks  Atul Mantri  and  Dominique Unruh  for useful preliminary conversations, with a special mention to  Céline Chevalier  whose discussions were a precious source of inspiration. A. C. would also like to show his appreciation to his grandmother,  Petra Ilie  for all the support and help she has given to him his entire life. The work was supported by  EPSRC  grants  EP/N003829/1  and  EP/M013243/1.
Using metagenomics data generated from a spacecraft assembly facility and the International Space Station (ISS), environmental samples were analyzed for radiation-resistant non-spore forming microorganisms  (Be et al. 2017 ). Among the wide spectrum of DNA sequence reads associated with microorganisms (~7 million), only 600 to 6,000 reads (~1 to 10%) were related to the functional gene sequences of the radiation resistant microorganisms of interest. Focused development of spacecraft specific nucleic acid databases to assist in future instrumentation/ experiment development, identifying and characterizing core microbiomes, assessing microbial changes to the environment and determining the prevalence of relevant microorganisms is necessary for this technology to be fully exploited as a risk analysis tool.
The 2018 COSPAR workshop  (Race et al. 2019 ) identified crew health microbial monitoring as a significant KG that could be addressed by developing and implementing a routine monitoring plan for all current and future missions. Samples should be collected at a higher frequency than at the (present) quarterly level, and be archived. A human health baseline must be established so that deviations can be detected. Crew health should be framed in context of event detection and risk, identifying critical steps and issues that pose risks; categorize those risks, identify by their likelihood and consequence to create a stepped approach to operational decision-making. DNA sequencing can be used to collect the needed data and integrate it with other data sets to understand the true key health issues, including prioritization of contamination risk, assessment of the best protocols for control and mitigation (see 3.
Search Strategy A narrative literature search was conducted on 8 September 2020 to address research questions related to the dominant comorbidities of CVD, infections, lymphoma and NMSC in patients with RA. For each of these comorbidities, the literature search aimed to identify publications relating to their prevalence and associated risk factors, their impact on clinical outcomes, health-related quality of life and patient management, and the effects of TNF inhibitors on these comorbidities. The PubMed database was searched using a keyword search restricted to "Title Only" using terms relating to RA and cardiovascular (CV), infection, lymphoma, BCC or SCC. Search results were further refined by limiting the search using a MeSH Major Topic or keyword title search using search terms to identify publications discussing the prevalence of comorbidities, the factors contributing to comorbidities, the impact of comorbidities and the effect of TNF inhibitors on comorbidities.
The complete search strings are provided in Table  S1  in the supplementary materials. Only articles published within the past 5 years were included. Articles were reviewed for relevance based on the article title and abstract, with all article types taken into consideration if they included data relevant to the research questions. To provide essential historical context to the current literature, several sections include references published before 2015. Additional references were identified through searching the bibliographies of retrieved articles, through a search of abstracts presented at the European League Against Rheumatism (EULAR) congress in 2019 and 2020, and through author suggestions.
Prevalence of CVD in Patients with RA CVD is a major comorbidity affecting patients with RA and a leading cause of morbidity and mortality in this population  [18]. Multiple recent studies have highlighted the extent to which patients with RA are affected by CVD, although comparisons between studies are often hindered by differences in the definition of events (Table  1 ). Patients with RA have been shown to be at higher risk of CVD compared with healthy controls. Using a large database of primary care patients across England, patients with early RA had a 33% higher CVD risk (composite endpoint of MI, stroke or heart failure) than matched controls without RA after adjustment for baseline differences including inflammatory markers, seropositivity and use of glucocorticoids (GCs) at diagnosis  [19].
Similarly, in a large cohort study of patients who experienced an acute coronary syndrome (ACS) event, patients with RA had a 27% and 50% increased risk of ACS recurrence or mortality, respectively, after a mean 2-year follow-up compared with controls, which remained statistically significant even after adjustment for baseline comorbidities. This increased risk could not be explained by differences in the use of standard-of-care secondary preventative drugs  [34]. The presence of RA can also have a negative impact on short-term outcomes following CV events. In a recent database study in Taiwan, patients with RA had a higher risk of inhospital mortality after acute MI, intracranial haemorrhage or ischaemic stroke compared with patients without RA  [35]. Similarly, a large Swedish study demonstrated that mortality rates within 1 week and 1 month following an ACS event were significantly higher in patients with RA compared with a matched cohort from the general population, even after adjustment for age, sex, pre-existing comorbidities and pharmacotherapies, and ACS type.
In terms of treatment, nonsteroidal anti-inflammatory drugs (NSAIDs) should be used with caution in patients with documented CVD or with CVD risk factors, and the dose of GCs should be kept to a minimum for prolonged treatments  [53]. The guidelines also emphasised the important role of the rheumatologist in CVD risk management  [53]. Fortunately, physicians appear to be aware of the need to monitor CVD risk in patients with active RA: a study of 14,503 patients in world-wide data from the SUrvey of cardiovascular disease Risk Factor management in Rheumatoid Arthritis (SURF-RA) database demonstrated that positivity for rheumatoid factor and anticitrullinated protein antibodies, longer disease duration and higher disease activity (measured by Disease Activity Score 28 joint count-C reactive protein (CRP)) was associated with a higher likelihood of lipid and blood pressure assessments  [54].
Similarly, a large study of patients with RA recruited to the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis (BSRBR-RA) demonstrated that treatment with TNF inhibitors significantly reduced the risk of MI compared with csDMARDs, although no differences in MI severity or mortality were observed between treatment groups  [59]. The benefits of TNF inhibitors and other biologics were also demonstrated in a prospective cohort study from Australia, which concluded that, after adjustment for a number of risk factors, the risk of CV events was significantly reduced following the use of these agents in patients with RA, psoriatic arthritis (PsA) or ankylosing spondylitis (AS)  [60]. Length of treatment may also have an impact on CV risk, with a large retrospective insurance claims database study in the USA reporting a positive correlation between duration of treatment with TNF inhibitors and reduction in CV risk.
The benefits of TNF inhibitors on CVD risk correlate with their impact on RA disease control, with data from the Swedish biologics register demonstrating that the 1-year risk of ACS for patients with a good EULAR response was approximately half that of patients with no EULAR response  [64]. Similarly, improvements in the apolipoprotein profile, a biomarker of CVD risk, were observed in patients with RA who exhibited a good or moderate EULAR response to etanercept but not in EULAR nonresponders  [65]. The relationship between RA disease control and the impact of TNF inhibitors on CV risk suggests that these agents may exert their effects through reducing systemic inflammation rather than by modifying traditional CV risk factors. This is supported by a phase IV, randomised, double-blind, placebo-controlled study, which demonstrated that etanercept did not affect levels of traditional metabolic risk factors (including glucose, insulin, lipid and apolipoprotein parameters) despite reducing RA severity, as indicated by decreases in CRP  [66].
However, this does not appear to translate to increased clinical risks, with a number of studies showing no significant differences between TNF inhibitors and tocilizumab in terms of CV risk  [71] [72] [73]. This included the ENTRACTE randomised controlled trial (RCT), which demonstrated no significant differences in the risk of MACE between tocilizumab and etanercept in a large population of patients with RA and at least one CV risk factor  [71]. Conversely, there is some limited evidence that tocilizumab may offer CV benefits compared with TNF inhibitors, including improvements in lipoprotein markers  [74, 75]  and a lower risk of MACE  [76]. Similarly, a large study utilising data from Taiwan's National Health Insurance claims database reported that TNF inhibitor nonresponders who received tocilizumab had a lower risk of CV events compared with patients who received rituximab  [77].
More recently, a longitudinal, prospective, real-world study of patients included in the FORWARD database (the largest patient-reported research data bank for rheumatic disorders in the US  [87] ) from 2001 to 2016 reported that the risk of SI and joint infections was 70% higher in patients with RA (n = 20,361) compared with a matched cohort of patients with noninflammatory rheumatic and musculoskeletal diseases (n = 6176; hazard ratio (HR): 1. 7; 95% confidence interval (CI): 1. 5-1. 8) [88]. Subsequent data from the FORWARD database demonstrated that 5. 9% of patients with RA treated with TNF inhibitors, non-TNF inhibitors, bDMARDs (abatacept, rituximab, tocilizumab and anakinra) or csDMARDs (n = 11,623) experienced an SI during 27,552 patient-years of follow-up  [89]. Studies from other parts of the world reinforce the association between RA and the increased burden of infection, with studies from the UK and India reporting that between 3% and 8% of patients with RA experience infections (Table  3 )  [90, 91].
Infections in Preliminary data on COVID-19 in patients with RA have been emerging throughout 2020, and although data are limited at the time of writing in December 2020, most data indicate that patients with RA are not at an increased risk of contracting COVID-19 compared with the general population  [99, 100]. A systematic review of eight observational cohort studies, comprising 6095 patients with rheumatic disease, indicated that patients were not particularly susceptible to COVID-19. The majority of those infected experienced a mild clinical course, and there was a low level of fatalities  [100]. Two survey studies of patients with rheumatological diseases also demonstrated that the incidence of COVID-19 and associated symptoms were consistent with the general population  [101, 102] , although, in a study from the Global Rheumatology Alliance registry, patients with rheumatic disease (n = 600) and comorbidities, such as hypertension, CVD and diabetes, had higher odds of hospitalisation due to COVID-19  [103].
0; 95% CI: 0. 9-1. 3) [114]. In addition, the aforementioned population-based cohort study in Denmark of patients hospitalised for pneumonia demonstrated that high RA disease activity prior to hospitalisation was associated with a five-fold increased risk of 90-day mortality compared with patients with low RA activity, although overall mortality rates were not higher for patients with RA vs. patients without RA (19. 9% and 18. 9%, respectively)  [107]. A study of the FORWARD database reported that compared with patients with noninflammatory rheumatic and musculoskeletal diseases, patients with RA with low disease activity, or in remission, had a similar SI risk; however, patients with moderate and high RA disease activity had a significantly increased SI risk  [88]. Authors of these studies discussed the clinical relevance of their results and suggested that for patients with high RA disease activity, the treatment goal should be to obtain low-grade disease activity or remission as this may result in improved outcomes for patients with SI  [88, 107].
Treatment Regimens and the Risk of Infection in Patients with RA Regimens used frequently in the treatment of RA, including GCs and DMARDs, have been associated with an increased risk of infection or the reactivation of latent infections (Table  4 ). GCs Increase the Risk of Infection in Patients with RA GCs are effective and widely used in RA, although the benefit-to-risk ratio of this treatment remains precarious  [118]. The role of GCs in increasing patient susceptibility to SIs and the associated mortality is supported by numerous studies  [88, 93, 95]. For example, in a study of the FORWARD database, the current use of GCs was the strongest predictor of SI. Additionally, when the HR was adjusted to account for GC use, the excess risk of SI for patients with RA, compared with a matched cohort of patients with noninflammatory rheumatic and musculoskeletal diseases, was attenuated from 70% to 30% (HR: 1.
TNF Inhibitors and the Risk of Infection in Patients with RA The increased risk of infections is one of the most important considerations when prescribing TNF inhibitors, although the magnitude of this risk is a topic of debate  [120]. Results from a study of the FORWARD database demonstrated that the SI incidence rate per 1000 patient-years was increased in patients receiving TNF inhibitors (26. 9; 95% CI: 24. 5-29. 6) or non-TNF-inhibitor bDMARDs (23. 3; 95% CI: 19. 0-28. 5) vs. csDMARDs  (22. 4 ; 95% CI: 19. 2-26. 1) (Table  4 )  [89]. A meta-analysis of  71  RCTs and seven open-label extension studies in patients with RA, PsA and AS in 2014 found significant increases in the occurrence of any infections, SI and TB associated with TNF inhibitor treatment (20%, 40% and 250%, respectively)  [117].
Data from a 10-year retrospective review demonstrated that the lowest rate of SI was observed in those receiving treatment with adalimumab (5. 3/100 person-years) and it was highest with infliximab (34. 5/100 person-years) vs. other bDMARDs  [110]. Multiple studies have reported no significant differences in the risk of infection between TNF inhibitors when compared with other biologics and drug classes. For instance, a study of the BSRBR-RA reported that after adjusting for confounding variables, there were no differences between a number of different biologics (all biologics, TNF inhibitors, rituximab and tocilizumab) in the risk of SIs for patients with RA  [96]. A study of the FORWARD database also demonstrated that the risk of SI among patients with RA treated with TNF inhibitors was not significantly different from that observed with other non-TNFinhibitor bDMARDs  [89].
Evidence from a propensity-score-matched study of 11,248 pairs of patients with RA included in the MarketScan database demonstrated increased rates of hospitalisation due to infection in patients treated with TNF inhibitors (as a class) compared with those treated with abatacept (HR: 0. 8; 95% CI: 0. 6-1. 0) [124]. Of note, hospitalisation rates due to infection continued to be higher when infliximab was compared with abatacept (HR: 0. 6; 95% CI: 0. 5-0. 9), although no significant differences were reported when etanercept or adalimumab was compared with abatacept  [124]. Conversely, a cohort study analysing Medicare data reported that patients treated with etanercept, infliximab or rituximab had a significantly higher 1-year risk of hospitalisation due to infection than patients treated with abatacept (adjusted HRs: 1.
Following the issuing of a US Food and Drug Administration (FDA) black box warning in 2009 for the use of TNF inhibitors and the risk of developing NHL (based on limited data), a nested case-control study within a retrospective cohort of adult patients with rheumatologic conditions (RA, PsA or AS), drawn from a US commercial health insurance database, was undertaken to fully assess any potential risk  [159]. This analysis revealed that compared with matched controls (n = 984), patients with NHL (n = 101) had greater TNF inhibitor use (33% vs. 20%), with any use of a TNF inhibitor associated with an almost two-fold increased risk of NHL (OR: 1. 9; 95% CI: 1. 2-3. 2). When analysed by drug, etanercept was associated with an increased NHL risk (OR: 2. 7; 95% CI: 1. 4-5. 3), but no significant associations were reported for other TNF inhibitors.
The findings from this study also suggested an increasing risk with increasing duration of therapy (p-value for trend: 0. 05). Considering these observations, the authors concluded that the FDA black box warning was warranted and that continued surveillance for this potential adverse outcome is required  [159]. In addition, a pooled analysis of 11,317 patients with autoimmune diseases treated with the TNF inhibitor certolizumab pegol in clinical trials demonstrated that for patients with RA, lymphatic and haematopoietic cancer incidence (principally lymphoma) was increased compared with the age-and gender-matched GLOBOCAN/SEER general population (standardised IR: 2. 1; 95% CI 1. 2-3. 6) [160]. These results, however, differ from those from the BSRBR-RA. After adjusting for differences in baseline patient characteristics, a prospective cohort analysis of the BSRBR-RA database found no difference in the risk of lymphoma for RA patients receiving TNF inhibitors (n = 11,931) compared with those who were biologic-naïve (n = 3367) (HR: 1.
These accumulating data from large national registries, therefore, call into question the earlier data suggesting a link between TNF inhibitor use and the development of lymphoma. Notably, a recent overview of systematic reviews and meta-analyses of malignancy risk with TNF inhibitors noted no increase in lymphoma risk in patients with RA  [163]. With respect to csDMARDs, there is currently no compelling evidence to suggest an association between methotrexate use and lymphoma risk in patients with RA, as reviewed in Klein et al. [148]. The aforementioned study of 12,656 cases of incident RA from a Swedish registry reported no impact of methotrexate on the risk of lymphoma  [150]. However, a large historical case-control study of patients with RA from Canadian databases (n = 23,810) noted that the adjusted RR for lymphoma was slightly increased (1.
Acknowledgments : Medical writing support, funded by  Fresenius Kabi SwissBioSim GmbH , was provided by  Claire Stoker  and  Stephanie Carter of Arc , a division of Spirit Medical Communications Group Ltd. P. C. T. thanks the  National Institute of Health Research  for their funding of The  NIHR Biomedical Research Centre in Musculoskeletal Disease at Oxford University Hospitals NHS Trust  and the  University of Oxford.
B. Experimental method The aim of this study is to investigate the effect of atmospheric-like neutrons on different commercial SiC MOSFET technologies. Accelerated testing of Single Event Burnout (SEB) by using terrestrial neutrons was performed. The obtained data were used to calculate the effect cross sections and failure in time (FIT) rates at ground level. Additionally, the devices that did not exhibit destructive failure during exposure were characterized and their operational reliability was studied. Several samples were selected from the commercially available SiC VD-MOSFET technologies. The references and the corresponding technical information are listed in Table  I. All the devices are rated for 1. 2 kV and they are mounted in a TO-247 package. The devices were irradiated in their original packaging.
Catchment characteristics The sampling site is part of the Save basin, drained by the Save river, a left tributary of the Garonne river (southwestern France, Fig. 1 ). The middle and downstream part of the Save basin is mainly covered by wheat and sunflowers in rotation cultivation, and the upstream area by meadows and forests  (Taghavi et al. , 2011). As recorded by the Direction Départementale des Territoires (DDT), some 3000 ponds were constructed for irrigation in this area. According to the DDT database, three small adjacent agricultural catchments were considered for the study since they contained representative ponds as regards size and volume, and due to their different positions and managements in the catchment areas  (Wu, PhD, in progress). The three catchments are drained by the tributaries of the Save river, located close together on the right (Montoussé (MON), 325 ha; Mican (MIC), 277 ha) and left bank (Nuguet (NUG), 116 ha) of the middle Save basin (Fig.
More data can be found in Xinda Wu's PhD manuscript. Special thanks give to Direction Départementale des Territoires (DDT, http://www. ha ute-garonne. gouv. fr/Services-de-l-Etat/Agriculture-environnement-a menagement-et-logement/Direction-Departementale-des-Territoires) for the very helpful pond database. We also thank the three anonymous reviewers for their fruitfull comments. The authors thank the CNRS in France and the Chinese government fo ensuring a financial support.
Acknowledgements The authors are very grateful to the staff of Laboratoire écologie fonctionnelle et environnement for field samplings and/or for their help with preparing samples (H. H. Amouvadi ,  T. Badassan ,  A. Benabdelkader ,  T. Camboulive ,  C. Fabre ,  F. Granouillac ,  V. Payre-Suc ,  V. Ponnou-Delaffon ,  J. -L. Probst ,  M. -J. Tavella  and  A. Zettam , from the  BIZ  team), as well as for their assistance during the elemental analysis at the technical platforms (PAPC and PLANET) ( W. Amblas ,  D. Baqué ,  F. Julien ,  D. Lambrigot ,  V. Payre-Suc ). Staff from the ICPMS platform at  GET-OMP  ( A. Marquet  and  C. Duquennoy ) and  G. Le Roux  ( BIZ Team ) are also thanked. We are grateful to  L. Boithias  ( GET ) and  Y. Grusson  ( EcoLab ) for sharing GIS data and information on the Save basin.
After describing the dataset used and our methodology in Section 2, we present in Section 3 a case study of a large gravitywave momentum-flux event, associated with a convective complex in the intertropical convergence zone (ITCZ). In Section 4, we statistically study the dependence between recorded momentum fluxes and the balloon distance to convective cells. The discussion section then addresses the observed differences in the behavior of short-and long-period gravity waves, as well as geographical contrasts in wave activity and intermittency in the tropics. The last section of the article is devoted to a brief summary and conclusion. Every balloon carried a GPS receiver and a Tsen instrument (Thermodynmical sensor), which records the in-situ air pressure and temperature  (Hertzog et al.
In such circumstances, the balloon volume decreases, and the balloon temporarily lowers its flight level by a few hundred meters typically until the longwave flux increases back or the sun rises. During a depressurization event, the balloon behavior is therefore no longer isopycnic. Wavelet coefficients influenced by such events were discarded from the following analysis. Those events represent less than 5% of the data from all the flights. In the following, we will use two different intrinsic-frequency bands. The wide frequency range (WF) corresponds to intrinsic periods between 15 min and 1 day, and includes a broad range of gravity-wave frequencies. The high-frequency range (HF), on the other hand, provides a focus on intrinsic periods between 15 and 60 min, and is associated with highfrequency waves that propagate nearly vertically in the atmosphere  (Preusse et al.