dataesr/scientific-paragraphs-categorization huggingface dataset:
The model can be extended to the prediction of heat load length λ q by simply assuming a proportionality factor with λ n. From Tore Supra database, we find λ q ≈ 0. 5λ n. Finally, the electron temperature can be replaced by an expression from the 2 point model in the high recycling regime, and equipartition between ion and electron will be assumed = T T i e. The ultimate model prediction for λ q becomes: = + q B A Z T T ZT 10 ( / ) 1 [mm] = q B R A Z P 25 ( / ) [mm] q sep 0. 63 0. 65 0. 25 0. 33 0. 09  (12)  where P sep is the power crossing the separatrix in MW. As shown in Fig. 4 , this prediction is in quantitative agreement with Tore Supra database (deuterium ions), and in correct agreement (within 20%) with extrapolations made for ITER startup conditions taken from an ITPA database analysis  [1]  (deuterium ions).
Besides, inclusion of parallel heat conduction in the model could also reduce the SOL width by enhancing parallel energy losses. To provide some answers, results from 3D turbulence simulations made with TOKAM3X  [21]  are briefly discussed. Two isothermal Fig. 4. Comparison of the spectral filament model prediction for λ q with a Tore Supra database (ohmic circular high field side limited plasmas). The model is also compared to previsions for ITER current ramp up scenarios, based on an ITPA multi-machine extrapolation  [1]. simulations with equivalent control parameters are compared, one in inner limited geometry, one in lower single null geometry as shown in Fig. 5. Both simulations feature interchange turbulence enhanced around the outboard midplane, dominating the transport and setting the SOL width.
Summary and discussion A predictive model of edge turbulent transport has been derived from a spectral decomposition of filamentary transport. For limited plasmas, this spectral filament model (SFM) returns a density decay length prediction = + ( ). Quantitative agreement is found against a Tore Supra database for inner limited ohmic discharges. Predictions for ITER startup conditions are also in quantitative agreement with multi-machines extrapolations. Finally, the parametric dependance of the λ q model is very close to experimental observations in diverted configurations, although the absolute amplitude is too large by a factor of about 7. Isothermal 3D simulations give a similar difference between limited and diverted configurations, suggesting that it is not due to enhanced parallel heat conduction in diverted geometry, but rather to the geometrical impact of magnetic X-point on interchange turbulence.
The central wave number k m dominating the transport is at the transition between these two regimes. The radial particle flux caused by interchange turbulence is expressed through this non linear model: = n g ¯49 x n 1/2 3/4 7/4. The model depicts a stiffness of the turbulent flux with an inverse dependance with the square (almost) of the gradient scale length. In a previous work, Halpern et al. [22]  proposed a comparison of a theory based scaling of heat load decay length with an experimental database in circular geometry (ITER startup database). The theoretical basis follows different approximations: linear theory around on a single wave number = k 0. 1, L 0 length applied to a meso-scale k k / , r p 0 and parallel plasma resistivity rather than sheath resistivity for parallel currents.
Statistical Analyses Statistical analyses were conducted with SPSS 20. 0 (SPSS Inc. , Chicago, IL) and R version 3. 5. 2 (42). Given that there were few participants (fewer than 50 per group), a Shapiro-Wilk test was used to test the null hypothesis that the samples were normally distributed. The assumption of normality was verified with respect to age and the number of significant events. However, it was rejected with respect to the scores for the three psychometric scales: SSI, BDI-SF, and PCL-S. Nonparametric tests were required to analyze these data. For the primary objective, a Wilcoxon-Mann-Whitney test was used to compare the SSI distributions in the two groups (ES vs. PNES). For the secondary objectives: A Wilcoxon-Mann-Whitney test was used to compare the distributions of the scores for BDISF and for PCL-S and the number of significant events in the two groups.
Climatological features of observed annual maximum hourly precipitation have not been documented systematically compared to those on daily timescales due to observational limitations. Drawing from a qualitycontrolled database of hourly records sampling different climatic regions including the United States, Australia, the British Isles, Japan, India and peninsular Malaysia over the 1950-2016 period, we examined climatological features of annual maximum precipitation (AMP) across timescales ranging from 1-hr (AMP 1 hr ) to 24-hr (AMP 24 hr ). Our analysis reveals strong relations between the magnitude of AMP and the climatological average annual precipitation (AAP), with geographic variations in the magnitude of AMP 24 hr across topographic gradients not evident in AMP 1 hr. Most AMP 1 hr are found to be embedded within short-duration storms (>70% of AMP 1 hr are embedded within 1-5 h storms), especially in regions with low AAP and in the tropical zone.
Unfortunately, the lack of sub-daily data sharing across the world has left the research community with little data over limited geographical regions  (Zhang et al. , 2017) , thus hampering global or multi-continental analyses. To bridge this gap, a Global Sub-Daily Rainfall (GSDR) dataset has recently been compiled  (Lewis et al. , 2019)  from multiple data sources in an international initiative under the Global Water and Energy Exchanges (GEWEX) Hydroclimatology Panel INTENSE project  (Blenkinsop et al. , 2018). We here examine the climatological features of hourly precipitation extremes in different climatic regions using the GSDR dataset to identify potential universal behaviors. We also examine how they compare to precipitation extremes on daily timescales to highlight the potential added-value of hourly data.
Global Sub-Daily Rainfall The Global Sub-Daily Rainfall (GSDR) dataset used in this analysis has been constructed from multiple sources  (Lewis et al. , 2019)  including records from the United States (US), Australia, the British Isles, Japan, India and peninsular Malaysia. We focused on these regions as they provide long and high quality records needed to derive robust statistics and have been extensively used in national studies in the US  (Barbero et al. , 2017; Canel and Katz, 2018) , the United Kingdom  (Blenkinsop et al. , 2017; Darwish et al. , 2018) , Australia  (Guerreiro et al. , 2018; Westra and Sisson, 2011) , Japan  (Utsumi et al. , 2011) , Malaysia  (Syafrina et al. , 2015)  and India  (Ali and Mishra, 2018). Moreover, these macro-regions encompass large latitudinal and topographic gradients from tropical to midlatitude areas, sampling different climate zones over a large spectrum of climatological average annual precipitation (Fig.
1 ). We only use gauges with at least 20 years of data and less than 20% missing hours in any given year, which does not exclude potential extended interruptions in the time series at some sites. Overall, the number of records meeting completeness criteria grows with time from 1 690 station records in 1951 to 3559 records in 1992, and then slightly decreases for the most recent years (except in Japan and Malaysia (Fig. S1 )) to 1 572 records in 2010. Although the coverage provided by this dataset is not uniform in either space or time and represents an ongoing effort by the international community, the GSDR still represents the most complete direct measurements of hourly precipitation presently available  (Lewis et al. , 2019). All data classified as suspect according to pre-existing quality-control flags were treated as missing.
Hourly measurements were aggregated up to 3-h, 6-h, 12-h and 24-h using fixed intervals (e. g. 0 000-0300, 0 300-0600, for 3-h data; 0 000-0600, 0 600-1200, for 6-h data and so on) relative to local time (i. e. daily accumulation are calculated from midnight to midnight). In the following, we only report results for 1-hr and 24-hr as analyses of intermediate durations only show a transition between the characteristics shown at 1-h and 24-hr (not shown).
The diurnal distribution of AMP 1 hr and the hourly peak intensity of AMP 24 hr For each gauge we examine the modal hour of AMP 1 hr and of the Fig. 4. a) Mean contribution (%) of AMP 1 hr to the corresponding total 1-day accumulation referred here to as AMP1 hr P24 hr 100 as a function of the average annual precipitation (AAP) gradient. b) Percent of AMP 1 hr embedded within AMP 24 hr with a 1-day tolerance referred to here as concurrent intensity as a function of the AAP gradient. The 95% confidence intervals of the composite means were computed using 1 000 bootstrapped datasets sampling at random 50% of the records in each AAP bin. The confidence envelope indicates the 2. 5 and 97. 5 percentile of the composite means from the bootstrapped datasets. Fig. 5. Mean percent of AMP 1 hr embedded within AMP 24 hr with a 1-day tolerance (referred here to as concurrent intensity) and mean contribution (%) of AMP 1 hr to the corresponding total 1-day accumulation (referred here to as AMP1 hr P24 hr 100).
, 2013; Dong et al. , 2018). Previous studies have suggested that antecedent CAPE might be a better predictor for subsequent convective precipitation  (Davies et al. , 2013). The secondary peak seen in Florida likely reflects the lag between the timing of some AMP with respect to the strong diurnal cycle included in CAPE in this region. Based on the whole dataset, Fig. 13  shows that AMP 1 hr (AMP 24 hr ) intensify with increasing CAPE until 1 500 (1 000) Joules kg 1 , a threshold above which AMP 1 hr (AMP 24 hr ) saturates as observed in regional analyses in China  (Dong et al. , 2018) , the central US  (McCorkle et al. , 2016)  and northern Australia  (Davies et al. , 2013). This saturation effect in precipitation intensity in response to CAPE shows that additional factors such as specific humidity or dew point temperature  (Lepore et al.
Sub-daily data also enables a better characterization of the true precipitation intensity as well as a better understanding of processes driving extremes. Given the growing interest in sub-daily precipitation extremes in the literature, the hourly precipitation dataset used here can provide the hydroclimate community with better information on intensities initiating flash floods. It is of interest to note that the seasonality of daily precipitation extremes shown here contrasts somewhat with the seasonality of daily flooding depicted in previous studies  (Villarini, 2016) , highlighting the dominant role of antecedent conditions in triggering floods  (Berghuijs et al. , 2016; Bennett et al. , 2018). A comparison of short-duration precipitation and flash-flood seasonality may also help to better elucidate different triggering mechanisms for regional flash flooding.
, 2017)  although convection permitting models (CPMs) have been found to simulate the diurnal cycle more realistically  (Kendon et al. , 2012; Prein et al. , 2015). The main limitation of this study is the uneven distribution of rain gauges across space. All statistics are based on hourly data-covered regions and thus only reflect the sampled regions. A quality control process of the GSDR dataset is currently underway in other regions and will soon provide a more complete coverage that could be used to more accurately quantify sub-daily precipitation features on a more global scale. Finally, further studies are needed to detect the effects of global warming on short-duration precipitation extremes across the world. Global trend detection studies have so far relied on daily data  (Westra et al.
, 2013; Donat et al. , 2017; Sippel et al. , 2017)  but the aggregation of precipitation across a day may affect the sign of the trend in extreme precipitation  (Zheng et al. , 2015; Morbidelli et al. , 2018). A recent study suggests that changes in hourly extremes may emerge before daily extremes  (Kendon et al. , 2018). On the other hand, trends in sub-daily extremes have only been examined in nation-wide studies  (Barbero et al. , 2017; Guerreiro et al. , 2018; Ali and Mishra, 2018 ) and a more global assessment is still lacking. The GSDR dataset provides for the first time the opportunity to examine these research questions across different climate zones with a consistent methodology and assess some of the World Climate Research Programme (WCRP) Grand Challenges on Weather and Climate Extremes.
Who is in the ELFE cohort? After a small-scale pilot cohort in 2007  12  and a national information campaign, the national cohort was launched in 2011. A total of 349 maternity units were randomly selected in metropolitan France and the children were recruited at birth from the 320 maternity units that agreed to participate. A stratified sampling strategy based on the size of each unit was adopted to allow for oversampling in larger units, thus reducing the cost of data collection (Figure  1 ). Recruitment took place during 25 selected days in 2011, grouped into four periods over the year; 12 of these days were selected to coincide with the French permanent demographic sample, a regular national survey of individuals born on specific days every year. 13 Inclusion criteria were single or twin live births at 33 weeks of gestation, mother 18 years old, no plan to leave metropolitan France within 3 years and informed consent signed by the parents or the mother alone, with the father being informed of his right to deny consent for participation.
Information and consent documents were provided in French, Arabic, Turkish and English, the most common languages of women giving birth in France. More than 96% of the mothers who satisfied the first two inclusion criteria (n ¼ 37 494) were contacted by research assistants during their stay in the maternity unit and 51% (18 040) agreed to participate in the cohort. The women gave birth to 18 329 babies, including 289 pairs of twins. With ethics approval, some data on births to mothers who refused to take part were collected from birth certificates and stored anonymously. This collection made it possible to apply a weighting procedure to correct for nonrepresentativeness. The weights take into account the sampling plan and refusals at both maternity unit and individual levels; details on the research section/data and questionnaire are available at [https://www.
a Some data have been collected only on subsamples (see Table  3 ). b Infant feeding data for the period 2-10 months collected monthly by or. Some of the samples collected at birth have been used by the French National Public Health Agency as part of the first national perinatal biomonitoring plan. The measurements obtained (see Supplementary data available at IJE online) are included in the ELFE database and are available to researchers. The results presented thus far have highlighted the greater exposure of French pregnant women to pyrethroids, a group of pesticides, as compared with pregnant women in the USA. 25 This finding is consistent with a 2007 observation in the French general population. 25 icroorganisms represent another type of environmental exposure. The dust collected in the rooms where ELFE infants slept during their first 2 months of life was analysed for the presence of DNA specific to 10 microorganisms (three bacteria, one mite, six moulds).
Another innovative aspect in the French context will be the linkage of social, familial and personal trajectories from birth to educational achievement, notably with detailed information on learning outcomes at nursery school in a subgroup of children. Importantly, ELFE is a multidisciplinary project. More than 100 researchers are working in the ELFE thematic groups covering the field of epidemiology and different specialist fields of medicine, biology, nutrition, physical activity, demography, economics, sociology, psychology and environmental science. They are contributing by proposing research questions, data collection tools and other protocols. Increasingly, each discipline is expanding the ELFE database by adding constructs, indicators and variables etc. from external sources. They bring specific methodologies that can be used by others with the support of a network of colleagues.
Acknowledgements We are grateful to: (i) the former members of the ELFE unit, without whom the project would never have started:  Henri Le  ´ridon, initiator and former PI of the project,  Stephanie Vandentorren ,  Claudine Pirus  and  Ando Rakotonirina ; (ii) for their expertise and assistance, members of the unit for support functions, notably:  Catherine Guevel ,  Sophie de Visme ,  Laure Gravier ,  Meryem Zoubiri ,  Helene Juillard, Cedric Ricourt and Adriana Candea ; (iii) all the researchers who contribute to the projects as members of the ELFE thematic groups and particularly their coordinators; (iv) all the field research assistants and interviewers; and (v) above all, all the ELFE families who have placed their confidence in us and given up their time to the study.
Epidemic threshold computation We compute the spectral radius of the infection propagator P, given by the expression of equation (2. 2) using the power iteration method. To compute the threshold, we find the zero for r[P(W; l ¼ l c , m)] 1/T 2 1 ¼ 0 using Brent algorithm  [43] , where l is a variable and m is informed from epidemiological data. This procedure returns the value of l for which the spectral radius is equal to one. A Python library to compute the critical transmissibility is publicly available online for interested researchers  [44].
Bovine tuberculosis in Italy Livestock infectious diseases are of primary interest for animal health and welfare and for the economy of a country, with the potential to produce devastating consequences  [47]. Bovine tuberculosis is one of the most widespread zoonotic diseases all over the world  [48]  and it is very difficult to contain since it can spread while unnoticed, before detection in the animals  [49]. Bovine tuberculosis is a notifiable disease in Europe. In Italy, in particular, it has affected cattle population for decades and still circulates in southern regions  [50]. Here, we focus on Puglia region in the south of Italy where outbreak data are available and the outbreak duration was shown to vary depending on the production type of the affected premises. We built the temporal network starting from the dataset of cattle trade movements of the whole population of bovines in Puglia obtained from the Italian National Database for Animal Identification and Registration that is managed by the Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise (IZSAM) on behalf of the Italian Ministry of Health  [51, 52].
These data were collected by the Italian National Animal Health Managing Information System, an informatics system developed by IZSAM on behalf of the Ministry of Health  [51, 52]. For each outbreak, we considered data reporting the identifiers of the affected animal holding, its production type, and the start and end of the outbreak based on the date of first infection detection and date of clearing of the infection, respectively. The farm is considered to be cleared from the infection after two consecutive negative tests on all animals that need to be performed each after a minimum of four and a maximum of six weeks from the previous control activity (either the royalsocietypublishing. org/journal/rsos R. Soc. open sci. 6: 181404 slaughtering or the first test). As shown in table 1, outbreak durations in the region vary with production types, as observed in other contexts  [57].
In order to understand how these differences may affect the vulnerability of a hospital setting to nosocomial infections, we focus here on the case of S. aureus, for which colonization durations are documented  [61] [62] [63]. Close proximity interactions are acknowledged to be a route along which nosocomial infections may be transmitted  [62, 63]. Here, we use a temporal network of contacts within a hospital ward in Lyon, France, collected by the SocioPatterns project  [64, 65]. The dataset records face-to-face interactions among patients and hospital workers over 4 days, at a 20 s resolution. It includes also individual information that allows us to divide the population into four groups: patients, nurses, medical doctors and administrative personnel (table  2 ). Spatial constraints appear to be major drivers in network topology, as, for instance, patients are mostly confined to rooms, and administrative personnel to offices.
We aim at understanding how the presence of asymptomatic individuals impacts the pandemic risk for a population of students at a school. We build the temporal network from data reporting time-resolved contacts in a French school  [72, 73]  collected by the SocioPatterns project [64], over a period of 2 days, at a resolution of 20 s. As for hospital facilities, proximity sensors were used to record face-to-face contacts between individuals. The resulting network is composed of N ¼ 242 individuals divided into 11 classes, corresponding to 10 classes distributed on five consecutive grades, plus teachers. The network exhibits strong community structure, as children connect more within the same class or the same grade (figure  3a ). While teachers connect with students from different classes, those links have a lower weight, as they occur less frequently and are shorter in time.
Acknowledgments This research has been carried out within the framework of the  COST Action FP 1404. The authors express their gratitude to the  Michoacana University of San Nicolás de Hidalgo Research Programme 2015-2016  for supplying the samples of tropical wood for this research. This work is supported by  MINECO (Spain)  under the project  BIA2014-52688-R. The authors would also like to thank the  Catalan Government  for the quality accreditation given to the research group GICITED ( 2014 SGR 1298 ).
Method Because of the high quality and the extensiveness of both the Belgian HTA report  [5]  and the systematic review of the Ludwig Boltzmann Institute  [6] , we chose to update these two reports. The Belgian HTA report closed its search in July 2018, the review on CIRT was closed in August 2017. Therefore, we reviewed the literature for systematic reviews and primary studies comparing particle RT with photon therapy in the databases Medline, EMBASE and Cochrane Library since the closing search dates. Single-arm studies are not included in this study. For CIRT, we searched between September 2017 and February 2019; for proton therapy, we searched between August 2018 and February 2019.
Results We could identify some new observational studies comparing a photon with particle therapy (Figure  1 ). The overall survival (OS) in breast cancer patients was assessed using the US National Cancer Database between 2004 and 2014. The OS of patients that received proton therapy was not statistically significantly longer than those that received photon therapy [Hazard ratio (HR) 0. 85 (95% Confidence interval (CI) 0. 68-1. 07)] [7]. The preliminary results of a study in non-small cell lung cancer with underlying idiopathic pulmonary fibrosis showed a tendency of non-statistically significant better survival compared to X-ray (p = 0. 08) for patients treated with proton therapy, especially in subgroups of GAP stages II and III at Samsung Medical Center in Korea  [8]. In unresectable hepatocellular carcinoma, proton RT was associated with improved survival, which may be driven by decreased incidence of post-treatment liver decompensation [Adjusted hazard ratio (AHR) = 0.