dataesr/scientific-paragraphs-categorization huggingface dataset:
Results During the study period, 25,059 patients were included in the Paris-SDEC registry. Cardiopulmonary resuscitation was not attempted in 7923 patients, an obvious non-cardiac cause of arrest was evidenced in 3782 patients, resuscitation failed in 8766 patients (who were not transported according to French EMS policy), and 663 patients with refractory CA were transported without ROSC to the hospital for potential extra-corporeal life support. This left 3925/25059 (16%) patients suitable for the present analysis, of whom 1847/3925 (47%) received TTM (see Additional file 1). Numbers of missing data are displayed on Additional file 2. Patients' characteristics according to temperature management are displayed in Table  1. As compared with controls, those who received TTM were more frequently men and younger; cardiac arrest occurred more frequently in a public place, and the proportion of patients with a long no-flow duration (higher than 3 min) was greater (P < 0.
Acknowledgements Individual members of the  Sudden Death Expertise Center Group  to be searchable through their individual PubMed records: Adnet F,  AP-HP, Paris 13 University, Avicenne Hospital, Emergency Medical Services (SAMU) 93, Bobigny, FranceAgostinucci JM, AP-HP, Paris 13 University, Avicenne Hospital, Emergency Medical Services (SAMU) 93, Bobigny, France Aissaoui-Balanant N, AP-HP, Georges Pompidou European Hospital, Medical Intensive Care Unit, Paris , France.
4 12-16 One example is the cohort multiple RCT (cmRCT) design. 4 In the cmRCT design, researchers set up an ongoing observational cohort that is designed from inception to serve as a framework for conducting trials. Participants who enrol in the cohort complete outcome measurements at regular intervals. When a trial is conducted using the cohort, a random selection of patients eligible for the trial is contacted and offered access to the intervention being tested. Patients who are eligible but not selected are not notified that the trial is occurring and therefore receive usual care. Outcomes for the two groups are compared post-trial using the cohort's routine data collection procedures. ] [19] [20] [21] [22]  Participants sometimes enrol in trials in order to receive a new intervention that would not be available to them as part of their usual care.
Sociodemographic and medical data Patients provided demographic data, including age, sex and years of education. SPIN recruiting physicians provided medical data, including time since first non-Raynaud's phenomenon symptoms, onset of Raynaud's phenomenon and SSc diagnosis; SSc subtype (limited or diffuse cutaneous SSc)  30  ; and modified Rodnan Skin Score. 31 gnalling items Nine signalling items were developed specifically for use in the SPIN Cohort to assess the self-reported likelihood that Cohort participants would agree to use online programmes designed to address one of nine problems related to living with scleroderma, including fatigue, hand function and mobility, sleep problems, emotions and stress, concerns about body image and appearance, pain, low self-efficacy for disease management, nutrition/ diet and exercise.
results sample characteristics Of 1704 participants with submitted baseline self-report data, n=228 had no data for the SAAS, as SPIN stopped collecting data for this measure in English-speaking cohort participants after 7 November 2016. Of the 1476 eligible participants, there were 416 (28. 2%) missing one or more variables. A commonly missing value was the time since the onset of the first non-Raynaud's symptom (n=103). The remaining patients (n=313) were missing one or more demographic or patient-reported outcome measures (i. e. , signalling or symptom measures). In total, 1060 participants had complete data for all variables and were included in regression analyses, including 128 men (12%) and 932 women (88%; table 1). Most patients (71%) were married or living as married. Mean time since Raynaud's onset was 14.
Funding SPIN has been funded by grants from the  Canadian Institutes of Health Research  ( TR3-119192 ,  PJT-148504 ,  PJT-149073 ), the  Canadian Initiative for Outcomes in Rheumatology Care  and the  Arthritis Society. In addition, SPIN has received institutional contributions from the  Lady Davis Institute for Medical Research of the Jewish General Hospital, Montreal ,  Canada , and from  McGill University, Montreal ,  Canada. SPIN has also received support from  Scleroderma Canada , the  Scleroderma Society of Ontario, Sclérodermie Québec , the  Scleroderma Society of Nova Scotia , the  Scleroderma Association of British Columbia ,  Scleroderma Manitoba , and the  Scleroderma Society of Saskatchewan. BDT was supported by a  Fonds de Recherche Québec -Santé  researcher awards outside of the present work.
Statistics Categorical variables were described as numbers and percentages and compared using Chi-square test or Fisher's exact test as appropriate. Continuous variables were expressed as mean ± standard deviation and compared using unpaired t-test. Arrhythmia-free Kaplan-Meier survival curves were built and compared using the log-rank test. Analysis and calculations were performed using StatView ™ program (Abacus Concepts, Inc. Berkeley, CA 1992-1996, version 5. 0). A p value < 0. 05 was considered statistically significant for each analysis.
Reflective skin markers (9 mm in diameter) were placed bilaterally at the hallux (toe markers), head of the fifth metatarsal (metatarsal markers) and posterior calcaneus (heel markers). In 10 subjects, a marker was also placed at the top spine level (C7) to investigate the transmission of the collision forces from the swing foot to the upper part of the musculoskeletal system. An additional marker was positioned at the middle of the obstacle to determine the safety distance, that is, the distance between the swing foot and the obstacle at the time of clearance. A V8i VICON eight-camera (Mcam2) motion capture system (Oxford Metrics Ltd. , Oxford, UK) with a 64-channel analogue card was used to collect both the position of these markers and the force plate data at a sampling rate of 500 Hz. Kinematic and force plate data were acquired and synchronised using the Vicon acquisition software (Workstation, Version 5.
Data Analysis After data collection, kinematic and force plate data were processed offline using a custom-made program written in MATLAB™ (Version 5. 3 (R11), The MathWorks Inc. , Natick, MA, USA). Data were low-pass filtered using a Butterworth filter with a 15 Hz cutoff frequency for kinematic data  [23]  and a 10 Hz cutoff frequency for kinetic data  [24]. The ML and anteroposterior (AP) coordinates of the centre of pressure (yP and xP, respectively) were computed from force plate data in accordance with the instructions from the manufacturer (AMTI) as follows: yP = Mx + Fy × dz Fz , (1) xP = -My + Fx × dz Fz , (2) where Mx and My are the moment around the AP and ML axes, respectively; Fy, Fx and Fz are the ML, AP and vertical ground reaction forces, respectively; and dz is the distance between the surface of the force plate and its origin.
Collision forces. The combined effect of the foot strike pattern (RFS vs. FFS) and vertical force braking on the collision forces and on the transmission of these forces through the body was assessed using variables extracted from force plate and VICON data, respectively. The variables obtained from the force plate were the peak and slope of the vertical ground reaction force trace occurring immediately after foot contact  [16]  (Figure  3 ). The variable obtained from VICON data was the slope (computed at foot contact) of the vertical acceleration of the marker placed at the C7 spine level.
Moreover, in the atmospheric analysis, LSTs are retrieved from infrared sounders for the assimilation of their brightness temperatures, but with no feed-back to the surface analysis. Our goal is thus to prepare the assimilation of these retrieved LST in the surface data assimilation scheme. Here, we focus on SEVIRI, IASI and model LSTs in order to study the agreement between them, evaluate their impact on the radiative transfer simulation and their potential relevance for their use in the surface analysis. The retrieved LSTs from SEVIRI are first assessed with local observations and with the AROME-France model forecast. The agreement between LSTs retrieved from two spaceborne sensors (SEVIRI, IASI) and with the AROME-France model over land is then examined. Finally the impact of using LSTs retrieved from one sensor on the observation simulation of the second instrument is evaluated to assess the possible synergy between infrared sensors to define a common LST.
AROME-France Model AROME-France (Applications de la Recherche à l'Opérationnel à Méso-Echelle) is the meso-scale non hydrostatic model of Météo-France, operational since December 2008  [22]. AROME-France merges a part of the physical package of Meso-NH research model  [23]  with the non-hydrostatic version of the ALADIN model dynamics  [24]. Table  1  summarizes the main characteristics of the operational version since 2015. The domain of AROME-France operational model extends from -12. 45E to 16. 67E and from 37. 26N to 55. 69N with 1. 3 km of horizontal resolution as shown in Figure  1  representing the 2-m air temperature field on the 31 October 2017, 23 UTC. For the surface component, AROME-France is coupled to SURFEX (SURFace EXternalized) model which is a surface modelling platform. SURFEX divides the surface into four tiles: Nature, Town, Lake and Sea  [25].
Satellite Data The Infrared Atmospheric Sounding Interferometer (IASI)  [11]  is a hyperspectral infrared sounder on board Metop-A, Metop-B and Metop-C (launched on 7 November 2018) satellites on a low polar Earth orbit. IASI sounds the atmosphere with a vertical resolution of 1 km and an accuracy of 1 K for temperature and provides information on temperature and humidity profiles. As an infrared sensor, IASI is also sensitive to clouds and to the surface. In addition, IASI detects with accuracy the atmospheric composition of different chemical components such as stratospheric ozone. IASI observes the Earth in 8461 channels every 0. 25 cm -1. The IASI field of view consists of a 2 × 2 matrix of four circular pixels of 12 km diameter at nadir. The IASI swath width is 2200 km. The Spinning Enhanced Visible and Infrared Imager (SEVIRI)  [10]  is on board MSG satellites on a geostationary orbit at about 36,000 km above equator.
This method uses a single selected window channel in order to retrieve LST and needs some a priori information such as the atmospheric transmittance and the surface emissivity. This latter can be considered from emissivity atlases. In fact, different emissivity atlases are used for different sensors. During this study, we have used the operational version of AROME-France that runs the RTTOV v11 for the retrievals. For IASI LST retrieval, the emissivity is defined with the infrared atlas of the University of Wisconsin which is a global monthly infrared land surface emissivity database  [29]  with high spectral resolution from 3. 6 µm to 14. 3 µm and a spatial resolution of 0. 05 •. This database was produced using principal component analysis regression of high spectral resolution laboratory measurements of selected materials from MODIS/UCSB (University of California, Santa Barbara) and ASTER emissivity libraries and CIMSS (Cooperative Institute of Meteorological Satellite Studies) Baseline Fit global infrared land surface emissivity database  [30].
Comparison to Local Data The aim of this section is to evaluate SEVIRI LSTs agreement with in-situ observations. Therefore, we compared the SEVIRI retrieved LSTs and the forecasted LSTs from the model to local data in France and Portugal. Two sites located in the AROME-France domain where observed surface temperature is available at an hourly temporal frequency were chosen for this study: Toulouse station in France and Evora station in Portugal. SEVIRI observes the Earth with a 15 min temporal resolution but the comparison is limited to clear sky SEVIRI observations taken on sharp hours only. Four periods of two months each were considered for the comparisons: spring (April & May 2018), summer (July & August 2018), autumn (October & November 2018) and winter (January & February 2018).
Local Data Acquisition The first comparison uses data from Toulouse station (1. 37E; 43. 57N) which is located in the Occitany region, south-west of France. This region has a warm and relatively dry summer and a mild and wet winter. The station is a part of Meteopole-Flux project  [34]  which aims to build a long-term survey of different variables such as the surface energy balance in a grassland zone in the suburb areas of Toulouse. The station is equipped among others with a KT15. 85D infrared radiation radiometer. The spectral band of this instrument ranges from 9. 6 µm to 11. 5 µm. The second comparison uses Evora station data. Evora station is one of four KIT (Karlsruhe Institute of Technology) LST validation stations of the LSA-SAF which are located in wide homogeneous areas and equipped with the KT-15.
Since Toulouse station is in the suburbs of Toulouse city, it's worth to mention that AROME-France model includes the Town Energy Balance (TEB) module that takes into account the impact of urban areas on the surface parameters, which might explain the overestimated temperatures by the model. Moreover, the heating effect of the urban areas that might be observed by SEVIRI can contribute to the positive bias of SEVIRI LSTs during daytime as shown in Figure  3 (a2). The heating effect can be noticed during nighttime also since urban areas continue to free the heat stored during daytime. An opposite effect is observed for Evora station, which is situated in an area where crops are dominating, but with forested area nearby. In fact, the trees have higher emissivities and have a cooling effect on the LSTs.
Principle of the Experiment In order to simulate brightness temperatures with RTTOV, a background information i. e. , vertical atmospheric profiles of temperature and humidity and a surface temperature is needed. Therefore, more than 21,000 vertical profiles have been extracted over land (See Appendix A. 1) from the AROME-France model representing different soil occupations and different areas of the AROME-France model domain (around 9000 profiles for daytime conditions and more than 12,000 profiles for nighttime conditions). Worth to mention that RTTOV model includes a module to take into account the errors resulting from the angle difference between the viewing angle of the sensor and the vertical profile of the model. For the land surface temperature, we defined three different values: IASI LST, SEVIRI LST and the one forecasted by the model.
Introduction Trees form a wide family of combinatorial objects that offers many application fields, e. g. , plant modeling and XML files analysis. Modern databases are huge and thus stored in compressed form. Compression methods take advantage of repeated substructures appearing in the tree. As explained in  [3] , one often considers the following two types of repeated substructures: subtree repeat (used in DAG compression  [4, 5, 7, 8] ) and tree pattern repeat (exploited in tree grammars  [6, 10]  and top tree compression  [3] ). We restrict ourselves to DAG compression of unordered rooted trees, which consists in building a Directed Acyclic Graph (DAG) that represents a tree without the redundancy of its identical subtrees (see Fig. 1 ). Two different algorithms exist for computing the DAG reduction of a tree τ [8, 2.
The paper is organized as follows. The structures of interest in this paper, namely unordered trees, DAG compression and self-nested trees, are defined in Section 2. Section 3 is dedicated to the definition and the study of the height profile of a tree. The approximation algorithms are presented in Section 4. We give a new insight on the definitions of the NEST and of the NeST in Subsection 4. 1. Our NEST algorithm is presented in Subsection 4. 2, while the NeST algorithm is given in Subsection 4. 3. Section 5 is devoted to simulations. We state that the NeST is mostly a better approximation of a tree than the NEST in Subsection 5. 1. An application to a real rice panicle is presented in Subsection 5. 2. A summary of the paper and concluding remarks can be found in Section 6. All the figures and numerical experiments presented in the article have been made with the Python library treex  [2].
Variables measurement Baseline characteristics of patients and perioperative outcome data within 30 days after TAVI were extracted from the FRANCE and FRANCE-2 registries  [18, 19]. For each patient, the number of blood glucose measurements performed, the average blood glucose value, the percentage of blood glucose value within the range of 4. 4-8. 2 mmol l -1 , the number of adjustments made in the insulin infusion rate, and the rate of insulin therapy adjustment (defined as the ratio of the number of adjustment made in the insulin infusion rate on the number of blood glucose measurements performed) were recorded during the first 48 h after TAVI. All patients spent the first 48 h after the procedure in the intensive care unit (ICU), and then, were discharged to the ward in the absence of complication.
The mean daily δ blood glucose was compared according to the preoperative glycosylated hemoglobin value ≥ 6. 5% or < 6. 5%  [5]  by using the Mann-Whitney U-test. No subgroup or sensitivity analysis were conducted. All statistical analyses were performed using SAS 9. 4 software (SAS Institute Inc. , Cary, NC, USA). All p-values are two-sided and p < 0. 05 was considered statistically significant. The post-study power was computed by using the Shieh-O'Brien approximation and estimated at 94%.
The present study was conducted in accordance with the Code of Ethics of the World Medical Association forth in the Helsinki Declaration of 1975 and with French bioethics law (Art. L. 1121-1 of the law no. 2004-806, August 9th, 2004). It was approved by the Institutional Review Board of the French Society of Thoracic and Cardio-Vascular Surgery (no. CERC-SFCTCV-2016-2-17-17-18-2-BEGu, Chairperson Prof JL de Brux) on March 12th, 2016. The study was registered on April 4th, 2016 at http://www. clini caltr ials. gov (Identifier: NCT02726958).
The present study was conducted in accordance with the Code of Ethics of the World Medical Association forth in the Helsinki Declaration of 1975 and with French bioethics law (Art. L. 1121-1 of the law no. 2004-806, August 9th, 2004). It was approved by the Institutional Review Board of the French Society of Thoracic and Cardio-Vascular Surgery (no. CERC-SFCTCV-2016-2-17-17-18-2-BEGu, Chairperson Prof JL de Brux) on March 12th, 2016. The study was registered on April 4th, 2016 at http://www. clini caltr ials. gov (Identifier: NCT02726958). This manuscript adheres to the applicable Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines.
In this first comprehensive case-control study to investigate the role of hot beverages in esophageal cancer in Kenya and East Africa, the authors find overall risks of 3. 7 and 1. 4-fold for drinking "very hot" and "hot" beverages, respectively, compared to "warm" These findings will contribute to local and global prevention efforts by addressing this potentially modifiable risk factor. and sex standardised data from the 2014 Kenya Demographic Health Survey (KDHS). 15.
Questionnaire and exposure assessment Consenting participants completed a face-to-face interview in their appropriate vernacular with trained interviewers, provided biospecimens and had anthropometric measurements taken. Data were immediately entered into a tablet with a preloaded Open Data Kit questionnaire. Across both study phases, participants were asked which hot beverage they consume most frequently (tea; coffee or other); the temperature at which they consume it (very hot; hot; warm; cold) and the number of cups/glasses per day (typically 200-300 ml serving sizes). In the main study phase, participants were additionally asked to estimate the frequency that they burn their mouths when drinking hot beverages (often; sometimes; never; do not know) as this has previously shown to be correlated with drinking temperatures;  12  whether they consume hot porridge and the temperature at which they consume it (very hot; hot; warm; cold).
Participant and exposure characteristics After the exclusion of 36 oesophageal adenocarcinomas and one each of Kaposi sarcoma, leiomyoma and papilloma, 430 cases and 440 controls were included. Their characteristics are shown in Table  1. The majority of participants were of Kalenjin (55%) or Luhya (22%) ethnicity and of Christian faith. A male: female ratio of 1. 94 was observed among cases (66% male), with a mean age at diagnosis of 59 years and 7% below age 40. Comparable distributions of religion and education between controls and KDHS data have been presented previously for our study population. 16 Geocoded residential locations of cases and controls occupied a comparable spatial extent-the median distance to MTRH was 54 km and 47 km, respectively. A mean consumption frequency of three servings per day (i.
e. 750 ml/day) was found for respondents' preferred beverages; of which tea was the most frequently consumed beverage by cases (98%) and controls (95%). Hot porridge was additionally consumed by a majority of participants in the main study phase (61% in cases and 69% in controls), but data on porridge consumption temperatures were incomplete. Mouth burning was reported to occur at least sometimes in >50% of main phase study participants. Among controls (both study phases), the prevalence of very hot, hot and warm drinking temperature was 7%, 68% and 25%, respectively. A higher prevalence of hot drinkers was found in men (p = 0. 03) and lower prevalences of very hot and hot drinkers were found among female ever tobacco users (p < 0. 01). Drinking temperatures did not differ by any other of the potential confounders investigated (Table  2 ).
for Research on Cancer; MTRH:  Moi Teaching  and Referral Hospital; OR: odds ratio Grant sponsor: The  European Commission FP7 Marie Curie Actions -People -Co -funding of regional, national and international programs (COFUND); Grant sponsor: An  IARC post-doctoral fellowship ; Grant sponsor: An  IARC-UICC Development Fellowship ; Grant sponsor:  NIH/NCI  grant; Grant numbers:  R21CA191965 DOI: 10. 1002/ijc. 32032.
Identification of jets and missing transverse momentum For each event, hadronic jets are clustered from the reconstructed particle-flow objects with the infrared and collinear safe anti-k T jet clustering algorithm  [60] , implemented in the FASTJET package  [65]. Two different jet radii, 0. 4 and 0. 8, are used with this algorithm, producing ob-jects referred to as AK4 and AK8 jets, respectively. The jet momentum is determined as the vector sum of all particle momenta in the jet, and is found from simulation to be within 5 to 10% of the true parton momentum over the entire p T spectrum and detector acceptance. Additional pp interactions within the same or nearby bunch crossings can contribute additional tracks and calorimetric energy depositions to the jet momentum. To mitigate this effect, tracks identified to be originating from pileup vertices are discarded and an offset correction is applied to correct for remaining contributions.