dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions In the current study, we present a recently designed and developed photochemical chamber, THALAMOS, with a wide temperature range thermostatic ability, 233 -373 K. THALAMOS is equipped with in-line FTIR, SIFT-MS and GC-MS complementary detection techniques that allow internal cross-validation of various type of quantitative measurements, such as kinetics and product yields studies. A detailed description of the facility, the instrumentation and the characterization of the conditions has been realized. The first kinetic results employing relative rate methods obtained during THALAMOS validation are also presented. Applying the relative rate method, and studying the temperature dependence of two well documented reactions it was evident that THALAMOS is capable of producing highly precise and accurate temperature kinetic data for atmospheric relevant OH and Cl reactions.
Acknowledgments This article is dedicated to the memory of  Dr. Ian Barnes  from the  Institute for Atmospheric and Environmental Research, University of Wuppertal, Germany , one among the leaders of chemical kinetics who inspired many scientists of our generation. This work is part of the chemical and physical properties of the atmosphere ( CaPPA)  project funded by the  Agence Nationale de la Recherhe (ANR)  through the  programme d'investissements d'avenir PIA  (No. ANR-11-LABX-0005-01 ), the  "Hauts-de-France" Regional Council  and the  European Regional Development Fund (ERDF). A. Tomas  and  M. Romanias  are thankful to the  Institut National des Sciences de L'univers (INSU)  les  Enveloppes Fluides et L'environnement-Chimie de L'atmosphère (LEFE-CHAT) program  for financial support.
N. Osseiran  acknowledges support from  Labex CaPPA  for his graduate fellowship. V. C Papadimitriou  acknowledges support from  Labex CaPPA  for his short term visit at the institute mines telecom (IMT)  Lille Douai. M. E. Angelaki  acknowledges support from the project make our planet great again (MOPGA) for her short term visit at  IMT Lille Douai , and the  Greek sate scholarships foundation  (IKY) program that funds her PhD.
The contrasting biochemical composition between the plant species considered may also induce substantial differences in water sorption of the cell walls under controlled hygrothermal conditions. Pejic et al. [26]  studied the influence of non-cellulosic biopolymers such as lignin on the water sorption of hemp fibre bundles, and showed that the decrease in lignin content tends to increase the water retention capacity of hemp fibres. Fig. 2  shows that the palm fibre bundles having the highest lignin contents (Table  2 ) also have low moisture content in overall. In contrast, the very high moisture content of nettle fibre bundles above 80% RH compared to other bast fibres could also originate from a poor retting inducing high pectin content and stronger hygroscopic character (Table  2 ). Moisture data obtained from DVS and WRV measurements will now be used to analyse the morphological and dimensional variations of the fibre bundles under the different hygro-and hydrothermal conditions according to their moisture content.
Acknowledgements William Garat thanks  Montpellier SupAgro  for funding his PhD work. The authors thank  Arnaud Day  ( Fibres Recherche Développement, Troyes, France ) for the supply of nettle fibre bundles, and  Yann Leray  and  Steve Bucknell  ( Diastron Ltd. , Hampshire, Great Britain ) for their technical support on FDAS and DSM devices. The authors thank the French research cluster  CNRS-INRA 'Symbiose' SYnthon et Matériaux BIOSourcés  for mission funding.
control system, in order that analysis for sensor placement and algorithms can be performed without extensive, and expensive, testing. A simulation framework called Simscape Environmental Control System Simulation under All Conditions has been proposed and implemented. It offers a library of components that can be assembled into specific aircraft environmental control system simulation configurations. It is capable of simulating the health state indicating parameters at sub-system and component levels under a wide-range of aircraft operating scenarios. The developed framework has been successfully implemented to simulate a Boeing 737-800 passenger air conditioner. Its verification and validation has been carried out against the actual data corresponding to a Boeing 737-800 passenger air conditioner operating at two different cruise operating points.
Lang X. et al. [18]  deployed Flowmaster for fault detection in pipes, simulations were focused on simulating the pipe leakage based on the pressure signal. The Boeing Company developed EASY5 software, targeting an integrated simulation modelling capability that can be employed to create both nonlinear and linearized analyses of the ECS system  [19]. The library was developed based on a modular modelling concept. Easy5 also supports the creation of additional components using Fortran. The user is required to organise the components to be placed according to a reference ECS configuration. The desired model and the interconnection between the components are formed by the built-in model generation program, which supports generating a schematic diagram of the target architecture. EASY5 was later used by Boeing for developing an aircraft PACK model for performance analysis and for sub-systems level diagnostics.
Following that, Hoffman et al. [20] reported a study that deployed EASY5 for the simulation of the F-14 fighter aircraft ECS. In another study Gulfstream Aerospace used this software to develop a PACK model for the G500 and G550 passenger jets  [21]. The SAAB Group collaborated with Linköping Institute of Technology to model a PACK for their JAS39 Gripen fighter jet  [22]. Fault modes identified from historic data, focussing mostly on valve jamming, were used to develop a model based diagnostic method. The overall research was however focused on validation of an existing sensor set, and was predominantly based on ground static test data. Based on the review of the existing simulation frameworks, it is noted that the existing public domain literature lacks: 1. A flexible, easy to use, ECS simulation tool, capable of modelling the sub-system and component level performance characteristics of an ECS under a wide-range of aircraft operating scenarios.
Implemented simulation environment and interface Having presented the component equations, the next step is to elaborate on how the overall simulation model is formed to represent a generic library of ECS components. The Matlab-Simscape environment was chosen for this purpose. The choice of software was based on a combination of factors that, amongst others, included: user friendliness, computational effectiveness, flexibility in enabling further development and refinements, integration with other potential software platforms, and the ability to independently model each component performance coupled with its degradation modelling. All these prerequisites were deemed to be promising in making the choose the Matlab Simscape environment. Simscape offers the implementation of an object-oriented modelling approach, enabling a drag-and-drop interface, where each component can be independently formulated.
Then, the acquired simulation results in terms of P, T and ṁ are compared with the validation data at component level with physical interpretation and analysis. Three other points of simulation detail are worthy of note. First, the PACK V&V data corresponding to both RCs begins at the PV outlet, whereas the simulation begins at the PV inlet. As such, the PV inlet pressure (PVIP) was used to match the data's PV outlet pressure (PVOP) in the simulation. Second, in order to calibrate the temperature drop at the PHX and SHX outlet, the ram air door area is used to calibrate the simulation temperature at PHX and SHX outlet against the actual data in both cases. To summarise, each case is calibrated using the PVIP and ram air door area to align the simulation with the data. Finally, the V&V data is collected at high altitude where the humidity is very both cases were simulated assuming dry air.
, 2001; Storme et al. , 2012; Garel et al. , 2013). Here we present a multi-proxy study of the Phare d'Ailly core that displays almost the whole local Sparnacian sedimentary succession. Compound-specific d 13 C values and K-Ar ages on authigenic glauconite were determined and compared to micropaleontology and palynology records to build a stratigraphic framework and unravel CIEs. Palynofacies and relative abundances and distributions of n-alkanes provided clues about vegetation succession and other environmental changes. Paleohydrological changes were constrained by d 2 H values of n-alkanes. Our integrated data unravel climatic and environmental changes at other time intervals than the one occurring at the Paleocene-Eocene boundary and their possible link with carbon isotopic events in this mid-latitude coastal environment.
, 2005)  data along with K-Ar absolute ages on authigenic glauconite (this work). CIE (carbon isotope excursions) 1 to 3 and P 1 and P 2 correspond to negative d 13 C excursions and peaks unraveled by  Magioncalda, (2004). Green rectangle: interval spanned by the Phare d'Ailly core studied here. L1 and L2: lignite complex 1 and 2. at 45 °C. The sediment was then sieved at 210 and 420 mm. The separation of glauconite grains in the granulometric fraction between 210 and 420 mm was performed using a Frantz magnetizer (intensity of 0. 5 A and tilt of 9°). The final purification was achieved under an optical microscope by hand picking the remaining impurities. Then, the grains of glauconite underwent ultrasonic cleaning (30 s for the first step and 2 minutes for the second step) to clean the cracks developed during the growth of glauconite grains.
Acknowledgements. S. G. thanks the  French "Ministère de l'Enseignement Supérieur et de la Recherche " for a Doctoral grant. We wish to thank  Florence Savignac  ( Sorbonne Université ) for her technical support,  Jean-Yves Storme  for scientific discussion,  Hervé Guillou  for  K-Ar  analyses and  Elizabeth Rowley-Jolivet  for English revision. We also thank  Vittoria Lauretano  and an anonymous reviewer for their comments and reviews, which considerably improved the manuscript. This paper is a contribution to the Research cooperation contract financially supported by the  BRGM ("Paléosurface éocène -PETM "  research  project) and to the  BRGM Scientific Programs  " Genèse et caractéristiques des Régolithes " and " Référentiel Géologique de la France ". The work was part of the  PalHydroMil  project, supported by  Agence Nationale de la Recherche  Grant  ANR-2010-JCJC-607-01.
Study design and patient population We conducted a retrospective observational study between January 2012 and December 2018 at Louis Pradel University Hospital (Hospices Civils de Lyon, France). The study protocol was approved by our Institutional Review Board (N°20-54; Chair: Prof. JF Guerin) and registered with ClinicalTrial. gov (NCT04323709). Given the retrospective and non-interventional design of the study, the need for written informed consent was waived. All consecutive adult patients admitted to the cardiothoracic intensive care unit (ICU) who underwent VA-ECMO for refractory cardiogenic shock were eligible for the study. Exclusion criteria were age < 18 years, VA-ECMO duration < 48 h, VA-ECMO for refractory cardiac arrest, right heart or veno-venous ECMO, and VA-ECMO for circulatory failure following lung transplantation.
Data collection The following data were collected at the admission: age, gender, body mass index, Simplified Acute Physiology Score (SAPS-II), Sequential Organ Failure Assessment (SOFA), hypertension, diabetes, hypercholesterolemia, smoking status, history of stroke or congestive heart failure, coronary or peripheral artery disease, renal failure with dialysis, left ventricular ejection fraction (LVEF), tricuspid annular plane systolic excursion (TAPSE), mean arterial pressure, heart rate, central venous pressure, ScvO 2 , presence of an intra-aortic balloon pump, and biochemical parameters. During the hospitalization, the following variables were collected: the reason for initiation of VA-ECMO and VA-ECMO characteristics (duration, type, flow (L/min), RPM, FiO 2 ), length of stay in ICU, catecholamines and inotrope maximal doses and durations of administration, and patients receiving heart transplantation or left ventricular assist device (LVAD).
Study endpoints The primary endpoint was VA-ECMO weaning failure defined as death occurring during VA-ECMO support or within 24 h after VA-ECMO removal  [12, 16]. Secondary endpoints were mortality at day 28 and at 6 months after VA-ECMO implantation. Based on the available literature  [17] [18] [19] [20] [21] [22] [23] [24]  and on the analysis of patient outcomes in our institutional database  [25, 26] , we classified indications for VA-ECMO into three categories (high, intermediate, or low) according to the potential for myocardial recovery.
In this study focused on France, we explore the uncertainties related to choices made while building a source model for hazard assessment and we quantify the impact on probabilistic hazard estimates. Earthquake recurrence models are initially built from the French Seismic CATalog (FCAT, Manchuel et al. in Bull Earthq Eng, 2018. https ://doi. org/10. 1007/ s1051 8-017-0236-1). We set up a logic tree that includes two alternative seismogenic source models (ESHM13 and Baize et al. in Bull Soc Géol Fr 184(3):225-259, 2013), two versions of FCAT catalog, two alternative declustering algorithms, and three alternative minimum magnitudes for earthquake recurrence modeling. We calculate the hazard for six cities (i. e. Nantes, Lourdes, Clermont-Ferrand, Briançon, Nice and Strasbourg) that are located in source zones with a minimum amount of data to work with.
SHEEC catalog The 1900 to 2006 time window is derived from the European-Mediterranean Earthquake Catalog (EMEC)  (Grünthal and Wahlström 2012, p. 542 ). The Laboratoire de Détection et de Géophysique (LDG) solutions are used from 1962 to 2004. A proxy for M W is estimated by successively applying two conversion equations: the original M L LDG is converted into a "Central European" M L magnitude, which is then converted into an M W with a dedicated conversion equation. From 1900 to 1961, moment magnitudes are estimated from epicentral intensity by applying an equation based on the "Central European" events. The 1000 to 1899 time period was compiled at Istituto Nazionale di Geofisica e Vulcanologia (INGV) and described in  Stucchi et al. (2012). Earthquake parameters were derived from the SisFrance macroseismic database by applying the Boxer method  (Gasperini et al.
In some cases, magnitudes M W ≤ 3. 4 are inferred from regional local magnitudes or from the duration magnitude of LDG. More details on the magnitude estimates in SiHex can be found in  Denieul et al. (2015)  and  Cara et al. (2017). Laurendeau et al. (2019)  analyzed the methods applied to obtain Mw proxies and discussed the uncertainties associated. For the historical part, described in two companion papers  (Traversa et al. 2018; Baumont et al. 2018) , the method applied to determine the magnitude depends on the macroseismic data available (SisFrance). The epicentral locations were not revised in this work, they remain those of SisFrance. For well-described events, magnitudes and depths are jointly inverted through exploring a tree of intensity prediction equations (IPE). For events with a poor macroseismic dataset, magnitudes are estimated assuming an a priori depth.
Two distinct slopes can be observed in Fig. 7 , indicating that the magnitude range below 3. 4 is not homogeneous with M W > 3. 4. Above M W 3. 4, the instrumental dataset is rather homogeneous, although only a fraction of the events have a magnitude determined from coda waves. We use a magnitude bin equal to 0. 3. The magnitude bin width should be approximately larger than or equal to the uncertainty on the magnitude of events; 0. 3 appears to be a reasonable compromise considering the uncertainty level on the instrumental magnitudes (around 0. 1-0. 2) and the uncertainty level on the historical magnitudes, which is strongly event dependent and can reach values as high as 0. 5-0. 6  (Traversa et al. 2018 ). 1 3 The earthquake recurrence model considered here is form 2 in  Anderson and Luco (1983) , with N the annual rate of events with magnitude larger or equal to m: Considering the FCAT catalog declustered with the Reasenberg algorithm (Fig.
0. We do not explore the uncertainty related to the M max value. Table  6  summarizes the parameters considered in the probabilistic hazard calculation. Calculations are performed for a generic rock site (V S30 = 760 m/s). Four ground-motion models for shallow crustal sources are used to explore the uncertainty for ground-motion prediction: • Boore et al. (  2014 ) built from the Next Generation Acceleration database (western United States and worldwide datasets); • Bindi et al. (2014) built from a pan-European dataset; • Cauzzi et al. (2015) built from a global dataset (~ 50% of data from Japan and ~ 30% from pan-European regions); • Drouet and Cotton (2015) built from a stochastic model developed for the French Alps. All models use the Joyner and Boore distance measure except  Cauzzi et al.
Source-model uncertainties versus ground-motion model uncertainties: impact on the hazard estimates The source-model logic tree based on FCAT (Fig. 11 ) is combined with a ground-motion model logic tree. Four ground-motion models potentially adapted to the French context are included, based on four different strong-motion databases. The variability of hazard estimates related to the uncertainties on the source model is now compared to the variability related to the uncertainties on the ground-motion model (following  Beauval et al. 2018). As the source model logic tree includes only one earthquake catalog (i. e. , FCAT), the earthquake catalog choice is not included in the uncertainty exploration, and the variability on the hazard estimate must be considered as a lower bound. Figure  14  displays the complete acceleration distribution, exploring the source-model logic tree based on FCAT combined with the ground-motion logic tree (24 × 4 = 96 branches).
3 6 Conclusions Our aim is to explore uncertainties related to the source model in hazard calculations for France. We study the impact on hazard when using alternative seismogenic source models, alternative earthquake catalogs, alternative declustering algorithms, and different minimum magnitudes for earthquake recurrence modeling. We use the FCAT and SHEEC earthquake catalogs. Alternative source models are combined with four ground-motion models (i. e. Bindi et al. 2014; Boore et al. 2014; Cauzzi et al. 2015; Drouet and Cotton 2015)  to estimate probabilistic seismic hazard. We focus on sites located in source zones with a minimum amount of data to work with, within areas of moderate seismicity in France (Alsace, Alps, Pyrenees, Massif Central and Southern Brittany). Considering FCAT, a logic tree can be set up to quantify the overall impact of sourcemodel uncertainties on hazard.
The results show that the parameters that have the highest impact on hazard vary among sites. Nonetheless, the parameters that most impact hazard are the minimum magnitude used to model earthquake recurrence (up to 31% impact on the mean hazard estimate) and the seismogenic source model (up to 30%). Considering different spectral periods (PGA, 0. 2 s) and different return periods (475 and 5000 years), the controlling parameters remain identical, and the estimated impacts remain stable. Because SHEEC has a high minimum magnitude of completeness (M W > 4. 0), most zones are left with few events. This lack of data prevents proper exploration of uncertainties. Nonetheless, there are a few source zones where the recurrence model is well-constrained. Earthquake recurrence models based on FCAT and SHEEC are found comparable in some sources (e.
g. , the Pyrenees). In other sources, seismic rates inferred from FCAT can be either lower (e. g. , in the Lower Rhine graben) or much higher (e. g. , in Southern Brittany) than the rates inferred from SHEEC. For the city of Nantes, choosing FCAT rather than SHEEC leads to twice as large mean hazard values (PGA and 0. 2 s, 475 year return period). Four ground-motion models that rely on four different databases are selected as an attempt to sample the epistemic uncertainty on the prediction of ground motions for France. The overall variability on hazard estimates can be obtained for the sites under study by combining these four ground-motion models with the logic tree established from FCAT. We also assess the respective contribution of the source-model uncertainty and groundmotion model uncertainty to the overall uncertainty.
The contribution of the source-model uncertainty can be lower than, equivalent to, or higher than the contribution of the groundmotion model uncertainty and varies with the site, spectral period, and return period. Some anomalous features in the FCAT earthquake catalog have been highlighted (e. g. , problem of homogeneity in magnitude between the historical and instrumental periods, apparently too many events around M W 5. 0 in the Pyrenees) that might impact the hazard estimates obtained in the present study. There is no unique method to infer earthquake parameters from macroseismic data or to homogenize an instrumental catalog in terms of moment magnitude. Earthquake catalogs built by different teams may lead to different seismic rates for seismogenic sources. One way to handle this uncertainty in seismic hazard modeling would be to integrate alternative earthquake catalogs in the source-model logic tree.
2. 2. The Lax-Oleinik semigroup. We recall that a solution of H(x, d x u) = h corresponds to a stationary solution U (t, x) = u(x) -ht of the evolution equation ∂ t U + H(x, ∂ x U ) = 0 , for which the Hopf-Lax formula reads U (t, x) = inf u 0 (y) + A L (γ) | y ∈ E N , γ ∈ C(y, x, t). In a wide range of situations, this formula provides the unique viscosity solution satisfying the initial condition U (0, x) = u 0 (x). Using the action potential we can also write the formula as U (t, x) = inf u 0 (y) + φ(y, x, t) | y ∈ E N. If the initial data u 0 is bounded, then U (t, x) is clearly well defined and bounded. In our case, we know that solutions will not be bounded, thus we need a condition ensuring that the function y → u 0 (y) + φ(y, x, t) is bounded by below. Assuming u 0 ≺ L + h we have the lower bound u 0 (x) -ht ≤ u 0 (y) + φ(y, x, t) for all t > 0 and all x ∈ E N , but this is in fact an equivalent formulation for the domination condition u 0 ≺ L + h, that is to say u ∈ S h.
Acknowledgements References Acknowledgements. The authors would like to express a very special thank to  Albert Fathi , who suggested the use of the method of viscosity solutions, as well as the way to construct the maximal calibrating curves of the horofunctions. The first author is also grateful to  Alain Albouy ,  Alain Chenciner  and  Andreas Knauf  for several helpful conversations at the IMCCE. Finally, we would like to thank the referee for his accurate and helpful comments, and  Juan Manuel Burgos  for pointing out a subtle mistake in one of the proofs.
Acknowledgements The authors thank  Andrey Shchukarev  for collecting the XPS data. The SEM images were obtained at the  Umeå Core Facility for Electron Microscopy (UCEM). The authors thank European This journal is © the Owner Societies 2020 Synchrotron Radiation Facility for granting beamtime and the ID26 beamline staff for assistance during the experiments. The  Knut and Alice Wallenbergs Foundation  ( Artificial Leaf Project ;  KAW 2011. 0055 )provided financial support. T. W. acknowledges support from  Vetenskapsrådet  ( 2017-04862 ), and  Energimyndigheten  ( 45419-1 ).