dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The author wishes to thank the contributors involved in dyesensitized solar cell group at LRCS,  Miguel Flasque ,  Vittoria Novelli ,  Iryna Sagaidak ,  Guillaume Huertas ,  Dr. Nadia Barbero ,  Dr. Gregory Gachot , and  Dr. Albert Nguyen Van Nhien  ( LG2A CNRS FRE 3517 ). He also expresses his gratitude to  Sarine Chhor  ( EPFL ) for her contribution to butyronitrile work,  Dr. Aravind Kumar Chandiran  ( EPFL ) for his doping work,  Dr. Robin Humphry-Baker  ( EPFL ) for FT-IR analysis of aged electrolyte,  Dr. Carine Davoisne  ( LRCS ) for TEM measurements, and  Mathieu Courty  ( LRCS ) for TGA analysis. Carine Lenfant (LRCS) is acknowledged for reading the paper. The author is also indebted to the  FEDER  and  Région Picardie  for financial support of  ROBUST research program.
The reaction can be monitored by using mass spectrometry to follow the change in concentration of D 2 , HD and H 2 , see e. g. Fig. 4. HD is an intermediate along the reaction pathway from D 2 to H 2 , and because the egress of HD competes with its transformation into H 2 , the slower intramolecular transport, the less HD dissociates from the enzyme's active site and the less it can be detected in the solvent. Modelling the change in HD concentration against time returns the ratio of rate of HD dissociation over H + /D + exchange at the active site. 135 Under certain conditions,  63  the data can also be used to directly measure the rate of dissociation, k H2 out. Alternatively, the information about the kinetics of ligand binding may be deduced from turnover-rate measurements: it is indeed possible to determine the rate of binding or release of a competitive inhibitor ("competitive" means that it targets the active site) by monitoring the change in turnover rate upon exposure to the inhibitor.
Acknowledgements This paper was partly written during a two-week residency in Marseille funded by  IMéRA, Institut d'études avancées de l'Université d'Aix-Marseille  (http://imera. univ-amu. fr/). P. -H. W. acknowledges the  Ministry of Education, Republic of China (Taiwan) , for a Ph. D. scholarship. J. B. acknowledges the  Royal Society  for a  University Research Fellowship  and the  Engineering and Physical Sciences Research Council  ( EPSRC research  grant  EP/J015571/1 ) for nancial support. L. D. G. acknowledges support from  Ministero dell'Istruzione, dell'Universita e della Ricerca  (Prin 2010M2JARJ). The Marseille team acknowledges  CNRS ,  Aix Marseille University ,  Région PACA ,  ANR  ( ANR12BS080014 ) for funding, and support from  French-BIC  (http://frenchbic. cnrs. fr).
Differential scanning calorimetry Thermal data were obtained by measuring about 10 mg of the sample placed in aluminum hermetic pans using a TA Instrument Q1000 Differential Scanning Calorimeter (DSC). The DSC scans were performed as follows. After equilibration at 40 1C the samples were cooled down to À150 1C using a cooling rate of 5 1C min À1. Subsequently, the samples were equilibrated at À150 1C for three minutes and thereafter heated to 250 1C at a heating rate of 5 1C min À1. After 3 minutes of equilibration at 250 1C, the samples were cooled down to À150 1C using a cooling rate of 5 1C min À1 and equilibrated for at least 3 minutes. Finally, samples were heated from À150 1C to 250 1C at a rate of 5 1C min À1. (1 À x)EMIMTFSI:(x)LiTFSI samples with x = 0. 66, 0. 70 and 0. 75 were heated up to 160 1C and 200 1C respectively.
Ionic conductivity measurements The temperature dependence of the ionic conductivity was measured by dielectric spectroscopy using a Novocontrol broadband dielectric spectrometer at frequencies ranging from 10 À1 to 10 7 Hz. The sample (about 0. 3 g) was placed between two stainless steel electrodes with a Teflon spacer (13. 2 mm in diameter and 0. 99 mm in thickness) and loaded into a cryofurnace with nitrogen flow. The cell, ''Liquid parallel plate cell BDS 1308'' -Novocontrol, was assembled in an argon atmosphere. Data were collected during heating from 20 1C to 180 1C with a temperature step of 10 1C and a stabilization time of 30 min at each temperature. The DC conductivity was deduced from the low frequency plateau of the conductivity isotherms obtained by plotting the real part of the complex conductivity as a function of frequency.
Raman spectroscopy studies Finally, the macroscopic data for the Li x EMIM (1Àx) TFSI system above are correlated with molecular level Raman spectroscopy data across all compositions and a wide range of temperatures. Raman spectra were collected at 23 1C, 90 1C and 165 1C to investigate the Ib, IIa, Ia, and L phases, respectively. ] [18] [19] [20] [21] [22] [23]  The pure Ib phase (x = 0. 66) is useful as a starting point as the TFSI anion coordination is known  11  and, thus, can serve as an internal reference. Here, the TFSI anion exists in three different combinations of conformation and coordination environment; in two cases in C 1 conformation and either coordinated by three lithium cations by four oxygen atoms or by two lithium cations by three oxygen atoms, and for the remaining case in C 2 conformation and coordinated by two  lithium cations by three oxygen atoms.
Instrumentation and operating conditions CE analyses were performed using a P/ACE TM MDQ Capillary Electrophoresis System (Beckman Coulter, San Jose, CA, USA) equipped with a photodiode array detection system. MDQ software provided by Beckman (GOLD, v 2. 3) was used to pilot the CE, for signal acquisition and for data treatment. CE analyses were performed in a fused-silica capillary (60. 2 cm total length, 50 cm effective length, 75 m i. d. ) purchased from Polymicro Technologies (Phoenix, AZ, USA). The capillary temperature was 25 • C. All rinse cycles were carried out at 50 psi. Separation was realized at +25 kV (normal polarity). The BGE solution in the separation vials was renewed every three runs. Hydrodynamic injections were performed at 1 psi during 5 s (∼56 nL). The UV detection was performed at 240 nm (bandwidth 10 nm).
A development of this car model using dynamic method is necessary to assess the performance of the car, generate its driving cycle, and evaluate its energy consumption and driving range during races. The simulation has to include a module that emulates the behavior of the driver on pedal like in the real propulsion system  [16]. The experimental data obtained from driving tests performed at Magny-Cours racing track are used to verify the accuracy of the model. Analysis of the track map and driving actions on certain zones of the circuit will be used to create a pattern of the driver behavior in function of distance. This method will create a prediction tool to forecast inputs on car accelerator pedal position for other race tracks, obtain the driving schedule, and further determine energy consumption and battery SoC evolution of this car.
As one of the  objectives is to evaluate the distance, the car can complete before the charge depletes to its lower limit. This will maintain the battery power capacity, prolong the battery lifetime, and prevent the batteries from deteriorating dramatically due to deep discharge and high battery peak current  [34] ,  [40]. Moreover, without the need of car testing on the intended racing track, a database of racing driving schedules can be created using this method, which are useful to optimize the system. The organization of this paper is as follows. Section II introduces the car, its components, and vehicle model. Section III covers the analysis of the driving cycle and the racing schedule prediction method, followed by the optimization of the control parameters. Discussion of the results is covered in Section IV, and finally perspectives and conclusion are given in Section V.
B. Vehicle Dynamics Model Model development of this system is implemented in a structured manner using EMR, modeled in simulation under MATLAB/Simulink software package, as shown in Fig. 3. EMR highlights energetic properties of a system based on action-reaction principle to organize the interconnection of subsystems according to the physical causality  [22] -  [24] ,  [43]. Like in the real propulsion system, the driver command for acceleration and braking actions (pedal position) imposed to the system is taken as input of the power-train model  [16]. The longitudinal dynamic derived from Newton's second law to determine the velocity of the vehicle is described in  (1). The force to accelerate the vehicle and the rotating parts inside the vehicle is equal to the available driving force F d , generated by prime mover minus the total resistance forces F res (Fig.
IV. DRIVING CYCLE MODEL DEVELOPMENT As race application is different from other vehicles applications, this car needs a driving cycle database of its own for optimization purpose. This is because the existing standard  driving cycles do not correspond to the design, and its driving style is not the same like any passenger car. This car has been tested on the real track of Magny-Cours Grand Prix racing circuit and a smaller circuit at site. The driving test results are then analyzed for further improvement of this car. A driving pattern is deducted by referring to the conducted experimental results and observation on drivers actions on pedal at particular locations of the circuit. However, this driving cycle prediction method can only be realized if there is a good vehicle dynamic model of the studied system.
MIR experiments under atmospheric condition (ISTO) The measurements and the subsequent conversion were verified by measuring equivalent spectra using a Fourier Transform Infrared Micro-Spectrometer (Nicolet Continµum, Thermo Scientific). Notice that this laboratory setup allows a wider thermal range (263K -363K) than the Soleil setup. In the following, we limit the discussion to the 275-350K temperature range, and report the other data and the comparison between the two datasets in a supplementary material. IR spectra were recorded, in the 850 cm -1 to 4000 cm -1 spectral range, using the laboratory spectrometer equipped with a XT-KBr beam splitter and a liquid nitrogen cooled Mercury Cadmium Telluride (MCT) wide range detector (250 µm). The microscope runs in confocal mode, using a 15X infinity corrected Schwarzschild objective and a matching 15X condenser.
Description of the bands The evolution of the IR bands in this spectral domain has been detailed by Brubach et al  31  from 264K to 320K. The present temperature range is wider, but the successive shape and absorption of the different bands meet their conclusions. Baseline correction is processed the same way for all spectra, using the Matlab function "backcor" developed by Mazet et al  33  , and the background is estimated by an asymmetric truncated quadratic cost function. The bending mode mostly reflects water molecules that do not lie in a symmetric tetrahedral environment  31  as in ice. The band (Fig. 1A ) exhibits an increasing absorbance with temperature, and the maximum slightly shifts toward lower wavenumbers from 1650. 7 cm -1 at 263K to 1648. 3 cm -1 at 363K (experiment under atmospheric condition) and from 1651.
Hence, each Gaussian sub-band describes the quantity and the energy of the water molecules with a given mean coordination number (Fig. 2 ). The low frequency Gaussian is associated to the fully tetrahedrally coordinated water molecules, called network water (NW) also known as ice-like water since the Gaussian peak is close to its ice counterpart (3250 cm -1 ). The high-frequency Gaussian sub-band is ascribed to the molecules with a low coordination number (two, one or zero),  The experimental bands are free-fitted (Fig. 2 ) with the software Igor and its Multipeak fitting 2. 0 package, to obtain the molecular fraction of each water population as a function of temperature. The molecular fraction of one population given by the ratio between the area of the Gaussian associated to the water population and the total area of the three Gaussians are reported in Table  1.
The bending mode is hardly sensitive to the environmental conditions, including temperature, and so the band frequency is constant for all classes of molecules in the probed temperature range. The libration band was fitted by two Gaussian components (Gauss 2 and 3) but they have varying width with T preventing their use for extrapolation. Therefore, only the main frequency of the complete band is fitted with T according to a linear dependency. Meanwhile, the connectivity band has only one Gaussian component, linearly varying with T (Table  2 ). Table  2. Values of the vibrational characteristic frequencies used in the IR-to-thermodynamic model. Data are either directly measured or calculated with an empirical -T relationship defined from lower-T measurements (reported in footnotes). For data recorded at ambient pressure with laboratory sources, the connectivity band and the low frequency part of the libration band were not recorded.
Acknowledgements. This work has received financial support from the  French Agency for Research (Agence Nationale de la Recherche) , grant  CONGE ANR-2010-BLAN-0610  and from  Region Centre  grant  201100070577   SIRE. It also benefits from the SOLEIL Synchrotron allocation n°99130036. At last, the support of labex  Voltaire  (grant  ANR-10-LABX-100-01 ) is also acknowledged.
Although data are not reported in Fig. 7 , no significant response was obtained for ozone, sensor signal not being distinguished from the electronic noise. A high level of selectivity is performed. In our working conditions and for an average ozone background level to 50 ppb, the sensor-system lifetime mainly conditioned by the efficiency of indigo/MWCNTs hybrid filter to remove this interfering pollutant was estimated to more than 3 months. Although this hybrid filter is especially appropriate in such sensor-system, it could be associated to others chemical sensors for which ozone represents the major interfering gas.
Acknowledgments This work was funded by grants from the  French program  " investissement d'avenir" , the  European Commission  ( Auvergne Feder  funds) and the " Région Auvergne " in the framework of the LabEx IMobS 3  Professor Maria-Luz Rodriguez-Mendez , from  University of Valladolid  (Spain), was invited for 2 months in order to be involved in the project " Selective Chemical Sensors ". A. L. Ndiaye  thanks the " Laboratoire d'Excellence IMobS 3 "  for postdoctoral fellowship. This work involves some developments associated to the  CAPBTX  project ( 2010 BLAN 917 01 ) and the authors wish to gratefully acknowledge the  Agence Nationale de la Recherche (A. N. R. , France). J. Brunet ,  A. Pauly  and  A. L. Ndiaye  would like to thank the transdisciplinary  COST Action TD 1105 "EuNetAir " in which they are involved for supporting these scientific works.
Hereafter they will be referred to as CG and CCl solutions. Moreover, LOx-IL-free solution (PBS 7. 4; 10mM) was also studied for comparison. PBS is used as a reference system in order to establish variations in the standard behaviour of the LOx enzyme when compared to non-conventional solvents, such as HyILs. In order to ascertain the effective solubilisation of LOx in the HyIL solutions an UV-vis nanodrop system (Thermo Scientific -NanoDrop 2000c) was employed, following a similar protocol to the one described by Weaver et al. 17  These experiments showed a negligible UV absorbance signal in the region of the spectra in which the ILs and the enzyme do not absorb, indicating that LOx was completely solubilised (data not shown).
Circular dichroism spectroscopy The secondary structure of the enzyme was investigated by circular dichroism spectroscopy in the far-UV region (190-250 nm) using a JASCO CD J-810 spectropolarimeter. CD spectra were recorded using a 0. 1 cm path length quartz cuvette loaded with 300 mL of the sample at the final concentration of 0. 25 mg ml À1 of LOx. Temperature induced denaturation of the protein was performed from 25 1C to 90 1C at the scan rate of 1 1C min À1 at 222 nm. Quantitative secondary structure analysis of LOx in solution was performed by fitting the far-UV CD data using the published analysis algorithms CDSSTR (reference set 4) of the online server DICHROWEB. 31, 32.
Under these experimental conditions, the production of hydrogen peroxide from LOx is assumed to be the only limiting step for the cascade of reactions. Furthermore, due to the higher IL concentrations, the pH of the PBS assay was affected and so its variation was recorded using a standard glass membrane pH meter (VWR, sympHony SP70P). Kinetic constants (K M and V max ) were obtained from the data through a nonlinear fitting of the Michaelis-Menten equation using an in-house Excel developed macro. † Turnover numbers (k cat ) were calculated from V max using the relationship, k cat = V max /[E] where [E] is the molar enzyme concentration, i. e. 50 nM.
Acknowledgements VFC, SS, FBL, and  DD acknowledge Science Foundation Ireland  (grant  07/CE/I1147 ) and the  Research Career Start Programme 2010 fellowship  from  Dublin City University. SS is grateful to the  Erasmus placement programme of the European Lifelong Learning Programme (LLP ). RMO acknowledges funding from the  European Research Council  ( ERC grant  agreement no. 258966 ). VFC and FBL want to thank  Dr. Niamh Gilmartin  for her advice during enzyme characterisation. DRM is grateful to the  ARC  for his Federation Fellowship. The authors of this work are grateful to the  MASK , a  Marie Curie International Research Staff Exchange Scheme. Thanks to  Roche Diagnostics Deutschland GmbH  for providing the LOx protein. Thanks also to the  Conway Institute  ( UCD -Dublin ) for access to the Circular Dichroism Spectropolarimeter.
Acknowledgments The authors would like to express their thanks to the  Dirección de Investigación y Posgrado del Instituto Mexicano del Petróleo and CONACyT  for their financial support. The authors are grateful to  S. Mendoza Acevedo ,  Centro de Investigación en Computación  ( CIC-IPN ), for fruitful discussions. FCS and JMS are grateful for the financial support from the  Physicis and Mathematics Department  and from the  Direction of Research at Universidad Iberoamericana.
Characterization The specific surface area was determined by the singlepoint BET method in 30 vol% N 2 /He using a QuantaChrome ChemBET 3000 instrument. Prior to measurements, all samples were degassed in pure N 2 at 200 °C for 30 min. The phase composition of fresh and aged catalysts was analysed by X-ray diffraction (X'Pert Pro PANalytical) using monochromatic Cu Kα 1 radiation (λ = 1. 54 Å). The diffraction patterns were recorded between 20°and 80°(2θ) with an angular step interval of 0. 0167°. Phase identification was performed using the ICDD reference database in the X'Pert HighScore Plus software. The morphology of the catalysts was observed using a Jeol 2200FS transmission electron microscope equipped with a 200 kV field emission gun and a high-angle annular dark field detector in STEM mode providing images with atomic number (Z  1.
5-1. 8  ) contrast. 56 The local composition was determined by energy dispersive X-ray spectroscopy (EDS). The samples were prepared by evaporation of an alcohol suspension on a copper grid coated with a holey carbon film. The palladium particle size distribution was obtained by measuring up to 200 particles using the software ImageJ. 57 he oxygen storage capacity complete (OSCC) defined as the total amount of desorbed oxygen was determined under static conditions using the thermogravimetric method. 58, 59 he samples were treated with 5 vol% H 2 /Ar at 400 °C for 70 min using a TGA Q500 setup (TA Instruments). The measured weight loss was converted into the corresponding oxygen content assuming that the sample is fully oxidized in its initial state. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) data were collected at a resolution of 4 cm -1 using a VERTEX 70 FT-IR spectrometer (Bruker) equipped with a high temperature reaction chamber (HVC-DRP2, Harrick) and a liquid-nitrogen cooled MCT detector.
Prior to CO adsorption, the samples were exposed to 20 vol% O 2 /Ar (50 mL min -1 ) at 500 °C for 30 min, followed by reduction at 300 °C for 30 min in 10 vol% H 2 /Ar. After changing to Ar and cooling to room temperature, a background spectrum was obtained prior to CO adsorption in 5 vol% CO/Ar. Extended X-ray absorption fine structure (EXAFS) spectroscopy data were obtained in the transmission mode at the Pd K-edge (24. 35 keV) at the SuperXAS beamline of the Swiss Light Source (PSI, Switzerland). The spectrum of the Pd foil was simultaneously collected for energy calibration. The required sample amount was homogeneously mixed with polyethylene and pressed into pellets. The spectra were energy and background corrected and normalized with the software Athena. 60 ime-resolved high energy XRD data (86.
The outlet of the cell was connected to a mass spectrometer (OmniStar, Pfeiffer) that was used to follow signals of m/z 28 (CO), 32 (O 2 ), 44 (CO 2 ) and 4 (He) and simultaneously to read the sample temperature. The 5000 time-resolved XRD data collected in each experiment were averaged over the number of modulation periods into a single period prior to phase sensitive detection (PSD): I T I t k t t k k T    PSD PSD d    2 0 ( )sin( ) (1) 3] [64]  According to the theory of modulation enhanced diffraction,  65  the integral of eqn (1) can be more explicitly (and correctly) written to contain two terms, one of which depends only on the component of the system that is stimulated, whereas the second one contains both this component and the static one. PSD with k = 2 should provide only the response of the former component, but we did not find any difference other than intensity by using k = 1, which is shown here.
Time-resolved high energy XRD The surface dynamics of the fresh and aged catalysts was addressed using high energy X-ray diffraction combined with the modulation excitation approach. 61, 79 High energy XRD is a suitable method because it provides information on the whole material in a snapshot and in a time-resolved manner. It has been shown that subtle structural changes occurring during reaction that are not visible in XRD can be enhanced if the experimental data are collected under pulsed conditions. 61 n this work, the modulation experiment consists of alternate and repeated CO vs. O 2 pulses that should simulate the protocol typically used to determine the dynamic OSC. 80 We restrict the discussion to fresh and aged 2Pd/YFO catalysts whose time-resolved XRD patterns recorded at 400 °C are dominated by the hexagonal and orthorhombic YFeO 3 structures, respectively (Fig.
Acknowledgements. We thank  F. Ménard ,  C. Dougados ,  J. -C. Augereau ,  J. -F. Gonzalez ,  S. T. Maddison ,  D. J. Price  and  J. B. Kajtar  for useful discussions. C. Pinte acknowledges funding from the  European Commission 's  FP7  (contract  PERG06-GA-2009-256513 ) and the  Agence Nationale pour la Recherche of France  (contract  ANR-2010-JCJC-0504-01 ). G. Laibe is grateful to the  Australian Research Council  for funding (contract  DP1094585 ) and acknowledges funding from the  European Research Council  for the  FP7 ERC  advanced grant project ECOGAL. Computations were performed at the  Service Commun de Calcul Intensif de l'Observatoire de Grenoble (SCCI).
The detection limit (in g/kg dry weight) for each pollutant was: 35. 0 for NP; 0. 35 for OP; 0. 05 for Ant, 0. 3 for BaP, BgP, BbF, BkF, DBA and Flu; 0. 2 for BaA. The limits of detection (LOD) were calculated by spiking a lyophilised biota sample in which that particular pollutant was absent with a known amount of a standard solution containing that compound. The LODs were the concentrations that resulted in signal-to-noise ratios of 3. Results are reported as g/kg on wet weight basis (w. w. ), as the guidelines and limits for dangerous substances in food for human consumption are normally expressed in wet weight basis. To enable comparison with data from other investigations, the reported values can be converted taking into account the measured humidity of the specimens, which was 80% for mussels and 75% for clams.