dataesr/scientific-paragraphs-categorization huggingface dataset:
All models were adjusted for age, sex, education, and country. Potential confounding effects of number of children, body mass index (BMI), ever smoking, regular intake of alcoholic beverages, and ever using hair dyes were examined, but none of them altered the estimates for mature B-cell neoplasms by more than 10%. Because occupational exposure to solvents has been previously associated with lymphoma, we analysed associations among the unexposed to solvents, and we included ever exposure to organic solvents as a covariate in the regression models evaluating specific groups of chemicals. Duration, age at first exposure, and time since last exposure were calculated based on the years at start and stop reported for each job. Data were missing for o5% of subjects for all variables, except for BMI, which reached 9% because its measure was introduced at a later stage in the study.
ACKNOWLEDGEMENTS We thank all those who took part in this study providing questionnaire data. We acknowledge funds provided by the  University of Barcelona  for the  Research Abroad Grant   2012  and a  Rio Hortega  ( CM13/00232 ) from the  Spanish Ministry of Economy and Competitiveness (Carlos III Institute of Health)  granted to LC. This work was partially supported by the public grants from  Health Ministry of Spain  ( PI11/01810  and  PI14/ 01219 ),  Catalan Government  ( 2009SGR1465  and  2014SGR756 ),  European Commission   5th Framework Programme  ( QLK4-CT-2000-00422 );  6th Framework Programme  (  FOOD-CT-2006-023103 );  Carlos III Institute of Health  ( FIS PI081555 ,  RCESP C03/09 ,  RTICESP C03/10 ,  RTICRD06/0020/0095  and  CIBERESP) ;  MaratoTV3 Foundation  ( 051210 );  International Agency for Research on Cancer  ( IARC-5111 ); MH CZ -DRO (MMCI,  00209805 ),  RECAMO CZ.
5174 at temperatures T between (229 to 348) K and pressures p between (1 to 32) MPa, which correspond to mass densities  of (20 to 600) kgm -3. The viscosity  was measured with a vibrating-wire-viscometer (VWV), clamped at both ends and operated in steady-state mode that has been described in detail previously  [8, 14]. To calculate viscosity from the measured resonance curve, the fluid mass density is required and in this work it was calculated from the measured T and p using the GERG-2008 equation of state (EOS)  [15]  as implemented in the software package REFPROP (REFerence fluid PROPerties database 23, version 9. 1, NIST)  [16]. The measured viscosities were then compared with predictions made using one of three models based on the principle of corresponding states: the Extended Corresponding States (ECS) model implemented in REFPROP, the SUPERTRAPP model implemented in MultiFlash 4.
Conclusions A doubly-clamped vibrating-wire viscometer operated in steady-state mode was used to measure the viscosity of a CO2+CH4 mixture at temperatures from (229 to 348) K and pressures in the range (1 to 32) MPa. The measured viscosities of this binary mixture show large deviations (up to +11%) from the ECS model in REFPROP, with the deviations becoming more positive as temperature decreases and density increases. These results validate measurements in the literature made at a similar composition, and also extend the results to lower temperatures. These new data may be used to aid the development of more accurate, wide-ranging viscosity models for the CO2 + CH4 mixture. In particular, the results validate recent models based on molecular dynamics simulations developed to predict the viscosities of acid-gas mixtures, which had a maximum relative deviation of 4.
Structural, morphological and compositional characterization The structural investigation of the sensors was performed in Bragg-Brantano geometry by the XRD method, using s Siemens D5000 X-ray diffractometer with a CuKα radiation (λ CuKα = 0. 15418 nm) and the graphite-curved monochromator. For phase analysis, θ /2θ -spectra is measured with an acceleration voltage of 40 kV at a step of 0. 020 • and a step rate of 3 s step -1. The obtained data were compared with the JCPS database (Joint Committee on Powder Diffraction Standards) via EVA software from Bruker AXS in the range of 10-80 •. The analysis of microstructure, surface morphology and chemical composition was carried out by using a field emission scanning electron microscope (FE-SEM, Carl Zeiss NTS Ultra 55) equipped with an EDX spectrometer.
Acknowledgements. This work has been partially supported by  DAAD-DLR  fellowship funding under the fellowship number  165. The authors thank  Uwe Schulz , the  head of the department High Temperature and Functional Coatings , for his valuable support and  G. C. Mondragon Rodriguez  for his assistance with FE-SEM. Edited by: A. Lloyd Spetz Reviewed by: three anonymous referees.
Improvements to the EXGAS software to extend the treatments of large olefins  18, 28  provided further understanding of the issues involving the role of the site of the C=C double bond in the fuel molecule, and Battin-Leclerc et al. 26  summarized the current state-of-the-art with respect to kinetic modeling of the linear alkene fuels. The present study examines how the same kinetic modeling capabilities can be applied to a branched olefin.
Conditions investigated during this study are provided in Hamamatsu 1P21 photomultiplier tube. The ignition delay time is defined herein as the time between the passage of the reflected shock wave, indicated by a pressure jump in the signal delivered by the sidewall pressure transducer, and the intersection of lines drawn along the steepest rate-of-change of OH* de-excitation and a horizontal line which defines the zero-concentration level, as can be seen in Fig. 1(a). Time zero is defined as the time of arrival of the reflected shock wave at the sidewall measurement location. All of the data signals were recorded through a 14bit GageScope digital oscilloscope with sampling rates of 1 MHz or greater per channel. Note that OH* profiles were more difficult to interpret at pressures above 1. 6 atm under fuel rich conditions.
The identification of other species was performed using a fourth gas chromatograph coupled with a mass spectrometer (GC-MS) operating under the same conditions as the other gas chromatographs (PlotQ and HP-1) enabling the direct comparison of both chromatograms. The mass spectra of all detected reaction products were included in the spectra database "NIST 08"  47. The calibration was performed by injecting known amounts of the pure substances when available, otherwise the method of the effective carbon number 48 was used (species having the same number of carbon atoms and the same functional groups were assumed to have the same response in the FID). Amongst products which are known as important for hydrocarbon oxidation, only hydrogen, water and formaldehyde were not quantified, but the presence of the two last ones can be identified in GC-MS analyses.
acetone, acetaldehyde, methanol, acrolein (C 2 H 3 CHO), and methacrolein (iC 3 H 5 CHO), were measured at levels above 100ppm, and smaller levels of other hydrocarbon and oxygenated hydrocarbon species were detected. In Fig. 5 , the species name "2M2Butenal" signifies "2-methyl-2-butenal", and "2M3B2-one" signifies "2-methyl-3-buten-2-one". In Fig. 6 , "2,2,3-TMO" represents "2,2,3-trimethyl oxirane", a C 5 cyclic ether. This broad variety of chemical species and the reaction pathways by which they are produced and consumed over a wide range of reaction temperatures, together with the ignition delay times from the shock tube experiments described above, form the body of data that was used to develop and test the present chemical kinetic reaction mechanism for 2M2B.
High Temperature Shock Tube Simulations Experiments described above of ignition of 2M2B in oxygen, diluted with 99% argon, were simulated using the constant-volume, closed homogeneous batch reactor option in the ChemkinPro software  60   and an assumption that the de-excitation of the OH* is very rapid following its production. Comparisons between computed and experimental ignition delay times are summarized in Figs. 9 and 10. Overall agreement is excellent, with all of the results within a factor of two over the entire temperature, equivalence ratio, and pressure ranges. There appears to be a slight trend in the computed results towards an effective activation energy very slightly larger than that which could be extracted by a fit to the experimental results, but no other systematic trends can be detected from the comparison plots.
Low-and Intermediate Temperature JSR Experiment Simulations The jet-stirred reactor experiments were simulated using the ChemkinPro software with the transient PSR application  60  , setting the reaction temperature fixed for each computed point, at temperature intervals of 50K from 600 to 1100K. Selected computed results for a wide variety of chemical species mole fractions are plotted, together with their experimentally measured mole fractions, in Figs. 4 Other species were measured or calculated at levels less than 100 ppm, including allene, propyne, 1,3-butadiene, 2methyl 1-butene (aC 5 H 10 ), C 2 H 5 CHO, 2-C 4 H 8 , and several oxygenated hydrocarbons that are important parts of the kinetic reaction mechanism such as 3-methyl-2-butenal , 2-methyl-2-butenal, and 2-methyl-3-buten-2-one.
The rapid consumption of fuel between 800 and 950K releases enough heat to increase the temperature to decompose the remaining allylic pentenyl radicals and the H 2 O 2. The present experiments demonstrate reaction on both sides of these transition temperatures. The kinetic mechanism reproduces the observed reactivity, with a smooth transition between those regimes. We carried out some preliminary kinetic modeling studies of these low and intermediate temperature oxidation condition for 2M2B using a semi-detailed kinetic reaction developed using the EXGAS mechanism generation software  56  to which new features were recently added  28  to provide kinetics specifically related to olefins fuels. The overall performance of this preliminary mechanism was very good, and the relative simplicity of the model permitted us to identify the portions of the detailed mechanism that were most important and therefore required the most attention.
ACKNOWLEDGMENTS The authors thank  Dr. Ellen Meeks  of  Reaction Design , who first suggested this study of 2-methyl 2-butene. The work at  LLNL  was supported by the  U. S. Department of Energy, Office of Basic Energy Sciences  (program manager,  Wade Sisk ),  Vehicle Technologies Office  (program manager  Gurpreet Singh  and  Leo Breton ) and was performed under the auspices of the  U. S. Department of Energy  by  Lawrence Livermore National Laboratory  under Contract  DE-AC52-07NA27344. The efforts at  Texas A&M University  were supported, in part, by the  TEES Turbomachnery Laboratory. The work at the  Universite de Lorraine  was supported by the  European Commission  through the  "Clean ICE" Advanced Research Grant  of the  European Research Council. NUI Galway  would like to acknowledge the support of the  Irish Research Council  in funding their portion of this work.
The SiO 2 support is clearly visible, principally in a-cristobalite and secondarily in tridymite forms. More importantly, the distributions of Mn 2 O 3 and Na 2 WO 4 show that they are not perfectly co-located. At 675 1C, the Na 2 WO 4 phase disappears, which is in agreement with the work of Hou et al. , and is coincident with the appearance of an amorphous phase. 19 However, a new phase is seen to appear which we identify as BaWO 4 (using the ICSD and the ICCD PDF crystallographic databases (Fig. S3 , ESI †)). The distribution of BaWO 4 does not match the starting distributions of Na 2 WO 4 but instead concentrated spots of this phase form predominantly at the catalyst/membrane interface. At 725 1C, Mn 2 O 3 decreases but significant amounts of BaWO 4 grow which appears to migrate towards the inner wall of the membrane.
It is essential to note that in both OCM experiments (i. e. OCM1 and OCM2) the same solid-state chemistry takes place demonstrating that the results from the OCM1 experiment are reproducible. In panel G of Fig. 3 , it is shown that when 5 vol% CH 4 diluted in He (total flow rate of 100 mL min À1 ) is used, there is a new signal in the mass spectrometry data (m/z 26) which corresponds to C 2 fractions. The profiles of selected masses throughout the experiment are presented in Fig. S5 (ESI † ) where it is shown that C 2 fractions increase with increasing CH 4 concentration, and that C 3 fractions are also forming. It is therefore reasonable to assume that the catalyst was captured in its active state in both experiments. The mass spectrometry data also suggest that there is no short term loss in activity with formation of BaWO 4.
The observation that there is no simultaneous loss of activity when W is being locked away (as BaWO 4 ) suggests there is Na 2 WO 4 present in the system which is not participating as part of the active catalyst. From the OCM2 experiment we observe that Na 2 WO 4 reforms during cooling after the OCM experiment, albeit in lower concentrations to that of the initial state, and that the formed BaWO 4 persists, as does the distribution and final forms of the support material (panels E and F in Fig. 3 ). This is also apparent in the micro-CT data where the hotspots (the overlaid red and green circles highlight example hotspot regions in panels A and B of Fig. 3 ) are large concentrations of the W-containing phases (Fig. S6 , ESI †). Our observations regarding the BaWO 4 phase are confirmed by ex situ SEM/WDS elemental mapping (Fig.
Acknowledgements This research was funded by  Ecole Polytechnique  (PhD scholarship of Claire Dupont), the  Conseil Régional de Picardie  ( MODCAP grant ), the  French Ministère de la Recherche  ( Pilcam2 grant ) and the  French Agence Nationale de la Recherche  ( CAPSHYDR  grant  ANR-11-BS09-013 ,  Labex   MS2T ANR-11-IDEX-0004-02 ).
50, 51 Experiments on lead nitrate with different MAS speeds showed that the frictional heating effect at 5 kHz MAS is less than 1 °C. Recycle delays ranged from 4 to 48 s for  19  F experiments and 3 to 12 s for 1 H experiments, and a delay of 24 s was used for 2 H experiments. Recycle delays were adjusted to ensure all spectra are quantitative. Between 8 and 64 transients were coadded for each NMR experiment. Spectral deconvolutions were performed using dmfit software  52  and the SOLA package in Topspin software. A single peak was used to fit in-pore resonances, while either one or two peaks were used to fit each ex-pore resonance. For accurate determination of spectral intensities, spinning sidebands were taken into account using a chemical shift anisotropy model in the SOLA package in Topspin software.
The authors declare no competing financial interest. ■ ACKNOWLEDGMENTS A. C. F. , J. M. G. , C. M. , P. M. B. , H. W. , and C. P. G. acknowledge the  Sims Scholarship (A. C. F) ,  EPSRC  (via the  Supergen consortium , J. M. G. ),The  School of Physical Sciences (University of Cambridge ) for funding through an  Oppenheimer Research Fellowship  (C. M. ), The  Marie Curie FP7 International Incoming Fellowship  (P. M. B. ), and the  EU ERC  (via an  Advanced Fellowship  to C. P. G. ) for funding. A. C. F. and J. M. G. thank the  NanoDTC Cambridge  for travel funding. P. S. acknowledges support from the  European Research Council (ERC, Advanced  Grant, ERC-2011-AdG, Project  291543-IONACES ). Finally, we thank  Nicole Trease ,  Andrew Ilott ,  Phoebe Allan ,  Andrew Pell ,  Kent Griffith ,  Beth Howe ,  Wan-Yu Tsai ,  Lorie Trognko ,  Pierre-Louis Taberna ,  Yury Gogotsi ,  Alexei Kornyshev ,  Volker Presser , and  Daniel Weingarth  for useful discussions.
The as-prepared SnO 2 samples were characterized using thermogravimetric analysis coupled with mass spectroscopy (TG-SM), X-ray diffraction (XRD) and scanning electron microscope (SEM). Batch experiments were carried out to study the adsorption kinetics of Congo red azo dye, as probe pollutant, on SnO 2. The effect of varying parameters such as contact time, initial dye concentration and adsorbent dose on the adsorption process was investigated. Experimental kinetic data were tested with the pseudo-first-order and pseudo-second-order kinetic equations.
Acknowledgments The authors would like to acknowledge  University of Science and Technology Mohammed Boudiaf, Oran, Algeria , the  University   Dr. Moulay Tahar ,  Saida , Algeria  and  Unit of Catalysis and Solid State Chemistry of Lille 1 University, Lille, France  for providing the facilities to carry out this research work. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://crea tivecommons. org/licenses/by/4. 0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
The Fit2D software package (developed at the ESRF) was used for data reduction and to convert the SAXS images to plots of radially averaged scattered intensity versus wave vector q, i. e. I(q). Immediately after mixing the reagents the solutions were injected into capillaries of borosilicate, having an outer diameter of 1 mm and a wall thickness of 0. 01 mm. Capillary and background contributions have been taken into account in the peak fitting procedure. Before further analysis, X-ray data were compensated for intensity fluctuations in the incoming X-ray beam. Nevertheless, due to the beam line setup constraints, X-ray transmission could not be measured whereby the measured X-ray intensities could not be normalized.
Acknowledgements The authors kindly acknowledge the financial support from  Chalmers' Areas of Advance Energy and Materials Science, AkzoNobel ,  The Swedish Foundation for Strategic Research  ( ICA 10-0074 ), and the  Swedish Research Council  (Grant No. 2010-3519  and  2012-3897 ). The  ESRF facility in Grenoble (France)  is acknowledged for the allocation of beam time. The authors also appreciate the help from  Dr Stefan Gustafsson  for providing the TEM images,  Bruno Corso  from the  ICSM  for his help with the X-ray scattering setup, and  Dr Christel Laberty-Robert  for her valuable comments.
Study of the Possible Poisoning of the Active SCR Sites The drop in activity observed for tR = 4. 0 s could be assigned to a deposit formation on the surface of the catalyst, as mentioned in the introduction section  [24]. It would lead to unavailable reductant for NOx reduction but the reductant would appear missing in the outlet gas (then increasing the (NH3 conversion/NOx conversion) ratio). Data reported in the experimental part indicate that urea is fully thermally converted into ammonia at 200 °C between the urea injection and the analyser. It appears that it is not the case at the catalyst level for tR = 4. 0 s since the catalytic activity is changed. In order to test a possible deposit formation, the stability of adsorbed species were examined by TPD and TPO experiments. After one hour of adsorption at 175 °C under 200 ppm urea (400 ppmeq.
DFT Calculations We calculated the energy of the highest occupied molecular orbital (HOMO) of a molecule consisting of three BDT and two T2 units by using hybrid density functional theory (DFT) calculation in vacuum at B3LYP/6-31G(d) level of theory. The HOMOs  for the planar and for the twisted structure were calculated to be -4. 59 and -5. 06 eV, respectively. Calculations for the twisted structure were carried out starting from the data obtained from the crystal structure without the salt to use a simple level of DFT theory. The ionization potentials of P3 with and without NaClO 4 were measured by photoelectron spectroscopy and the ionization potential increased from -4. 8 to -5. 6 eV when sodium salts were preloaded into the thin fi lm. The larger ionization potential obtained from the PESA measurements can be explained by a charge transfer from the ligand to the sodium ions which also affects the ionization potential of the polymer.
Material and Methods In order to assess their feasibility for use in NV livestock barns, the NDIR sensors were first tested in the laboratory for linearity, variability between sensors and sensitivity to static pressure. Subsequently, the sensors were brought to the field for exposure to actual CO2 concentrations in a NV dairy cow barn, and compared with two other measuring devices: the PAS analyzer and the OP-laser. Bland-Altman charts were plotted to assess the agreement between the compared measurement techniques. A detailed description of the methods, experimental procedures and data analysis conducted to meet the objectives of this study is provided below.
5, 4. 5, 9. 0, 15. 0, 23. 0 and 33. 0 hPa. The relative pressure values (relative to room static pressure) were achieved in the laboratory by applying an overpressure inside a sealed protecting case where the sensor was housed. After full reading stabilization, sensor raw data was recorded for each static pressure level. Air temperature was kept approximately constant and equal to (24 ± 1) °C during the test. The sensitivity of the NDIR sensors to static pressure was calculated according to Equation (2): Ssp = ((Δraw)/(Avgraw×Δsp)) × 100  (2)  where: Ssp = sensitivity of the NDIR to change in static pressure (% of change in raw data per unit of pressure); Δraw = measured range of raw data (mV); Avgraw = average raw data value (mV); Δsp = measured range of pressure (hPa). To account for sensor individual variability and to allow independent direct comparison with the reference calibration gases, a two-point calibration was developed in the laboratory for every NDIR sensor.
Field Experimental Setup and Data Collection Procedure Prior to each measurement campaign, the OP-laser was installed in the barn to sample the average CO2 concentration in an open-path of 64 m along the central axis of the barn (3 m from the slats, 19 m of distance from each side). For the comparison of NDIR sensors with the OP-laser, five sensors were placed in the central axis of the barn (Figure  5 ). The central line of NDIR sensors was located at a height of 3 m above the slats, 19 m from both side walls. The distance between sensors being approximately 13 m, where the first and last sensors were 6 m away from front and back walls. Measurements with both NDIR sensors and OP-laser were taken for a minimum of 48 h per trial, with a total of six trials. To reduce the effect of sensor individual variability, five NDIR sensors were, in every trial, randomly selected from a set of 17 new sensors.
Data was downloaded from the analyzers at the end of each measurement. During every trial, three NDIR sensors were installed at the same height and next to each of the PAS analyzers' sampling ports (within a maximum distance of 0. 5 m) for simultaneous measurement of CO2 concentration. A total of three trials were performed, each lasting a minimum of 48 h. During each trial, the three used NDIR sensors were randomly selected from a pool of 17 new sensors, in order to take into account the effect of sensor individual variability. Data sets for all performed trials were pooled together prior to the statistical analyses, and hourly averaged values were calculated for each measuring device, for posterior analysis.
Analysis of Agreement between Laboratory and Field Comparison Methods The agreement between CO2 concentration data from the NDIR sensors compared to the concentration data from the OP-laser and PAS analyzer was assessed by regressing the difference between CO2 concentrations (Diff[CO2]) determined with the NDIR method and OP-laser or PAS analyzer and the average CO2 concentration (Avg[CO2]). Results were compared by using the analysis of agreement of Altman and Bland  [37] , by regressing Diff[CO2] and Avg[CO2] according to the linear model in Equation (  3  In Equation (  3 ), the intercept (βo) and the slope (β1) represent homogeneous and heterogeneous systematic bias, respectively. A test of significance for each coefficient was carried on with procreg in SAS ® (Version 9. 4, Cary, NC, USA) to assess whether βo and β1 were statistically different from zero.