dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank  J. -L. Barrat  for discussions. L. W. , E. F. , and G. S. acknowledge funding from  NSF   DMR-1608086. This work was also supported by a grant from the  Simons foundation  (No. 454933 L. B. ). L. W. and P. G. acknowledge support from the  National Natural Science Foundation of China  (No. 51571011 ), the  MOST 973 Program  (No. 2015CB856800 ), and the  NSAF joint program  (No. U1530401 ). We acknowledge the computational support from  Beijing Computational Science Research Center.
Protocol Testing and Deployment Ten sites were chosen based on latitudinal positions, known chemical characteristics, historic atmospheric data and logistical support. The characteristics for each site are described in Table  1  and the geographic distribution can be seen in Figure  2. Sites included Arctic and Antarctic stations as well as mid-latitude stations. In order to access information on long range transport of aerosols, dusts and airborne microorganisms, three sites that are frequently in the free troposphere were selected. Temporal variability is an important but poorly understood factor of microbial community diversity (e. g. ,  Bertolini et al. , 2013) , so we completed the dataset with continuous sampling for more than one entire year at a 1-week resolution at a single reference site: puy de Dôme, France.
To avoid snap-shot sampling, each site was sampled for a minimum of 2 months, so manned research sites were selected. At all sampling sites, meteorological parameters, such as wind speed and direction, rainfall, temperature, humidity, air pressure, and solar radiation were systematically recorded. Depending on the site, continuous measurements providing additional information for data interpretation were also collected. Several brands of size selective high volume air sampling instruments (TISCH, DIGITEL, home-made) were used in the present study. All these samplers are based on the same physical principle. Air was drawn into the sampler and through a large quartz fiber filter by means of a powerful pump, so that particulate material impacted the filter surface. All the samplers, but one (at Concordia station in Antarctica -DMC), were equipped with a PM10 size-selective inlet in order to collect particulate matter smaller than 10 µm (cut-off aerodynamic diameter).
The use of the PM10 inlet was an important aspect in order to guarantee that both chemical and microbial data could be compared among the sites and to prevent rain and hydrometeors from reaching the filter and modifying its porosity and air flow rate properties. At DMC, total suspended particles were collected (median aerodynamic diameter of 20 µm approx). Sampling air flow rates were between 30 and 70 m 3 /h (±2%) and collected volumes ranged from 2000 to 10000 m 3 over a 1-week period (except at DMC, where the samples were collected over a 2-week period). Flow regulation of the pump was controlled with a flow-meter that was regularly checked and calibrated. The total volume of air was subsequently corrected to standard ambient temperature and pressure (SATP, 298K, 101. 325 kPa) to standardize air collection at all the sites (Table  1 ).
CONCLUSION We developed suitable easy-to-use and standardized protocols that generated consistent microbial and chemical datasets from the same samples at concentrations high enough for confident analysis. The validity of these protocols was then tested by deploying them on 10 sites over the globe and collect samples to explore atmospheric bacteria, fungi, or viruses over large spatial scales. For large scale studies coupling chemical measurements to biological measurements, we were able to demonstrate that quartz filters can be used, but that the extraction protocols must be optimized to maximize DNA yield. In addition to using the protocol outlined here, we also recommend the following: • carefully prepare the filter and all the material using a combination of heating (500 • C) and UV treatment (254 nm).
ACKNOWLEDGMENTS We would like to thank  IPEV GMOStral 1028 and ALCHIMI 399 program. We are very grateful to  Gannet Hallar  and  Ian McCubbin  at  Storm Peak ,  Joel Savarino ,  Nicolas Caillon ,  Roxanne Jacob  for DMC samples, Benny and Jesper for the sampling at  Villum Research Station , and to  Bjarne Jensen  and  Henrik Skov  for their support,  Isabelle Jouvie  at  Amsterdam Island. We deeply thank  Ross Edwards  at  Curtin University  and  James Schauer  and  Christopher Worley  at  University of Wisconsin-Madison  for lending us a high-volume sampler. We would like to thank  Alessia Nicosia ,  Mickael Ribeiro  ( OPGC/LaMP ),  Ludovic Besaury (FRE) , and the  UMS 831 Pic du Midi Observatory team  for help with sample collection. We thank  Manuel Rocca  and  Fernando Velarde  for help at  CHC.
FUNDING This program is funded by  ANR-15-CE01-0002 -INHALE. RT-P 's doctoral grant is funded by  Région Auvergne -Rhöne Alpes. Part of the analytical equipment was supported at IGE by the  AirOSol platform within Labex OSUG@2020  ( ANR10 LABX56 ). AD and QZ were also supported by the program  CAMPUS France program XU GUANGQI  ( 38718ZC INHALE_NAMCO ). Financial support for AMS, DMC and Villum field campaigns was provided by the  French Polar Institute IPEV  (programs 1028 and 399).
The main advantage of 1D models is that the simulations are simple, easy to perform, and do not take time. The examples presented below were obtained using the Ludovic © software, initially designed to calculate the flow conditions along a twin-screw extruder  [5]. To be applied to reactive extrusion, the flow model has to be coupled with reaction kinetics and possibly a rheokinetic module, describing the change in viscosity with the extent of the reaction  [6]. This simulation was successfully applied to various reactive systems: reactive blending of polymers  [7] , extension of polyamide 12 chains by a coupling agent  [8] , controlled degradation of polypropylene  [9] , cationization of starch  [10] , synthesis of nanoparticles by sol-gel method  [11] , transesterification reaction of EVA copolymer  [12].
Few authors have studied the effect of hydrocarbons on catalytic DRM. A study conducted by Chiodo et al. [13] reported the influence of several contaminants added to clean biogas on a Ni-based catalyst. Among these contaminants, a mixture of hydrocarbons formed of ethane, ethylene, acetylene, and propylene was studied. With poisoning concentrations below 200 ppm, the catalytic performance obtained was stable for 100 h. Conversely, when a total hydrocarbon concentration of 800 ppm was added to the inlet gas stream, methane conversion was reduced by about 12% after 25 Acknowledgments: The authors would like to thank the  ULCO , the  Agence Universitaire de la Francophonie (AUF)-Région du Moyen-Orient , and the  Lebanese CNRS  for funding this project. The authors would also like to thank the  ARCUS E2D2  project, the  French Ministry of Foreign Affairs , and the  "Région Hauts de France"  for financial support.
Experimental Section Surface tension measurements were performed with ad u-Noüy ring on aD CATt ensiometer (Data Physics) at 25, 30, 40, and 50 8C. The temperature was maintained by ac irculating thermostat with prior heating of the surfactant solution in an oven and an equilibration time of 20 min. The surface tension was measured until the value remained constant for agiven period, as defined by the measurement software (typically 350 s). The measured average surface tension was determined for each in ac oncentration range from 10 À5 up to 0. 02 wt %a nd plotted as af unction of logarithmic concentration. The cmc was determined by calculating the point at which the surface tension reaches ac onstant plateau value. In addition, the surface tension measurements were used to determine the surface excess concentration (G)a nd the head group area (a 0 ) using the Langmuir-Szyszkowski isotherm  [36]  [Eq.
Acknowledgements This work has been carried out within the project " Dream Resource '' ( 033RC002C ). The project is fundedb yt he  German Federal Ministry of Education and Research (BMBF)  within the funding priority " CO 2 Plus-Stoffliche Nutzung von CO 2 zur Verbesserung der Rohstoffbasis". Covestro Deutschland AG  is much thankedf or providing thes urfactants and  M. Sebastian  and  M. Weinkraut  for input regarding this manuscript. In addition, we are gratefult o the LLB and JCNS for allocating SANS beam times. This work is based upon experiments performed at theK WS-1 instrument operated by JCNS at the  Heinz Maier-LeibnitzZ  entrum (MLZ), Garching, Germany and at the PAXY instrument at the  Laboratoire LØon Brillouin (LLB, CEA-CNRS ). Additionally,w ew ould like to thank  Professor Auhl  for the use of the MCR301Rheometer.
The 13 C NMR experiments the acquisition parameters used are 20 s repetition delay to allow complete relaxation, a 1 H π/2 pulse length of 2. 5 μs to afford 100 kHz 1 H decoupling using the SPINAL 64 decoupling method. A contact time between 1 H and 13 C was set to 8 ms. 5,000-15,000 scans were performed, the MAS frequency varied between 8 and 10 kHz. All 13 C NMR spectra were referenced to adamantane with the higher frequency peak set to 38. 48 ppm with respect to TMS (0 ppm). DNP enhancements factors (εH) of the TCE solvent were determined by comparing the integration of the resonance of interest for the spectra acquired with and without microwave irradiation. 13 C spin lattice relaxation times were measured using a saturation recovery experiment. Data are fitted using either a stretched-exponential (Formula 1) or a mono-exponential (Formula 2) with  being the equilibrium signal intensity when microwave irradiation is used, () the integrated intensity at recycle delay time  ,  being the stretching parameter and  1 * the build-up time.
Gao et al. calculated the Raman frequency for a monomeric oxide structure in this location and confirmed that it falls within the range observed experimentally  [27]. The resulting ZSM-5 model had a Si/Al ratio of 47. On the clusters one and two CO molecules were placed and their geometry optimized. All spin polarized DFT calculations were performed by using the Vienna Ab initio Simulation Package (VASP, version 5. 3. 5) [52] [53] [54] [55] [56]. The PBE functional based on the generalized gradient approximation was chosen to account for the exchangecorrelation energy  [57]. A plane-wave basis set in combination with the projector augmented wave (PAW) method was used to describe the valence electrons and the valence-core interactions, respectively  [58, 59]. The kinetic energy cut-off of the plane wave basis set was set to 450 eV.
Acknowledgements Financial support from the  Sabic-NWO   CATC1CHEM   CHIPP  project is gratefully acknowledged. Thanks go to  Dr. Christoph Dittrich  (SABIC),  Dr. Frank Mostert  ( SABIC ) and  Dr. T. Alexander Nijhuis  ( SABIC ) for helpful discussion. G. Li  acknowledges financial support from The  Netherlands Organization for Scientific Research (NWO)  for her personal VENI grant (no. 016. Veni. 172. 034 ) and  NWO-Surf SARA  for providing access to supercomputer resources. The  FAME-UHD  project is financially supported by the  French "grand emprunt" EquipEx (EcoX ,  ANR-10-EQPX-27-01 ), the  CEA-CNRS CRG consortium  and the  INSU CNRS  institute.
The litter surface was virtually divided into six equal zones, in each of which three measurements were taken, resulting in a total of 18 temperature measurements averaged to have one mean temperature data per week (except for week 1 of sub-period 1 of period 2 due to equipment failure). Gas emission measurements. Gas emissions, as well as temperature and humidity in the rooms, were continuously measured for both LM and SM from weeks 1 to 4 of each subperiod (Supplementary Table  S1 ). Once per period (after sub-period 2), in the SM treatment only, gas emissions were In the LM treatment, for each sub-period, animals were tied for the first 2 weeks (LM tied , hatched boxes) and then allowed to move freely in the free-stall barn with cubicles (LM free , empty boxes) for the last 2 weeks. In the SM treatment, cows were allowed to move freely over the whole area of the deep litter throughout the experience.
Statistical analyses In the LM tied treatment, variables related to the N balance were recorded at the individual level and averaged over the 4 days of urine and faeces collection: N intake; N excreted in milk, faeces and urine; retained and unaccounted N; urea-N content in urine, urea-N excreted in urine and N efficiency (N in milk divided by N intake). During period 2, two cows unexpectedly dried off (one per group). Only one was involved in measurements for LM tied. Considering this cow in the N balance calculation could lead to biased interpretation as no more N is exported in milk for this dried cow. All N ingested was therefore excreted in urine and faeces, modifying the repartition of N excretion. To ensure a consistent N balance at the individual level, measurements for this cow were removed from the dataset for all of period 2.
The two cows that unexpectedly dried off in period 2 could not be removed from the dataset because they continued to ingest feed and emit gases in the rooms. This can lead to biased intake and emissions results at the group level; however, as both groups were concerned, all treatments were considered to be similarly affected. In the SM treatment, gas emissions and litter temperature at a 10-cm depth were averaged per week and analysed to determine the influence of dietary treatment (LowN v. HighN), the weeks (1 to 4) and their interaction using the statistical model (SAS, 2013; PROC MIXED): Y ijkl ¼ þ Nconc i þ Week j þ Nconc Â Week k þ Group l þ e ijkl where Y ijkl is the variable studied; μ is the mean; Nconc i is the dietary CP concentration (1 df); Week j is the week of measurement for each sub-period (3 df); Nconc × Week k is the interaction of the two factors (3 df); Group l is the group of cows (1 df); and e ijkl is the error associated with each Y ijkl.
Acknowledgements This study was supported by  ADEME  ( CORTEA programme , contract no. 1160C0041 ) and the  French Ministry of Agriculture, Agro-Food and Forestry (RFI   CASDAR  project no. 1122 ). We are also grateful to the staff from the  INRA unit PEGASE , both at the experimental dairy farm and the laboratory. Finally, many thanks go to  Luc Delaby  for his valuable advice on statistics. N. Edouard ,  0000-0002-6158-0956 Declaration of interest None.
Calculations The UV/VIS absorption spectra were analyzed following the Multivariate Curve Resolution-Alternative Least Square (MCR-ALS) technique using toolboxes working in Matlab R2018b software. 28 Chemical constraints were fixed to a minimum: (1) the total amount of the metal was normalized (2) the independent UV/VIS absorption spectra do not have negative absorbance values and (3) the concentrations of the species cannot be negative. Principal component analysis (PCA) (using the same toolbox in Matlab) was performed prior to the MCR-ALS study to determine how many different species were present in the solutions and the results were compared with the literature. The results of the MCR-ALS analysis are displayed in the form of the UV/VIS absorption spectra of the independent species present in all samples containing that metal ion and of the mole fraction of all species in function of the acid or salt concentration.
Acknowledgments The financial support from the  French Environment & Energy Management Agency (Agence de l'Environnement et de la Maîtrise de l'Énergie, ADEME , PhD fellowship to GZ) is gratefully acknowledged. The authors thank  Dr A. Boos ,  P. Ronot  and  I. El-Masoudi  ( IPHC, France ) for the ICP-OES analysis.
Mechanical characteristics The pressure regulation in the cell is controlled by a hydraulic power unit, where an air-oil exchanger keeps the oil supply at a temperature set by the user. The unit provides the test sleeve with sealant oil that can reach a flow rate of 10 l/min at a controlled pressure. Oil returning from the cell is collected in a sump tank. By using this arrangement, the oil is given more time to settle in the tank in order to prevent the formation of air bubbles. The sealant tank contains a relief valve and pressure gauges to monitor the sealant supply pressure, and to guarantee a safety backup for the pressure regulators. An electric motor with an operating range of between 500 rpm and 4000 rpm is used to rotate the shaft in the system. The speed of the motor is adjusted by a regulator and monitored by data acquisition software.
FEATURE Fluent software to illustrate the influence of the sensor holes on the pressure distribution in the lubricant channel along which they were expected to be made. A velocity of 2. 5 m/s was applied to the inlet (on the left side). Data are extracted along the x axis for y = 0. 25 mm, and y = 0. 1 mm. As can be seen from the figure the disturbance induced by the holes, through which the measuring instruments pass, is of the order of 2-4 Pa, which is extremely low, and hence, negligible. Therefore, it is assumed that the measuring holes do not affect the measurements.
Control station A control station located (see Figure  2 ) near the experimental apparatus was used to control of the systems used in this experiment. The control software was written in the LabView development environment (National Instruments). During the entire signal-acquisition process, the LabVIEW program monitored, controlled, analysed and displayed the experimental results, with the data acquisition being managed by subroutines that enabled recording at an imposed frequency and sampling size. Security conditions were also incorporated into the software to stop the test-bench in the event of an anomaly. The conditions for initiating the security process are based on a critical threshold of the friction torque, pressure, supply flow-rate or average oil temperature. The userinterface for controlling the test-bench is shown in Figure  10.
Modelling The formation and the stability of Mn, Cu and V chlorides in the used reaction conditions were evaluated by modelling with HSC Chemistry 6 software. The equilibrium compositions versus temperature have been calculated by the Gibbs energy minimization method. The input concentrations corresponded to our real experimental mixture. The total concentration of the compounds was fixed to 1000 mol and the pressure used in the modelling was 1 bar. Solid phase as oxides was introduced in the modelling as input and the amounts corresponded 10 and 30 wt-%. The different cases studied are summarized in Table  1. An additional modelling was done to check the situation also when the by-products are present in the reaction mixture. However, this did not change the results of the modelling related to metal chlorides and thus they are not presented in more detail.
154184 nm) equipped with a Ni filter. LynxEye, 192 channels on 2. 95°) fast multistrip detector was used for intensity measurements. Diffraction patterns were collected at 25°C in the 4-80° 2θ range with 0. 02° 2θ step size and 2 s per increment. dwell time. TOPAS v. 4. 2 software package and ICSD database were used for the analysis of the X-ray patterns  [27]. X-ray photoelectron spectroscopy (XPS) was performed using Al Kα monochromatized source in a commercial KRATOS AXIS Ultra DLD spectrometer. XPS high resolution spectra revealed well-resolved chemical states corresponding to Fe 2p, Fe 3p, Mo 3d, Te 3d, O 1s and C 1s levels. Each core level was decomposed into a combination of Voight functions with an overall FWHM of around 1. 6 eV. In order to quantify iron species, we used Fe 3p instead of the strongest photoemission line Fe 2p.
No loss of tellurium was observed using the same technique for the iron containing catalysts. The catalysts were analyzed before and after catalytic testing, using X-ray photoelectron spectroscopy (XPS), in order to determine the oxidation state and atomic concentration of the elements at the surface as well as variation of these quantities, after catalytic testing. The results obtained are presented on Table  4  and in Fig. 3. As far as the oxidation states of the elements are concerned, Table  4  shows that in the fresh catalysts only one species of molybdenum was present, with a binding energy of 232. 4 eV (Mo3d5/2 peak) was characteristic of Mo(VI)  [34]. On the used FeMoO and MoTeO catalysts, a second contribution at 231. 7 eV could be distinguished, and by comparison with data published in the literature, assigned to Mo(V)  [34, 35].
This is in agreement with the reported phenomenology of the smoke point  [15, 16]  where the conditions close to the centerline region around the flame tip do not allow complete oxidation of soot. As a result, soot is released through the tip of the smoking flame E (see the plateau of non-zero value in the upper profile of F v for flame E in Fig. 2 ). Since the simulation of the transition from non-smoking flames to smoking ones is crucial to the control of carbonaceous nanoparticles release process from flames, the supplemental material contains the two-dimensional fields of both soot temperature and volume fraction measured in flames A-E, as an original experimental database for the validation of numerical codes.
mental fields as inputs to gain a comprehensive understanding of the radiative quenching that leads to incomplete soot oxidation, therefore soot release through the flame tip beyond the smoke point. Thus, controlling the onset of the smoke point transition to mitigate or promote carbonaceous nanoparticles release process by such flames requires numerical simulations that decently capture the radiative quenching at the flame tip. To this end, the supplemental material S1 delivered along the present study contains the two-dimensional fields of both soot temperature and volume fraction measured. Such a dataset constitutes new high-quality experimental data for validation of soot models to complement existing temperature and soot volume fraction data taken in laminar non-premixed flames under conditions below the smoke point.
4 Fields 40 5 440 mental fields as inputs to gain a comprehensive understanding of the radiative quenching that leads to incomplete soot oxidation, therefore soot release through the flame tip beyond the smoke point. Thus, controlling the onset of the smoke point transition to mitigate or promote carbonaceous nanoparticles release process by such flames requires numerical simulations that decently capture the radiative quenching at the flame tip. To this end, the supplemental material S1 delivered along the present study contains the two-dimensional fields of both soot temperature and volume fraction measured. Such a dataset constitutes new high-quality experimental data for validation of soot models to complement existing temperature and soot volume fraction data taken in laminar non-premixed flames under conditions below the smoke point.
ACKNOWLEDGMENTS: XRD measurements, N2 adsorption-desorption isotherms,  X-Ray  fluorescence, SEM, and TEM analysis were performed on the technical platforms of IS2M. The authors are very grateful to  NOUALI Habiba ,  MICHELIN Laure ,  JOSIEN Ludovic  and  VIDAL Loic  for their assistance. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Instrumentation Electropolymerisation of the electrodes and electrochemical measurements were performed using the Auto LAB potentiostat/galvanostat (Eco Chemie B. V. ) in conjunction with General Purpose Electrochemical System (GPES) software and Frequency Response Analyzer (FRA) software (Eco Chemie B. V. ) for electropolymerisation/cyclic voltammetry (CV) and electrochemical impedimetric measurements respectively. A portable impedimetric reader system was developed for the microfluidic cartridge with IDE array but a separate connector frame was designed and fabricated for the preliminary measurements and for the biofunctionalisation processes. The connector frame included two red LEDs (powered by a 9V battery) to allow quick connection and accurate alignment of the microfluidic cartridge with the spring-loaded connector pins (Figure  1A ) with the AUTOLAB system for the polymerisation process and analysis of the functionalised bio-layer.