dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements. We wish to thank  Philipp Assmy ,  Greta Fryxell ,  Dimitri Gutiérrez ,  Patrick Holligan ,  Catherine Jeandel ,  Ian Joint ,  Kalliopi Pagou ,  Sergey Piontkovski ,  Tatjana Ratkova ,  Ralf Schiebel ,  Mary Silver ,  Paul Tett ,  Jahn Throndsen  and  Paul Wassmann  for granting permission to use and redistribute coccolithophore data, the BODC, JGOFS, OBIS,  OCB-DMO, PAN-GAEA ,  WOD09  and the  Observatoire Océanologique de Villefranche databases  for providing and archiving data,  Erik Buitenhuis  for producing the gridded dataset,  Scott Doney  for assistance with the quality control procedure and  Stéphane Pesant  for archiving the data. The research leading to these results has received funding from the  European Community 's  Seventh Framework Programme  ( FP7 2007-2013)  under grant agreement number (238366).
1 NMFS-COPEPOD: National Marine and Fisheries Service -The Coastal & Oceanic Plankton Ecology, Production, & Observation Database; BODC: British Oceanographic Data Centre; OBIS: the Ocean Biogeographic Information System; OCB DMO: Ocean Carbon and Biogeochemistry Coordination and Data Management Office; Pangaea: Data Publisher for Earth and Environmental Science; WOD09: World Ocean Database 2009; OOV: Observatoire Océanologique de Villefrance-sur-Mer.
This method is applied here to Infrared Atmospheric Sounder Interferometer (IASI) observations for the period from July 2007 to December 2011. Compared to AIRS, IASI has the advantage of a higher spectral resolution (0. 50 cm -1 apodized), being constant throughout the whole spectrum, and of a full coverage of the spectral domain, allowing the selection of channels more specific to the variable considered. Its drawback is a larger noise at short wavelengths which may be overcome by averaging a few adjacent and radiatively similar channels. Data and method are described in Sect. 2. Section 3 presents the results from IASI and comparisons with other aerosol products. For the AOD, these products are derived from the Moderate Resolution Imaging Spectro-radiometer (MODIS/Aqua and Terra), from the Multi-angle Imaging SpectroRadiometer (MISR), from the Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL), and from the AErosol RObotic NETwork (AERONET).
Data In addition to IASI, the core instrument of this study, several other space-based instruments and their aerosol products have been used for the purpose of comparison and validation: MODIS, MISR and PARASOL, all measuring visible AOD and, therefore essentially sensitive to the fine mode. CALIOP, which is also part of the A-train, provides a measure of the aerosol vertical distribution. Developed by CNES in collaboration with EUMETSAT, the IASI instrument  (Chalon et al. , 2001 ; http://smsc. cnes. fr/IASI), onboard the MetOp-A polar platform, is a Fourier Transform Spectrometer that measures Earth-emitted infrared radiation. Launched in October 2006 (operational since July 2007), it provides 8461 spectral channels, between 15. 5 µm and 3. 63 µm, with a spectral resolution of 0. 50 cm -1 after apodisation and a regular spectral sampling interval of 0.
25 cm -1. Metop-A crosses the Equator at 9:30 p. m. on its ascending node. IASI provides a near global coverage twice a day at a spatial resolution of 12 km at nadir. MODIS (http://modis. gsfc. nasa. gov/) is an imaging radiometer flying on board the Terra platform since December 1999 and on board the Aqua platform since May 2002. Its data products are widely used in the aerosol community  (Tanré et al. , 1997; Remer et al. , 2005 Remer et al. , , 2008)). Aqua (Terra) crosses the Equator at 01:30 a. m. (10:30 a. m. ) on its descending node. Aqua (Terra) crosses the Equator at 01:30 a. m. (10:30 a. m. ) on its descending node. This temporal shift with IASI is not significant at the monthly scale. Here, we use the Level 3 monthly products (total and fine mode) from Terra, which provide the optical depth reported at 550 nm at a spatial resolution of 1 • ×1 • (see: http://disc.
sci. gsfc. nasa. gov/giovanni/overview/index. html). MODIS fine mode AOD is obtained by multiplying the total AOD by the fine mode fraction. We have verified that no significant differences are observed between Terra and Aqua, at least at the monthly scale considered here. MISR (http://www-misr. jpl. nasa. gov; Diner et al. , 2002) , flying on board the Terra platform since December 1999, views the sunlit Earth simultaneously at nine widely spaced angles. The MISR Level 3 global data products are reported on a rectangular grid 0. 5 • by 0. 5 • degree. Here, use is made of the AOD reported at 555 nm. Launched in December 2004, PARASOL carries a POLDER-like (Polarization and Directionality of the Earth's Reflectances) wide field radiometer. The instrument  (Deschamps et al. , 1994)  measures the polarized light in different directions for retrieving aerosol and cloud optical and physical properties  (Tanré et al.
The subset of CALIOP data resulting from this selection represents about 65 % of all CALIOP data where aerosol layers are detected (see Pey2010 for more details). Contrary to CALIOP, the IASI dust retrieval algorithm outputs the mean altitude of the whole dust layer, i. e. the altitude at which half of the AOD is below and half of the AOD is above, with low sensitivity to a complex layering of the dust. Finally, IASI-retrieved 10 µm AOD and coarse mode effective radius are compared to AERONET (see, for example,  Dubovik et al. , 2002)  visible AOD (550 nm) and coarse mode radius for several sites of the northern tropical Atlantic and one site of the Arabian Sea.
Use is made of the MITR aerosol model from the OPAC database  (Hess et al. , 1998). Maps of the aerosol 10 µm IASI AOD over the Atlantic Ocean illustrate the main patterns of dust transport: during the May-September dust season, a fast westward decrease of the optical depth is observed, from about 0. 2 at the African coast to about 0. 1 at ∼55 • W. This value remains approximately constant up to the Caribbean. MODIS, MISR and PARASOL visible AODs at 550 nm confirm these results. Comparisons at regional scale (three regions of the northern tropical Atlantic: East Atlantic (EA), Mid-Atlantic (MA), West Atlantic (WA) and one region of the Arabian Sea (AS)) show a good agreement between IASI and the other instruments either during the summer peak of the dust season or outside of it. Differences between IASI AODs and the properly scaled (see Sect.
Finally, CNES has begun feasibility studies on a new-generation atmospheric sounding interferometer (IASI-Next Generation) to be flown aboard the second-generation MetOp satellites. IASI NG will improve the IASI performances by a factor of two in both the spectral resolution and radiometric noise, leading to major improvements in the accuracy of retrieved aerosol characteristics: AOD, altitude, and, particularly, effective radius. Acknowledgements. MODIS and MISR data were obtained through NASA Giovanni, an online visualisation and analysis tool maintained by the Goddard Earth Sciences (GES) Data and Information Services Centre (DISC). PARASOL data have been extracted from the archive maintained by the ICARE datacenter (http://www. icare. univ-lille1. fr/). We thank the PI investigators and their staff for establishing and maintaining the AERONET sites used in this investigation.
We are also happy to thank the ICARE Thematic Centre for providing us with CALIPSO/CALIOP data (http://www. icare. univ-lille1. fr/). This work has been supported in part by the European Community under the Grant Agreement no. 283576 (MACC project) and by CNRS, CNES and Ecole Polytechnique. We have also benefited from the large facilities of IDRIS, the computer centre of CNRS.
1258, 1756, 2411, 3254, 4116, 4965, 5795 757, 1258, 1756, 2411, 3254, 4116, 4965, 5795 Radii values (µm) N/A 2. 3 (R eff ) or 3. 0 (r modV ) 0. 5, 0. 8, 1. 0, 1. 5, 2. 0, OPAC/MITR 2. 5, 3. 0, 4. 0, 5. 0 selected at 9. 315 µm and for the values of the dust infrared optical depth, mean altitude and R eff of Table 1, using a monomodal lognormal size distribution. In order to simulate IASI brightness temperatures (BT) for the different effec- tive radii, the optical properties were calculated using a Mie code (Mishchenko et al. , 2002 and ftp://ftp. giss. nasa. gov/ pub/crmim/spher. f) and the refractive indices of the "Mineral Transported" (MITR) aerosol model from the "Optical Prop- erties of Clouds and Aerosols" (OPAC) database.
Tips were then transferred to PBS buffer supplemented with 1 mg/ml BSA (PBS-B) for subsequent antibody binding studies. C9 was prepared as a twofold serial dilution (starting at 20 mg/ml) plus buffer blanks. Antibody association was measured for 5 minutes followed by a 50 minute dissociation in buffer. Non-specific binding was assessed using sensor tips without VLPs. Data analysis was performed using Octet Data Analysis v6. 4 (ForteBio, Menlo Park, CA). Binding kinetics were analyzed using a standard 1:1 binding model.
mAbs were detected using 3. 75 mg/ml AlexaFluor488-conjugated secondary antibody in 10% NGS (Jackson ImmunoResearch Laboratories) for 1 h. Mean cellular fluorescence was detected using the Intellicyt high throughput flow cytometer (HTFC, Intellicyt). Antibody reactivities against each mutant Env clone were calculated relative to wild-type env protein reactivity by subtracting the signal from mock-transfected controls and normalizing to the signal from wild-type Env-transfected controls. Mutations were identified as critical to the epitope if they did not support reactivity of the test human mAb, but did support reactivity of the other CHIKV antibodies. This counter-screen strategy facilitates the exclusion of env mutants that are misfolded or have an expression defect  [34]. Critical amino acids required for antibody binding were visualized on CHIKV env crystal structures (monomer PDB ID #3N41 and trimer PDB ID #2XFC,  [15] ), to obtain 3D epitope maps.
Arthritis was monitored by measuring the height and width of the metatarsal area of the hind feet using digital calipers  [35]. The data is presented as a group average of the percentage increase in foot height6width for each foot compared with the same foot on day 0. Viremias were measured by collecting 40 ml of blood from a tail vein into 0. 8-ml MiniCollect serum separation tubes (Greiner Bio-One GmbH, Kremsmunster, Austria). The tubes were spun at 4,0006g for 2. 5 min on a bench-top microcentrifuge. Serum was collected and viral titers were determined as described previously and expressed as CCID 50 per ml  [35].
Potent in vitro neutralization C9 and E8 were tested in neutralization assays performed in HEK 293T cells using CHIKV pseudoviruses bearing an envelope from the prototypical West African, Asian, and East/Central/ South African (ECSA) CHIKV strain, S27. The C9 and E8 IgG antibodies neutralized CHIKV pseudoviruses at approximately 0. 1 mg/ml and 1. 0 mg/ml (IC 50 ) respectively (Figure  1 ). Pseudoparticles produced using envelopes derived from the LR2006 OPY-1 strain from the La Reunion outbreak were similarly sensitive to neutralization, with IC 50 values of 0. 4 mg/ml and 10 mg/ml for C9 and E8 respectively (Figure  S1 ). Similar neutralization was observed regardless of the cell type used (data not shown). Neutralization was specific to CHIKV, with no detectable cross-reactivity to pseudoviruses expressing other alphavirus envelopes from RRV, SFV and SINV, as well as VSV-G (Figure  1 ).
Binding properties of anti-CHIKV human mAbs In order to determine how strongly each mAb interacts with the native virion, intact CHIKV VLPs were captured onto the surface of ForteBio Octet RED biosensor tips (ForteBio, Menlo Park, CA) and antibody binding to the immobilized particles was measured using BioLayer Interferometry (ForteBio, Menlo Park, CA). Whereas C9 bound to VLPs with an apparent affinity of 1. 2 nM (Figure  2A  & B), E8 failed to recognize CHIKV envelope protein on intact VLPs (data not shown), suggesting that the E8 epitope may be occluded in the native E1/E2 conformation on virions. This finding is consistent with the inability of E8 to neutralize live CHIKV. C9 and E8 antibodies recognized envelope derived from CHIKV VLPs under semi-native conditions (protein run in SDS-PAGE gels without reducing agent), suggesting that both C9 and E8 recognize conformation specific epitopes that are dependent on disulfide bonds (Figure  S2 ).
(C) The critical residue A162 (shown in green) was visualized on the CHIKV env crystal structure. The E1, E2, and E3 env protein subunits in the monomer (PDB Entry #3N41) are depicted in yellow, red, and blue, respectively and the fusion loop is shown in silver (left panel). In the side-view and top-down trimeric representations (center and right panels, PDB entry #2XFC), E3 is not in the structure. In the side view trimeric representation (center panel), the viral membrane is positioned at the bottom of the figure. doi:10. 1371/journal. pntd. 0002423. g004.
Acknowledgments The authors acknowledge  Bridget Puffer  for assistance in phage display library construction,  Simona Jusyte  for assistance with phage display library panning,  Surabhi Srinivasan  and  Nick DiStasio  for assistance with epitope mapping,  Joe Couto  and  Silveria Rodriguez  for DNA plasmid engineering and construction, and  Dr. Marina Fomin  for mouse breeding. The authors would like to thank  James Robinson  ( Tulane University ) for advice and reagents for B-cell cloning. We also thank  Dendritics  for kindly providing an anti-CHIKV monoclonal antibody and  IBT Bioservices  for provision of the rabbit anti-CHIKV polyclonal antibody.
In this paper, we present a HARMonized dataset of OZone profiles (HARMOZ) based on limb and occultation measurements from Envisat (GOMOS, MIPAS and SCIAMACHY), Odin (OSIRIS, SMR) and SCISAT (ACE-FTS) satellite instruments. These measurements provide high-vertical-resolution ozone profiles covering the altitude range from the upper troposphere up to the mesosphere in years 2001-2012. HARMOZ has been created in the framework of the European Space Agency Climate Change Initiative project. The harmonized dataset consists of original retrieved ozone profiles from each instrument, which are screened for invalid data by the instrument teams. While the original ozone profiles are presented in different units and on different vertical grids, the harmonized dataset is given on a common pressure grid in netCDF (network common data form)-4 format.
The pressure grid corresponds to vertical sampling of ∼ 1 km below 20 km and 2-3 km above 20 km. The vertical range of the ozone profiles is specific for each instrument, thus all information contained in the original data is preserved. Provided altitude and temperature profiles allow the representation of ozone profiles in number density or mixing ratio on a pressure or altitude vertical grid. Geolocation, uncertainty estimates and vertical resolution are provided for each profile. For each instrument, optional parameters, which are related to the data quality, are also included. For convenience of users, tables of biases between each pair of instruments for each month, as well as bias uncertainties, are provided. These tables characterize the data consistency and can be used in various bias and drift analyses, which are needed, for instance, for combining several datasets to obtain a long-term climate dataset.
Introduction The creation of homogenized ozone profile datasets based on limb or occultation measurements from sensors on board the European Space Agency (ESA) Envisat satellite, as well as from ESA Third Party Missions (TPM), is one of the primary objectives of the European Space Agency Climate Change Initiative project (Ozone_cci, http://www. esa-ozone-cci. org). Six instruments that provide long-term measurements are involved in this project. Three of them are on board Envisat: Global Ozone Monitoring by Occultation of Stars (GOMOS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and Scanning Imaging Spectrometer for Atmospheric Chartography (SCIAMACHY); two of them are on board Odin: Optical Spectrograph and InfraRed Imaging System (OSIRIS) and Sub-Millimeter Radiometer (SMR), and one is on board the SCISAT-1 satellite: Atmospheric Chemistry Experiment -Fourier Transform Spectrometer (ACE-FTS).
Three of the instruments -GOMOS, SCIAMACHY and OSIRIS -retrieve ozone profiles from measurements in the UV-visible wavelength range. MIPAS and ACE-FTS use infrared wavelengths, and SMR operates at sub-millimeter wavelengths. Two of the instruments use the occultation technique: GOMOS uses stellar occultation and ACE-FTS performs solar occultations. SCIAMACHY and OSIRIS are limb-scattering instruments; MIPAS and SMR measure thermal emission spectra. More details on individual datasets are presented in Sect. 3. Overall, the datasets cover the years 2001-2012 (not all instruments cover the whole time period). The yearly data volume for the HARMOZ instruments is illustrated in Fig. 1. Between the various datasets, there are ozone measurements available for all seasons, various times of day, and good latitudinal coverage (as an example, Fig.
2  illustrates the latitudinal coverage in 2008). The data from different sensors have different properties such as specific quality flags, and the data can have outliers due to problematic retrievals under some conditions. In some cases (like for GOMOS), ozone data quality strongly depends on a set of parameters, which makes using this dataset complicated for non-experts. As a first step towards data homogenization, we have created a HAR-Monized dataset of OZone profiles (HARMOZ). HARMOZ consists of independent datasets from individual instruments, which are carefully screened for outliers, interpolated to a common pressure grid and saved in the common netCDF (network common data form)-4 format. This database is used in various "higher-level" analyses performed within the Ozone_cci project (in particular, in creating Level 3 data, see the Ozone_cci web page http://www.
esa-ozone-cci. org/ ?q=node/160 for details). Convenience of using the harmonized dataset has prompted us to make this dataset available to the scientific community. This dataset contributes to the initiative on past changes in the vertical distribution of ozone (SI 2 N (SPARC -Stratospheric Processes and their Role in Climate, IO 3 C -International Ozone Commission, IGACO-O 3 -Integrated Global Atmospheric Chemistry Observations, NDACC -Network for the Detection of Atmospheric Composition Change) initiative, http://igaco-o3. fmi. fi/VDO/working_groups. html). The paper is organized as follows. Section 2 presents a general description of the dataset and the data processing. Each dataset has mandatory parameters, which are the same for all instruments (discussed in Sect. 2), as well as optional, instrument-specific parameters (discussed in Sect.
General description of the harmonized dataset The individual datasets from each instrument passed quality control, which has been performed by the instrument experts. The quality control procedures are described in detail in Sect. 3. Only valid data are included in HARMOZ. Each profile has been interpolated onto a common pressure grid (Ozone_cci pressure grid hereafter), which is an extension of the SPARC Data Initiative pressure grid  (Hegglin and Tegtmeier, 2010; Tegtmeier et al. , 2013). The Ozone_cci pressure levels and the corresponding pressure altitudes are presented in Appendix A. The vertical spacing of the Ozone_cci grid corresponds to ∼ 1 km below 20 km and ∼ 2-3 km above. The number of pressure levels included in the individual datasets depends on the valid altitude range of the ozone profiles.
For example, GOMOS data are provided on the Ozone_cci grid in the range 250-10 -4 hPa, while MIPAS data are provided in the range 400-0. 05 hPa. The altitude range of the individual datasets can be found in Table  1  and is illustrated in Fig. 3. The largest altitude range is achieved for occultation instruments, which cover also the lower thermosphere. The data files contain the mandatory variables that are the same for all sensors. The main variables are profiles of ozone concentrations (moles cm -3 ) and their uncertainties. The auxiliary information includes temperature and altitude profiles at the measurement locations for converting ozone data to different units (mixing ratio/number density on pressure/altitude in all possible combinations), as well as geolocation, time, and vertical resolution.
Note also that the Ozone_cci grid is finer than the vertical resolution of the ozone profiles, therefore the uncertainties at adjacent layers are correlated. Without covariances provided, there is the risk to overestimate the independent information contained in the profiles. For some of the instruments, there exist "advanced" versions of HARMOZ files with full covariance matrices C stored. These data can be provided upon request. Three instruments (GOMOS, SCIAMACHY and OSIRIS) provide ozone number density profiles, thus the conversion to concentration (moles cm -3 ), the unit used in HAR-MOZ, is simply division by the Avogadro constant N A = 6. 02214 × 10 23 moles -1. MIPAS, ACE-FTS and SMR retrieve ozone mixing ratio profiles. For MIPAS and ACE-FTS, the retrieved temperature and pressure profiles were used for conversion to HARMOZ ozone concentration representation, thus making it fully consistent with the original mixing-ratio profiles.
For SMR, temperature profiles are taken from the ECMWF fields. Therefore, small (∼ 0. 1 %) drifts and jumps in the ECMWF density (which can be caused, for example, by different amounts of assimilated data over time, http://www. ecmwf. int/research/era/do/get/index/ QualityIssues) can induce an additional uncertainty of the same magnitude in SMR ozone concentrations reported in HARMOZ.
GOMOS GOMOS is a stellar occultation instrument on board Envisat  (Bertaux et al. , 2010; Kyrölä et al. , 2010). Ozone profiles are retrieved from UV-visible spectrometer measurements at wavelengths 250-692 nm. In this dataset, nighttime ozone profiles (solar zenith angle larger than 105 • ) processed with the IPF version 6 processor are used. GOMOS provides stratospheric ozone profiles with vertical resolution of 2-3 km and estimated precision of 0. 5-5 %  (Tamminen et al. , 2010). GOMOS data were filtered for outliers and unreliable data using the recommendations of the readme document http://earth. eo. esa. int/pcs/envisat/gomos/documentation/ RMF_0117_GOM_NL__2P_Disclaimers. pdf. In addition, we have excluded occultations terminated above 40 km. The stellar flux recorded by GOMOS, and thus signal-tonoise ratio and precision of retrieved profiles, depends on stellar magnitude and spectral class.
The GOMOS optional parameters include the star identification number in the GO-MOS catalogue (the smaller the star number, the brighter the star), as well as the information about the star's visual magnitude and effective temperature. Note that occultations of stars with insufficient UV flux (dim and cool stars), which cannot provide information about ozone in the upper stratosphere, are not included in the harmonized dataset. In the previous GOMOS processor, IPF version 5, ozone retrievals from dim and cool stars were problematic also in the stratosphere due to inaccurate dark charge correction and low signal-to-noise ratio (e. g. ,  Keckhut et al. , 2010). The quality of ozone profiles in such occultations in the version 6, which uses a more advanced dark charge correction method, is still under evaluation.