dataesr/scientific-paragraphs-categorization huggingface dataset:
Isabel Carrera Suarez's comparative study of short story women writers  (Oviedo, 1988)  is the first to adopt a transnational approach to women's literature, combining postcolonial and gender theory. Mercedes Bengoechea Bartolomé's work on Adrienne  Rich (Madrid, 1991)  opens the productive 1990s with a study of language and gender. This new decade brings a dramatic rise in the number of theses combining Anglicist and Gender Studies, a figure which has grown steadily up to the present. According to TESEO, the official database of doctoral theses of the Spanish Ministry of Education, these theses have been submitted in 30 out of 40 Spanish universities that either have degrees in English Studies, English departments or have incorporated these studies and research into other structures, like Translation or Humanities degrees, or interdisciplinary postgraduate programmes.
10 he Gender and Sociology Department at the Czech Academy of Science 11  has been most active in promoting research on gender issues and feminist theory and efficient in obtaining financial support from abroad, especially from EU-funded research grants. In her exploration of the post-2000 development of gender studies in the Czech Republic, Hašková emphasizes the role of the Gender and Sociology Department in publishing the journal Gender, rovné příležitosti, výzkum [Gender, Equal Opportunities, Research], but simultaneously warns that the existence of the journal, which is 'entirely dependent on grant support'  (Hašková 2011: 141) , is seriously jeopardized. Further, Hašková highlights the establishment of the National Contact Centre for Women in Science, funded by the Czech Ministry of Education, Youth, and Sports, and argues that the Centre's research and focus on gender equality significantly contributes to meeting the EU requirements placed on national governments (142).
e. 7 out of 30 universities offering philology study programmes. As has been seen, the bravest of these departments, the one in Timişoara, set up one of the three MA programmes in the country through its Interdisciplinary Centre for Gender  Studies (2004). However, with the exception of the SNSPA one, MA programmes in gender studies have so far not fared well in Romania, and moreover Romanian universities have been reluctant to join in the transnational European programmes MATILDA, the European MA programme in Gender and Women's History, and ATHENA: the European Network for Gender Studies, although they have profited from their experience, participated in their conferences and contributed to their databases. Outside the institutional confines of dedicated study programmes, women's and gender studies flourish in Romania.
27 Al,  11  B and  23  Na spectra were acquired with single pulse excitation of short lengths (1usec, tip angle ~10-20°) to ensure quantitatively and with recycle delays ensuring a full relaxation of the nuclear spins (0. 5s for  23  Na and  27  Al, 2s for 11 B). Multiple Quantum MAS (MQMAS) spectra were collected using the Z-filter pulse sequence (for  27  Al) or the RIACT (II) pulse sequence for  23  Na and 11 B 26. For  29  Si, the CPMG pulse sequence has been employed, coadding echoes, followed by Gaussian apodization of 100 Hz before Fourier Transform Data were processed and fitted with an in-house written code  26. Other experimental data are gathered in the Supplementary Information. For purpose of comparison, spectra collected on the pristine and heavy Ion (Xe and Au) irradiated ISG glasses are also presented.
Acknowledgements The authors thank the  European Commission Euratom   FP7  funded project (no 269923) EURACT-NMR for support under grant  RP02/05  -Radiation damage in nuclear glass. This work was also carried out under a research program funded by  CEA  and  AREVA NC. T. C. thanks the  European Commission  for its grantholder position at  JRC-ITU  ( 06-09/2013 ). Authors are thankful to  Chris Selfslag  for is support with the NMR experiments.
ment (ACE) provides seasonal global distribution in the upper troposphere (e. g. , González  Abad et al. , 2009). The data used in this study are provided by IASI. This instrument has two important advantages: a low radiometric noise and a high spatial coverage. HCOOH is a weak absorber, so it is a challenge to retrieve total columns from the IASI radiance. Global distributions of HCOOH over land were initially derived using a method based on brightness temperature difference and using forward simulations  (Razavi et al. , 2011). More recently, R  'Honi et al. (2013)  developed a specific method to study extreme events occurring during the large fires in Russia during the summer 2010. These studies, however, highlighted discrepancies between the retrieved distributions and especially within enriched HCOOH air masses as, for instance, over large forest fires.
The spectroscopic parameters were from the HI-   et al. (2007). The retrievals have been done with the same a priori profile as in  Razavi et al. (2011)  but with a loose constraint (350 %). The reference channels used for the calculation of T b were chosen on both sides of the HCOOH channel (1105 cm -1 ), i. e. , at 1103. 0 and 1109. 0 cm -1. In the OEM-based retrieval, only cloud-free scenes (when the cloud coverage for the pixel is below 2 %) have been used. The total columns of interfering species in the studied spectral range, such as ozone, ammonia, and CFC-12, in addition to the partial columns of water vapor, were retrieved simultaneously. The details of the retrieval parameters are given in Table  2. The EUMETSAT L2 operational data were used, and daytime and nighttime data with a positive thermal contrast (TC) were taken into account.
(2011)  only averaged data in a 0. 5 • × 0. 5 • grid with TC higher than 5 K were considered. This implies that only data with a strong signal were used, probably overestimating the threshold of the T b and thus also the retrieved columns. Yearly global distributions between 2008 and 2014 with the updated data set are also presented in Fig. 8 (on a 1 • × 1 • grid). These distributions highlight well the recurring source regions detected by IASI such as equatorial Africa, northern Australia, Amazonia, and India, as well as the longrange transport such as over the Atlantic Ocean from Africa. The long-range transport over oceans (Atlantic, Indian, and Pacific) was not investigated in  Razavi et al. (2011). The retrieved columns over the Atlantic Ocean are consistent with the Fourier transform infrared spectroscopy (FTIR) data from ship cruises reported in the study of  Paulot et al.
Comparison with ground-based FTIR measurements The IASI HCOOH retrieved columns in this work have been compared with ground-based FTIR measurements. This comparison was done without smoothing the data since the averaging kernels (AKs) were not provided by our retrieval method. This comparison is presented at four sites: Jungfraujoch (46. 55   9 ). The current retrieved columns have also been evaluated with those using the methodology from  Razavi et al. (2011)  over the same sites (Fig. 10 ). A complete description of the FTIR instruments and the retrieved HCOOH data can be found in  Zander et al. (2010) ,  Paton-Walsh et al. (2005) , and  Vigouroux et al. (2012)  for the Jungfraujoch, Wollongong, and Saint-Denis stations, respectively. For the Jungfraujoch, spectra were typically recorded at spectral resolutions of 0.
004 and 0. 006 cm -1. For the present subset, a mean signal-to-noise ratio (SNR) of 895 was computed, with 10th and 90th percentiles of 525 and 1525, respectively. A uniform scaling of the HCOOH a priori was performed, and no information was available regarding the sensitivity of the retrieval with altitude. For Wollongong, the spectral resolution was 0. 004 cm -1 and the SNR was around 1000-2000. Over La Réunion, the HCOOH retrieval parameters were the same for Saint-Denis and for the more recent data at the Maïdo station. The spectral resolution of La Réunion spectra was 0. 007 or 0. 011 cm -1 , depending on the time of the measurement. The SNR was about 1000-2000 depending on the spectra. The current IASI retrieved columns were also compared with a set of columns retrieved by OEM around the sites.
(2012)   for each data set. These AKs and the Jacobians show that FTIR and IASI were both mostly sensitive to the free troposphere but that the FTIR measurements presented a broader vertical sensitivity, reaching higher altitudes than IASI. A difficulty in comparisons of satellite columns with ground-based measurements over mountain sites like Jungfraujoch over the Swiss Alps (3. 6 km altitude) or Maido at La Réunion (2. 2 km altitude) is the difference of altitude between the FTIR sites and the co-located IASI ground pixel height. To account for the altitude dependence, both the IASI and the FTIR total columns were normalized to the sea level altitude using C corrected = C × exp(H /7. 4), (3) where H represents the ground measurement height (in km) and C is the total column (in 10 16 molec cm -2 ).
This simplified formula is a variation of the hypsometric equation  (Wallace and Hobbs, 1977). This normalization relies on the assumption that the HCOOH mixing ratio is constant as a function of altitude. Although crude, this procedure improved the comparisons. The time series of the IASI and FTIR columns over the selected sites are shown in Fig. 9. The comparison used IASI data collocated within 0. 5 • of the site location in both latitude and longitude. To keep enough IASI data to compare, daily averages were used. A more stringent criterion of ±2 h was tested but provided similar results, except over Maido where the correlation increased to 0. 6 without improvement of the bias. The advantage of this daily average is the possibility to derive the seasonal variation over each site. Over all sites, the broad patterns of seasonal and interannual variations were similarly captured by IASI and the ground-based FTIR.
The comparison between the ground-based measurements and the total column derived from the IASI spectra may be affected by sampling differences associated, e. g. , with cloudiness. IASI may be able to measure through clear skies in the vicinity of the station when the FTIR data are not available due to localized cloud. Moreover, despite the use of strict co-location criteria (spatial and temporal), most mismatches in peak values could be a result of mismatches in the spatial and temporal scales of the measurements being compared. The correlation coefficients and the biases between FTIR and IASI are also provided for each year in Table  3. Over Jungfraujoch (Fig. 9 ), large total columns were measured by the ground-based instrument during the spring and the summer for each year. These large values were not captured by IASI data, causing a large bias of 1.
Comparison with IMAGESv2 The IMAGESv2 global CTM runs at 2 • resolution in latitude and 2. 5 • resolution in longitude. The model is resolved at 40 vertical levels, from the surface up to 44 hPa  (Stavrakou et al. , 2011). The biogenic emissions of isoprene (believed to be the most important precursor of HCOOH) were obtained from MEGAN-MOHYCAN  (Stavrakou et al. , 2014). The vegetation fire emissions were from GFEDv3 (van der  Werf et al. , 2010). This data set distinguished emissions from savanna, woodland, forest fires, agricultural waste burning, peatlands, deforestation, and degradation fires. Anthropogenic emissions were constructed from a mix of inventories: REASv2 in Asia  (Kurokawa et al. , 2013) , NEI in USA (from www. epa. gov/ttnchie1/trends/), EMEP (obtained from www. ceip. at/webdab-emission-database/ emissions-as-used-in-emep-models/) in Europe, and the RETRO database  (Schultz et al.
Conclusions Global distributions of HCOOH were derived from IASI radiance spectra, using conversion factors between representative retrieved total columns and selected radiance channels ( T b ). This paper presents 7 years of HCOOH measurements recorded by IASI. A limitation of this data set is its lack of characterization for vertical sensitivity due to the conversion technique used, even though the maximum sensitivity is shown to be in the mid-troposphere. This approach has the significant advantage of reducing the computing time necessary to analyze large amounts of data and to provide a global representation of the HCOOH distribution around the world, including ocean and land scenes, and emission sources as well as remote areas. IASI provides global distributions of HCOOH, highlighting the long-range transport of tropospheric HCOOH over the Atlantic Ocean and the detection of source regions, e.
75 to 0. 94. This comparison also points out a misrepresentation of the distribution between IASI and the CTM over India and Africa and a global underestimation of the distribution by the CTM. A small decreasing trend during the 7-year period is observed over Siberia, while a small increase is noted over India, Amazonia, and Australia (0. 7, 0. 9, and 1. 5 % year -1 , respectively). The HCOOH columns from IASI will require further evaluation and probably improvements to narrow down the biases but the data set available now spans 7 years and it will likely contribute to a better understanding of the tropospheric HCOOH budget. The data set will be made available through the Ether database (http://ether. ipsl. jussieu. fr) for further scientific studies. This 7-year record will be completed by the data provided by IASI/MetOp-B, launched at the end of 2012, and IASI/MetOp-C, to be launched in 2018.
Acknowledgements. IASI was developed and built under the responsibility of  Centre National des Etudes Spatiales (CNES)  and flies onboard the MetOp satellite as part of the EUMET-SAT Polar system. We thank the  Aeris data infrastructure  (http://www. aeris-data. fr/)for providing access to the IASI L1C data and to the ECCAD emission inventories used in this study. The French scientists are grateful to  CNES  for financial support. We also gratefully acknowledge  Yasmina R'Honi  and  Lieven Clarisse (ULB)  for their help with the HCOOH retrieval. The authors would like to thank the other researchers involved in the ground-based solar remote sensing program at Wollongong (including  Nicholas B. Jones ,  David Griffith ,  Nicholas Deutscher , and  Voltaire Velazco ) and the  Australian Research Council  for its support for the NDACC site at Wollongong, most recently as part of project  DP110101948.
Acknowledgements are addressed to the  Université de La Réunion  and  CNRS  ( LACy-UMR8105  and  UMS3365 ) for their support of the  OPAR station (Observatoire de Physique de l'Atmosphère de la Réunion ). The authors gratefully acknowledge  C. Hermans ,  F. Scolas , and  B. Langerock  from  BIRA-IASB , and  J. -M. Metzger  from  Université de La Réunion  for the Réunion Island measurements. The  University of Liège contribution  to the present work has been supported by the F. R. S. -FNRS, the  Belgian Science Policy Office (BELSPO), Brussels , the  Fédération Wallonie-Bruxelles , and MeteoSwiss ( GAW-CH program ). We thank the  International Foundation High Altitude Research Stations Jungfraujoch and Gornergrat (HFSJG, Bern). We are grateful to all Belgian colleagues who contributed to the acquisition of the FTIR data at Jungfraujoch.
Mineralogical Analyses Procedures The mineralogical composition of bulk powder samples was determined by X-ray diffraction (XRD). The data were collected in Bragg-Brentano geometry with a PANalytical X'Pert PRO MPD diffractometer equipped with an X'Celerator detector. Co Kα radiation (λ Kα1 = 1. 78897 Å, λ Kα2 = 1. 79285 Å) was used in order to minimise the effect of Fe fluorescence on background. Data were recorded over the 3° 2θ to 90° 2θ range, with 0. 017° 2θ steps and a total counting time of 6 hours. Aluminium-bearing goethite, anatase, calcite, dolomite, gibbsite, haematite, kaolinite, lithiophorite, magnetite/maghemite and quartz were identified using International Centre for Diffraction Data (ICDD) references (PDF-2 database). Least squares refinement of the experimental XRD patterns were performed using the Rietveld method, fitting the experimental patterns with theoretical ones calculated from the crystal structure of each phase identified in the sample.
Chemical Analyses Procedures and Data Chemical analyses have been carried out in the Geochemical Analytical Unit (GAU) of the ARC Centre of Excellence for Core to Crust Fluid Systems (CCFS) and the Department of Earth and Planetary Sciences at Macquarie University. Selected chip samples were powdered using a tungsten carbide mill to obtain a fine powder (below 50 µm in size). Thorough care was taken when cleaning the mill with ethanol and Milli-Q® water between samples to avoid cross-contamination. Standard X-ray fluorescence (XRF) technique was used for bulk sample major and minor elements analysis (e. g. ,  Potts et al. , 1984). Approximately 1 g of powder of each sample was mixed with 10 g of lithium tetraborate-meta-borate flux (12:22 mixture), fused in a Pt crucible and cooled to give glass discs.
Synchrotron Measurement Procedures Micro-X-ray absorption near-edge structure (XANES) and micro-fluorescence X-ray spectroscopy (µ-XRF) data were collected on the LUCIA beamline at the SOLEIL synchrotron in Paris (France) and on the ID21 beamline at the European Synchrotron Radiation Facility (ESRF) in Grenoble (France). The former operated with a storage ring current of 450 mA and an energy of 2. 75 GeV while the latter operated with a storage ring current of 200 mA and an energy of 6 GeV. The layouts of the LUCIA and ID21 beamlines are described in  Vantelon et al. (2016)  and  Salomé et al. (2013) , respectively. XANES spectra were collected using an Si(311) and an Si(220) double crystal monochromator on LUCIA and ID21, respectively. The monochromators were calibrated against the maximum intensity of the first inflection of the first derivative of a Fe foil (7112.
Two spectra were recorded for each reference with a counting time of about 50 s per spectrum. For Sc reference materials, the spectra were collected on LUCIA in XRF mode on pellets obtained from powdered material and mounted on a holder between two Ultralene® films, using a four-element silicon drift detector (SDD). For natural samples, the data were collected on ID21 in XRF mode on polished sections for both Fe and Sc K-edges using a photodiode and a large area (80 mm 2 collimated area) SDD, respectively. The beam was focused with a Kirkpatrick-Baez mirror system, down to 0. 7 µm (horizontal) x 0. 3 µm (vertical) at the Fe X-edge and 0. 9 µm (horizontal) x 0. 3 µm (vertical) at the Sc K-edge. The selection of the spots for analysis was made by combining prior SEM and EMP analyses and imaging with chemical mapping of Sc using µ-XRF mapping.
The maps were recorded with step sizes of 1 µm x 1 µm with an incident energy of 4800 eV and a dwell time of 100 ms. The XRF spectra obtained for each pixel was then fitted using the PyMCA software to obtain Sc maps. At the Sc K-edge, 10 to 40 XANES spectra were acquired for each spot with a counting time of about 80 s per spectrum. At the Fe X-edge, 2 XANES spectra were acquired for each spot with a counting time of about 50 s. Individual spectra acquired on each spot were merged to obtain average spectra before background subtraction and normalisation using the PyMCA software  (Solé et al. , 2007). Due to the high Fe concentration in the natural samples, self-absorption occurred during XRF Fe K-edge XANES measurements. This phenomenon has been corrected using the FLUO algorithm from the ATHENA software  (Ravel and Newville, 2005).
The input parameters have been chosen considering the geometry of the experiment and the chemical composition obtained from EMP measurement on the same spot. In order to map qualitative Fe speciation, we recorded µ-XRF maps on ID21 in the same area but with three incident energies: 7133. 8 eV, corresponding to the maximum intensity of the Fe K-edge XANES spectrum of goethite; 7136. 9 eV, corresponding to the maximum intensity of the Fe K-edge XANES spectrum of haematite and 7165. 0 eV corresponding to an identical intensity in the normalised Fe K-edge XANES spectra of goethite and haematite. These maps were recorded with step sizes of 2 µm x 2 µm and a dwell time of 50 ms. As for µ-XRF mapping of Sc, the three maps have been obtained by fitting the spectra at each pixel using the PyMCA software.
Acknowledgements We thank  Benoît Baptiste ,  Omar Bouddouma ,  Ludovic Delbes ,  Michel Fialin ,  Thierry Pilorge ,  Jean-Louis Robert  and  Peter Wieland  for help in sample preparation and analyses. ESRF and SOLEIL facilities are acknowledged for beamtime allocation. We are grateful to  Marine Cotte  and  Delphine Vantelon  for providing help in these experiments. We also thank  Christian Polak ,  Guillaume Morin  and  Martine Gérard  for fruitful discussions and  Hal Aral ,  Rod Ewing ,  Adam Simon  and two anonymous reviewers for constructive comments on the manuscript. This work was funded by scholarships from the  École Normale Supérieure (ENS)  and  Macquarie University , by the  Institut Universitaire de France (IUF) , a  Foundation Grant  from the  ARC Centre of Excellence for Core to Crust Fluid Systems (CCFS)  and  Jervois Mining Ltd.
, 2008; Werner et al. , 2011). The 50-year long simulation is used to identify uncertainties associated with annual layer counting based on the seasonal cycle in precipitation δ 18 O. On the contrary, the ice-core record and the stake area network will allow for an assessment of the skills of this simulation in coastal Adélie Land. These model-data were further expanded through investigation of recent mass balance and temperature variations from the regional atmospheric model MAR (Modèle Atmosphérique Régional;  Gallée and Schayes, 1994). Section 2 describes the material and methods underlying this study, including our new measurements, the methodology for the annual layer counting, as well as the regional instrumental (near-surface air temperature, wind speed and stake area measurements) and remote sensing (sea-ice extent) datasets and the simulations performed with these two atmospheric models.
Field work and ice-core sampling The field campaign was conducted from the 16 to the 26 January 2007 in Adélie Land by a French joint LGGE (Laboratoire de Glaciologie et Géophysique de l'Environnement) and IPEV (Institut Français Polaire Paul-Emile Victor) expedition. Several shallow firn cores were drilled along a transect between the Italian-French Cap Prud'Homme station at sea level and the D47 point, located around 1600 m a. s. l. and approximately 100 km from the coast. This round-trip traverse was part of the ANR-VANISH (Vulnerability of the Antarctic Ice-Sheet) and IPEV-TASTE-IDEA (Trans-Antarctic Scientific Traverses Expeditions -Ice Divide of East Antarctica) scientific programmes. The scientific aim of the programmes was to obtain new firn core records and ground-penetrating radar measurements to improve knowledge of coastal East Antarctic accumulation.
Regional climate records We extracted DDU monthly near-surface air temperature data spanning the period 1958-2006 from the Reference Antarctic Data for Environmental Research (READER) dataset (https://legacy. bas. ac. uk/met/READER/)  (Turner et al. , 2004). We also calculated annual mean values of wind speed spanning the period  1950 -2006 (with gaps in years 1953 -1955 ) at DDU (P. Pettré, personal communication, 2016). Finally, we extracted the average sea-ice concentration from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and Defense Meteorological Satellite Program Special Sensor Microwave/Imagers -Special Sensor Microwave Image/Sounder (DMSP SSM/I-SSMIS) passive microwave data (http://nsidc. org/data/nsidc-0051) and focused on the region situated between 90 and 150 • E  (Center, 1996).