dataesr/scientific-paragraphs-categorization huggingface dataset:
Cassiterite Cassiterite grains in seventeen samples of the thirteen Sn ore deposits/occurrences were analysed for In and other trace elements. At least 50 analyses were performed in all the cassiterite samples, except for two samples where cassiterite content was very low (Le Prunet, Marcofán6). More analyses were done when In was detected in only small amounts and the amounts of cassiterite allowed it. All data are available in a supplementary electronic file (Table  S1 ) and are presented in summary form with averages and standard deviations in Table  2. Sorting and visual inspection of the data give a good idea of trace element distribution. Averages are low and standard deviations are high compared to averages in most of the cassiterite ores studied because in many analyses, contents were too low to be detected.
ROLIS camera ROLIS is a dual-purpose camera, designed to work both as a descent imager and as a close-up imager after touch-down. The technical details of the experiment are described by  Mottola et al. (2007) , and we provide a short summary here. The camera was able to switch from the former to the latter mode by refocusing to a nominal object distance of 30 cm by shifting the foremost optical element, the Infinity Front Lens (IFL), out of the optical path. The field-of-view (FOV) is 57. 7 • × 57. 7 •. The images acquired by the frame transfer CCD detector were transmitted with a resolution of 14 bits, i. e. a maximum of 16383 data numbers (DN). ROLIS made use of four LED arrays to illuminate the near-field scene below the lander in the following colors: Blue, Green, Red, and IR, spanning the wavelength range from 400 to 950 nm.
Acknowledgments We acknowledge the exceptional skills and diligent efforts made by the  MSL  project's science, engineering, and management teams in making this work possible. We are also grateful to the many MSL team members who participated in tactical and strategic operations during the Kimberley campaign. We thank  Ryan Anderson  and two anonymous reviewers, whose comments have improved the manuscript. Rice was supported by the  NASA   Astrobiology Institute (NAI) Postdoctoral Program  and the  MSL Participating Scientist Program. Gupta was supported by grants from the  United Kingdom Space Agency (UKSA). Le Deit  and  Lasue  acknowledge the support of the  French Space Agency (CNES). Data presented in this paper are archived in the Planetary Data System (pds. nasa. gov).
Pressure estimates are from Putirka et al. 68  (see Supplementary Tables  1 2 3 4 5 6 ). (e) Equilibrium phase diagram (pseudosection) for an ultramylonite. The pseudosection has been constructed using modal amounts of the phases in the ultramylonite layer shown in b (see text and methods section). Based on the P-T conditions recorded in the ultramylonites (dotted white rectangle) and using isopleths of clinopyroxene (dotted red line), pargasite (dotted blue line) and tremolite (dotted green line), we estimate a water content of B600 p. p. m. during deformation of this ultramylonite band. For comparison, we also show the predicted conditions before deformation based on the P-T data recorded in porphyroclasts (dotted black rectangle). Amph ¼ amphibole; Chl ¼ chlorite; CPx ¼ clinopyroxene; Ol ¼ Olivine; OPx ¼ orthopyroxene; Pl ¼ plagioclase; Serp ¼ serpentine; Spl ¼ spinel.
Methods Scanning electron microscope. BSE images were acquired on polished (using 1 mm diamond paste) and carbon coated (20 nm) thin sections using a TESCAN scanning electron microscope (SEM) at ISTO/BRGM (University of Orleans, France). The SEM was set at an accelerating voltage of 20 kV, a probe current of B6 nA and a working distance of 10 mm. We also used the TESCAN SEM at ISTO/BRGM with an accelerating voltage of 15 kV to perform energy-dispersive X-ray spectroscopy (EDS) on cracked spinel. Microprobe. Major-element compositions and element maps were acquired using a CAMECA SX-five electron microprobe at ISTO/BRGM (University of Orleans, France). , except for antigorite  57  , amphibole  58  and plagioclase  59. Electron backscatter diffraction. The EBSD data were collected using an SEM either coupled to an EDAX Pegasus system at ISTO/BRGM, or using an e À Flash HR detector at Bruker Nano Analytics GmbH (Berlin, Germany).
Crystallographic information was also combined with EDX (Energy-Dispersive X-ray) spectroscopy to identify phases. The EBSD measurements were performed at a working distance of 15 or 20 mm with an accelerating voltage of 20 kV and a probe current of B6 nA on polished thin sections (diamond paste of 0. 25 mm followed by colloidal silica). In order to avoid indexing errors, we constructed pole figures using one measurement per grain collected manually. The iso-contours and grey shadings on pole figures were plotted using the Unicef careware software package written by David Mainprice (www. gm. univ-montp2. fr/PERSO/mainprice/ W_data/CareWare_Unicef_Programs). We further used the open-source matlab-based MTEX toolbox to construct IPF of misorientation axes and to calculate the texture (J) and misorientation (M) indices  30, 60.
To plot pole figures and calculate the J index, we used a Gaussian half-width angle of 10°. For acquisition data processing and analysis of EBSD maps, we used the OIM Analysis 7 software (EDAX) and/or HKL Tango channel 5 system (Oxford Instruments). The indexing hit rates were higher than 80% for all maps, including cavities. We used a minimum of six indexed bands and a maximum band mismatch of 2°. The outlier pixels and zero solutions were removed up to a maximum pixel count of 10. Grain detection was performed using correlated misorientation angles higher than 10°for grain boundaries and between 2 and 10°f or sub-grain boundaries. Each grain contains a minimum of five pixels considering a hexagonal grid. The average grain size corresponds to the mean equivalent diameter calculated using the grain ellipsoid fit.
Acknowledgements We thank  Carlos J. Garrido  for his help in acquiring field data. We also thank  Holger Stu ¨nitz ,  Nicole Le Breton ,  Alexandra R. L. Kushnir  and  Jessica M. Warren  for their help and comments, as well as  Florian Fusseis  for his fruitful reviews. This project has been funded by the  ETH Zu ¨rich (ETH  fellowship application  FEL01 09-3 ),  ERC RHEOLITH  (Grant  n°290864 ),  Labex Voltaire  ( ANR-10-LABX-100-01 ) and  ANR   DSP-Tibet  ( ANR-13-BS06-0012 ).
For point analyses, we applied a counting time of 10 and 5 s for peak and background signals, respectively. Calibration was carried out against natural and synthetic minerals, including albite, MnTiO 3 , Fe 2 O 3 , MgO, Al 2 O 3 , andradite, orthose, Cr 2 O 3 , NiO and vanadinite. 54,55e_X calculations. The pseudosections were calculated using Perple_X (ref. 53)with the thermodynamic database of Holland and Powell54. It was built in the NCFMASH (Na 2 O-CaO-FeO-MgO-Al 2 O 3 -SiO 2 -H 2 O) chemical system. The weight percent of oxides was calculated by combining the volume percent of mineral modes, which were determined by point counting on elements maps, and the composition of mineral phases determined at the microprobe. No phase was excluded, but we did not consider chromium in spinel for simplicity.
01 µg L -1. High-resolution continuous rBC data recorded every second were smoothed at a depth resolution of 1 cm, except for the upper section (surface to 7. 2 m depth) of the 2009 core that was discretely analyzed at a depth resolution of ∼ 5-10 cm. The density of rBC data points per year (N = 8∼ 376) depends on annual snow accumulation rates and ice thinning with depth. The two ice cores are overlapped for snow layers of years 2007-2009 (Fig. S1  in the Supplement). The records described here for rBC concentrations are (i) the 2009 ice core from 2. 9 to 156. 6 m, corresponding to calendar years  1825-2008, and (ii)  the top 15. 9 m of the 2013 core, corresponding to calendar years 2009-2013. These two ice core records cover the calendar years 1825-2013. As a first survey of long-term rBC size distributions of the ice core record, the mass equivalent diameter of a measured single rBC particle, D rBC , was calculated, assuming a void-free BC density of 1.
To avoid inaccurate separation of an annual ice layer into winter and summer intervals, only mid-summer and mid-winter rBC concentrations were extracted by considering data comprised between the 25th percentile and the 75th percentile of the depth thickness of each seasonal snow layer. This seasonal separation method is fairly supported by the fact that (i) observed precipitation in the western Caucasus is equally distributed throughout a year (e. g. , at Klukhorskiy Pereval station located at 2037 m a. s. l. , 50 km westward from the drilling site: 52 % of the annual precipitation (or 48 %) is observed during summer (or winter) and each monthly precipitation accounts for 6-11 % of the total precipitation for the period 1966-2009; www. meteo. ru) and (ii) maximum or minimum values of both δ 18 O and ammonium coincide for most of the Elbrus core annual ice layers.
We selected these periods because (i) year 1979 is the first year of ECMWF data and year 2009 is the last year of our longer ice core (2009 ice core) that was analyzed prior to the 2013 ice core, and (ii) these years show inflection in rBC trends (Sect. 3. 2). It would thus be sufficient to analyze transport patterns influencing rBC at ELB and determine potential changes in these transport patterns. In simulations, 1000 particles are released at the drilling site during every 5-day interval in June to August (JJA) and in December to February (DJF). Modeled global average atmospheric lifetimes of BC particles vary by a factor of more than 3, ranging from 3 to 10 days  (Bond et al. , 2013). Because BC particles reaching the high-altitude ELB site would experience longer lifetimes than the particles transporting in the planetary boundary layer (PBL), simulations were performed using BC lifetimes of 5 and 7 days.
8b ). For anthropogenic emissions, the largest BC emissions in the EEU and CEU regions occurred in 1980, followed by decreasing trends. WEU had the strongest BC emissions lasting until 1960, followed by a decrease in BC emissions lasting to the present day. In 2008, anthropogenic BC emissions in the EEU, CEU and WEU regions are comparable, with an order of 0. 2 Tg yr -1. To investigate factors controlling long-term rBC trends preserved in the ELB ice core, the temporal evolution of measured ice core rBC particles can be directly compared with that of atmospheric BC load at the ELB site, at least in a relative manner. This comparison is provided in Fig. 9 , in which the ice core record is averaged along a decadal scale to be comparable with the historic BC emission data available on the decadal scale only  (Lamarque et al.
Knowing that sulfate and BC are often co-emitted in anthropogenic emission sources, e. g. , in industrial sectors, one can expect a large increase in European BC emissions since the mid-20th century, as suggested by the ELB ice core rBC record. The re-  liability of historic emission inventories for BC is reported to be lower than that for SO 2 , CO and NOx emissions, particularly for the period prior to 2000  (Granier et al. , 2011) , which is due to the uncertainties in BC emission factors for coal, gasoline and diesel fuels in various sectors (differ by a factor of 10 or more in the literature) and activity data  (Granier et al. , 2011; Vignati et al. , 2010). Thus, the lack of a substantial increase in the atmospheric BC load for the period 1960s-1970s could be associated primarily with underestimated European anthropogenic BC emissions for this period (Fig.
On the other hand, many eastern European countries, such as Ukraine and the European part Russia which are geographically close to Mt. Elbrus, are the countries with the greatest land use for agriculture in Europe  (Rabbinge and van Diepen, 2000) , and thus emissions of smoke aerosols from their agricultural waste burning are expected to be significant in summertime  (Barnaba et al. , 2011; Bovchaliuk et al. , 2013; Stohl et al. , 2007). Large emissions of smoke aerosols over eastern Europe from summer forest/agricultural fires have been recently reported  (Barnaba et al. , 2011; Bovchaliuk et al. , 2013; Sciare et al. , 2008; Yoon et al. , 2011; Zhou et al. , 2012)  and burned area from the Global Fire Emissions Database (GFED;  Giglio et al. , 2010)  increased over eastern Europe for the period 2004-2008  (Yoon et al.
Acknowledgements. This work was supported by the  PEGASOS  project funded by the  European Commission  under the  Framework Programme 7  ( FP7-ENV-2010-265148 ) and by the  Russian Foundation for Basic Research (RFBR)  grants  07-05-00410  and  09-05-10043. This work received funding from  French ANR  program  RPD COCLICO  ( ANR-10-RPDOC-002-01 ) and the  European Research Council  under the European Community's  Seventh Framework Program   FP7/2007-2013  grant agreement no. 291062  (project  ICE&LASERS ). Saehee Lim acknowledges the support of the  Korean Ministry of Education and Science Technology  through a government scholarship and of the  Basic Science Research Program  through the  National Research Foundation of Korea (NRF)  funded by the  Ministry of Education  ( 2015R1A6A3A01061393 ).
In Fig. 2  the location of all sondes analyzed in this paper is presented and demarcates the area of flight operations as indicated earlier. All dropsondes were processed using the ASPEN V3. 3-270 software, and the data were further visually inspected for possible biases or malfunction before being incorporated into the analysis. Differences between the composite moisture sounding for NARVAL-1 versus NAR-VAL-2 measure differences between the winter trades (subsidence zone, Fig. 1 ) and the atmosphere near and around the ITCZ. In the NARVAL-1 soundings, the lower free troposphere is very dry, almost devoid of water vapor (Fig. 3 ). The shallow cumulus layer is well defined in terms of a moist layer extending from just above the top of a yet moister PBL to a height of 2 km, where it terminates in a strong hydrolapse.
Remotely Sensed Humidity Variations During NARVAL-1 and NARVAL-2 To better assess the structure of water vapor in the tropical atmosphere, we evaluate to what extent satellite retrievals capture important forms of water vapor variability as measured during the NARVAL series of campaigns. To do so, we compare water vapor retrievals from the SAPHIR and IASI instruments with dropsonde and water vapor lidar data collected during NARVAL-1 and NARVAL-2 research flights. Because of its better temporal sampling and its ability to extract water vapor information also in the presence of clouds, we focus on SAPHIR.
General Structure of Humidity Retrievals from SAPHIR SAPHIR retrievals capture well the main, climatological, features of the humidity field as seen in the dropsonde data across the entire NARVAL-1 and NARVAL 2 periods. During NARVAL-1, an exceptionally dry free atmosphere (Fig. 7 , left panel), with humidities well below 20%, is consistent with the dropsonde data presented in Fig. 3. A broader distribution of relative humidities between 750 and 800 hPa (SAPHIR layer 5) is consistent with the top of the shallow cumulus (trade-wind) layer being near this level-drier conditions being indicative of days with a shallower cloud layer. The August NARVAL-2 flights predominantly differ through a moister, and more variable, free troposphere as compared to the December NARVAL-1 flights. Figure  7  shows these differences to be evident at every level, but most pronounced between 400 hPa and 800 hPa, consistent with the dropsonde data in Fig.
8 ) in the SAPHIR data and sampled at around 1840 UTC by WALES. A second, somewhat broader, feature is also apparent at the very end of the record, near 51 W. These features are also evident in the layer 5 (2-2. 6 km) retrievals, but much less pronounced than in WALES. These differences illustrate the challenges that retrievals from passive sensors face in the vicinity of a strong humidity gradient (80-10%), where the interpretation of the upwelling irradiances is not clear cut. In this case, the breadth of the sensitivity functions probably also leads to some of the moisture from the lower layers being interpreted as having arisen higher up. Earlier in the flight (before 1730 UTC), where the moisture is more homogeneous, the SAPHIR retrievals match the measurements by WALES quite well. RH [%] RH [%] p [hPa] ) 6 1 0 2 g u A ( 2 L A V R A N ) 3 1 0 2 c e D ( 1 L A V R A N Considering their lack of coincidence, the SAPHIR humidity retrievals on 12 August also appear to capture the variability in relative humidity in the upper troposphere, and the gravest features of the vertical structure.
11 ). SAPHIR under estimates the humidities (by about 15% absolute) around 3. 4 km (its level 4) and compensates with commensurately higher humidities one kilometer lower (its level 5). Here again the broadness of the SAPHIR sensitivity functions makes it difficult to unravel the moist layer near 4 km from the absolutely drier layer aloft and a relatively drier layer below. When layers 4 and 5 are taken together, the SAPHIR retrievals capture the horizontal humidity variations seen in the WALES data below 3 km, but we interpret them in terms of a more climatological vertical structure, wherein relative humidity is strictly decreasing with height. Because the area of aircraft operations on August 12, 2016, was relatively cloud-free, we can explore whether IASI humidity retrievals are, by virtue of more independent information, better able to measure the vertical structure of water vapor in the lower free troposphere.
Acknowledgements Open access funding provided by  Max Planck Society. This paper arises from the  International Space Science Institute (ISSI)  workshop on '' Shallow clouds and water vapor, circulation and climate sensitivity ''. The NARVAL campaign was co-sponsored by the  Max Planck Society , the  Deutsche Forschungsgemeinschaft (German Science Foundation , project  HALO-SPP 1294 ) and the  DLR Institute of Atmospheric Physics. Jean-Lionel Lacour  is grateful to the  CNES  for postdoctoral funding. P-E Kirstetter  ( NOAA NSSL ) and  C. Dufour  ( LATMOS ) are acknowledged for their help on the SAPHIR data. The  CNES  and  CNRS  are gratefully acknowledged for the financial support to the scientific activity of the Megha-Tropiques mission. The  ICARE group  is also acknowledged for realizing the ground segment of the mission: The data are available at http://www.
Acknowledgements We are grateful to  E. Bernard  ( NHM, London ) for her help about Polygyrodus specimens and to  P. Catto  for providing material. We thank  P. -Y. Le Bail  ( INRA, Rennes ) for discussions on serrasalmid dentitions and for providing piranha jaws,  W. M. Dahdul  ( University of South Dakota, Vermillion ) for bibliography,  L. Cazes  ( MNHN, Paris ) and  Kevin Webb  ( NHM, London ) for the photographs, and  S. Fernandez  ( MNHN, Paris ) for the artistic reconstruction of Serrasalmimus. This study benefited from the "Phosphapal" scientific convention of collaboration in the palaeontological field between the  Office Chérifien des Phosphates (OCP) , the  Mining Development Direction of the Ministère de l'Energie, des Mines, de l'Eau et de l'Environnement du Royaume du Maroc , the  Université Cadi Ayyad of Marrakech, Morocco , and the  Muséum National d'Histoire Naturelle, France.
INTRODUCTION Tropical coastal systems represent <1% of the world's ocean volume, yet they host some of the most productive and diverse ecosystems on earth  (Jennerjahn, 2012; Bowen et al. , 2013). Although, recent studies suggest that tropical marine regions will experience less drastic environmental changes than temperate regions in the future  (Acevedo-Trejos et al. , 2014) , they remain largely understudied. This is particularly true in the southern hemisphere where very few datasets that capture the seasonal variations in bio-optical properties exist. The literature available on the tropical coastal waters of Far North Australia, referred to as the North Marine Region (NMR, Figure  1 ), is limited to marine phytoplankton productivity of this region  (Hallegraeff and Jeffrey, 1984; Ilahude and Mardanis, 1990) , its geology  (Woodroffe et al.
, 1993)  and the physical processes that influence its oceanography  (Condie, 2011; Li et al. , 2014). Across the NMR there is a need to develop better coastal ecosystem-based management strategies, which require quantitative assessment of the processes controlling the coastal marine environment. Combined bio-optical and biogeochemical measurements are key to quantify the ecosystem response to physical and chemical drivers. However, the remote location of the NMR makes the acquisition of in situ data by conventional sampling methods difficult (Figure  1 ), thus the use of ocean color and sea surface temperature (SST) satellite datasets for the study of the spatio-temporal patterns of biogeochemical processes in such remote areas is ideal. Recent studies using satellite-derived subsurface light attenuation  [K d (λ) ], Chlorophyll-a (Chl-a) and total suspended solids (TSS) concentrations have shown the distinct seasonal cycles of those parameters in the NMR  (Schroeder et al.
Characteristics of the Sampling Effort The dataset presented in this study comprises 23 metadata, biogeochemical and optical parameters ( sampling concentrations EEM, nutrients 1 X X X 2 X X 3 X X X X X 3 X X X X X C Variable or Description Units symbol Salinity n/a PSU Secchi depth n/a m Temperature n/a    1A ). Additionally, DH was also sampled on two occasions but only during the dry season: first, an intensive field campaign that solely focused on DH was undertaken during 3 days at the end of the 2012 dry season (24, 26 September and 8 October 2012; N = 15) and second, several stations (N = 10) were sampled in DH at the end of the September 2013 dry season field campaign when returning from the VDG (Figure  1 ; Table  1A ). At the time of their sampling, the bottom depths of all stations ranged from 5 to 60 m (median: 21 m; N = 63).
, 1997). The incomplete recovery of the scattered light in the ac-s absorption tube was rectified using the proportional method described in  Zaneveld et al. (1994). The BB-9 backscattering dataset was corrected for light loss due to absorption over the path length at each angle and wavelength using light absorption and scattering values from the ac-s  (Boss et al. , 2004). All vertical profiles were binned at 0. 2 m depth intervals. In addition, the water transparency was visually estimated by the same observer at all stations by lowering a black and white disk (Secchi disk). The Secchi depth reported in this study is the depth at which the disk is no longer visible. Assuming that dissolved organic matter in water has a negligible effect on scattering, the particulate scattering coefficient b p (λ) was derived by subtracting the scattering by pure water, b w (λ) from the difference between the total light attenuation c(λ) and total light absorption (particulate+dissolved), a Tot (λ) [i.
Specific Inherent Optical Properties Mass-specific inherent properties (SIOPs), the absorption and backscattering coefficients normalized to their respective concentrations, are necessary for the parameterization of (semi-) analytical bio-optical models for complex coastal waters (e. g. ,  Brando et al. , 2012; Tilstone et al. , 2012; Le et al. , 2015). However, SIOP datasets are seldom available for most of the world's coastal ocean. To further characterize our optical dataset and to help the development of ocean color algorithms for this sub-region of the NMR, we computed the specific absorption coefficients for phytoplankton, a phy * (λ), obtained by normalizing a ph (λ) to Chl-a, as well as the mass-specific non-algal particulate absorption, a NAP * (λ), and backscattering, b bp * (λ), coefficients by normalizing a NAP and b bp by their TSS concentrations.