dataesr/scientific-paragraphs-categorization huggingface dataset:
001A  and  NSF   AST-1715692  grants. TC and GCR acknowledge support from  HST-GO-15163. 015A. This research was supported by the  Munich Institute for Astro-and Particle Physics (MIAPP)  which is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) under Germany's Excellence Strategy -EXC-2094 -390783311. This work is based on observations made with  ESO Telescopes at the Paranal Observatory  under programme  ID 0104. A-0147 (A), observations made with the 6. 5m  Magellan Telescopes  located at  Las Campanas Observatory , and spectroscopic data gathered under the  HST-GO-15163. 01Aprogram using the  NASA/ESA Hubble Space Telescope  operated by the  Space Telescope Science Institute  and the  Association of Universities for Research in Astronomy, Inc. , under  NASA  contract  NAS 5-26555.
This research has made use of  NASA 's Astrophysics Data System and the  NASA/IPAC  Extragalactic Database (NED) which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration. Software: CarPy (Kelson 2003) ACKNOWLEDGMENTS We thank  Sergei Balashev ,  Evan Kirby ,  Martin Bureau , and  Jay Gallagher  for useful discussions. HWC, EB, and  MCC  acknowledge partial support from  HST-GO-15163. 001A  and  NSF   AST-1715692  grants. TC and GCR acknowledge support from  HST-GO-15163. 015A. This research was supported by the  Munich Institute for Astro-and Particle Physics (MIAPP)  which is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) under Germany's Excellence Strategy -EXC-2094 -390783311.
This work is based on observations made with  ESO Telescopes at the Paranal Observatory  under programme  ID 0104. A-0147 (A), observations made with the 6. 5m  Magellan Telescopes  located at  Las Campanas Observatory , and spectroscopic data gathered under the  HST-GO-15163. 01Aprogram using the  NASA/ESA Hubble Space Telescope  operated by the  Space Telescope Science Institute  and the  Association of Universities for Research in Astronomy, Inc. , under  NASA  contract  NAS 5-26555. This research has made use of  NASA 's Astrophysics Data System and the  NASA/IPAC  Extragalactic Database (NED) which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration. Software: CarPy  (Kelson 2003) ACKNOWLEDGMENTS We thank the referees for helpful comments, and  Sergei Balashev ,  Martin Bureau ,  Jay Gallagher , and  Evan Kirby  for useful discussions.
SL was funded by project  FONDECYT 1191232. This research was supported by the  Munich Institute for Astro-and Particle Physics (MIAPP)  which is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) under Germany's Excellence Strategy -EXC-2094 -390783311. This work is based on observations made with  ESO Telescopes at the Paranal Observatory  under programme  ID 0104. A-0147 (A), observations made with the 6. 5m  Magellan Telescopes  located at  Las Campanas Observatory , and spectroscopic data gathered under the  HST-GO-15163. 01Aprogram using the  NASA/ESA Hubble Space Telescope  operated by the  Space Telescope Science Institute  and the  Association of Universities for Research in Astronomy, Inc. , under  NASA  contract  NAS 5-26555. This research has made use of  NASA 's Astrophysics Data System and the  NASA/IPAC  Extragalactic Database (NED) which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration.
, under NASA contract NAS 5-26555. This research has made use of NASA's Astrophysics Data System and the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. Type Ia SNe. We discuss possible origins for the H 2 -bearing gas in the outskirts of this galaxy, including interactions with companion galaxies and a past epoch of AGN activity. Although we cannot rule out the presence of an undetected, intervening galaxy lost in the glare of the QSO light, the lack of [O III] 5007 emission in the quasar spectrum at the absorber redshift places a 3 upper limit on the star formation rate of SFR < 0. 1 M yr 1. preferential enrichment by spectroscopy remains the only viable method to directly de-tect molecular gas at the low and moderate column densities that may be characteristic of circumgalactic environments (log[N(H 2 )/cm 2 ].
A similar pre-collapse evolution towards more differentiated products was observed on Taburiente volcano, La Palma, Canary Islands 62 , but this trend persisted during the early post-collapse stage (Bejenado lavas) until volcanic activity moved to the South, thus building a new shield (Cumbre Vieja). The central edifice of Tenerife provides another example of such correlation between volcano growth, storage conditions, eruptive processes shifting from effusive to explosive, and flank instability of an ocean island  48, [63] [64] [65]. However, the unique dataset presented here for Fogo volcano highlights two different scales of consequences of the flank collapse on lava composition. The delayed response to the unloading effect of the collapse takes ~ 50 kyrs at the lithospheric scale (i. e.
Acknowledgements This research was financed by the  French Government Laboratory of Excellence initiative  No. ANR-10-LABX-0006 , the  Region Auvergne  and the  European Regional Development Fund. We thank  Claire Fonquernie ,  Jean-Luc Devidal , and  Christophe Constantin  ( LMV Clermont-Ferrand ), and the members of the PhD jury of  M. N. Cornu  for helpful discussion ( Meritxell Aulinas Junca ,  Maud Boyet ,  José Madeira  and  Georges Boudon ). This work also benefited from a wise review of our regretted colleague  Hervé Martin , to whom we wish to dedicate this contribution. We are also grateful to  Takeshi Kuritani ,  Ricardo Ramalho  and an anonymous reviewer for their relevant comments. This is Laboratory of Excellence ClerVolc contribution No. 500.
2. 3. a) FTIR spectroscopy After thermal ageing, the samples were analysed by infrared spectroscopy in transmission mode using a Nicolet 6700 spectrophotometer and in attenuated total reflection mode (ATR) using a Nicolet 380 spectrophotometer equipped with a diamond crystal (refractive index = 2. 5). Spectra were recorded with 64 scans at a resolution of 4 cm -1. In the spectra obtained with the ATR mode, the angle of incidence is specified at 45° and the refractive index of the material is set at 1. 5. In order to correct the wavelength-dependent penetration depth, we used the Omnic software produced by ThermoScientific. Moreover, the CH 2 scissor band at 1463 cm -1 was chosen as a reference band because of its insensitivity to the oxidation process. The absorbances at the various maxima considered were corrected using the absorbance of the reference band.
2. 3. e) UV/Vis spectroscopy The UV-Vis spectra of the polymer were recorded with a Shimadzu UV-2600 scanning spectrophotometer equipped with an integrating sphere, working with UVProbe software. Measurements were performed with polymer plates (1500 µm). The spectra were recorded in transmission mode by analysis the 1. 5mm plates, which were transparent enough to obtain absorbances in a convenient range (A<3). The degree of yellowing is determined by plotting the absorbance at 450 nm.
, 2019). In this work, we use the official TCCON XCO product as well as an XCO product without the application of the empirical scaling factor, herewith referred to as unscaled XCO. The unscaled XCO was calculated following Eq. (2) of  Wunch et al. (2015) , where the TCCON data without the scaling to the WMO scale were obtained from the site PIs. The validation work is done using the standard and rapid delivery of TCCON data from the whole network. The publicly available TCCON data can be accessed via https://tccondata. org/ (last access: 1 June 2021).
Ground-based NDACC-IRWG reference data set The IRWG of the NDACC represents a network of highresolution Fourier transform spectrometers that records solar absorption spectra in the mid-infrared (MIR) spectral range. It is a multi-national collection of over 20 stations distributed from pole to pole (Eureka at 80 • N to Arrival Heights at 77. 8 • S). The solar absorption spectra are used to retrieve the atmospheric concentrations of a number of gaseous atmospheric components, including ozone (O 3 ), nitric acid (HNO 3 ), hydrogen chloride (HCl), hydrogen fluoride (HF), carbon monoxide (CO), nitrous oxide (N 2 O), methane (CH 4 ), hydrogen cyanide (HCN), ethane (C 2 H 6 ) and chlorine nitrate (ClONO 2 ) (https://www2. acom. ucar. edu/irwg, last access: 1 June 2021). NDACC CH 4 and CO data from several stations have been used in previous studies for satellites validation  (Borsdorff et al.
, 2020; Hedelius et al. , 2019; Hochstaffl et al. , 2018; Sha et al. , 2018b; Buchholz et al. , 2017; Olsen et al. , 2017). In this study, data from all stations (19 in the Northern Hemisphere and 5 in the Southern Hemisphere) are used and are listed in Table  3. Several of the stations are located in high-latitude regions and many stations are located at high altitudes to reduce the interference of water vapour in the measurements. Some of these stations (e. g. Karlsruhe, Garmisch, Sodankylä, Porto Velho) are not officially part of NDACC but performs observations and data analysis fully compatible with NDACC guidelines. The co-located NDACC and TCCON stations often share one FTIR instrument, applying the respective detector and filter settings. The spectra are analysed either with the SFIT4 algorithm, an evolution of SFIT2  (Pougatchev et al.
(2010). The surface pressure (P s ) is recorded at the local weather station of the FTS stations and H 2 O total column (TC H 2 O ) is derived from the National Centers for Environmental Prediction (NCEP) reanalysis data set. In the event that there is no surface pressure available, we extrapolate the pressure grid to the surface. The XCH 4 calculated values for NDACC measurements are then used for the validation of the S5P XCH 4 data. Unlike TCCON data, where a species-specific scaling factor is applied to tie the measurements to the WMO in situ scale, the NDACC data do not apply any scaling of the retrieved results. The typical accuracy and precision of the NDACC CH 4 data are about 3 % and 1. 5 %, respectively. The typical accuracy and precision of the NDACC CO data are about 3 % and 1 %, respectively.
High systematic uncertainty is mainly due to the too-conservative spectroscopic uncertainty component. Both the consolidated data available via http://www. ndaccdemo. org/ (last access: 1 June 2021) and the rapid delivery data supported by the CAMS27 project (https://cams27. aeronomie. be/, last access: 1 June 2021) have been used in this study. 3 Validation methodology S5P provides the total column density of CO, which can be directly validated against the NDACC CO total column density product. However, we need to calculate the corresponding XCO values in order to compare to the TCCON XCO products. The S5P XCO is calculated by taking the ratio of the total column of CO (TC CO ) divided by the total column of the dry air (TC dry,air ) (following Eq. 1 in  Deutscher et al. , 2010). XCO = TC CO TC dry,air = TC CO P s /(g × m dry,air ) -TC H 2 O × (m H 2 O /m dry,air ) , (1) where P s is the surface pressure, TC H 2 O is the total column of H 2 O, g is the column-averaged acceleration due to gravity, m dry,air and m H 2 O are the molecular masses of dry air and H 2 O, respectively.
P s and TC H 2 O are taken from the S5P files. The validation of the S5P methane and carbon monoxide data is performed based on the reference data sets from the ground-based TCCON and NDACC networks. We present the results for both of the networks with different co-location criteria applied to the data sets. The differences in the validation results are also based on whether or not a common prior has been used for the satellite and ground-based FTIR data sets; details are discussed in Appendix A. S5P provides daily global coverage with a huge data set having a wide swath at a high spatial resolution for every overpass. Therefore, the selection of good co-location criteria is a crucial task in finding the best strict criteria while ensuring sufficient co-located data for a statistically significant validation.
We tried several co-location criteria to test the sensitivity of the method in relation to the choice of the parameter (e. g. time, distance, line of sight). The best colocation criteria will be such that the bias is robust and not sensitive to small changes in the co-location criteria. In the next sections, the results of the application of these criteria are shown for the case with the reduction of uncertainty due to smoothing and in relation to direct comparisons. The validation results of the S5P bias-corrected and standard methane products with reference TCCON and NDACC data are discussed in this section. The S5P observations colocated with the ground-based reference measurements are found by selecting all filtered S5P pixels within a radius of 100 km around each site and with a maximal time difference of 1 h for TCCON and 3 h for NDACC observations.
Acknowledgements. Part of this study has been carried out in the framework of the  Copernicus Sentinel-5 Precursor Mission Performance Centre  ( S5P , MPC) contracted by the  European Space Agency (ESA/ESRIN , contract no. 4000117151/16/I-LG ) and supported by the  Belgian Federal Science Policy Office (BELSPO) , the  Royal Belgian Institute for Space Aeronomy (BIRA-IASB). Part of this study has also been supported by the  S5P Validation Team  ( S5PVT )  AO  project  TCCON4S5P  (ID no. 28603 ,  PI Mahesh Kumar Sha, BIRA-IASB)  with national funding from the  BELSPO  through the  ESA ProDEx projects TROVA  and  TROVA-E2 (PEA 4000116692 ). This work contains modified Copernicus Sentinel-5 Precursor satellite data (2018-2020) post-processed by  BIRA-IASB. The authors wish to thank the instrument operators and scientists doing the retrieval for the delivery of the ground-based reference data, which were used for the validation study in this paper.
Funding for the Darwin, Lamont and Pasadena TCCON sites is provided by  NASA 's  OCO-2/-3  projects (grant nos. NNN12AA01C  and  80NM0018D0004 ), while the  Park Falls site plus TCCON  (the network) is funded through  NASA   Carbon Cycle Science Program  (grant no. NNX17AE15G ). Measurements in Ny-Ålesund and Paramaribo are supported by the  Alfred Wegener Institute Potsdam. We thank the  AWIPEV station personnel in Ny-Ålesund ,  Cornelis Becker  and  Sukarni Mitro  ( Meteorologische Dienst Suriname ) in Paramaribo and the  Senate of Bremen  for support. The observations at Ny-Ålesund are supported within the  DFG ,  German Research Foundation , project  ID 268020496 -TRR 172 project (AC)3, Arctic Amplification , subproject  E02. The Sodankylä site received financial support from the  European Space Agency  under the grant agreement no.
ESA-IPL-POE-LG-cl-LE-2015-1129. The Paris TCCON site has received funding from  Sorbonne Université , the  French research centre CNRS , the  French space agency CNES  and  Région Île-de-France. TCCON sites at Tsukuba, Rikubetsu and Burgos are supported in part by the  GOSAT  series project. Burgos is supported in part by the  Energy Development Corp. Philippines. The  TCCON Nicosia  site has received additional support from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement no. 856612  and the  Cyprus Government , and by the  University of Bremen. The Ascension Island TCCON station has been supported by the  European Space Agency (ESA)  under grant no. 4000120088/17/I-EF  and by the  German Bundesministerium für Wirtschaft und Energie (BMWi)  under grant nos.
50EE1711C  and  50EE1711E. We thank the  ESA Ariane Tracking Station at North East Bay, Ascension Island , for hosting and local support. The TC-CON and NDACC sites at Réunion Island is operated by the  Royal Belgian Institute for Space Aeronomy  and local activities supported by LACy /UMR8105  and by  OSU-R/UMS3365  - Université de La Réunion. The TCCON Réunion Island site is financially supported since 2014 by the  EU  project  ICOS-Inwire and the ministerial decree for ICOS  ( FR/35/IC1  to  FR/35/IC5 ). The CH 4 and CO measurements at Porto Velho have been supported by the cooperation agreement BAAF and the  BRAIN-pioneer  project  IKARE , respectively, both funded by  BELSPO. We thank  Carlos Augusto Bauer Aquino  (IFRO) and  Luciana Vanni Gatti  ( INPE ) for their technical support for the measurements at Porto Velho.
A B All patients diagnosed with MTC through analysis of the anatomopathological examination of the TT piece were included in the study. The exclusion criterion was the absence of an anatomopathological report confirming the MTC diagnosis of patients from other institutions who had an informal report of this neoplasm. Anatomopathological criteria reviewed by  Wei (2020)  were those considered to evaluate the TT piece  (10). Data sampling was performed using physical and electronic medical records from the TASY ® system at the Ciro Antonio Kreuz Study and Research Center, Uopeccan, between June and August 2018. All patients with thyroid cancer under follow-up at Uopeccan from 2013 to 2018 were considered for this study. Clinical and demographic data, information on treatments performed and their complications, and information on the follow-up and evolution of patients with MTC were collected.
The clinical and demographic data used were age, sex, age at diagnosis, family history of MTC, and occurrence of metastases. The ultrasound findings were reported using criteria from the American College of Radiologists (2017), such as echogenicity (very hypoechoic, hypoechoic, isoechoic, hyperechoic, or anechoic), composition (solid or almost completely solid, mixed cystic and solid, spongiform, or cystic), shape (wider than tall or taller than wide), margins (smooth, ill-defined, lobulated/irregular, or extrathyroidal extension), and echogenic foci (none or large comet tall artifact, macro-calcifications, peripheral/rim calcifications, or punctate echogenic foci). Following ultrasound analysis, the characteristics of the nodules were scored to determine the TI-RADS grade, which can be categorized into TI-RADS 1 (benign), TI-RADS 2 (not suspicious), TI-RADS 3 (mildly suspicious), TI-RADS 4 (moderately suspicious), and TI-RADS 5 (highly suspicious).
Finally, data were collected on the nodule vascularization pattern, number of nodules, and suspicious lymph nodes  (11). The cytopathological FNAB results of the thyroid nodule diagnosed with MTC were classified according to the Bethesda System, as follows: (I) non-diagnostic sample, (II) benign, (III) atypia of undetermined significance, (IV) suspicious for follicular neoplasm, (V) suspicious malignancy, and (VI) malignant. We considered diagnostic FNAB as those classified as Bethesda category VI or Bethesda category V with suspected MTC, following Suzuki and cols. (2017)  (7). The surgical methods performed and the anatomopathological data of the surgical products were analyzed, including the largest tumor diameter (cm), number of nodules, presence or absence of angiolymphatic infiltration, impairment of surgical margins, and presence of lymph node metastases.
The data were collected as a single database in a Microsoft Excel spreadsheet and analyzed using descriptive statistics, including the arithmetic mean, standard deviation, median, minimum and maximum values, and frequencies. The correlation between nodule size and preoperative CT levels was calculated using Pearson's correlation coefficient with the following reference values: 0 to 0. 19, very weak correlation; 0. 20 to 0. 39, weak correlation; 0. 40 to 0. 69, moderate correlation; 0. 70 to 0. 89, strong correlation; 0. 90 to 1, very strong correlation. Where continuous variables had a parametric distribution, they were analyzed using the Student's t-test, while non-parametric variables were analyzed with the Mann-Whitney test and Welch's t-test. The Student's t-test was chosen when the hypothesis of normality and homoscedasticity of the data were verified and the Welch's t-test was selected when the hypothesis of normality was verified but the hypothesis of homoscedasticity was not, while the Mann-Whitney test was chosen when the data were not normally distributed.
Acknowledgments: we thank the team of the outpatient clinic of  União Oeste Paranaense de Estudos e Combate ao Câncer (Uopeccan) , who helped to select patients' records used in this research. We are also grateful to the  Laboratory of Molecular and Translational Endocrinology, Federal University of São Paulo (Unifesp) , for performing genetic tests for mutation in the RET gene of patients with MTC under follow-up at Uopeccan. Statement: the study was funded by the authors. Disclosure: no potential conflict of interest relevant to this article was reported.
The increasing demand for energy is leading to the increasing use of renewable resources, such as biomass, resulting in the significant development of the wood energy sector in recent years. On the one hand, and to a certain extent, the sector has generated many benefits. On the other hand, the challenges related to wood ash (WA) management such as increasing tonnages, landfilling, restrictive regulations for reuse, etc. , have been weighing more heavily in the debate related to the wood energy sector. However, all studies have assumed that no environmental impacts can be attributed to WA production. This study aims at discussing this assumption, whether the WA is a waste or a co-product of heat generation. In the first place, WA deposits were estimated using the biomass database and ash content from the literature regarding the collective, industrial and tertiary biomass power plants (BPP) in the French region of Brittany.
Data related to wood fuel consumption (C wood ) for both scales were recovered from AILE database in Brittany  [24]. In addition to these datasets, other assumptions were made to get as close as possible to the actual situation. Table  1  gathers the main assumptions considered for the calculations of WA tonnages. A grate furnace has been considered for the wood combustion process, this technology representing the main type of biomass boiler used in France as in Brittany  [4]. This assumption has a direct impact on the mass distribution of ashes, based on the way of collecting them (80% of bottom ash, 20% of fly ash)  [29]. Moreover, several ash content values (t wa ) were selected according to the type of wood fuel used, varying from 0. 5% (low hypothesis) to 3% (high hypothesis) of incoming wood fuel  [4, [28] [29] [30]  with an average moisture content (h) of 30% considered appropriate based on data in the literature  [31].
Life Cycle Inventory Analysis and Modeling Assumptions Figure  1  and Table  2  show respectively the main processes and flows related to the production of 1 ton of WA in BPP. They were inventoried based on Ecoinvent v. 3. 3. (2016) database, Zurich, Switzerland  [36]  and several assumptions reflecting the current average situation in Brittany, especially regarding the three main aspects of the wood energy sector: wood fuel, energy production, and wood ash. The present study considers a combustion process unfolding in a BPP with an installed capacity higher than 1 MW, using grate furnace technology and an average efficiency estimated at 90%  [37]. Note that co-generation plants were not considered since 95% of the BPPs in Brittany are strictly dedicated to heating. Forest wood chips, as the first resource used in the studied region, were considered as fuel with 1% total ash and 30% moisture content.