dataesr/scientific-paragraphs-categorization huggingface dataset:
Determining the thickness After aligning the stacked images, the region of interest (Figure  2a ) was clipped out, (i. e. , the area containing texture and stripes or felt on the surface), followed by application of the DfF algorithm (the only treatment made on MATLAB). We first made an initial very coarse depth map for measuring the tilt of the ceramic with respect to our device (fitting with a polynomial surface of degree 1). If the sample was not flat, we could then further determine its shape (fitting with a polynomial surface of degree 2). We then produced a second depth map. High levels of precision are necessary for this second map so that information on both sides of the glaze may be detected. Using the surface shape established with the coarse depth map (untilting for a flat ceramic, correction of the volume otherwise), we then transformed our depth map and obtained the planes above and under the glaze at constant depth (Figure  2b ).
However, this thickness is not a localized measurement but a global measurement for the region of interest studied. It is an average measurement on a sample that can reach more than 1 cm 2. Finally, Python is used to code all the presented processing. For the entire process, the time required for thickness measurement is very short. Once the equipment is installed, it takes no more than 5 min to create the image stack. The processing of the DfF on MATLAB and subsequent Python coding  (Cou & Guennebaud, 2022)  can then be done within 15 min after setting the parameters using our non-optimized implementation.
ACKNOWLEDGEMENTS This study has been executed in the context of the " Smart 3D " project, which is part of the pilot project " La Fabrique du Caire Moderne ," coordinated by  Dr Mercedes Volait ,  InVisu  ( USR 3103 ),  CNRS/INHA. The authors gratefully acknowledge the support of the  Centre National de la Recherche Scientifique (CNRS)  for financial support. The authors also would like to thank the archaeologists for the samples that have been entrusted to IRAMAT- CRP2A  ( CNRS UMR 5060 ) and  Daniel Pierce  ( Université Bordeaux Montaigne ) for his invaluable help in writing and proofreading this article.
3 cm À1  (Liuzzi et al. , 2019) , the strongest Martian gas absorption lines can be measured in nadir mode. The global and local time coverage is much better than the SO channel (which is mainly limited to high latitude observations and regions along the terminator), which also means that the co-incident spectra can be averaged to increase SNR if required. NOMAD LNO continues to monitor the major seasonal cycles on Mars, extending existing datasets made by successive space missions in the past decades (e. g. Smith et al. , 2021). Global datasets of H 2 O and CO will be invaluable to monitoring changes in the atmosphere of Mars  (Vandaele et al. , 2015).
The SNR of Mars nadir and blackbody observations are too low, giving poorly constrained fits, and solar occultations and calibrations have high signal but only cover ~20 rows i. e. the width of the solar disk. The gas cells illuminated by the Globar, as measured during ground calibration, provide a good trade-off between SNR (the Globar peaks at 3 μm) and detector row coverage (almost 100 detector rows are illuminated). Using ground calibration data also allows us to check for instrument temperature effects, as measurements were made at five temperature setpoints. Examples of the detector smile are shown in Fig. 7 , for the same absorption at different instrument temperatures (horizontally, A-B and C-D) and for different diffraction orders at the same temperature (vertically, A-C and B-D).
All the strongest gas cell molecular absorptions measured during the ground calibration campaign have a similar shape, with a minimum spectral pixel around row 152 (i. e. the centre of the illuminated region). In total, the observed smile is around 0. 5 pixels in extent, however the Globar does not illuminate the entire field of view, and hence a smile of around 1. 25 pixels is a more realistic estimate over the entire illuminated detector region (i. e. rows 80 to 224). As the nadir data is vertically summed to improve SNR, producing a single spectrum per detector frame, the smile measured here will cause an absorption band to spread over an additional 1. 25 pixels, increasing the width of the instrument line shape. Differences between the detector smile when the instrument is cold and hot are small, and negligible when considering that the SNR of the LNO nadir channel is around 10.
First, an approximate wavenumberfrequency relationship was found in the lab, before the AOTFs were integrated into the instrument, where a monochromator was used to shine specific wavelengths of light through the AOTF and onto a detector. This was done for multiple AOTF frequencies, to correlate the AOTF peak transmission wavelength with driver frequency. This approximate relationship was uploaded to the instrument, which was then refined during ground calibration. In the thermal vacuum chamber, the gas cells were measured and an improved set of AOTF frequencies corresponding to each diffraction order were then uploaded to the instrument. Once in flight, further measurements were made of the Sun, using the AOTF frequency calibration derived on the ground, and the AOTF shape, the AOTF-frequency-to-central-wavenumber relation, AOTF-frequency-todiffraction-order relation and diffraction grating parameters were then determined using in-flight data for the LNO channel  (Liuzzi et al.
Temperature dependency of spectral calibration The in-flight diffraction order stepping observations are ideal for calibrating and checking the instrument, but in-flight the thermal environment and hence instrument temperature cannot be controlled (unlike in the thermal vacuum chamber). Therefore, to understand temperaturerelated effects, the ground calibration data are essential. In particular, the pixel-to-wavenumber relation is highly dependent on temperature, as the Fig. 9. LNO solar occultation saturation time. The shape is very similar to the SO channel, except that the increased slit width permits more radiation onto the detector, which subsequently saturates at a lower integration time. Fig. 10. Diffraction order 135 (3035-3059 cm À1 ) spectra of the CH 4 gas cell measured at different instrument temperatures.
This last parameter is calculated as: S ¼ πð r sun d sun Þ 2 (2) Where r sun is the radius of the Sun and d sun is the distance between the Sun and Mars (accounting for the non-circular orbit of Mars around the Sun). The LNO nadir field of view sweeps across the surface of Mars as TGO moves, and therefore the real zenith angle will change during the acquisition of a nadir spectrum. The SZA used here is calculated as the From equation (1) above, the reflectance factor calculation requires a solar spectrum measured in the same conditions as each nadir observation. Observing the raw data (e. g. Figs. 10 and 11), it is clear that the absorption lines shift on the detector as the instrument temperature changes. The LNO channel can typically be any temperature between À15C and þ5C during a nadir observation, and so there are insufficient solar observations to cover all possible temperatures.
Therefore, we use all the solar spectra available, taken at different temperatures, and interpolate between them to create a synthetic solar spectrum for any instrument temperature. By using the LNO data itself to calibrate the channel, we can be sure that instrumental effects, such as temperature, are accounted for in the calibration. The LNO solar spectra are acquired using the calibration mode (final row in Table  1 ) which returns each pixel value individually, without binning. Only the centre lines on the detector are considered, where the fields of view are centred on the Sun and are fully encompassed by the solar disk; this is done so that the spectra are independent of the Sun-Mars distance, which changes throughout the mission. The detector sensitivity has been constant throughout the missionfurther analysis of this can be found in the companion paper  (Cruz-Mermy et al.
14 ), to make a synthetic solar spectrum for the same  Next, the same principle is applied to the nadir data: the approximate spectral calibration is calculated from the instrument temperature, which is then improved by fitting to solar and/or molecular absorption lines in the spectra for those orders that contain such absorptions (Fig. 15, C ). The quality of the LNO dayside nadir data varies depending on the measurement parameters used and the solar zenith angle, which varies from 0 to 90 as the TGO orbit precesses. Also, within an observation, the solar zenith angle changes as the observation begins at high northern/ southern latitudes, crosses the equator, and ends at high southern/ northern latitudes. If the data are too noisy, the absorption line fit will be poor, and therefore the spectral calibration could be shifted away from the correct value, and be worse than the calculated values.
e. the SNR. Following the radiometric calibration procedure described above, it is clear that some steps will contribute more to the total uncertainty than others. The radiometric calibration uses data acquired by the LNO channel to calibrate the LNO nadir data, which minimises any systematic optical or detector effects. The SZA in equation (  1 ) is calculated with SPICE kernels  (Acton, 1996)  from the reconstructed TGO orbit, and a 4 pixel per degree digital shape kernel is used to accurately determine the angle between Sun and the mean slope of the surface being observed, giving the most accurate value possible. An error of even 1 in SZA would only give a small bias to the reflectance factor: for example the relative percentage difference between cos(45 ) and cos(  44 ) is 1. 7%, and less for smaller angles.
Other results also agree between the two papers, such as the temperature-induced pixel shift, even though the two calibration methods have different approaches. The LNO calibration here includes no correction to the continuum shape, and hence all surface, cloud and atmospheric features are preserved in the data. The companion paper analysis  (Cruz-Mermy et al. , 2021, this issue)  uses a continuum removal technique to flatten the spectra, and the results confirm that when the LNO blaze and AOTF functions are simulated and the derived ILS is used, the resulting continuum-removed solar spectra match well with simulations. To use the dataset presented in this work for atmospheric retrievals, such as for fitting to H 2 O or CO lines, a continuum removal method e. g. (Eilers and Boelens, 2005)  should be used to remove the effects of the surface and dust/aerosols from the spectra.
Applications With all LNO data converted to reflectance factor, further analysis can be performed such as molecular retrievals, dust/opacity studies and surface composition studies. The reflectance factor data presented here was used to derive maps of the CO distribution  (Smith et al. , 2021). This dataset can also be used for water vapour distribution studies. By removing the molecular absorption lines and calculating the mean continuum reflectance factor of each LNO nadir spectrum, a map of surface reflectance can be produced such as that shown in Fig. 16. The resulting map matches the TES albedo map well, once a correction has been applied to the TES data to convert the bolometric albedo values to reflectance factor albedo at the wavelength of the chosen diffraction order. This correction is derived from a comparison of TES and OMEGA data of the same spectral range, where reflectance factor for order 167 is approximately equal to 0.
These features are retained in the LNO nadir calibration dataset presented in this work, so for retrievals of atmospheric gases (e. g. H 2 O or CO) either a continuum removal method should be applied to the nadir spectra to flatten the spectra  (Smith et al. , 2021) , or surface and dust/aerosol spectral features should be incorporated into the retrieval forward model. Conversely, the spectra of (Cruz-Mermy et al. , 2021, this issue) can be used directly for retrievals of atmospheric gases but not for analysis of other spectral features.
Data availability At the time of writing, SO occultation and UVIS occultation and nadir calibrated datasets are available on the ESA Planetary Science Archive  (Besse et al. , 2018)  at https://psa. esa. int/for all data since the beginning of the nominal science mission (21 st April 2018) up to 2020, with more recent data delivered regularly. LNO, UVIS limb, and calibration datasets for all channels are under preparation and are expected to be released to the public soon. The peer-reviewed EAICD (experiment-to-archive interface document), written by the lead author of this work, is available on the ESA PSA and describes the data archived there in much more detail.
Funding This project acknowledges funding by the  Belgian Science Policy Office (BELSPO) , with the financial and contractual coordination by the  ESA Prodex Office  ( PEA 4000103401 ,  4000121493 ), by  Spanish Ministry of Science and Innovation (MCIU)  and by European funds under grants  PGC2018-101836-B-I00  and  ESP2017-87143-R (MINECO/FEDER) , as well as by the  UK Space Agency  through grants  ST/V002295/1 ,  ST/ V005332/1  and  ST/S00145X/1  and  ST/R001405/1  and  Italian Space Agency  through grant  2018-2-HH. 0. This work was supported by the Fig. 16. Top: LNO continuum level for diffraction orders 167-170 (those typically used for H 2 O mapping), binned onto a 1 Â 1 grid. The surface albedo map matches well to the TES bolometric albedo map (bottom ). Funding acquisition. Frank Daerden: Investigation.
Geographical scale might be expected to impact significantly the efficiency of DNA barcoding as spatially comprehensive sampling provides opportunities to uncover intricate relationships among closely related species and to detect cryptic diversity for widespread taxa. Here, we present a DNA barcoding study on a Xencyprididae subfamily (Culterinae) involving the production of 998 newly generated DNA barcodes from East Asian drainages (80 localities). Together with 513 barcodes mined from BOLD and GenBank, a reference library consisting of 1511 DNA barcodes (116 localities) for 42 species was assembled, accounting for 66% of known Culterinae species. Intraspecific genetic distances are positively correlated to geographical scale, while a negative correlation is detected between interspecific genetic distances and geographical scale.
| DNA sequencing, data preprocessing and assembly Genomic DNA was extracted using the Genomic DNA Isolation Kit (Axygen) according to the manufacturer's instructions. The standard 652-bp fragment from the 5′ end of the mitochondrial cytochrome c oxidase subunit I gene (COI) was amplified using the fish universal primers FishF1 and FishR1  (Ward et al. , 2005). Amplifications included an initial denaturation step at 95°C for 5 min followed by 30 cycles of denaturation at 95°C for 1 min, annealing at 50°C for 45 s, and extension at 72°C for 45 s followed by a final extension at 72°C for 10 min. All amplified fragments were purified using 1. 0% low-melting agarose gel electrophoresis and bidirectionally sequenced with the same primer pair using an ABI PRISM 3700 (Applied Biosystems) automatic DNA sequencer.
COI contigs were checked and assembled using the SEQMEN procedure in the laser- gene package (DNASTAR). Sequences were aligned and trimmed to the same length using mega version 6. 0  (Tamura et al. , 2013)  and further translated into amino acids to check for the potential occurrence of stop codons. Aligned sequences, primer pairs, trace files, taxonomic information and collection data were deposited at the Barcode of Life Data system (BOLD;  Ratnasingham & Hebert, 2013)  in the project CUBAR "Barcodes of Culterinae species" (dx. doi. org/10. 5883/DS-CUBAR). Alongside newly generated DNA barcodes, DNA barcode records belonging to Culterinae species were mined from GenBank and BOLD, where sample sources were available (Table  S1 ) and sequences exceeded 600 bp.
RESL analysis was used to produce Barcode Index Numbers (BINs) as implemented in BOLD. ABGD analysis was performed on the web interface (www. abi. snv. jussi eu. fr/publi c/abgd/) using the default value for the relative gap width (X = 1. 5) and K2P genetic distance. PTP in its multiple rates version was run using the web server (http://mptp. h-its. org). As the mPTP algorithm needs a phylogenetic tree as an input file, a maximum-likelihood (ML) tree was built using raxml-vi-hpc  (Stamatakis, 2006). ML analyses were conducted using the GTR + I + Γ model, according to the model selection procedure implemented in mrmodeltest  (Nylander, 2004). Single-and multiple-threshold GMYC analyses were conducted using a web server (http://speci es. h-its. org/gmyc/). As GMYC requires a fully resolved, ultrametric gene tree as input for the analysis, we reconstructed a Bayesian tree using beast version 1.
8. 1  (Drummond & Rambaut, 2007). Bayesian reconstructions were conducted using a Yule pure-birth model and GTR + I + Γ substitution model. Duplicated sequences were collapsed into haplotypes using alter  (Glez-Pena et al. , 2010)  prior to running beast analyses. An uncorrelated relaxed lognormal clock model was used with the rate estimated from the data and ucld-mean parameters with a uniform prior value of 0 as a lower boundary and 10 as an upper boundary. All other settings were kept as the default values. Markov chain Monte Carlo (MCMC) runs were performed using 50 million generations, sampled every 1000 trees. Stability around unimodal posteriors and effective sample sizes (ESS) for all parameters were assessed using tracer version 1. 5  (Rambaut & Drummond, 2007). After removing 50% of the trees as burn-in, trees were summarized in a maximum credibility tree using treeannotator version 1.
| RE SULTS Within 998 newly acquired samples between 2010 and 2020, 26 Culterinae species, belonging to 13 genera, were delimited and identified based on their external morphology. Among them, 998 DNA barcodes were successfully produced. All the sequences were above 600 bp in length without stop codons or insertions, indicating collected sequences represent functional coding regions. Alongside newly generated DNA barcodes, 513 DNA barcodes belonging to 35 Culterinae species were mined from GenBank and BOLD (Table  S1 ). After aligning newly generated and mined sequences, the final alignment consisted of 602 bp for 1511 specimens from 116 locations, covering most drainages in East Asia (Figure  2 ), and corresponding to 42 species and 15 genera (Table  S1 ). The number of sequences per species ranged between one and 261, with an average of 34, originating from two to 38 sampling sites (Table  1 ).
| DISCUSS ION The present study provides the first comprehensive DNA barcode reference library of the subfamily Culterinae, including 42 species (~66% of known Culterinae species) and covering most major East Asian watersheds  (Luo & Chen, 1998). Notably, all Anabarilius species and several monotypic genera such as Pogobrama and Hainania are missing. These species have very restricted distribution ranges and little information is available regarding their abundance and ecology  (Jiang et al. , 2016; Luo & Chen, 1998 ). In addition, DNA sequences are scarce for these species in international repositories such as GenBank, EMBL and BOLD. By contrast, most widespread species were aptly covered, with multiple individual sequences originating from different East Asian drainages, which allows assessment of the impact of geographical scale on the performance of DNA barcoding in this subfamily.
Riverine transport of particulate organic carbon (POC) associated with terrigenous solids to the ocean has an important role in the global carbon cycle. To advance our understanding of the source, transport, and fate of fluvial POC from regional to global scales, databases of riverine POC are needed, including elemental and isotope composition data from contrasted river basins in terms of geomorphology, lithology, climate, and anthropogenic pressure. Here, we present a new, open-access, georeferenced, and global database called MOdern River archivEs of Particulate Organic Carbon (MOREPOC) version 1. 1, featuring data on POC in suspended particulate matter (SPM) collected at 233 locations across 121 major river systems. This database includes 3546 SPM data entries, among them 3053 with POC content, 3402 with stable carbon isotope (δ 13 C) values, 2283 with radiocarbon activity ( 14 C) values, 1936 with total nitrogen content, and 299 with an aluminum-to-silicon ratio (Al / Si).
, 2015; Hilton et al. , 2008; Coppola et al. , 2019; Hemingway et al. , 2019; Eglinton et al. , 2021) , there is still a lack of quantitative constraints on the effect of environmental drivers on the carbon isotopic composition of riverine POC. The recent release of the International Soil Radiocarbon Database (ISRaD)  (Lawrence et al. , 2020)  has enabled us to improve Earth system models aiming to predict global SOC radiocarbon distribution and turnover time  (Shi et al. , 2020; Carvalhais et al. , 2014). However, such prediction is still hampered for fluvial POC, despite existing capabilities for modeling water discharge, SPM concentration, and POC content based on global water quality datasets  (Ittekkot, 1988; Ludwig et al. , 1996; Meybeck, 1993) , such as the WBMsed global hydrology model  (Cohen et al.
, 2014)  or Global NEWS2  (Mayorga et al. , 2010). Recently, owing to the improved water quality datasets, other sophisticated river biogeochemistry models have been built to understand riverine carbon cycling and environmental inturbations, such as the regional process-based Dynamic In-Stream Chemistry module (DISC-CARBON), but they still focus on different carbon fluxes  (van Hoek et al. , 2021). Here we provide a new database for riverine POC, called MOREPOC (for MOdern River archivEs of Particulate Organic Carbon) v1. 1, compiling 2283 14 C data, thereby representing a significant update of the previously reported global dataset by  Marwick et al. (2015)  with 531 reported 14 C measurements. MOREPOC v1. 1, featuring data published in international, peer-reviewed articles, provides the basis for (1) uncovering the fundamental mechanisms of preservation and alteration of river POC (in terms of "bulk" POC as well as for the individual POC bio and POC petro pools) and (2) helping with the construction of numerical models able to simulate the isotopic compositions of POC in the context of global change.
The MOREPOC database is publicly available on the Zenodo repository at https://doi. org/10. 5281/zenodo. 7055970 (Ke et al. , 2022). 1 ), and 299 with aluminum-to-silicon mass ratios (Al / Si). In addition, reported analytical uncertainties for POC content, δ 13 C, and 14 C are included in MOREPOC. Note that riverbed or bank sediments are not included in this database. We selected studies reporting at least one carbon isotopic datum and those with paired elemental and dual carbon isotopic values. Studies reporting only POC contents were not compiled into MOREPOC v1. 1. Potential mistakes generated during the compilation of data entries were carefully checked, and duplicate data were removed. A supplementary table, "MORE-POC_RM", is provided to give additional information on the references, sampling method of SPM, filtration strategy, and carbonate removal methods and detailed information for the types of acid used to remove carbonate, etc.