dataesr/scientific-paragraphs-categorization huggingface dataset:
As illustrated in Figure  2 , a simple form of the experimental design can be captured in mzTab-M using a combination of assay, "study_variable", and "sample". In a complex, nested design, linkages between different study variables are not explicitly modeled but captured through the annotated values, as shown in the Supporting Information. The MTD table also has the (optional) capability to capture additional metadata that can be useful to interpret the study, such as limited details about the sample processing steps performed, the MS instrument, software and parameters, contact details for the study producers, etc. However, it is acknowledged that other formats may capture such details, such as referenced mzML (including instrument information and parameters), other MS data file formats, or ISA-Tab files (containing experimental design and sample processing), which may be more appropriate locations for such information.
After the header row, each row reports one molecule, with the first cell containing "SML", followed by the data values for each specified column. The columns include a unique local identifier for the molecule (SML_ID), followed by a cell (SMF_ID_REFS) containing references to features in the SMF table. The referenced features are the different adduct forms or in-source fragments of the molecular features actually detected by MS. The next set of columns provides different ways to identify the molecule (database_identifer, chemical_formula, smiles, inchi, chemical_name, uri, theoretical_neutral_mass; see section Identif ication evidence and ambiguity below). The following columns report quantitative data for the n assays (in n columns, where n is the count of assays reported in MTD) and the m study_variable groups (in m columns) e.
g. as an average (e. g. , mean) across assay values within that study_variable. A value can also be provided for the variability in the study_variable quantification value reported e. g. a standard error value. A parameter in MTD specifies how to interpret the quantitative values in these columns in terms of a data type exported from a specific piece of software or where appropriate, absolute values with units. At the right-hand end of the SML table (and SMF and SME tables), it is possible to include user-specified (optional) columns, with a method for annotating that the columns refer to the entire molecule, or the measurement of the molecule in particular assays or study_variables. The user-specified columns thus make mzTab-M extensible to support custom data types not covered in the core model.
The SMF table next contains information about the type of adduct and charge state observed, the experimental m/z value, the retention time of the feature (in a master or averaged run), and a method for optionally specifying if a given isotopomer has been quantified (+1 or +2 peak,  13  C peak, etc. ) as used in some isotopic labeling/flux studies. The following columns represent the quantitative data within each of the n assays recorded in the MTD section. For SML, a parameter in MTD also describes how to interpret the quantitative values recorded. Small Molecule Evidence (SME) Table. The SME table represents strands of potentially heterogeneous types of evidence supporting the identification of a molecule (Figure  1D ). Each row contains the result of one identification process (library search, pattern match, manual curation, etc.
). The header of the table starts with "SEH" followed by a set of columns. The second column is a local identifier for a row of evidence (SME_ID), followed by a local identifier for the input data to the process (evidence_input_id). evidence_input_id is needed for the cases where different rows of evidence are reported for the same input data (MS 2 spectrum, accurate mass + retention time, isotope pattern, etc. ). They can be linked by sharing the same value for evidence_input_id. As in the SML table, a set of columns exists to specify the molecular identity from a variety of sources or identifier types (database_identifer, chemical_formula, smiles, inchi, chemical_name, uri). The experimental m/z value of the feature, the charge, and the theoretical m/z value (e. g. , from a database) can be recorded, along with scores or confidence measures coming from the software used to support the identification.
If a fragmentation spectrum has been used, there is a mechanism for referencing the exact spectrum in the source file (e. g. , mzML file) and the MS level of the input data to the identification process. Identification Evidence and Ambiguity. Small-molecule identification is a well-known challenge in MS metabolomics, and even more so in MS lipidomics, where complete structural elucidation of molecules is often not possible. Different levels of "identification" might be possible, ranging from having the accurate mass only, the chemical formula, a list of possible identifiers to molecules in a database (with the same or different formula), or a complete molecular structure resolved: e. g. , if a complementary technique such as NMR has been used. mzTab-M has been designed to accommodate all the different possibilities in a simple yet flexible structure (Figure  3 ).
For further details on how identifications of lipids and other compound classes can be represented see the Supporting Information. In a row of the final results (SML table), the export software can include one or more identifiers from external databases: e. g. , "CHEBI:16811" where the prefix is defined in MTD as referencing the ChEBI database  24  (with a URL) and the identifier is the ChEBI unique identifier (in this case for methionine). Similarly, the specification allows for the chemical formula in standard notation, simplified molecular-input lineentry system (SMILES  25  ), or InChi 26 to be provided. In all cases, if ambiguity has not been resolved, then a Pipe "|" separated list of identifiers can be provided in the same cell. There are several measures for describing the confidence of identification, including the use of reliability codes such as those developed by the MSI  11, 12  and the score or confidence measures from identification software where available.
To trace the evidence source, references via the features (SMF table) and on to the SME table should be provided. In the case that adduct grouping (i. e. , multiple SMF rows) has been performed prior to identification, then the different SMF rows will reference the same SME rows. At the SME level, if there are different rows from the same input data (e. g. , different database matches), then it is expected that the SMF element(s) references multiple SME elements that share the same value for evidence_input_id. It is also possible to report different evidence streams to support identification, such as searches in different libraries. As such, SMF rows can reference multiple SME elements carrying different values of evidence_input_id. Given that these two cases would both result in multiple SME identifiers referenced from an SMF row, an extra code can be provided at the SMF level (SME_ID_REF_ambiguity_code) containing values to differentiate whether ambiguity has been resolved or still remains (see the specification document for a full description).
Using CVs and File Validation. mzTab-M extensively uses CVs to provide unambiguous terms for annotation. For parameters relating to MS and associated processing, CV terms should generally be sourced from the PSI MS CV. 27  Several other CVs are recommended for describing details about sample types, species taxonomy, sample preparation, etc. (see the specification document). To ensure that valid CV terms are used, we have extended the concept of the PSI semantic validation framework. 28 The framework includes a mapping file that states the groups of CV terms allowed at each position in mzTab-M, enabling the list of terms to expand over time, without changes in the standard or software. New terms can be added straightforwardly by making a request on a mailing list: e. g. , for a term describing new software, scores, or statistics.
A crucial part of the standard is therefore a validator to ensure that files exported from different packages fulfill the rules defined in the specification, so that they can be read without error by other software. We have developed validation software for mzTab-M, available from jmzTab (project: https://github. com/lifs-tools/ jmzTab-m), which checks not only that the structure of the file is correct but also that valid and correct CV terms have been used throughout. Implementation in Software and Databases. The specifications have been verified by both PSI and MSI formal review processes, from which the stable version (mzTab-M 2. 0) has been released. It is not expected that there will be changes to the format for several years to allow implementations to be developed. A reference implementation with parser, writer, and validator (in jmzTab-m) has been developed in Java (as for mzTab 1.
0  29  ). jmzTab-m provides an OpenAPI 2. 0 compatible API model that serves as the basis for automatic model generation in a wide number of programming languages (C++, JavaScript, R, Python), reducing the burden of implementation. The library provides parsing, validation, and writing of mzTab-M files and object models. A web-based application (https:// apps. lifs. isas. de/mztabvalidator/) provides a user-friendly user interface to perform standard and semantic validation and to display validation results. Additional implementations are under development in software including XCMS,  30  Progenesis QI (Waters), Lipid Data Analyzer,  31  OpenMS,  32  and Metabo-Lights. 15 Over the coming years, we will be promoting the implementation of the standard in a wide variety of both opensource and commercial software to act as a universal standard for metabolomics and lipidomics.
■ CONCLUSIONS We have developed mzTab-M for metabolomics data representation and sharing. The standard has been developed in an open process with widespread consultation of different approaches taken in the field and involvement of software teams from academic research groups as well as industry. The standard has undergone a rigorous peer review process by both the MSI and PSI to ensure that the resulting standard is of high quality and is stable. The standard is expected to remain stable for several years, except for improvements to documentation and extensions to the CV, allowing research groups and commercial developers to invest time in the implementation. We also encourage other groups interested in standardizing omics data, particularly those using MS (e. g. glycomics), to adopt the mzTab model/design, CV infrastructure, and associated software.
AUTHOR INFORMATIONCorresponding Authors *E-mail for R. M. S. : Salekr@iarc. fr. *E-mail for S. N. : sneumann@ipb-halle. de. *E-mail for A. R. J. : andrew. jones@liverpool. ac. uk. ACKNOWLEDGMENTSN. H. acknowledges funding by the Ministerium fur Kultur undWissenschaft des Landes Nordrhein-Westfalen, the Regierende Burgermeister von Berlin-inkl. Wissenschaft und Forschung, and the Bundesministerium fur Bildung und Forschung (de. NBI/BMBF 031L0108A). S. N. acknowledges funding by the Bundesministerium fur Bildung und Forschung (de. NBI/ BMBF 031L0107). S. N. , P. R. -S. , K. H. , and R. M. S. acknowledge funding from PhenoMeNal (H2020-EU. 1. 4. 1. 3 grant no. 654241). A. R. J. acknowledges funding from the BBSRC (BB/ M020282/1, BB/L024128/1, BB/K01997X/1). J. T. M. P. was supported by the Medical Research Council and National Institute for Health Research UK through funding for the Imperial College MRC-NIHR Phenome Centre, MRC grant number MC-PC-12025.
ACKNOWLEDGMENTS The authors thank the  Agence Nationale des Bourses du Gabon  (No. 2016. 101326/PR/ANBG/CT ) and  Campus France  for the Ph. D. grant of KISK. The authors also acknowledge the financial assistance of the  Union Européenne  and  Région Occitanie  through the  Chia-Innov project (Convention Région  RECH n • 16004168).
6 /120 1. 787  [32]  /120 3 57-4 /120 = 57-6 /120 3 5 2. 34  [33]  /120 3 7-64 /120 = 7-/120 6. 73  [33]  /120 3 27-64 /120 = /7-0 6  likely that breakage of the crystal lattice will affect the lanthanide polyhedrons. A monazite slab with an exposed (100) facet was generated using the VESTA program  [34]. This model is presented in Fig. 8. To make the model easier to read, the atomic radii were decreased by 50%. As shown in the 3D model, the lanthanide polyhedrons exposed on the mineral surface are missing one or two of their nine oxygen sites. Based on this under-coordination, the lanthanide ions may form chemical bonds with water molecules, media species, and dissolved species to restore their nine-fold coordination shells. In the case of carbonate minerals, studies have shown that under-coordinated ions on such mineral surfaces may be subjected to reaction mechanisms similar to those affecting dissociated ions in the bulk  [11, 12].
Acknowledgements This research was funded by the  Carnot Institutes ICEEL and BRGM  through the  TERRAFINE Inter-Carnot Action  (Carnot-ICEEL no. 118-IC  and  IC-BRGM  no. 2013-01 ). Financial support from  LabEx RESSOURCES21  is also acknowledged (contract Investissements d' Avenir  no. ANR-10-LABX-0021 ). The authors would like to thank  Odile Barres  ( GeoRessources ) for her expertise in FTIR spectroscopy and  Pierric Hubert (GeoRessources)  for his assistance with XRD analysis.
Acknowledgements Financials upport from the  Deutsche Forschungsgemeinschaft , the  Julius-Maximilians-UniversitätW ürzburg  and the  Netherlands Organisation for Scientific Research (NWO)  is gratefully acknowledged. D. K. R. is grateful for ap ostdoctoralf ellowship from the  Science and Engineering Research Board  (Award no. SB/OS/PDF-052/2016-17 ) of India.
While pointings #2 and #3 coincide well with compact CO peaks observed with ALMA, pointing #4 is somewhat offset by a few arcseconds with respect to the ALMA clump. Given the GREAT beam size (14. 4 ; Sect. 2. 1), part of the spatially offset CO cloud emission is expected to contribute to the GREAT pointing #4. Figure  4  also shows the comparison between MAGMA and ALMA spectra. Overall, there is good agreement between the two datasets over a 45 resolution, with the ALMA spectra showing a drastic S/N improvement. We also show the ALMA spectra calculated for a 14. 4 resolution (i. e. , similar to GREAT). On the one hand, ALMA spectra at 14. 4 and 45 resolution are similar for pointing #2, confirming that most of the emission originates from a cloud smaller than 14. 4 with no significant contamination from nearby clouds.
VLT/GIRAFFE Optical spectroscopy is used to examine tracers of the ionized gas. We use archival ESO/VLT/U2 GIRAFFE observations with the MEDUSA fiber system feeding component. GIRAFFE is a medium-high (R = 5 500-65 100) resolution spectrograph in the 3700 -9500 Å wavelength range. The MEDUSA fibers allow up to 132 separate objects (including sky fibres) to be observed in one go. Each fiber has an aperture of 1. 2 on the sky. The sky-subtracted spectra from program 171. D-0237 were downloaded from the GEPI GIRAFFE archive. We examined in particular Hα observed with the HR14a grating with R = 18 000 (≈ 17 km s -1 ), and [Ne iii] 3868Å observed with the HR2 grating with R = 19 600 (≈ 15 km s -1 ). Some details on the dataset can be found in  Torres-Flores et al. (2015). Most GREAT positions could be associated with a nearby GIRAFFE fiber position, except #12.
The H i profile is always much broader than the CO and [C ii] profiles, with FWHM in the range ≈ 16 -40 km s -1. Similar results were found in various star-forming regions within nearby galaxies  (Braine et al. 2012; de Blok et al. 2016; Requena-Torres et al. 2016; Okada et al. 2015; Fahrion et al. 2017). We verified that the difference in the profile line width between H i and CO is not due to the spatial resolution by matching both datasets. However, the wider H i profile as compared to [C ii] is likely driven by the difference in spatial resolution. The H i spectra, taken with 60 resolution (Sect. 2. 3), include the emission of clouds outside the GREAT beam. The profile decomposition will allow us to mitigate the biases due to different beam sizes (Sect. 4). Whether from the spectral profiles (Fig.
We now revisit this finding by extending the measurement of ([C ii]+[O i])/PAH to all PACS maps in LMC-N 11. Since there is no mid-IR spectra available for all pointings in N 11, we use the IRAC photometry bands to evaluate the PAH emission. We refer to  Lebouteiller et al. (2012)  for the method. In short, we use the Spitzer/IRAC photometry data points to identify and flag out stellar emission, to estimate and correct for the dust continuum, in order to provide the emission of PAHs either in the IRAC 5. 8 µm band (corresponding to the PAH 6. 3 µm feature) or in the IRAC 8. 0 µm band (corresponding to the PAH 7. 7 + 8. 6 µm features). Results are shown in Figure  7 , where it can be seen that the cooling rates provided by sion arising from the ionized phase. Potential PAH emission in the ionized gas is ignored as it is plausible that they are photodestroyed (see e.
g. ,  Okada et al. 2019). We decided to use a statistical approach instead, by adjusting the various profiles simultaneously with velocity components not being fixed or inferred from any other specific profile. Any given component is defined by its velocity and line width, while the component intensity is determined independently for each CO, [C ii], and H i. The sum of the components reproduces the global CO, [C ii], and H i profiles. We also performed decompositions allowing potentially different line widths for each tracer for any given velocity component, but the main results shown in the following remain unchanged. We use a Bayesian approach with the Markov Chain Monte Carlo (MCMC) PyMC3 code  (Salvatier et al. 2016 ) along with the Metropolis-Hastings sampling algorithm. Parameters are described in Table  6.
Acknowledgements. Based on observations made with the  NASA/DLR Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is jointly operated by the  Universities Space Research Association, Inc. (USRA) , under  NASA  contract  NAS2-97001 , and the  Deutsches SOFIA Institut (DSI)  under  DLR  contract  50 OK 0901  to the  University of Stuttgart. This paper makes use of the following ALMA data: ADS/JAO. ALMA# 2012. 1. 00532. S and ADS/JAO. ALMA# 2013. 1. 00556. S. ALMA is a partnership of  ESO  (representing its member states),  NSF (USA)  and  NINS (Japan) , together with  NRC (Canada)  and  NSC and ASIAA (Taiwan)  and  KASI (Republic of Korea) , in cooperation with the  Republic of Chile. The Joint ALMA Observatory is operated by  ESO ,  AUI/NRAO  and  NAOJ. V. Lebouteiller  wishes to thank  S.
4 Five years later, Rüdorff described the rst layered structure in the system and wrongly assigned it the NaHF 2 type [modern prototype according to the Inorganic Crystal Structure Database (ICSD): CrOOH(R 3m)]-not yet aware of its hydrogen positions. 5 Reliable sodium positions were not established before the rst systematic study in 1971. 6 Today, ve kinds of Na-Ti-S compounds can be distinguished: The structure of the intercalates Na x TiS 2 with 0 < x # 1 consists of 2 N [TiS 2 ] xÀ sandwich layers with sodium ions in between. The compounds exist in four different structurally elucidated stacking variants: the polytypes 2H, 3R 1 , 3R 2 , and 6H (see Table  1  and Fig. 1 ). With these materials, the remaining article is concerned. The excess-titanium compounds Na x Ti 1+d S 2 with 0 < d # 1 3 and 0 < x # 1 À 3d contain additional titanium ions in intercalation layers, which hinder diffusion of the otherwise mobile sodium ions.
For Na1 at 600 and 700 C, anharmonic displacement was observed. Terms up to the fourth order were tested and only kept in renement if they were signicant (|C ijk | $ 3s[C ijk ]) and led to a signicant drop in R values. Thus, two additional unique parameters C 111 (Na1) and C 333 (Na1) were rened. Towards the end of renement, z(Na1) was found to be within a 3s interval of 1 6 (coplanarity of sodium ions) and was xed at this value, yielding slightly better residuals despite one free parameter less. Structure graphics were produced using Diamond 4. 5 and VESTA. 34, 35 Renement results are summarized in Table  2. Diffraction datasets are available in the ILL repository. 36 CSD 1942255 to 1942259 contain the supplementary crystallographic data for this paper; these data can be obtained free of charge from FIZ Karlsruhe via https://www.
Acknowledgements Financial support by the  Deutsche Forschungsgemeinscha  ( SPP 1613 ,  LE 781/13-2 ) is gratefully acknowledged. The article processing charge was covered by  FILL2030 , a  European Union  project within the  European Commission's Research and Innovation programme Horizon 2020  under grant agreement no. 731096. We thank  Dr Stefan Berendts  for XRF analyses and temperature-dependent XRD,  Dr Suliman Nakhal  for the synthesis of TiS 2 -1T,  Ms Juana Krone  for sulphur and hydrogen determination, and  Ms Iris Pieper  for sodium determination.
Former  (Komasa et al. 2011 ) and present calculations show that the energy of the v=2, J=29 level is not bound so that the transition is misidentified. Our present computations report a closebye transition at 2. 1784 µ corresponding to (8-5) S(  14 ) with a very low emission probability of 2. 52 10 -11 s -1 , which appears not realistic. The H 2 quadrupole transition wavenumbers and corresponding emission probabilities are also displayed in the HITRAN database  (Gordon et al. 2017). We have checked the overall agreement between our computations and those displayed in the HITRAN database. The transition wavenumbers values are restricted to four significant digits in HITRAN whereas the quoted uncertainty reported in the present work is variable and spans an interval between a few 10 -3 and a few 10 -6 cm -1 , so that some differences in the last digits can be obtained.
Acknowledgements. We thank the referee for his(her) pertinent suggestions which helped to improve the paper. Part of this work was supported by the  Programme National de Physique et Chimie du Milieu Interstellaire (PCMI)  of  CNRS/INSU  with  INC/INP  co-funded by  CEA  and  CNES. The computational part of this work was supported by  NCN (Poland)  grant  2017/25/B/ST4/01024  as well as by a computing grant from the  Poznan Supercomputing and Networking Center.
Funding: This work was funded by  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie Innovative Training Network-MIGRATE (Miniaturized Gas flow foR Applications with Enhanced Thermal Effects ), grant agreement No. 643095  [ H2020-MSCA-ITN-2014 ]. This work has also received funding from the  Clean Sky 2 Joint Undertaking  under the European Union's  Horizon 2020 research and innovation program  under grant agreement No  687014  ( MACAO  Project).
Methods and Computational details Structural optimization, harmonic frequencies, IR intensities, and anharmonic frequencies issuing from second order perturbative approach (VPT2) and ab-initio molecular dynamic simulations were performed with Gaussian 09 program  [26]. Spectral analysis from the MD simulations was obtained using the VAMD (Vibrational Asignments in Molecular Dynamic) program developed in our group and described in reference  [27]. Electronic structure calculations were performed at the DFT level using the most common three parameter hybrid functional of Becke (B3LYP)  [18]  and a valence double zeta Pople basis set including diffuse and polarization functions, 6-31+G(d,p). This model chemistry was chosen since it has been previously shown that, for the prediction of harmonic and anharmonic force constants and in the case of small organic  [18, 28, 29]  and radical  [30] , systems it is able to recover the results obtained using the more expensive CCSD(T)  [31] /Aug-ccp-VTZ  [32]  approach.