dataesr/scientific-paragraphs-categorization huggingface dataset:
The inuence of the atomic H I (656. 10 nm), Ca I (318. 13 nm and 643. 91 nm) and ionic Ca II (458. 52 nm) lines has been evaluated with a quaternary diagram (Fig. 2 ESI † ). Note that the secondary crystallizations seem close to the geological phase but intermediate with the micritic crystallization of the binder. The same treatment was then applied to two other datasets (samples M2 and M3). These samples have been characterized in great detail in a previous article. 24 Our objective was to evaluate the robustness of the methodology on an extended measurement period. Indeed, the LIBS measurements in M1 are about one year behind those in M2 and M3. Besides, during this time, the micro-LIBS instrument moved to another building and had to be totally recongured and optimized. M2 and M3 also differ in their preparation.
Conclusion In this paper, we have demonstrated that the use of an ANN algorithm for the processing of LIBS imaging data may be helpful as much as powerful. Even a simple network structure, a 3-layer perceptron with 80 neurons in total, can provide a fast, automated, robust, and efficient processing for a large number of spectra. Its optimization points out that the ANN robustness does not depend so much on its own parameters (neuron number in the hidden layer, iteration number for the training, and spectra normalization) as on the quality of the reference dataset for training. The accuracy of the nal identication is also improved by the use of a threshold on output values, to allow as much identications as possible and avoiding misrecognition. In particular, for mortar characterization, ANN provides good identication of spectra thanks to a specic training on nearly 1000 spectra which has been validated on a 300 spectra set.
It allows us to supply in an automatic way a mask of each mineral phase present on the mortar surface, depending on the component categories we implemented. Furthermore, it clearly differentiates the calcium carbonates from the binder and from other origins (geological especially and secondary phase probably) that may be due to the difference in the densities of each one (quantity ablated and plasma parameters), as well as the physisorption of H 2 O in the binder (micro)porosity. It allows us to precisely map the mortar and determine where the lime binder of interest for radiocarbon dating is. Nevertheless, ANN treatment is limited by the training dataset; to improve its capacity of mineral identication, it will be necessary to implement more data and a broader reference dataset in terms of their mineralogical nature.
Acknowledgements This work was partially supported by the  French region Rhônes Alpes Auvergne (Optolyse ,  CPER2016 ), the  French "Agence Nationale de la Recherche " ( ANR-22-xxx  " MEMOAr " and  ANR-20-CE17-0021  " dIAg-EM ), and the  French government "France 2030" initiative , under the  DIADEM program  managed by the  "Agence Nationale de la Recherche " ( ANR-22-PEXD-0014 , "Libelul"). This project has also received nancial support from the  CNRS  through the  MITI interdisciplinary programs ("CaPhyMOAr "). In addition, we gratefully acknowledge  Dr Frédéric Pelascini  from the  Cétim Grand Est  and  Dr Florian Trichard from Ablatom , for fruitful discussions.
MALDI FTICR analysis Desalted peptides (1 µL) were deposited on 384 ground steel MALDI plates (Bruker Daltonics, Bremen, Germany), then 1 µL of HCCA matrix at 10 mg/mL in ACN/H2O 70:30 v/v 0. 1% TFA was added for each sample spot and dried at room temperature. MALDI FTICR experiments were carried out on a Bruker 9. 4 Tesla SolariX XR FTICR mass spectrometer controlled by FTMS Control software and equipped with a CombiSource and a ParaCell (Bruker Daltonics, Bremen, Germany). A Bruker Smartbeam-II Laser System was used for irradiation at a frequency of 1,000 Hz using the "Minimum" predefined shot pattern. MALDI FTICR spectra were generated from 500 laser shots in the m/z range from 693. 01 to 5,000. 2M data points were used per spectrum which corresponds to a transient duration of 5. 0332 s.
Bioinformatics MS raw data from MALDI FTICR were processed using DataAnalysis 5. 0. For deisotoping and extracting the monoistopic peaks the SNAP algorithm was employed with the following parameters of S/N > 3 and quality 0. 6. The procedure for the deamidation value calculation from MALDI FTICR was based on Bray et a,l 2023. 26  The identification is supported by all peptide markers presented in previous reports. [27] [28] [29] [30] [31] [32]  Proteomics data were processed with Mascot v 2. 5. 1 against NCBI database mammalian (NCBI_2022_01, 9,016,701 sequences) and Aves (NCBI_2022_01, 2,494,584,292 sequences). Three missed cleavages, 10 ppm mass error for MS and MS/MS were applied. Cysteine carbamidomethylation (+57. 02 Da) was set as fixed modification. Methionine oxidation (+15. 99 Da) and asparagine, glutamine deamidation (+0.
98 Da) were selected as variable modifications. The second bioinformatics analysis was performed with PEAKS X plus (Bioinformatics software, Waterloo, Canada) against a home-made database containing 1,765 collagen sequences extracted from NCBI database (All_Collagen, from Bray et al 2023) restricted to Mammalian. 26  Precursor's mass tolerance was fixed to 10 ppm and fragment ion mass tolerance to 0. 05 Da. Three missed cleavages were allowed. The same post-translational modifications (PTMs) above were allowed plus hydroxylation of amino acids (RYFPNKD) (+15. 99 Da) as variable modifications. Five variable PTMs were allowed per peptides. PEAKS PTM and SPIDER ran with the same parameters. Results were filtered using the following criteria: protein score -10logP ≥ 20`, 1% peptide False Discovery Rate (FDR)`, PTM with Ascore = 20`, mutation ion intensity = 5% and Denovo ALC ≥ 50%.
Peptides with amino acids substitutions was filtered with minimal intensity set as 1e107. Peptides identified on collagen I alpha 1 and I alpha 2 were aligned against the NCBI   33  The specific peptides were validated with a score of 100% of identity and full query coverage. The mass spectrometry proteomics data have been deposited on the ProteomeXchange Consortium (http://proteomecentral. proteomexchange. org) via the PRIDE partner repository with the data set identifier PXD044039 (Private data, Username: reviewer_pxd044039@ebi. ac. uk, Password: WzZDnHxu). 34.
Calculation of deamidation and hydroxyproline level MS raw data were also processed by MaxQuant (MQ) software 1. 5. 8. 3 (https://www. maxquant. org/) to further investigate about deamidation level of the proteins identified. 35  In this search, for each identified species specific COL1A1 and COL1A2 sequences from Uniprot and NCBi were used. 26  Database search was carried out using the following parameters: (i) full tryptic peptides with a maximum of 3 missed cleavage sites; (ii) cysteine carbamidomethylation as a fixed modification and (iii) oxidation of methionine, the transformation of N-terminal glutamine and N-terminal glutamic acid residue to pyroglutamic acid, hydroxyproline oxidation, and the deamidation of asparagine and glutamine as variable modifications. Match type was "match from and to" and the decoy mode was set to "revert".
PSM (Peptide-Spectrum Matches) and Protein and Site decoy fraction False Discovery Rate (FDR) were set at 0. 01 as threshold for peptide and protein identifications. Match between run was used with 2 min for match time windows and 20 min for alignment time windows. Dependent peptides FDR was set at 0. 01 All the other parameters were set as default. An estimation of the percentage of deamidation for N and Q residues for each sample was calculated using the freely available command-line script "deamidation" (https://github. com/dblyon/deamidation), which use the MaxQuant "evidence. txt" file. The calculations were done separately for potentially original peptides and potential contaminants peptides as previously reported in  Mackie et al. 2018. 36  For the determination of deamidation following the traditional ZooMS approach COL1A1 peptides named P1 m (position COL1A1-508-519) with the sequence GVQ dem GP ox PGPAGPR for mammals was used.
27, 37  The peptide sequence GVQ dem GP ox PGPQGPR named P1 b with the same position on COL1A1 compared to mammals and wich appears conserved across all birds, Australian marsupials and some reptiles was used. 38  In MALDI FTICR the percentage of deamidation of the peptide from COL1A1 is calculated simply by dividing the intensity of the monoisotopic peak of the deamidated peptide by the sum of the intensity of the monoisotopic peak of the non-deamidated and that of the deamidated peptide without any assumption. In LC-MS/MS analyses without database search the same percentage is calculated from the MS spectrum of the relevant peptides identified by their MS/MS spectra and retention times. The MS/MS spectra are given in Supplementary Information S3, Figure  S1 -S4. The m/z of the peptides with and without deamidation used for the calculation of deamidation percentage are presented in Supplementary Information 1, Table  S3  which contains the masses expected in the MALDI FTICR and LC-MS/MS analyses for native and deamidated peptides An estimation of the percentage of hydoxyproline residues for each sample was calculated with PEAKS X+ PTM results.
It should be noted that the main difference between the two instruments is the 100 times higher resolution of the MALDI FTICR MS, which allows for the unambiguous detection of monoisotopic peak of native and deamidated peptides. The same samples were also analyzed by LC-MS/MS to validate the MALDI FTICR MS identifications. Sample identification was performed using the NCBI mammalian and aves database which contains protein sequences from several sources, including annotated coding region translations in GenBank, RefSeq and TPA, as well as SwissProt records. The mammalian and aves databases were chosen because MALDI identifications only identified mammal and bird species in the same way as morphological identifications by archaeologists and palaeontologists. In this database, there are few protein sequences of extinct species such as cave bears and aurochs which complicates the identification of extinct species.
This shows that the sampling method and proteomic analysis could be used to study bones contained in museums. This method would make it possible to obtain the global proteome and MALDI spectra of reference species. With these reference spectra, new marker peptides could be discovered even if the type I COL sequences are not in the databases. In this way, it will be possible to increase species identifications on archaeological sites. The Nand C-terminal parts are not identified because they are removed during collagen maturation. 44  High number of the identified peptides correspond to the type I collagen sequence. Proteomic identification correlates with taxonomic identification by archaeologists and paleontologists using comparative anatomy. Analyses are 100% consistent with the family level and 95% consistent with the genus level of taxonomic identifications (Table  1 ).
The LC-MS/MS analysis showed that the Wa24 sample corresponded to an Ursidae, as did the MALDI FTICR. This difference between the identification by mass spectrometry and that achieved by anatomy is due to the size of the bone, the preservation of the bone which did not allow for formal identification of the bone. Unique peptides identified by LC-MS/MS on collagen 1 alpha 1, 1 alpha 2, and 1 alpha 3 (major bone proteins), with Mascot software were selected and further analyzed with BlastP to validate family, genus and species. The database mining of the LC-MS/MS proteomics data led also to the identification of noncollagenous proteins (NCP) such as biglycan, chondroadherin, osteomodulin, calmodulin. 46  This type of protein has been identified in bones from different periods and for different species such as humans, mammoths, moas, cattle, horses, turkeys, rabbits, squirrels, extinct rhinoceros.
91, Supplementary data S1, Figure  S8 ). The de novo analysis of the PTMs present in the samples using the PEAKS X+ software shows the presence of hydroxyproline. Hydroxyproline is naturally present in collagen to stabilize the structure. [63] [64]  The average percentage of hydroxylation is 65%, with no significant difference between periods but a slight increase in Pleistocene sample (Figure  3 ). The percentage of hydroxylation is 12-13% in fresh collagen. 65  There is an increase in hydroxyproline in archaeological bones, but this change is not correlated with sample age.
Elucidating the origin and significance of a bone fragment or artefact, while preserving its integrity, is a crucial issue for archaeologists, and the use of dermatological skin tape-disc is an alternative for these studies. Our study shows a potential application for museum analysis of reference and archaeological bones or artefact analysis. Our methods will allow to create a database of reference sample form museum for paleoproteomics community. This database will allow the identification of species for which no MALDI or LC-MS/MS data are available.
ACKNOWLEDGMENT The authors thank warmly  Cédric Lepère , ( ÉVEHA -Études et valorisations archéologiques, Limoges, France  and  Univ. Côte d'Azur ,  CNRS ,  UMR 7264 -CEPAM -Cultures et Environnements Préhistoire, Antiquité ,  Moyen Âge, Nice, France ) for allowing the authors to sample material from the cave  Pertus II (Méailles, Alpes-de-Haute-Provence, France).
The authors acknowledge the IBiSA network for financial support of the UAR 3290 (MSAP) proteomics facility. The mass spectrometers were funded by University of Lille, CNRS, Région Hauts-de-France and the European Regional Development Fund. The authors deeply thank CNRS -Mission pour l'Interdisciplinarité for the funding of the Prot_HR_DAT project (2021-2022) and the AgroPastCN project (2020-2021). The authors are grateful to the Région Hauts-de-France for the funding of the ProtéOsHdF project (2021-2022) and the financial support from the IR INFRANALYTICS FR2054 for conducting the research is gratefully. The EU_FTICR _MS project Grant Agreement 731077, and the IPERION HS project Grant Agreement 871034) funded by EU Horizon 2020 Research and Innovation Program are profoundly thanked.
Type of Data Method or qualifying characteristics Teeth present FDI World Dental Federation numbering system Teeth lost ante / post-mortem  ( Seguin et al. , 2014)  Visual and radiological appearance of the alveolar bone opposite the affected tooth Dehiscences, fenestrations and developmental bony defects Alveolar bone destroyed by infectious process, marked by rounded cavity in spongey bone and radiolucent lesion Dental caries  (Nyvad, 2004)  Evaluation by physical criteria of size, depth, and presence of cavitation. Tooth wear  (Chattah and Smith, 2006)  Located on the occlusal surfaces primarily, it is the result of various phenomena: abrasion, attrition, and erosion. Estimated horizontal bone loss Evaluation of the loss of bone height in relation to the amelo-dentinal junction Dental calculus Calcified dental plaque still be noted.
Acknowledgments The skeleton of  Anne d'Alègre  ( ML-OST-A-0433  to  ML-OST-A-0632 ) is preserved at the  Museum of Sciences of Laval  that we thank for its availability. This work was supported by the  Fossil team (Forensic Sciences  and the  Study of Image Libraries) of the Centre for Anthropobiology and Genomics of Toulouse -UMR 5288  ( CNRS/UT3 ) and the  Marie Sklodowska-Curie individual fellowship ,  AIDE  project for  Rozenn Colleter  (grant  897565 ). We also thank the anonymous reviewers who improved the quality of this paper with their constructive comments.
The data used in this paper come from the translations of A. Camus (1942) L'Étranger and J. K. Rowling (1997)  Harry Potter and the Philosopher's Stone, two multilingual corpora compiled in the Time in translation project. 2  The source language of the Camus corpus is French, a liberal perfect language, whereas the source language of the Harry Potter (HP) corpus is English, a classical perfect language. By combining data from the two corpora, we reduce the problem of source language influence on translation ('translationese'). The dataset is compiled through Translation Mining, a methodology that works as follows. We extract (finite indicative) verb forms from a text, and annotate them in traditional grammatical terms (e. g. passé compose, passé simple for L'Étranger, simple past, present perfect for Harry Potter).
Section 3 applies the methodology to the comparison of Dutch, Catalan and Breton with French and English (source languages of the two corpora). Van der Klis et al. (2022)  extract all the instances of the passé composé from Chapters 1-3 of L'Étranger, and align them with their translations in Italian, German, Dutch, Spanish, English and Greek. Based on the distributional patterns in the Camus corpus, they put forward the perfect scale in Figure  1. Languages with a distribution in between a liberal and a classical perfect are called 'intermediate' perfect languages. The liberal status of French and Italian is mirrored in the high frequency of present perfects and the almost complete absence of perfective pasts in the dataset. In contrast, the Greek translator chooses the perfective past in almost all the environments in which French and Italian use a present perfect.
Distributional patterns: A quantitative analysis of the Camus dataset In the Camus dataset, French is the source language, and all verb forms are translations of a passé composé in L'Étranger. As Table  1  shows, French has the highest frequency of present perfects in the dataset, and English the lowest, whereas Dutch, Catalan and Breton are in between. This leaves the question whether Dutch, Catalan and Breton can be ordered with respect to each other on the perfect scale. Based on distribution, the answer would be negative, because the subset relation breaks down between rows 3 and 7. When it comes to three languages displaying a present perfect, it can be either Dutch which allows a present perfect and not Breton (row 3), or vice versa (row 4). Row 5 presents the most frequent tuple in the dataset, with a present perfect in French and Catalan, a past perfect in Breton and simple past forms in Dutch and English.
The intermediate position of the Dutch present perfect Examples from the Camus dataset illustrate that the Dutch vtt can describe a past situation that lasts up to the speech time ((  12 )). The relevant verb forms in italics are all translations of the French passé composé. (12) a. Je les voyais comme je n'ai jamais vu personne et pas un détail de leurs [French, passé composé] visages ou de leurs habits ne m' échappait. b. Ich sah sie, wie ich nie jemanden gesehen habe, und keine Einzelheit in [German, Perfekt] ihren Gesichtern oder an ihrer Kleidung entging mir. c. Ik zag hen zoals ik nog nooit iemand heb gezien, en geen onderdeel van  [Dutch, vtt]  hun gezichten of van hun kleren ontsnapte aan mijn aandacht. d. I saw them more clearly than I've ever seen anyone and not a single detail [English, present perfect] of either their faces or their clothes escaped me.
(32) a. [French, passé composé] Aujourd'hui j'ai beaucoup travaillé au bureau. b. [Breton, ada] Hiziv em eus labouret kalz er burev. Sensitivity to lexical aspect thus opposes the Germanic languages to the Romance languages and Breton. To report pre-hodiernal past events in isolation (no story telling), Breton aligns with Dutch ((33c)) in using a present perfect ((33b)), but the Catalan translator switches to the passat perifràstic ((33c)). (33) a. [English, simple past] But Snape tried to kill me! b. [Breton, ada] Snape en deus klasket ma lazhañ koulskoude! c. [Dutch, vtt] Maar Sneep heeft geprobeerd me te vermoorden! d. [Catalan, pp] Però si l'Snape va intentar assassinar-me! Because the Camus dataset mostly involves hodiernal past time reference, we didn't see this in Table  2 , but the Harry Potter example ((33)) is part of a larger conversation about things that happened a long time ago.
[ 10 ] 10 Eric Corre, Henriëtte de Swart and Teresa M. Xiqués languages convey with a present perfect. Row 2 of Table 2 contains 11 contexts in which all languages except English maintain the present perfect from the French original, so Dutch, Catalan and Breton have a wider distribution than a classical perfect language. In rows 8 and 9, only French uses a present perfect, and Dutch, Catalan and Breton are more restricted. The quantitative analysis of the Camus dataset supports the status of Dutch, Catalan and Breton as intermediate perfect languages.
The quantitative analysis of the Camus dataset in Section 3. 1 shows that the three languages cannot be ordered with respect to each other on a linear scale. The qualitative analysis of data from L'Étranger and Harry Potter in Sections 3. 2-3. 4 reveals the grammatical ingredients the present perfect is sensitive to in each language. Le Bruyn et al. (2022) and de Swart et al. (2022) , we know that Dutch has a less liberal present perfect than German, and the Catalan present perfect is more liberal than its Spanish counterpart. The aim of this paper is to determine how Dutch and Catalan relate to each other, and to Breton.
The author (KD) interviewed individuals who were involved with NAMI in some capacity, or at times, individuals who had been referred to the project because of their unique stories or experiences which reflect living with mental illness. Data collection began in the summer of 2021 and was completed in fall of the same year. Analysis of the interviews began in the fall as the final interviews were being conducted. Identification of the final themes and writing of the manuscript began in early 2022. The semi-structured interviews were geared toward discussing participants' experiences and perceptions of living with mental illness, and their narratives surrounding the recovery process. All interviews took place online and were transcribed verbatim. We de-identified all transcripts which were then uploaded into NVivo (ISR International, Melbourne), a qualitative analysis software used for computerized support and organization of qualitative analysis.
This paper reports on two ways in which success and failure can be operationalized and quantified in a non-institutional L2 learning context such as language tandem setting. We draw on the SITAF database, where we gathered 25 hours of video-recorded conversations held by 21 pairs, each consisting of a native speaker of English and a native speaker of French. The tandems performed collaborative tasks in both languages, thus giving each participant ample opportunity to be both the 'expert' and the 'novice' (learner) part of the dialogue. The tandem partners met regularly and autonomously outside of the recording sessions, and making progress in their L2 was one of their declared goals. Two possible measures of success in achieving this goal are: (1) the quality and quantity of learner uptake which followed the expert's corrective feedback (CF) during the recorded conversations.
12609 p. 4/28 Sylwia Scheuer, Céline Horgues ogy for describing such phenomena (e. g. ,  Lyster & Ranta, 1997; Gass, 2003; Mackey, 1999 Mackey, , 2006;; El Tatawy, 2002; Sheen, 2006) , although some more varied learning contexts are now being explored  (Nassaji & Kartchava, 2021). Some methodological adaptations will necessarily have to be made when transferring previous categories and typologies  (which, as Lyster and Ranta (1997)  explain, were conceptualized for the needs of a particular database) into the specific learning environment of non-informal and semi-naturalistic NS-NNS tandem interactions (see our Methods section).