dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We wish to thank  Marie Matu  and  Patrice Courtaud  for granting us access to the " Ostéothèque de Pessac " to study some of the material. We thank the  LAMPEA  for their help and support of this research. We are very grateful to  Brad Gravina , the Editor  José S. Carrión  and two anonymous reviewers for their constructive comments that greatly improved the quality of the manuscript.
This resulted in 12. 1% bases and 13. 9% reads originating from modern human mitochondria. A consensus modern human contaminating sequence covering 89% of bases was generated from reads mapping to the human rCRS rather than to the Denisovan sequence, and haplogroup assignment was assessed both by using the K-mer-based haplogroup assignment software Phy-Mer  (43)  and by its position on a maximum likelihood tree of reference haplogroups. A more detailed description is available in the Supplementary Materials and Methods.
Acknowledgments: We are grateful to the following curators and scientists who granted us access to fossil material or helped in acquiring the data:  E. Dewaemme ,  C. Polet , and  P. Semal  ( Royal Belgian Institute of Natural Sciences, Brussels, Belgium );  D. Castex  and  P. Courtaud  ( Bordeaux University, Pessac, France );  J. Radovcic  ( Croatian Natural History Museum ) and the  European TNT  project for the access to the Krapina collection;  A. Froment ,  D. Grimaud-Hervé ,  P. Mennecier  ( National Museum of Natural History, Paris, France ), and  A. Thomas  for the study of La Ferrassie 1, 2, and 3 hand bones;  B. Vandermeersch  and  J. -J. Hublin  ( Max Planck-Insitute, Leipzig, Germany ) for the analysis of the Saint-Césaire 1 remains;  V. Merlin Anglade  ( Musée d'Art et d'Archéologie du Périgord, Périgueux, France ) for the access to the Regourdou 1 Neanderthal specimen;  K.
Kolobova  and  S. Markin  for the access to the Chagyrskaya hand remains; and  I. Hershkovitz  and  J. Abramov  ( Tel-Aviv University, Israel ) for pictures and measurements of Kebara 2 and Amud 1 phalanges. We thank  E. Rubin  ( University Berkeley ) for giving us the opportunity to perform the genomic work on the Denisova 3 distal phalanx. We thank two anonymous reviewers for valuable comments that helped us to improve the manuscript. Funding: The study was supported by the  French National Research Center CNRS. E. A. B. was supported by the  CNRS  and the  Labex "Who am I. " B. V. was supported by the  Social Sciences and Humanities Research Council of Canada  (insight grant  435-2018-0943 ). The paleogenomic facility obtained support from the  University Paris Diderot  within the program "Actions de recherches structurantes.
"The sequencing facility of the IJM, Paris, was supported by grants from the  University Paris Diderot , the  Fondation pour la Recherche Médicale  ( DGE20111123014 ), and the  Région Ile-de-France  ( 11015901 ). The research of I. C. and B. M. was supported by the  ANR (French National Research Agency)  project  LabEx Sciences archéologiques de Bordeaux , no. ANR-10-LABX-52 , and the project " NATCH " convention  2016-1R40240-00007349-00007350  of the  Région Nouvelle Aquitaine. Author contributions: E. -M. G. and B. M. designed the project. E. A. B. and T. G. designed the molecular biology experiments. E. A. B. performed the molecular biology experiments and mtDNA analysis. E. -M. G. measured and photographed the phalanx using a stereomicroscope. I. C. and B. V. measured the phalanx on the stereomicroscope photos.
I. C. performed the comparative analysis with support from B. M. B. V. carried out the virtual reconstruction of the phalanx. A. P. D. and M. V. S. directed the excavations. E. -M. G. , E. A. B. , T. G. , and I. C. wrote the manuscript with contributions from B. V. and B. M. Competing interests: The authors declare that they have no competing interests. Data and materials availability: Ancient DNA sequences are available from the  NCBI Sequence Read Archive SRA   ID PRJNA525697. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.
Material A graphite block digestion system was manufactured by Environmental Express (Charleston, USA), and 15 mL polypropylene screw cap tubes (SC415) were purchased from Courtage Analyses Services (Mont-Saint-Aignan, France). In the laboratory, the tubes were cleaned using 1% nitric acid and dried prior to use. An Elmasonic S120 ultrasound bath was purchased from Grosseron (Couëron, France). A precision balance (MC210P) was provided by Sartorius (Göttingen, Germany). An Agilent Technologies (Santa Clara, USA) 7500ce ICP-MS was used. The samples were handled using a CETAC (Waltham, USA) ASX-520 autosampler, a Micro-Flow nebulizer, and a Scott nebulization chamber. The instrument was controlled by an HP Compaq 8000 computer and the Mass Hunter software.
Acknowledgements  Claude Briens  and  Françoise Lacroix  from  Laboratoire  d'étude et recherche en environnement et santé (LERES) are gratefully acknowledged for their technical support. Bernard Jegou  and  Cyril Harpet , who followed the work at its early beginning, must also be thanked. We thank  EHESP  and  Irset (Institut de recherche en santé , environnement et travail)-UMR_S 1085 for supporting the achievement of this research activity.
Lexis, 17 | 2021 (cf. bibliography). Subslikescript was favoured because the names of the characters do not appear in the scripts, which allows to have less irrelevant data, but there are a few episodes for which the scripts were not available and were therefore collected on Foreverdreaming. The final file contains around 600,000 words. The number of words is approximative because some stage directions, character names, and song lyrics are sometimes mentioned. In order to attempt to collect occasionalisms in the scripts, I created a list of stop words by compiling an existing list of 466,553 English words 6 and a list of 5,493 proper nouns 7. I then uploaded the scripts in AntConc and extracted the words that were only present in the scripts. The list contained 1,698 words. There were two main problems with this list: -Firstly, many of the words retrieved thanks to AntConc were not occasionalisms but occurrences due to a missed space (alwaysbeen, backrub), words that were misspelt (answerign, apartement), onomatopoeia (aaaaaaaaaaa, aaarrrggg), etc.
Not all occurrences were selected, and most of them were taken from the first six seasons as enough data was collected at this point. The occurrences provided in Section 1, which mainly appear in the overview of the different nonce-formation processes, are simply examples which are meant to illustrate each of these processes. The occurrences analysed in Section 2 were retrieved because they were interesting for being not so successful or for being deceptive; they could not have been retrieved and analysed thanks to corpus analysis tools. In order to confirm that the occurrences mentioned in the paper were indeed occasionalisms, I first checked whether they appeared in the list of 1,698 words that was compiled thanks to AntConc. I then searched the Merriam-Webster online dictionary (which was chosen because it is a reference dictionary of American English) so as to confirm that they were not lexicalised.
Acknowledgements I would like to thank the audience at the  Wittgenstein Notebooks conference (UQAM & Trois-Rivière) , the Granger conference (Clermont), and the  Wittgenstein seminar of Paris-Pantheon Sorbonne. This article benefited from the helpful comments of  Juliet Floyd ,  Juliette Kennedy ,  Lydia Patton ,  Quentin Rodriguez ,  Mark Wilson , and three anonymous reviewers. Special thanks to  Chris Pincock  whose comments were particularly useful to me during the final phase of the writing process.
In  [4] , authors propose a study aiming to analyze the impact of the subtitle positioning systems over hearing impaired people. Both regular and dynamic subtitles positioning methods are considered for comparative evaluation. The objective criterion retained exploits the gaze data acquired with a dedicate gaze tracking approach. A baseline gaze pattern is determined with the help of normal users that are watching the videos without subtitles. The main observation of the paper is that the dynamic subtitle systems create gaze patterns that are closer to the baseline than those induced by regular subtitles. The work has been extended in  [6] , where inferential statistics are applied to the gaze data in order to determine the hearing impaired satisfaction regarding the subtitle placement. The authors conclude that the static subtitle makes it easier to look around, but more difficult to understand the video content.
A. THE BENCHMARK The test dataset includes 30 video sequences, with an average duration of 20 minutes, recorded at a resolution of 1024 × 576 pixels, at a frame rate of 25 fps. Twenty videos have been selected from the France Télévisions TV series ''Un si grand  VOLUME 7, 2019  soleil'' and ten from the movies ''Friends'' and ''The Big Bang Theory''. We decided to include in our test database the US TV series aforementioned in order to provide a fair comparison with the methods in  [3]  and  [5] , which focus on such videos.
B. CNN TRAINING 1) CNN TRAINING FOR FACE RECOGNITION For face recognition purposes, we have considered a training dataset of 110 categories of known persons. For each person, a maximum number of 800 face instances have been retained. The faces have been detected (cf. Section III. A. 1) and spatially aligned using facial landmarks, as described in  [29]. The resolution of the input faces has been set to (224×224) pixels. After each ReLU activation function, a batch normalization (BN) has been applied, in order to help solving the gradient exploding or vanishing problems while guaranteeing a near optimal learning regime for the succeeding convolutional layers. Next, we have performed the training with 50k iterations, at a learning rate of 0. 0001 and a batch size of 64. In addition, based on transfer learning, we initialized the weight of the CNN with the pre-trained VGG16 face model  [22]  that achieves state of the art accuracy for face recognition tasks on static images.
2) CNN TRAINING FOR SPEAKER RECOGNITION The candidate list of persons included in the active speaker recognition task is taken from the visual face recognition module and includes the movie actors. This list contains 110 identities of which approximate half are male and half are female. For the ''Un si grand soleil'' series, we have used for training the first 100 episodes while for ''Friends'' and ''The Big Bang Theory'' series we have used all episodes from season I (which correspond to 24 and 17 episodes, respectively). For this stage, the challenge was to automatically construct, with the help of the visual analysis process previously described, a speaker recognition-dedicated learning database. To this purpose, we have applied the face tracking and recognition approach, in order to identify the potential active speakers.
Then, we have determined the audio-video synchronization between the mouth motion and the speech in the video in order to determine which visible face (if any) corresponds to the speaker. This task is performed with the help of the SyncNet network  [30] , a CNN architecture which estimates the correlation between the audio track and the mouth motion in videos. This method allows us to reject movie segments where the active speaker is not visible. In order to ensure that our system is highly confident about the identity of the speaking person, without any manual intervention, we have imposed conservative thresholds in order to minimize the number of false positives. The database contains approximate 13000 appearances of the 110 characters (actors) involved. The lowest length of the speech segment admitted as input is set to 1.
e. , missed classified subtitle sequences that belong to one of the known classes). In order to provide a comprehensive experimental evaluation of the proposed framework we have established a ground truth by manually annotating the test dataset. For each utterance, we have identified the active speaker and included this information in the associated subtitle files. For the test dataset, 15208 sentences have been identified. From the 15208 sentences, a number of 13547 represent known active speakers existent in the training database. In order to evaluate the influence of each component of our system over the speaker recognition performances, we have considered for comparison: (1) An active speaker recognition strategy based solely on the face recognition module. When only one character exists in the scene, the displayed subtitle is automatically assigned to the recognized face.
D. SUBJECTIVE SYSTEM EVALUATION In order to provide a qualitative system evaluation we have conducted a comprehensive usability study, aiming at comparing the following three paradigms: (1) Static Caption (SC) -in this case, the subtitle is positioned on a fixed location at the bottom of the screen. (2) Speech bubbles (SB)a dynamic subtitle positioning system where the sentences are located near the active speaker head as in  [3]  and  [5]. (3) The proposed Dynamic Subtitle (DC) -where the subtitle is positioned in the vicinity of the active speaker using the 15 regions of interest described in Section III. D. For the usability study we have considered the whole set of 30 videos in the test dataset (cf. Section IV. A). Concerning the end users, we have recruited 30 anonymous volunteers (19 male and 11 females) with an average age of 23 years.
A video temporal segmentation method is introduced that divides the image sequence into high semantic units based on face tracks and visual consistency. Finally, a novel speaker recognition method is proposed designed as a multi-category classification strategy that receives as input spectrograms developed from the filtered audio segments. The experimental evaluation performed on a large dataset of 30 videos taken from the French and US TV series ''Un si grand soleil'', ''Friends'' and ''The Big Bang Theory'' validates the DEEP-HEAR proposed methodology, which is able to return a F1-score superior to 92%. When compared with state of the art systems  [3]  and  [5] , our framework shows an increase in performances of more than 8%. As future work, we envisage to further extend the DEEP-HEAR architecture to cope with sound-to-text libraries for videos where the subtitle document is not available in advance.
2011; Williams 2012 ), we performed a simulation (Figure  4 ). The probability density function of the archaeological samples was compared with the sum of probabilities of a simulated series of dates under the assumption of the deposition of one archaeological event per year. On the other hand, the uncertainty was fixed as the lowest possible standard deviation, which is ±10  (Chiverrell, Thomdycraft, and Hoffmann2011). Thanks to that, it was possible to observe the irregularities in the calibration curve and to determine if the peaks of intensity of the empirical series were or were not an effect of the calibration curve. These statistical tests were performed using the Calib software as it allowed us to overlap the calibration curve with the chronological distribution of the radiocarbon dates on the same scale.
Site However, what can indeed be noted based on the data available to us, is that there is a greater concentration of dates between a broader range of 4000-3700 cal. BC (2σ), so we are therefore able to gird the chronology distribution of these burials within this range. Finally, we analysed the chronological distribution distinguishing the different geographical areas where the burials were found (Figure  5 ). In this case, the graph was made with CalPal software because it allows us to overlap different chronological distributions in the same picture on the same scale, thus facilitating their analysis and interpretation. As can be observed from the graph, if we take the geographical location as a category of analysis, the southern burials had a chronological distribution of between 4300-3800 cal.
If this condition was not fulfilled when tested using the F-test, we applied the Welch's ttest, or unequal variances t-test, in order to verify if two variables have equal means. In this case study, such tests have enabled us to investigate the potential correlation between the sexes of the buried individuals and the characteristics of the grave goods associated with them. These tests were applied for each category of such grave goods (used and non-used tools, the related activities and the exogenous raw materials), in an attempt to explore the entirety of the available dataset. The tests were initially performed specifically taking into account the presence/absence of a variable (such as the used or non-used tools) within the different burials; a further application was carried out in relation to the frequency of the occurrence of that variable within the burials.
However, It is also important to emphasise that men accumulated the majority of the "honey flint" cores (vide infra)as well as that male exogenous PBA were significantly bigger and heavier  (Masclans 2017 ). According to these information, if we removed from the dataset both male and female burials lacking exogenous raw materials, the Student's t-test would return a positive value ("Exogenous raw materials 2" in Table  4 ). That is to say that the differences between men and women are the most evident in the wealthiest sepulchres. Regarding the cores, used and non-used tools, women are associated with 46. 50% (33 items) of used tools and 35. 20% (25 items) of non-used tools, while men are associated with 51. 20% (107 items) of used tools and 33. 50% (70 items) of non-used tools (Table  6 ).
Acknowledgments The authors would like to thank the members of the  IMF-CSIC Laboratory of Prehistoric Technology  for their constant help and infrastructural facilities. This research has been carried out thanks to the  Generalitat de Catalunya PhD fellowship FI-DGR  and the support of the members of the  History and Art History Department of the University of Girona  and the  Prehistory Department of the Autonomous University of Barcelona , to whom we are especially grateful. Our work was financed by the project  HAR2011-23149 : " Aproximación a las primeras comunidades neolíticas del NE  peninsular a través de sus prácticas funerarias", the Project  HAR2015-67323-C2-1-P y HAR2015-67323-C2-2-P : " Aproximación a las primeras comunidades neolíticas del Mediterráneo nordoccidental: construyendo respuesta desde los análisis paleoantropológicos y genéticos " ( Ministerio de Economía y Competitividad del Gobierno de España) , the Project  HAR2016-75201-P : " La difusión del neolítico en el Mediterráneo centrooccidental: agricultura, innovaciones tecnológicas y carbono 14 " and the fundomg recieved by the  Archaeology of Social Dynamics Group (ASD)  ( 2017SGR995 ) by the  Generalitat de Catalunya.
Introduction 1 All SLs and over 90% of all Vocal Languages  (VLs)  have not yet developed or acquired a writing system. Linguistic study, however, requires collecting, grouping and classifying data. To do so, one needs to use a typeface that represents language in a graphic form  (Slobin et al. 2001). The aim of this paper is to present Typannot, a typographic system able to: 1) transcribe the multi-linearity 1 of SLs; and 2) solve the time-consuming issue of SL transcription. In this paper, we will exemplify the principles of Typannot through the parameter of handshape (HS), although the system is also able to represent other SL parameters: orientation, location 2 (LOC), movement, and facial expression.
2 To start, we will bring to light the stakes and issues in SL that call for a new tool. The first issue is that SLs are multi-linear 3 languages that challenge the VL-centric conception of representation (see §2). Some Sign Language transcription systems (TranSys) have already been proposed and we will present them through the perspective of translation/ identification, on the one hand, and transcription of forms on the other hand (see §3). The following review of existing SL TranSys provides cues to understanding the gap between the purpose of each TranSys and the reality of SLs and their notations. The second issue pertains to the transcription scope, i. e. data searchability: transcriptions are chiefly made for database queries. What is the structure of the information and how can we design a system to represent the combination of its components in an exhaustive way (see §4)? Handling sign language handshapes annotationwith the typannot typefont CogniTextes, Volume 19 | 2019 Next, we will present the four design principles that we developed as working guidelines: genericity, readability, modularity, scriptability.
Through an interdisciplinary reflection involving linguists, designers, and developers, we define the junctions between the different working frames, from linguistic modelization to a systematic typographic system (see §5). We applied these principles to design an initial typeface that represents the parameter of handshape (HS) (see §6). With the typographic system in place, we had to develop our own typesetting tool and to propose input options that utilize current technology such as OpenType format, gesture capture, and recognition solutions (see §7). Apart from the representation of the forms of SL's parameters, another problem we tackle is the reduction of transcription time. Finally, we will present a corpus in French Sign Language (LSF) that has been transcribed entirely using Typannot HS generic characters.
SignWriting SignWriting (SW; Sutton 1995) is a typographic system developed to write 5 (not to transcribe) SLs; it is made from over 35,000 characters, which enables both manual and non-manual parameters to be written. Visually, SW is different from any other existing typeface, because it is the only one that tries to take into account SL's multi-linearity, using highly iconic characters placed in a bi-dimensional vignette that represent signing space (cf. Figure  1 ): these features make it very legible and quite easy to learn, but handwriting can be laborious. SW has been developed for educational and cultural purposes and for this reason, even if software did exist dedicated to SW (e. g. , SignMaker), it would not meet the researcher's need for searchability. In 2017, SW entered the Unicode standard but non-dedicated software (like MS Word) could not support the bidimensional layout of SW, which must be converted into a mono-linear string, and in so doing, lost all information transmitted by the use of space.
A transcription system : what is at stake Therefore, except in a few corpora  (Efthimiou et al. 2010; Hanke et al. 2012) , SL parameters are not really annotated, or else just partially. One of the reasons is the time needed to do this, even if it has been rarely quantified  (Colletta et al. 2009:57). This time consuming activity could be reduced if a glyph inserted into the annotation software used carried several pieces of information (in ELAN for instance, this would help reduce the number of tiers used to annotate sign forms to one). In the next section, we will present our typographic system (one for each parameter: HS, LOC, movement, and facial expression), in which every glyph embeds layered information for sign representation by way of generic characters (see §4. 1). This system allows a linear (like a text) and a multi-linear organization (like a score) of the information within the textual space.