dataesr/scientific-paragraphs-categorization huggingface dataset:
On the technological front, advances in computer software and hardware have provided new opportunities (as applies to almost all facial imaging methods), such as core gains in fast and accurate calculations of complex algorithms for large datasets under repetitive conditions. Capabilities, even on standard desktops, are now much more advanced than they were 10 years ago. This has ushered in completely computerised and largely automated methods of facial approximation, often using CT scans as training sets  [30, [34] [35] [36] [153] [154] [155]. Furthermore, advances in computer technology have enabled manual drawing and sculpting methods to be shifted to the electronic domain with the development of touchscreens (such as Cintiq V R pen displays by WACOM V R  [156] ) and haptic feedback devices (such as Geomagic V R Touch TM by 3D SYSTEMS V R  [24] ), respectively.
Methods for the acquisition of face shape in the research context have progressed with substantial improvements in 3D scan technology, including advances in acquisition speed, resolution, and reliability (e. g. NextEngine V R by NextEngine V R , Vectra V R by Canfield V R , 3dMDface System V R by 3dMD V R , DI3D V R by Dimensional Imaging V R , and Space Spider V R by Artec V R ). Of course, these developments are accompanied by challenges to stay current with technology (e. g. expense), but in relative terms, the capability per dollar amount is much better now than 20 years ago and, as a result, more widely accessible. Advances in this area have enabled the comprehensive mapping of changes in soft tissue thickness with posture  [148, 157, 158] , their visualization as general trends  [148] , and the presentation of correction values for supine datasets, such as CT  [148].
Traditionally, these adjustments have been made by a forensic artist sketching the face to produce a postmortem portrait  [3, 219]. Computer assisted facial depiction employs image editing software such as Adobe V R Photoshop V R  [249, 250]. Often, the analyst uses a databank of facial images to extract facial features to assist in the face reconstruction process  [249, 250]. Thus far, postmortem portraiture and facial depiction have resided almost entirely in the forensic art sphere. Brief history: postmortem portraits have been a common undertaking in the forensic art domain for many years  [3, 219]. The use of postmortem images, or photographs to produce sanitised images is a more recent undertaking  [249, 250]. Recent research developments: studies in this area have been limited, but one attempt (n ¼ 6) quantitatively studied facial changes specifically associated with decomposition  [249].
Perspective distortion can also be matched when the subject-to-camera distance is known so that a 1:1 comparison can be undertaken  [255, 257, 263]. The utility of this approach depends on the legal permission/freedom to acquire a 3D scan of the person of interest and the co-operation of this person during the scan acquisition process (a stationary position is normally required). The facial expression recorded in the 3D image should also be similar to that in the 2D image  [263]. Between 11 and 18 points are typically marked on each image and used for metric comparisons between the 2D and the 3D conditions, which are additionally viewed on the screen for morphological inspection using custom superimposition software (such as 3D-Rugle3 V R by Medic Engineering V R )  [254, 257, 259, 263]. Brief history: while the use of photographs in the courtroom has a long history (approximately 150 years in the UK, stretching back to the first use of mug shots by Bertillon  [261] ), facial photocomparisons are by contrast rather recent-first used in England in 1993 and Australia in 2001  [253].
Spectroscopic ellipsometry The theoretical background and data analysis methods of SE are described elsewhere. 43 In an ellipsometry measurement, the change in the polarization state of light is represented by the ratio (ρ) of reflection coefficients for electric field components of light parallel and perpendicular to the plane of incidence. ρ ¼ r p r s ¼ tanΨe i Δ (1) The ratio is a complex value and Ψ and Δ are ellipsometric angles. In ellipsometry, information about the system under the study is obtained by fitting measured ellipsometric spectra to optical and structural models. The current study used a rotating analyzer spectroscopic ellipsometer (J. A. Woollam Co. Alpha-SE) for optical characterization of corroded ISG glass samples. This ellipsometer configuration had a wavelength range of 381-893 nm with a step of about 6 nm wavelength increment and measured tanΨ and cosΔ.
SE data analysis The SE spectra in this study were analyzed using the CompleteEASE software package (J. A. Woollam Co. ). The sample was kept at 0% RH for about 10 h before adsorption measurements and ellipsometric spectra at 0% RH was analyzed to determine the initial void and solid volume fractions as well as the thickness of sublayers. The corroded glass samples were analyzed using multilayer optical models and the Bruggeman EMA was used in modeling the optical response of each sublayer in the alteration layer. 29 The general equation for EMA is given in Equation (  2 ), in which ε is the effective dielectric function of the layer, f i and ε i are the volume fraction and dielectric function of constituent i, respectively. X N i¼0 f i ε i À ε ε i þ 2ε (2) For non-absorbing spectral regions, the refractive index is related to the dielectric function via n 2 = ε.
Time-of-Flight Secondary Ion Mass Spectrometry The monolith sample corroded for 1625 days was analyzed using ToF-SIMS (IONTOF TOF 5). An O ion beam was set at 2 keV and 510 nA and used for surface abrasion (200 × 200 μm). Actual depth profile analysis was provided by a Bi ion sputtering beam (25 keV, 2 pA, 30 × 30 μm). The surface was neutralized during analysis by a low-energy electron flux (<20 eV). Measuring the depth of the final crater allowed elemental profile depth calibration. B, Na, and Ca profiles were then normalized to the Zr profile to avoid matrix effects. Zr was chosen as it is immobile during glass alteration in these conditions. 47 The resulting data were normalized to the mean measured in pristine glass to extract quantitative information.
Lexical databases RIO Ontology 1  [5]  is a domain ontology that was constructed from transcribed speech. Its construction method is based on hybrid method. A statistical method is used for extracting the concepts (14 concepts) by calculating the frequency of each term in TUDICOI corpus  [6]. High frequency terms are used as domain concepts. A linguistic method is also used for the identification of semantic relations (25 semantic relations) between concepts. It is composed of only 14 concepts and 387 concept instances. Bouchlaghem et al. [7]  exploited a 32. 848 words to create a TunDiaWN wordnet for TA. After collecting the corpus, they extracted TA words preserving useful data. Next,  [7]  applied a clustering method (using a k-mode algorithm) that aims to group extracted TA words into meaningful clusters.
It is composed of 4. 662 dialogues with 18. 657 statements. TARIC contains 71. 684 words and it is transcribed in accordance with the transcription convention "CODA-TUN"  [11]. The vocabulary used in both TUDICOI and TARIC is of a restricted domain (railway services). They present only a small part of the TA vocabulary that makes them inadequate corpora for modeling TA. Boujelbane et al. ,  [12]  transcribed 5 hours and 20 minutes of recordings using Transcriber tool. These recordings come mainly from a Tunisian TV channel. It is composed of 37. 964 words. 12. 207 words are from a TV News program with 21. 4% TA words and 25. 757 words from political debate broadcasts. TA words represent approximately 32. 1% of this corpus. This is the smallest corpus in the presented raw text corpora. [19]  have syntactically annotated the Tunisian constitution  [20] , which contains 12.
POS Tagging Boujelbane et al. [31]  retrained the POS tagger Stanford. They used the translated corpus from MSA to TA which is generated from an automatic translation of ATB. For the test, they used a transcript of the political debates for TA. This system offers an accuracy of 78. 5%. Boujelbane et al. [31]  have used a translated corpus from MSA to TA. Although, the used resources will affect the proposed systems. Hamdi et al. [32]  proposed to exploit MSA resources for tagging TA. They convert each TA sentence into an MSA lattice by analyzing them morphologically with "MAGEAD-DT"  [28]  to generate for each word much analysis. The proposed root and pattern for a given word which are then translated into their MSA equivalents. Afterwards, this lattice passes through a disambiguation step, which makes it possible to transform the words into pseudo-MSA.
Trabecular bone quantification and characterization The methods employed in this study are described in detail elsewhere and are only briefly summarized here. An illustration of the workflow, along with the specific software packages, may be found in the SOM S1. In short, each bone was segmented using the Ray Casting Algorithm  (Scherf and Tilgner, 2009)  and then the script-based whole bone/epiphyseal approach Medtool v4. 0 (Dr. Pahr Ingenieurs e. U, 2017; see below) was used to extract the cortical bone from the trabecular bone and generate a fine tetrahedral mesh representing the morphology of both tissues  (Gross et al. , 2014). Quantification of BV/TV, E, and DA of the trabecular mesh was performed in 3D by moving a 5 mm spherical VOI along a background grid with 2. 5 mm spacing for each scan  (Pahr and Zysset, 2009b) , while mean trabecular thickness (Tb.
To explore how trabecular structure may reflect differences in joint loading, each metacarpal head/base segment was subdivided into four regions at the radioulnar and dorsopalmar midlines (i. e. , dorsoulnar, dorsoradial, palmoulnar, and palmoradial regions) and each phalangeal head/base segment was subdivided into two regions at the radioulnar midline (i. e. , radial and ulnar regions). Trabecular parameters for each region were quantified using a Medtool script containing the dimensions of each bone segment.
Model implementation Six separate model setups were used to test for trabecular structure differences across regions of the hand. Each model was fitted using a Gaussian error structure and maximum likelihood  (Bolker, 2008)  using the lmer function within the lme4 package  (Bates et al. , 2014)  for R. Each of the six model setups contained two models -a 'hand' subtype and 'thumb' subtype -for each trabecular parameter compared (i. e. , the response variables BV/TV, E, and DA). Models in type 1 were run on data at the level of the bone and bone segment (i. e. , metacarpal or phalangeal head and base, or carpal). Models in type 2 were run on data at the level of the metacarpal region (e. g. , dorsoradial or palmoulnar regions of the Mc head and base) while models in type 3 used data at the level of the phalangeal region (i.
In the same models, we also tested for whether there were any patterns across samples and segments or regions that differed based on the functional group being considered, but as these tests did not address our primary aim, the results are presented in SOM S4. Type 1 model setup segment-level models. The type 1 models included data from bone segments (complete carpals, and metacarpal/phalangeal heads and bases). Subtype 1a included data derived from all bones of the hand, excluding those of the thumb. The two models in subtype 1a, each with a response variable of BV/TV or E, contained the predictors sample (post-Neolithic vs. forager), segment (head, base, or carpal), side (left or right), and the samplesegment interaction. Additionally, we included random effects of functional group, skeletal element, specimen, hand ID (e.
Both models in subtype 2a contained the predictors sample, segment, region (i. e. , dorsoradial, dorsoulnar, palmoradial, or palmoulnar), side, and all two-and three-way interactions among sample, segment, and region. The random effects included were functional group, skeletal element, specimen, hand ID, specific ID, and region group (e. g. , Qafzeh9-Left-Mc2-Base). The predictors for models in subtype 2b were identical to those in subtype 2a except for the exclusion of functional group and hand ID as random effects. Test predictors were all three-and two-way interactions, sample, and region for all models in type 2. All secondary test predictors from subtype 2a are described in SOM S4. Type 3 model setup phalangeal region-level models. These included data at the level of the phalangeal head/base regions (ulnar and radial).
Visual analysis To compare sample differences in the distribution of site-specific BV/TV with morphologies that most closely approximate the actual shape variation between the post-Neolithic and forager bones, we used a custom Python 3. 5 (Python Software Foundation) script to chain together slightly modified versions of the methods described in detail previously  (Boyer et al. , 2015; Gee et al. , 2015; Tsegai and Stephens et al. , 2017). A detailed illustration of the workflow, along with the specific software packages, is described in SOM S5 and SOM Figure  S2. In short, we used modules within Medtool to interpolate and map site-specific BV/TV to the nearest elements of the mesh representing the trabecular volume (spacing 0. 6 mm). Hereafter, each individual mesh was globally aligned and registered to a representative mesh for each bone (e.
Acknowledgements This work was supported by the  Max Planck Society  (N. B. S. , M. M. S. , T. L. K. , J. J. H. ) and the  European Research Council Starting Grant  (grant number  336301 ; T. L. K. and M. M. S. ). We are grateful for the samples provided by the  Research Centre for Palaeolithics and Palaeoethnology, Věstonice (Jiří Svoboda) ,  Museo Nazionale Preistorico dei Balzi Rossi (Elisabetta Starnini) , the  Museo Archeologico del Finale (Andrea De Pascale) , the  Sackler School of Medicine at Tel Aviv University  ( Israel Herskovitz ,  Alon Barash , and  Yoel Rak ),  Naturhistorisches Museum Wien  ( Maria Teschler-Nicola  and  Ronald Muehl ), the  University of Florence  ( Jacopo Moggi-Cecchi  and  Silvia Bortoluzzi ),  University of Kent  ( Chris Deter  and  Patrick Mahoney ), and the  Johann-Friedrich-Blumenbach-Institut für Zoologie und Anthropologie  der Georg-August-Universität Göttingen (Birgit Großkopf ).
e. unlike dictionaries, they are non-linear and non-textual. They were first presented in  Polguère (2009) , based on an experiment in automatically compiling a dictionary-like Explanatory Combinatorial lexical database for French into a network structure closer to what we expect is a plausible representation of the organization of the logical mental lexicon  (Polguère 2016b ). 15 Since then, the notion of Lexical System has been refined through large-scale lexicographic work centered mainly around the construction of the first handmade Lexical System: the French Lexical Network, hereafter fr-LN (Lux-Pogodalla and Polguère 2011). A Lexical System of a given language, such as the fr-LN, is formally a huge graph whose nodes are in most cases lexical units of the language (lexemes and idioms) and whose arcs are in most cases paradigmatic and syntagmatic relations that connect these lexical units.
At present, lexicographic work focuses on Lexical Systems for three languages: French -the fr-LN, on which the present study is based -, Russian  (Krylosova 2017)  and English  (Gader et al. 2014 ). Small samples have also been constructed for Arabic, Italian, Korean and Spanish. The main change introduced in Explanatory Combinatorial Lexicology by the use of Lexical Systems as structural models of lexicons -as opposed to "textual" dictionaries -is that each lexical unit in this approach is first and foremost characterized by its lexical cluster (see 3. 1 below): the micro-system of paradigmatic and syntagmatic relations the lexical unit is at the center of. Within the framework of Lexical System lexicography, the lexical cluster of each lexical unit is systematically taken into consideration while interpreting linguistic data and making decision on how to model them.
Acknowledgments We are extremely grateful to  Lucie Barque ,  Lidija Iordanskaja ,  Veronika Lux-Pogodalla ,  Igor Mel 'čuk,  Ophélie Tremblay  and two anonymous reviewers of  Russian Journal of Linguistics  for their comments on a preliminary version of this paper. Many thanks to  Sandrine Ollinger  for the extraction and processing of polysemy data from the fr-LN database. Finally, a very special thank to the staff of the  Segafredo café at Telok Ayer Singapore  for their excellent coffee, their hospitality and their kindness which contributed significantly to our ability to bring this work to its conclusion.
Conclusions and Perspectives This short survey was intended to highlight two types of data present in the Syriac versions of Galen's Simples that make them important for future research. The fi rst has to do with the importance of the earliest (and probably very fi rst) Syriac version, that of Sergius of Reš ʿAynā, not only for the study of Syriac medicine, but also and especially for its role as a very early indirect witness to the Greek text of Galen in circulation in the late antique Near East. A single, striking example was presented here, and several others will be made available shortly. 46 The Syriac material assumes an even greater importance, since a critical edition of the Greek text of Galen's Simples is currently in preparation. The second group of examples con onts the sixth-century Syriac translation of Sergius with the ninth-century one attributed to Ḥunayn ibn Isḥāq and his school, through a small but instructive corpus of around thirty parallel passages.
14 For a list of editions and translations of Galen published during the Renaissance, see R. J. Durling, "A Chronological Census of Renaissance Editions and Translations of Galen," Journal of the Warburg and Courtauld Institutes 24 (1961): 230-305; S. Fortuna, "Galeno e le sue traduzioni," Comunicare la cultura antica. I Quaderni del Ramo d'oro on-line 5 (2012): 112-2⒉ See also the latter's online database: Catalogo delle traduzioni latine di Galeno, galenolatino.
Nous avons construit une telle base de données en nous appuyant sur les signes de la LSF et ses correspondances écrites du français que nous avons extraites de la base de données lexicales Lexique 3. 55  (New et al. , 2001)   1. Nous nous interrogerons dans un premier temps sur le rôle de la conscience morphologique 2 et de son impact chez les enfants entendants en lecture. Celle-ci devrait d'autant plus concerner les enfants sourds pour lesquels elle pourrait servir de base unique à une mise en correspondance entre les signes et les lexèmes. Nous introduirons ensuite une analyse de la morphologie de la LSF comme point de départ pour la construction de notre corpus de familles morphologiques. Pour finir, nous présenterons l'analyse quantitative et qualitative de 62 familles morphologiques et nous tracerons les perspectives de recherches expérimentales permises par ce matériel.
Notre souci a été d'extraire le ou les paramètres maintenus (voir figure  2 ) pour déterminer s'il y avait : • une relation dérivative par un ou plusieurs paramètres (entre lait et allaiter , les paramètres d'emplacement et de mouvement sont identiques) • une relation de composition avec maintien de la base (entre la base lait et laitierpersonne vendre lait) • aucune relation morphologique paramétrique. Après avoir constitué ce matériel linguistique, nous avons extrait les voisins orthographiques via la base de données BRULEX  (Content et al. , 1990).
Ce matériel devrait servir à la mise au point d'une série d'expériences de psycholinguistique ayant pour objectif de mesurer la sensibilité de l'apprenti lecteur sourd à la fois à la structure interne de sa langue maternelle (i. e. la LSF) et à la structure morphologique de la langue écrite, laquelle doit être mise en correspondance avec la première afin d'établir des connexions entre représentations mentales signées et représentations mentales orthographiques. La question que pose la L'hypothèse que nous formulons à l'égard de la comparaison des différentes caractéristiques de ces deux langues en contact chez l'apprenti lecteur sourd, est liée à la notion de conscience morphologique (selon  Carlisle, 1995). Le corpus présenté se donne pour objectif de constituer une base de données pour l'étude de la conscience morphologique chez ces apprentis lecteurs particuliers qui ne disposent pas -ou dans une très faible proportion -d'accès à la conscience phonologique (e.
e. the combination of two lexically independent signs) and some words that can be considered as derived (i. e. , a sign + a modifier, as Aronoff (2005) suggested). We first selected the 100 most representative families of French in Grade 2 (CE1 in French) from EDUSCOL lexical database, proposed by the French Educational Ministry (http:// eduscol. education. fr). Then we kept nouns, verbs and adjectives and rejected other grammatical forms. Then we used a second database (MANULEX: database created with scholar books,  Lété et al. , 2004)  to extend our corpus to 62 morphological families, representing 1140 words (whose mean frequency= 330 occ. /million). We spread the data according to their morphological structure that is derivative or compound. We observed that 79% of the 1140 words were derived (896 words) and 21% were compound (244 words).
differences of the words shared by these two languages. The construction of such a lexical database required on one hand the selection of the most representative morphological families (in terms of the frequency of use and their familiarity for second grade children), the analyses of their structural and distributional properties (i. e. family size, cumulated frequencies, Correspondances morphologiques entre le français et la langue des signes fran. TIPA. Travaux interdisciplinaires sur la parole et le langage, 34 | 2018.
avons réalisé une base de données regroupant 62 familles morphologiques du français et leur équivalent en LSF (support vidéo) et nous avons analysé la structure morphologique et la répartition de la dérivation et de la composition de chaque famille. Afin de comprendre le lien que les enfants sourds font entre les mots écrits et la lecture, nous nous sommes concentrées sur le degré de correspondance du mot signé par rapport à un mot écrit. Notre hypothèse est que lorsqu'il existe une consistance entre le mot écrit et le mot signé, l'enfant sourd peut faire correspondre le signe et le morphème afin de faciliter la reconnaissance du mot.
avons réalisé une base de données regroupant 62 familles morphologiques du français et leur équivalent en LSF (support vidéo) et nous avons analysé la structure morphologique et la répartition de la dérivation et de la composition de chaque famille. Afin de comprendre le lien que les enfants sourds font entre les mots écrits et la lecture, nous nous sommes concentrées sur le degré de correspondance du mot signé par rapport à un mot écrit. Notre hypothèse est que lorsqu'il existe une consistance entre le mot écrit et le mot signé, l'enfant sourd peut faire correspondre le signe et le morphème afin de faciliter la reconnaissance du mot. Pour ce faire, nous avons tout d'abord sélectionné les bases selon leur fréquence sur EDUSCOL 7 , une liste de fréquences lexicales de 1500 items, connue des enseignants du cycle 2.