dataesr/scientific-paragraphs-categorization huggingface dataset:
Data Collection In this step, the components of the crafting process are digitally recorded, postprocessed, and curated in an online platform. These digital assets record objects and actions, acquired from documenting photographically and in 3D materials, tools, products, and workspaces and recording practitioner crafting actions, in recording sessions. The organization of these sessions is facilitated by the vocabulary and storyboard, in identifying the objects, sites, and practitioner actions to be digitized. Moreover, some of the photographic and video assets may be recorded in combination with ethnographic fieldwork. A requirement relevant to the glasswork, but also relevant to other crafts, is that the viscous nature of hot glass prohibits the pause of the crafting process during some sequences of tasks.
During this, fourteen carafes were produced in the workshop to observe and capture social and body interactions that take place during glasswork. Apart from the audiovisual documentation acquired, the process was recorded using MoCap equipment and, in particular, the Nansense MoCap suit and gloves. Table  1  illustrates the tasks that were recorded for glassblowing. The activities presented in the previous subsection create a large amount of data that should be rationalized, post-processed, and curated to be exploitable for future research. In this context, photographic documentation, video recording of the creation process, 3D objects, and 3D reconstructions are uploaded to the Mingei repository and documented in MOP. Motion recordings are also stored in the repository and documented in MOP to formulate Motion Vocabularies.
All digital assets receive unique IRIs for semantic interoperability. Photographic, audiovisual, and 3D assets that are ingested in the MOP can be browsed by file properties and by thumbnail preview, as shown in Figure  7. The activities presented in the previous subsection create a large amount of data that should be rationalized, post-processed, and curated to be exploitable for future research. In this context, photographic documentation, video recording of the creation process, 3D objects, and 3D reconstructions are uploaded to the Mingei repository and documented in MOP. Motion recordings are also stored in the repository and documented in MOP to formulate Motion Vocabularies. All digital assets receive unique IRIs for semantic interoperability. Photographic, audiovisual, and 3D assets that are ingested in the MOP can be browsed by file properties and by thumbnail preview, as shown in Figure  7.
The activities presented in the previous subsection create a large amount of data that should be rationalized, post-processed, and curated to be exploitable for future research. In this context, photographic documentation, video recording of the creation process, 3D objects, and 3D reconstructions are uploaded to the Mingei repository and documented in MOP. Motion recordings are also stored in the repository and documented in MOP to formulate Motion Vocabularies. All digital assets receive unique IRIs for semantic interoperability. Photographic, audiovisual, and 3D assets that are ingested in the MOP can be browsed by file properties and by thumbnail preview, as shown in Figure  7. The activities presented in the previous subsection create a large amount of data that should be rationalized, post-processed, and curated to be exploitable for future research.
In this context, photographic documentation, video recording of the creation process, 3D objects, and 3D reconstructions are uploaded to the Mingei repository and documented in MOP. Motion recordings are also stored in the repository and documented in MOP to formulate Motion Vocabularies. All digital assets receive unique IRIs for semantic interoperability. Photographic, audiovisual, and 3D assets that are ingested in the MOP can be browsed by file properties and by thumbnail preview, as shown in Figure  7. The activities presented in the previous subsection create a large amount of data that should be rationalized, post-processed, and curated to be exploitable for future research. In this context, photographic documentation, video recording of the creation process, 3D objects, and 3D reconstructions are uploaded to the Mingei repository and documented in MOP.
Motion recordings are also stored in the repository and documented in MOP to formulate Motion Vocabularies. All digital assets receive unique IRIs for semantic interoperability. Photographic, audiovisual, and 3D assets that are ingested in the MOP can be browsed by file properties and by thumbnail preview, as shown in Figure  7. The activities presented in the previous subsection create a large amount of data that should be rationalized, post-processed, and curated to be exploitable for future research. In this context, photographic documentation, video recording of the creation process, 3D objects, and 3D reconstructions are uploaded to the Mingei repository and documented in MOP. Motion recordings are also stored in the repository and documented in MOP to formulate Motion Vocabularies. All digital assets receive unique IRIs for semantic interoperability.
Photographic, audiovisual, and 3D assets that are ingested in the MOP can be browsed by file properties and by thumbnail preview, as shown in Figure  7. The activities presented in the previous subsection create a large amount of data that should be rationalized, post-processed, and curated to be exploitable for future research. In this context, photographic documentation, video recording of the creation process, 3D objects, and 3D reconstructions are uploaded to the Mingei repository and documented in MOP. Motion recordings are also stored in the repository and documented in MOP to formulate Motion Vocabularies. All digital assets receive unique IRIs for semantic interoperability. Photographic, audiovisual, and 3D assets that are ingested in the MOP can be browsed by file properties and by thumbnail preview, as shown in Figure  7.
Knowledge Representation The objects and actions of the crafting process are semantically represented in this step. The representation uses a few classes, called basic knowledge elements, which contain links to semantic metadata provided by the user and links to the digital assets formed in the previous step. From motion recordings, reference postures and gestures are identified by the user. To associate frames and segments from motion recordings with postures and gestures respectively, the AnimIO annotation editor  [45]  was employed, which facilitates bodymember-specific annotation of motion recordings. To represent tool and machine usage, motion recordings and 3D models are combined. The recorded gripping postures come into use in this task. The recordings are combined under the context of the Event knowledge entity, which contains links to the representations of the Location, Participants, Tools, Materials, and.
Knowledge Representation The objects and actions of the crafting process are semantically represented in this step. The representation uses a few classes, called basic knowledge elements, which contain links to semantic metadata provided by the user and links to the digital assets formed in the previous step. From motion recordings, reference postures and gestures are identified by the user. To associate frames and segments from motion recordings with postures and gestures respectively, the AnimIO annotation editor  [45]  was employed, which facilitates bodymember-specific annotation of motion recordings. To represent tool and machine usage, motion recordings and 3D models are combined. The recorded gripping postures come into use in this task. The recordings are combined under the context of the Event knowledge entity, which contains links to the representations of the Location, Participants, Tools, Materials, and (intermediate) Products pertinent to the event.
Digital Preservation The digital assets hosted in the MOP repository are provided online in conventional and open formats. Each asset has a unique IRI to be directly integrated by third parties. Our knowledge is available to the Semantic Web via the MOP and the SPARQL endpoint exposed. Furthermore, to ensure compatibility with online knowledge sources, definitions of terms are imported to MOP through linking to terms from the Getty Arts and Architecture thesaurus and the UNESCO thesaurus. For further exploitation of semantic knowledge encoded in MOP, an EDM export facility has also been implemented, allowing (a) export of data in semantic compatible to EDM format and (b) formulation of SPARQL queries to the MOP SPARQL endpoint to receive EDM formatted results.
Craft Documentation The represented knowledge network is available through the WWW and the MOP in hypertext format. Semantic links are implemented as hyperlinks that lead to the pages of cited entities. Contents are also organized and presented thematically, per class type. A keyword-based search is also provided. Documentation pages contain links to digital assets, textual presentation of metadata, and previews of the associated digital assets. For locations and events, specific UI modules are provided. For locations, embedded, dynamic maps are provided through OpenStreetMap  [32]. Timeline and calendar views are available for events. The vocabularies formulated in the first step of the craft representation are provided as illustrated vocabularies of tools, which bring together verbal descriptions and visual recordings.
Implementation of Virtual Humans and Animation The virtual human bodies and clothes are created to obtain one unified and optimized model, enhancing the visual impact of the characters with texture mapping and material editing. The 3D generation of the virtual bodies also must take into consideration the total number of polygons used to create the meshes in order to keep a balance Heritage 2022, 5 119 between the 3D real-time simulation restrictions and the skin deformation accuracy of the models. Avatars are created with a combination of different software: Adobe Fuse CC/Mixamo  [59]  is used for creating the body character, the clothes, the hair, and the rigging. The generated model is then imported into Autodesk 3DS max [60] for mesh geometry optimization. Manual methods, by using the editable poly tools, is preferred because it allows us to keep the regularity of the topology while the automatic methods generate a mess geometry which is not suitable for skin deformation nor a regular UV texture map generation.
• Transposition of the received animations (. bvh files) on the actor • Synchronization of the avatar with the actor by adjusting the the models so that the measurements match and the animations are correctly reproduced (retargeting). Heritage 2022, 5, FOR PEER  REVIEW 17  Avatars are created with a combination of different software: Adobe Fuse CC/Mixamo  [59]  is used for creating the body character, the clothes, the hair, and the rigging. The generated model is then imported into Autodesk 3DS max [60] for mesh geometry optimization. Manual methods, by using the editable poly tools, is preferred because it allows us to keep the regularity of the topology while the automatic methods generate a mess geometry which is not suitable for skin deformation nor a regular UV texture map generation.
Craft Training To experience glassblowing gestures, an interactive installation was created, with the use of MAX/MSP 8, a visual programming framework, in combination with python programming, as well as an RGB-D Intel Realsense camera for the real-time tracking and recognition of the gestures of the user. The information that was used from both videos from the gesture recognition engine was the upper body joints (shoulders, elbows, wrists, neck), as extracted from the OpenPose [62] framework. OpenPose is a system for real-time human joints detection, with the use of Deep Learning architectures. In the screen (see Figure  16 ), a big frame with the video of the expert glassblower appears, while a smaller one with the video of the visitor places on the top-left of the screen. The user can either start experimenting directly or choose the question mark sign on the top of the installation screen, to see the instructions before starting imitating.
Despite recent advances in artificial intelligence, human translators outperform MT for at least three types of tasks: identifying referents in anaphora (especially of the interphrastic kind), resolving semantic ambiguity (which is mainly due to polysemy or homonymy), and resolving syntactic ambiguity (especially with poorly inflected source languages such as English). Using the results obtained by two freely available online machine translation programs, Google Translate and DeepL, we examine how these two types of ambiguity are processed in translation from English into French, Spanish and Italian. Our results show that the two programs perform well overall in resolving the simplest cases of syntactic ambiguity, with difficulties arising more frequently for noun phrases featuring atypical syntactic divisions and rarely used collocations.
, 2015; Vyverberg et al. , 2018; Stephenson et al. , 2019)  to investigate paleo sea-level changes. Dutton et al. (2015)  and later  Vyverberg et al. (2018)  analyzed fossilized coral deposits amongst the boulders of the granitic Seychelles, identifying slight mid-MIS 5e drop in relative sea level. Stephenson et al. (2019)  resurveyed and re-dated fossil reef terraces on the northern tip of Madagascar that were originally described by  Battistini (1965). This series of terraces, argue  Stephenson et al. (2019) , have been subject to post-depositional movement driven by mantle upwelling. Boyden et al. (2021)  highlight that, while these are the only reliable sea-level datasets within the western Indian Ocean region, there are many other locations that would benefit from new field data, that may build upon the results of earlier works.
SURVEY The GNSS survey of the Pleistocene coastal facies at Lembetabe was carried out using a pair of Emlid REACH RS+ singleband GNSS receivers, set up in a Base/Rover Post-Processing Kinematic (PPK) workflow. While not ideal, due to the remote nature of Lembetabe there was no possibility to take advantage of receiving Real Time Kinematic (RTK) corrections through an NTRIP (Networked Transport of RTCM via Internet Protocol) service, nor via a permanent known base station broadcasting corrections over a LoRA (Long Range) radio. In order to obtain the most reliable results despite these shortcomings, the base station receiver was set up in an open area and left to collect data over each field day (approximately 12 hr, 24°40' 47. 54841"S, 43°56' 36. 13244"E, see processing reports available in the Electronic Supplementary Material).
U-SERIES DATING Ten samples were analyzed for U-series isotopic ratios. All of these coral samples showed calcite content below 1%. The only exception is the sample IT-19-25 that returned an averaged calcite content of 1. 95 ± 0. 13% over three separate analyses. While this is greater than the 1% calcite content threshold used here, it is still below the 2% calcite content screening limit employed by others (e. g. ,  Dutton and Lambeck, 2012; Hibbert et al. , 2016). The 10 U-Th ages obtained in this study and accompanying metadata are summarized in Table  3. They range from 126. 9 ±0. 2 ka to 542 ±36 ka. All following chronological uncertainties are reported in ±2σ. Measured 230 Th/ 232 Th activity ratios were greater than the recommended value of 500, and all sample 232 Th concentrations were well below the recommended concentration of 12 ppb  (Chutcharavan and Dutton, 2021) , preventing any need for detrital thorium correction in the final age calculation.
ACKNOWLEDGEMENTS The authors would like to acknowledge the IRD mission in Antananarivo, specifically  Claude-Anne Gauthier ,  Regine Rakotoniaina , and  Hary-liva Ravelonjatovo. We would also like to thank the support staff including drivers who made this remote fieldwork possible and finally,  Hélène Mariot  and  Marion Defrance  for their attentive support in CEREGE's lab.
DATA ACCESSIBILITY STATEMENT 3D reconstructions are available on Sketchfab at: https:// skfb. ly/o7CWB. GNSS metadata, SfM-MVS reports, and additional outcrop photos are available in the Electronic Supplementary Material at https://doi. org/10. 5281/ zenodo. 5727117 (Version 1. 0, Boyden and Rovere, 2021).
FUNDING INFORMATION This research was funded by the DFG (Deutsche Forschungsgemeinschaft) Excellence Cluster "EXC 2077: The Ocean Floor -Earth's Uncharted Interface" (Project number: 390741603), the French National Institute for Sustainable Development (IRD), the Agence Nationale pour la Recherche (ANR, France) through the project EQUIPEX ASTER-CEREGE, the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 802414), and the Helmholtz-Exzellenznetzwerke (grant No. ExNet-0001-Phase 2-3) "The Polar System and its Effects on the Ocean Floor (POSY)".
AUTHOR CONTRIBUTIONS PB, JWA, PD, and AR conceived the project; PB, JWA, PD, MNR, and AR planned the field campaign; PB, JWA, PD, NG, NJ, MO, and AR conducted field measurements and sample collection; PB analyzed both GNSS and SfM-MVS datasets; JWA, AG, and MH processed and analyzed U-series data; AR curated 3D outcrop visualizations on Sktechfab; PB wrote the initial manuscript; all authors reviewed and edited the manuscript.
Camel reliefs and LNEC are usually also depicted with pronounced humps and rounded bellies, signs that they are well fed, and a possible reference to the wet seasona time of year when vegetation was abundant, which would have coincided with the mating season  (Gauthier-Pilters and Dagg, 1981). Here we explore the possibility that the reliefs of the Camel Site may have been created during the Holocene humid period (ca. 8000-4000 BCE). We present data from archaeological excavations, scientific dating and technological analyses to support a Neolithic age for the reliefs. In northern Arabia, characteristics that are typically used to define the Neolithic in the Levantine sphere, such as sedentism, agriculture, and pottery, are only known from Bronze Age and later contexts  (Magee, 2014). The presence of domesticated livestock is therefore often used to define the pastoralists of the 6th millennium BCE as Neolithic  (Crassard and Drechsler, 2013).
Portable X-ray fluorescence spectrometry Measurements by portable X-Ray Fluorescence Spectrometry (pXRF) were conducted on selected elements at the Camel Site to determine the density of manganese in the rock varnish in order to derive age estimates for the carvings. The technique has been described in detail elsewhere  (Macholdt et al. , 2018; Macholdt et al. , 2019)  and will only be outlined briefly here. Measurements were conducted using a Niton XL3 pXRF (Thermo Fisher Scientific) in the "mining" mode. The instrument is equipped with an X-ray source with an energy of 50 keV and a silver anode and has a spot size of 8 mm in diameter. For quality control, the reference materials TILL1 and FeMnOx-1 (GeoReM database, version 25; http://georem. mpch-mainz. gwdg. de; Jochum et al. , 2005)  were measured before and after each XRF measurement sequence.
, 2019). The varnish density is represented by the areal density of manganese (Mn), D Mn , and its normalized equivalent, N Mn. The average D Mn on the intact varnish at the Camel Site, 172 ± 50 µg cm -2 , is in the range typical of northern Arabian varnish  (Andreae et al. , 2020; Andreae et al. , 2021; Macholdt et al. , 2018). We calculated the rate of Mn accumulation on the rock art surfaces by dividing D Mn and N Mn measured on Hismaic and Mixed Safaitic/Hismaic (MSH) inscriptions by the age of these scripts, ca. 2. 0 ± 0. 3 ka  (Macdonald, 2004; Norris, 2018). To obtain a representative average, we used data from both the Sakaka and Kilwa areas for this purpose  (Andreae et al. , 2020). The resulting absolute and normalized accumulation rates are R Mn = 28 ± 11 µg cm -2 ka -1 (95% confidence interval: 18-38 µg cm -2 ka -1 ) and R NMn = 14.
4 ± 6. 1 % ka -1 (95% confidence interval: 9. 4-19. 3 % ka -1 ), which are the values that we used as the basis for our estimates of rock art ages. The objective of our pXRF measurements at the Camel Site was to obtain data from rock art elements with a presumed wide range of ages, in order to support a chronology of rock art creation at the site. Regarding the high relief camel images, our selection was constrained by the very advanced degree of erosion of many of the reliefs and by the difficulty of access to the reliefs on the high cliffs. We chose Panel 1 (CS1-1, Fig. SI23 ), a fallen boulder that was originally above Panel 2 and showed a reasonably well preserved part of the body of a camel, and the head of the equid on Panel 2 (CS2-1, Fig. SI25 ), which could be reached from above. On the north side of Spur A, we measured on some wusum (CS2-2, Fig.
In addition, multiple stone tools were recovered from the base of reliefs and show visible signs of intense abrasion. These have been collected and their locations plotted; traceological (use-wear) analysis of these possible engraving tools is planned. This will provide a better understanding of the function of these tools. The raw material (a coarsegrained silicified sandstone) does not outcrop within a 15 km radius of the site, providing evidence for the extent of planning and logistics that was involved in the production of these tools. An exploratory experiment with stone tools was conducted to create a reference collection for the traceological analysis. This will give a comparative dataset that records the types of damage resulting from the use of stone tools to carve sandstone.
Acknowledgements We wish to thank  HRH Prince Badr b. Abdullah b. Mohammed b. Farhan Al-Saud ,  Ministry of Culture , and to  HRH Prince Sultan Bin Salman Bin Abdulaziz al-Saud , the former President of the  Saudi Commission for Tourism and National Heritage (SCTH)  for giving us permission to carry out research at the  Camel Site , and we also wish to thank his  Excellency Prince Faisal bin Nawwaf bin AbdulAziz al-Saud , governor of the  Jawf Province  for the support of his administration. We also thank  Mr Rustom al-Kubaisi , vice-president of the former SCTH, and the General Director for Archaeological Excavations at the  Heritage Commission Dr Abdullah al-Zahrani  and his assistants especially Saud M. al-Tamimi. Local support in Jawf province was provided by  Mr. Yasser  al -Ali  and  Mr.
Ahmed  al-Qaeed (SCTH now Heritage Commission). We thank  Wael Abu-Azizeh  for providing comparative data with lithic assemblages from the Levant; RC thanks  CEFREPA Kuwait  for funding part of this research. YHH's work leading to this publication was supported by the  PRIME programme of the German Academic Exchange Service (DAAD)  with funds from the  German Federal Ministry of Education and Research (BMBF). AMA acknowledges the support of the Research Center at the  College of Tourism & Archaeology, King Saud University, Riyadh, Saudi Arabia. We also thank  Mathew Stewart  for constructive comments on an initial draft of the manuscript. Fieldwork and research were funded by a grant from the  Gerda Henkel Foundation  (Grant No AZ  43_V_18 , to MG and GC), the  CNRS  (to GC),  Labex  Resmed  ANR-10-LABX-72 / ANR-11-IDEX-0004-02  (to GC), the  French Ministry of Foreign Affairs  and the  French embassy in Riyadh  (to GC), the  CEFAS  (to RC and GC), the  Dahlem Research School at Freie Universität Berlin  (to MG), the  Distinguished Scientist Fellowship Program of King Saud University  (to MOA and AA), and the  Max Planck Society  (to MG and MOA).