dataesr/scientific-paragraphs-categorization huggingface dataset:
dated from the Palaeolithic to the Iron Age (database published in Fischer et al. 2018). Since potential maternal kinship within both UN and GLN necropolises has been previously noted (which may bias haplogroup frequency estimations), we carried out PCA either considering all the individuals (Fig 3) or only one individual per haplotype (S2 Fig). As the exclusion of potentially maternally related individuals had no significant effect on the PCA structure, we decided in the main text to present the PCA obtained for the entire UN and GLN groups.
Acknowledgments We would like to warmly thank  R. Petit  and the  Pierroton Genome Transcriptome team  for their comments and assistance. We would also like to thank  G. Depierre  as well as the members of the  Université de Bourgogne  and the  UMR 6298 ArTeHiS  for their hospitality during the sampling of the Gurgy 'Les Noisats' collection. We also acknowledge everyone who contributed to excavations at UN and GLN. We finally thank anonymous reviewers for helpful and constructive comments which greatly improved the manuscript.
Funding sources 26 This study benefitted from excavation grant support from the  Ministère de la Culture et de la Communication , the  Service Régional de l'Archéologie de Basse-Normandie  (number  OA2033  and  OA3123 ) and DRASM (Direction of submarine archaeological research), and from  Department of Manche , as well as the  Service Régional de l'Archéologie de Bourgogne  (site number  89 198 008 ). This research was funded by a ministerial grant from the  Research National Agency  as part of the  ANR-10-LABX-52  (http://www. agence-nationale-recherche. fr/)( Identi-Fer  project,  S. Rottier Dir ,  2018-2020 ). The study was also financially supported by a PhD research grant from the  Ministère de l'Enseignement Supérieur et de la Recherche  for CEF (http://www. enseignementsuprecherche.
gouv. fr/). Part of the experiments presented (SNPs analyses) were performed at the  Genomic and Sequencing Facility of Bordeaux , grants from the  Conseil Régional  d'Aquitaine n°20030304002FA and 20040305003FA, https://www. nouvelle-aquitaine. fr/, from the  European Union ,  FEDER n°2003227  and from Investissements d'avenir, Convention attributive d'aide  N°ANR-10-EQPX-16-01 , http://www. agence-nationale-recherche. fr/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data collection To capture discourses and thus representations at a macro level is particularly problematic. Scholars have mobilised different methods to capture these macro representations, for instance analysing cartoons  (Hardy & Phillips, 1999) , scholarly texts, Internet movie database  (Lawrence & Phillips, 2004) , or press articles  (Patriotta et al. , 2011; Selsky, Spicer, & Teicher, 2003). This research also relies on press articles to account for discourse at the industry level. In line with historical studies of institutional fields inspired by discourse analysis  (Hardy & Phillips, 1999; Lawrence & Phillips, 2004; Maguire & Hardy, 2006; Munir & Phillips, 2005; Selsky et al. , 2003) , we sought to trace shifts in the words which appeared in a consistent body of texts which informed debate and discussion related to the recorded music industry.
We used two press databases-Factiva and Europresse-to identify articles whose main topic relate to the music industry, using as keywords (in French) "music AND (industry OR sector). " After excluding articles deemed to be irrelevant-for example, duplicates, short news or commercial announcements-this gave us an archive of more than 800 articles (1,800 pages) drawn from a variety of French newspapers (appendix 1). The articles come from generalist newspapers (e. g. , Le Monde, Le Figaro, Libération), the economic press (e. g. , La Tribune, Les Echos), monthly magazines (e. g. , Le Monde diplomatique, Courrier International), and web articles (e. g. , Le Monde. fr, La Tribune. fr). These sources cross the political spectrum from the right (Le Figaro) to the left (Libération). As such, their content may present some variations depending on the ideological position of the editorial board.
Data analysis In order to highlight the stabilization of discursive repertoires at the industrial level, we employed the lexicometric software program Prospéro, with a corpus linguistics approach  (Perren & Sapsed, 2013; Pollach, 2012). This software is similar to WordStat in the way that it determines frequency lists, keywords and collocated words, and allows researchers to draw on collective dictionaries. We chose Prospéro for several reasons. First, it was initially designed by sociologists to explore texts in the context of conflict and change. One very useful feature is that it relies on the dynamic analysis of texts. It is possible to divide a corpus into different periods and compare them with a view to identifying stable arrangements or changes. Second, Prospéro relies on dictionaries in French which have been progressively refined by an active community of scholars in linguistics, sociology and psychology.
Generally, this study is focused on highlighting the advantage of using the integration between the historic topographical maps, Optical Landsat data, and the Radar Sentinel-1 data in archaeological and heritage studies. In more detail, the ancient topographic maps, Corona, Landsat satellite MSS, TM images, and SRTM data can give an accurate vision of the landscape in Egypt in the last Century and the Sentinel-1 radar data. The integration, analysis and interpretation of all of these datasets is addressed to improve our knowledge about Tells in the Northern Nile Delta in Egypt with the primary goal of detecting the extents of the ancient kingdoms of Buto and Sakha, and, therefore, to expand the study area to the North Delta. This is undertaken by performing a landscape classification to identify geomorphological units with more potential to contain archaeological evidence (from settlements to burials and all sorts of evidence) and identify potential buried buildings which can reveal ancient settlement areas in the captured satellite images.
Finally, correlating ancient topographic maps and remote sensing data (e. g. optical and radar data) can help to expand our understanding of the settlement history of the delta when correlated with archaeological data that verifies image interpretation and provides chronological control. This preliminary study is a further step, building on the work of the EES (Egyptian Exploration Society) Delta Survey, the EAMENA (Endangered Archaeology in the Middle East and North Africa) project, and the work of other researchers in developing a methodology to address the lack of data related to the evolution of socio-political complexity in the Nile Delta.
Materials This study used the archives of the British Library 1722 topographic map, the American War Office 1941 topographic map with a scale of 1:100000, the topographic maps of the Egyptian General Survey Authority published in 1950 with a scale of 1:25000, and the topographic maps of the Egyptian General Survey Authority published in 1997 with a scale of 1:50000, to identify topographic features and to detect natural and anthropogenic changes in study area. Also, SRTM, Corona Jan 1965, the Landsat satellite images MSS May 1973, MSS May 1978, MSS May 1988, and TM May 2005 were used to define elevation and vegetation values for the various layers in the study area. The current SRTM, Corona, and Landsat archive are accessible from the USGS earth explorer  [47]. Radar data from Sentinel-1 from 5 May 2018, and Sentinel-1B captured on 22 May 2019, were selected because May offered clear visibility and it is in the harvest season in Nile Delta (Table  1 ).
The current Sentinel-1A/B archive is accessible from the Sentinel Scientific Data Hub  [48]. The topographic maps and SRTM data were rendered using the tools available in the ArcMap 10. 4. 1 software. Optical satellite imagery processing was done using tools available in Envi 5. 1 and ArcMap 10. 4. 1 software. The Sentinel application platform (SNAP 6. 0) software was used for processing the Sentinel-1 data. The analyses were used to detect potential buried settlement areas through georectification of digitized images, analysis of features in the radar data, and band-combination techniques of the past data (Figure  2 ).
Digitizing the Topographical Maps Topographic map sheets were scanned and the raw data were geographically corrected using the georeferencing tool (add control points) in ArcMap software based on the projection coordinate system WGS_1984_UTM_Zone_36N  [49]. The registered topographic maps were aligned with the georeferenced satellite images (Landsat) for assessment of the accuracy of the referenced data. The topographic maps were clipped according to the area of interest of the study area to facilitate processing speed. The required thematic layers (e. g. points, lines, and polygons) were defined according to identifiable features on the GIS and created in a geodatabase. All topographic map analyses were completed using the GIS software (ArcMap 10. 4. 1).
Band Indices Landsat Multi-Spectral Scanner (MSS) and Thematic Mapper (TM) images were geometrically corrected, calibrated, and removed from their dropouts. Histogram equalization enhancement techniques were also performed on each image to improve the quality of the data. According to the differences in the band-designations of the two sensors (Landsat MSS and TM data)  [50] , the band properties for the collected data were taken into consideration before applying the band combination method (Tables  2  and 3 ). In this study, the original marshlands and barren areas of the northern delta were detected according to four kinds of band indices by measuring the vegetation values. The band combinations were extracted from Landsat MSS and TM imagery. The first method used was the Global Environmental Monitoring Index (GEMI), which is produced by Equation  (1)  [51].
4. Preparing the Radar SRTM Data After downloading the Shuttle Radar Topography Mission (SRTM) 1 arc-second data, the raw data were geometrically corrected based on the WGS_1984_UTM_zone_36N projection coordinate system. Then, the SRTM data was clipped according to the area of interest. Using the ArcMap software, the disparity in the topography of the earth in the study area was detected using SRTM data.
• Radiometric calibration Radiometric correction of an image was carried out so that the pixel values truly represented the backscattering of the reflecting surface. After data preprocessing, the calibrated data were filtered to reduce SAR inherent speckle noise and clipped in range and azimuth in order to remove image border noise. The result of the preprocessing is a reprojected, radiometrically-calibrated, and rescaled normalized radar cross-section (NRCS) image  [58]. The radiometric calibration was applied using Equations (  5 )-(  12 )  [59] : value(i) = |DN_i |ˆ2/(A_iˆ2 ) (5) where, depending on the selected Look Up.
• Radiometric calibration Radiometric correction of an image was carried out so that the pixel values truly represented the backscattering of the reflecting surface. After data preprocessing, the calibrated data were filtered to reduce SAR inherent speckle noise and clipped in range and azimuth in order to remove image border noise. The result of the preprocessing is a reprojected, radiometrically-calibrated, and rescaled normalized radar cross-section (NRCS) image  [58]. The radiometric calibration was applied using Equations (5-12)  [59] : value(i)=|DN_i |^2/(A_i^2 ) (5) where, depending on the selected Look Up Table (LUT), value(i) = one of 〖β_i〗^0,〖σ_i〗^0 or γ_i or originalDN_i. A_i=one of betaNought (i),single Nought t(i) ,gamma(i) or dn(i) Bi-linear interpolation should be used for any pixels that fall between points in the LUT.
Therefore, the Multilooking technique tool in the SNAP software was required to reduce the speckle noise effect, reaching a spatial resolution of 20 m  [60]. • Speckle filter Furthermore, speckle filtering was needed to suppress the noise and to remove observations that were not affected by noise and that contained valuable land surface information (e. g. soil moisture and biomass extent). In this study, the single product speckle filter method in SNAP was used to remove the speckle. The SNAP Sentinel-1 Toolbox operator supports the speckle filter types for handling speckle noise of different distributions (Gaussian, multiplicative or Gamma): Mean, Median, Lee, Refined Lee, and Gamma-MA. Therefore, the Refined Lee filter was applied because it maintains the detail of the standing boundary  [61].
• Radiometric calibration Radiometric correction of an image was carried out so that the pixel values truly represented the backscattering of the reflecting surface. After data preprocessing, the calibrated data were filtered to reduce SAR inherent speckle noise and clipped in range and azimuth in order to remove image border noise. The result of the preprocessing is a reprojected, radiometrically-calibrated, and rescaled normalized radar cross-section (NRCS) image  [58]. The radiometric calibration was applied using Equations (5-12)  [59] : value(i)=|DN_i |^2/(A_i^2 ) (5) where, depending on the selected Look Up Table (LUT), value(i)=one of 〖β_i〗^0,〖σ_i〗^0 or γ_i or originalDN_i. A_i=one of betaNought (i),single Nought t(i) ,gamma(i) or dn(i) Bi-linear interpolation should be used for any pixels that fall between points in the LUT.
The Results of the Sentinel-1 (C-Band) In this study, we tested the suitability of the observations of the Sentinel-1 interferometric wide swath (IW) acquisition mode for detecting the potential areas for settlements in wetland using SAR data. In order to achieve our aim, the data were analyzed using apply orbit file, radiometric calibration, multilooking, speckle filtering, and geometric terrain correction. Two Sentinel-1 images (GRD) were tested, i. e. , S-1A May 2018 and S-1B May 2019. The results of the investigated imagery dates showed that the composite value could be seen using the Intensity VV+VH and Amplitude VV+VH. A calibration vector allowed a simple conversion to be made of image intensity values into sigma0 values (Sigma0_VV and Sigma0_VH), the most suitable polarization for showing the potential settlements in this study is the Sigma0_VV value.
This enormous change in the land use in the study area led to these barren lands being covered with the vegetation. Four optical satellite images were also used to detect the original marshlands. The enormous changes in the land use/land cover in the study area could be observed using Corona data from 1965 (most of the total space of the discovered areas were still barren land with some signs that show the ancient boundaries of the original koms) and the subsequent dates of Google Earth images between 1984 and 2016 (Figure  6a-d ). potential buried settlement sites in the Nile Delta. In general, the topographic maps can give information about some features that have since disappeared according to the changes in the land use/land cover  [65]. Also, the reflected vegetation value from the band indices techniques in the optical satellite images can give accurate information about land cover classes  [66].
According to the changes in the barren land area in the analyzed topographic maps between 1941 and 1997, the barren lands were higher than the surrounding marshlands and all of these barren lands except for an area of 9. 3 km² became cultivated lands. This enormous change in the land use in the study area led to these barren lands being covered with the vegetation. Four optical satellite images were also used to detect the original marshlands. The enormous changes in the land use/land cover in the study area could be observed using Corona data from 1965 (most of the total space of the discovered areas were still barren land with some signs that show the ancient boundaries of the original koms) and the subsequent dates of Google Earth images between 1984 and 2016 (Figure  6ad ). In the 19th century, Sir William Smith referenced the Diocese of Buto (Butos in Greek language) that corresponds to the Ancient city of Buto in the Nile Delta, and noted that north of the town of Buto was a lagoon formed by the Nile near its junction with the Mediterranean Sea has that was likewise named Buto Lake; within the lake was the islet of Chemmis  [69].
The SRTM data was used to detect the differences in surface elevation in the study area which demonstrated that the potential settlement areas (5-7 m) have a higher value than the surrounded areas about 2 or 3 m. It was observed that the study area was situated at three main elevations between one and thirteen meters. The first level, between 1-2 m, represents the total elevation of the agriculture land. The second level, between 5-7 m, clearly demarks the total selected areas as possible archaeological sites. The third level, between 9-13 m, represents known archaeological tells. In general, the elevation data collected in the interstitial areas do not provide evidence of archaeological features, whereas known tell sites with the highest elevation and the suggested sites with an elevation between 5-7 m do indicate known and a possible history of ancient architecture.
These results support the notion that the selected areas are candidates for buried archaeological features now hidden in the floodplain alluvium which has accumulated an overburden of Nile silt (up to 6 m) and a general rise in the water table, which would place the deeper archaeological features below well below the water table  [79]  (Figure  8 ). yielded low values in the areas of recent tells; the variance between these images can be explained by the anthropogenic processes of reclamation and soil enhancement in recent decades. The disparity in the land topography in the current study (having about 10 potential archaeological sites around the potential settlements areas) suggests the presence of significant occupation features under the recent urban and agriculture lands. The SRTM data was used to detect the differences in surface elevation in the study area which demonstrated that the potential settlement areas (5-7m) have a higher value than the surrounded areas about 2 or 3m.
Sentinel-1 (c-band) data were analyzed to detect buried material in the study area. As the result of the large size of the potential discovered areas and the previous results of the ancient topographic maps integrated with the optical imagery, the results of the analyzed Sentinel1-A May 2018 and Sentinel1-B May 2019 data suggest that the barren lands observed in 1941 and 1950 could have been occupations in ancient times. This supposition is supported by the identification of three separate areas of possible occupation. These discovered features are not completely contiguous in every area, and they appear in discrete blocks. The first discovered area covers about 12. 2 km 2 , the second covers about 3. 12 km 2 , and the third covers about 2. 2 km 2. Furthermore, after the matching between the extracted layers of the maps, the optical data, and the Sentinel1 radar data, the results of the study support a theory that the old barren lands were relicts of ancient landscapes associated with human occupation  [80].
Conclusion The current improvements in earth observation technologies offer advanced technical characteristics that enable new applications of methods specifically designed for the documentation, discovery, and risk monitoring of cultural heritage. In particular, the most recent space missions such as the European Space Agency (ESA) Sentinel-1 A, B are specifically concerned with flooding studies and heritage prospection, and have been systematically acquiring data for the entire globe [87]. This study explores the possibility of integrating historical topographic maps, optical, and radar data for the detection of ancient landscapes and sites in Egypt. The results of the topographic map analysis helped in detecting the changes in the land-use/land-cover between 1941 and 1997. Also, the changes in the land use/land cover between 1965 and 2016 were detected by integrating the optical Corona.
Conclusions The current improvements in earth observation technologies offer advanced technical characteristics that enable new applications of methods specifically designed for the documentation, discovery, and risk monitoring of cultural heritage. In particular, the most recent space missions such as the European Space Agency (ESA) Sentinel-1 A, B are specifically concerned with flooding studies and heritage prospection, and have been systematically acquiring data for the entire globe [87]. This study explores the possibility of integrating historical topographic maps, optical, and radar data for the detection of ancient landscapes and sites in Egypt. The results of the topographic map analysis helped in detecting the changes in the land-use/land-cover between 1941 and 1997. Also, the changes in the land use/land cover between 1965 and 2016 were detected by integrating the optical Corona data from January 1965, and the Google Earth Images  (1984, 1995, and 2016).
Evidence of changes in the original boundaries of the ancient koms and tells were detected using Corona data from 1965. In the same context, four types of remote sensing indices were applied in  Landsat MSS 1973 , 1978 , 1988 , and TM 2005  to detect the original marshlands. Radar SRTM data was used to identify the disparity in the elevation and topography between the potential settlement areas and the surrounding lands. By correlating older topographic maps with the Sentinel-1 radar outputs, we were able to analyze variations between the higher elevation and low-lying lands and compare contours derived from multiple sources. Overall, the results indicate that the areas identified from the radar Sentinel1 as potential settlements are very close to the lost areas around Lake Buto (Diocese of Buto) correlate with the barren land in the 1941 topographic map, the areas with low vegetation values in the investigated optical images using band indices techniques, and the higher elevation lands in the SRTM data.
Furthermore, the higher elevation areas in the SRTM data tend to be larger than the selected areas in the radar data, because the Sentinel1 data indicated a reflectance from possible architectural remains yielding the solid in white color. Areas identified based on elevation could represent areas of ancient activity that lack architectural remains due to the land-use history, and thus, that would not be detected by the Sentinel1 data. Likewise, the same reasoning can be applied to the topographic and optical data. In the same context, some observed areas in Sentinel1 data are not completely contiguous, so some green strips (no indication of settlement) are observed inside the suggested areas as settlements based on the optical data. In this study, we applied a multifaceted study of various sources of high-quality landscape mapping to build a general vision of the modern and ancient geomorphological and topographic dynamics of landscapes of the Delta civilizations.
The outline of each tooth was captured using the freeware GIMP (www. gimp. org). Points are placed around the outside of the tooth using the lasso tool. The image is then converted into a black and white image  with the bucket fill tool (Figure  1 ). Conservative estimates were made for teeth that had interproximal wear or damage to the crown. For each tooth (i. e. , M 1 , M 2 and M 3 ), the binarized black and white images of the teeth were loaded into the R statistical programming language (R Core Team, 2017) using the "import_jpg" function from the "Momocs"  (Bonhomme et al. 2014)  library which extracts points along the edge of the shape of the tooth. An EFA was then performed on the shape of the outline of the occlusal surface in order to produce amplitudes of the harmonics. The amplitudes are the degrees of deviation between the object in question and an original ellipse  (Brophy et al.