dataesr/scientific-paragraphs-categorization huggingface dataset:
Pre-rift structural framework of the Circum-North Atlantic region The main accretionary events predating CNAR breakup were the mid-Neoproterozoic Sveconorwegian-Grenvillian  (Bingen et al. 2008b; Roberts and Slagstad 2015) , the Neoproterozoic Timanian  (Roberts and Siedlecka 2002; Gee and Pease 2004 ) and the Phanerozoic Caledonian  (Roberts 2003; Gee et al. 2008)  and Variscan orogenies  (Matte 2001; Winchester et al. 2002; Franke 2006 ). These orogenies were in essence the expressions of two Wilson cycles: (i) the assembly and dispersal of the supercontinent Rodina in the Neoproterozoic leading to the formation of the Iapetus Ocean, followed by (ii) the renewed assembly and dispersal of Pangaea in the Phanerozoic and formation of the North Atlantic in the Cenozoic  (Stampfli et al. 2013).
The Caledonian Orogeny Prior to opening of the North Atlantic Ocean, Europe, North America and Greenland comprised part of the most recent continental amalgamation, Laurasia, the northern constituent of Pangaea (reconstructions in Figure  3 ,4)  (Cocks and Torsvik 2006, 2011; Lawver et al. 2011; Stampfli et al. 2013). As part of Laurasia, Laurussia was formed by closure of the Iapetus Ocean and Tornquist seaway, and collision of three palaeocontinents -Laurentia, Baltica and Avaloniaas well as smaller terranes, culminating in the Scandian phase of the Caledonian orogeny at 425-400 Ma  (Soper and Woodcock 1990; Pharaoh 1999; McKerrow et al. 2000; Roberts 2003; Gee et al. 2008; Leslie et al. 2008). This was preceded by phases of arc-accretion in Norwegian, British and North American Caledonides in the late Cambrian-early Ordovician, i.
The Wilson Cycle revisited The breakup of Pangaea to form the NE Atlantic was a protracted and piecemeal process with many local complexities  (Gernigon et al. this volume; Peace et al. this volume; Roberts et al. 1999; Ady and Whittaker 2018). The original Wilson cycle theory does not conclusively explain how and why the opening of the North Atlantic occurred and why its manifestation varies across the CNAR. During the past 50 years, more data have been acquired, and new theories proposed, but the mechanisms driving the Wilson Cycle are still a matter of debate. The simplest explanation for breakup along former orogens is that mountain ranges are usually the weakest zones in supercontinents and hence regions where deformation is expected to concentrate. We show that most rifts are associated with former collision zones, implying that structural inhomogeneity may be preserved long term.
Conclusions 1. The CNAR is the type example of the Wilson Cycle concept and, in general, reopened elements of the Caledonian fold belt. However, evidence from the CNAR and elsewhere clearly demonstrates that the Wilson Cycle only partially accounts for the observations. Where breakup does occur along an older orogenic belt, it does not simply re-open the older suture, and intact cratons may fragment. 2. Rift evolution and opening of the CNAR is to varying degrees linked to structural inheritance at lithospheric, continental, basin, fault and micro-scales. However, other factors were influential, such as changing stress directions imposed by plate boundary effects and supercontinent (Pangaea) breakup and magmatism. 3. Caledonian rejuvenation of anisotropies imparted at different depths (crust vs.
Acknowledgements Christian Schiffer's Carlsberg Foundation postdoctoral fellowship was held at  Durham University , where the series of North Atlantic workshops that led to this special issue were planned and held. Thomas Phillip's postdoctoral fellowship at  Durham University  is funded by the  Leverhulme Foundation. M. Stoker  gratefully acknowledges the award of Visiting Research Fellow at the  Australian School of Petroleum. The authors thank all participants of the North Atlantic workshop series. Four anonymous reviewers and the handling editor are thanked for constructive and useful comments, and  John Kipps  ( Equinor ) for help with some of the figures.
From 2013 to 2018 a team from the Association for Coroplastic Studies that has comprised Marina Albertocchi, Christine Aubry (University of Lille), Stéphanie Huysecom-Haxhi (CNRS, formerly Lille, now Paris), Arthur Muller (University of Lille/ IUF), Marion Muller-Dufeu (University of Lille), Antonella Pautasso (IBAM-CNR Catania), and Jaimee Uhlenbrock (State University of New York at New Paltz) has met twice a year, either at the University of Lille or at the University of Catania, in order to prepare two didactic projects for coroplastic research. As reported in previous issues of Les Carnets de l'ACoSt 1 the first project consists of an aid for the study of Greek figurative terracottas tentatively titled The Handbook for Coroplastic Research, and the second is a searchable database for Franz Winter's Die Typen der figürlichen  Terrakotten (1903) , referred to as "Winter On Line.
We are pleased to report that Oxford University Press has expressed a strong interest in this publication, although we currently are negotiating in which series this handbook will appear. This prospect of publication by an important academic publisher gives a new, more ambitious dimension to our project. It also will require that all contributions be translated into English. Winter On-Line 4 While the Handbook for Coroplastic Research has seen significant progress, the same cannot be said for our second project "Winter on-Line. " In 2017 a database was prepared by Christine Aubry of the University of Lille using FileMaker Pro that was based on the iconographic features of the figurines in Winter's catalogue. Over the course of 2018 a trial of this database was conducted by uploading images and matching data, with some 100 records added.
Results and Discussion The proposed experimentations were carried in the GIPSA-Lab controlled tank system. Figures  7  and 8  illustrate the transient signals obtained from the four sensors (accelerometers and ultrasound) in passive configuration, after right circular shift and common bandpass filtering. In order to build the testing database, five steel balls with different diameters have been selected for the experiments. For each ball, 25 independent impacts have been recorded using the bedload transport monitoring platform from Figure  1. The balls have been manually released form the surface of the water at approximately the same position on the steel plate. An independent buffer has been recorded for each impact with the four sensors simultaneously and coherently. After concatenating the 25 × 5 buffers, Figure  9  shows the derived signals used to test the proposed hierarchical agglomeration algorithm.
The obtained results are presented in the confusion matrix from Table  1. There are at least two facts to be noticed. First, the diagonal structure of the confusion matrix reveals a rather good classification accuracy. Second, the L-method stopped the segment merging at eight classes. This is explained by the fact that the impacts of the ball B4 have been split in two classes, while some impacts from B1 and B3 generated two additional classes. This is in agreement with the subjective visual assessment of the signals from Figure  9. For comparison purposes, the conventional K-means classifier has been applied on the same dataset with the number of classes equal to 8 (as before). The input feature vector is formed by taking the trace of the sample covariance matrix estimated using the complex spectra within each buffer.
We identify the source of the Mw = 5. 6 earthquake that hit west-central Epirus on March 21, 2020 00:49:52 UTC. We use synthetic aperture radar interferograms tied to one permanent Global Navigation Satellite System (GNSS) station (GARD). We model the source by inverting the INSAR displacement data. The inversion model suggests a shallow source on a low-angle fault (39°) dipping towards east with a centroid depth of 8. 5 km. The seismic moment deduced from our model agrees with those of the published seismic moment tensors. This geometry is compatible with the Margariti thrust fault within the collision zone between Apulia and Eurasia. We also processed new GNSS data and estimate a total convergence rate between Apulia and Eurasia of 8. 9 mm yr -1 , of which shortening of the crust between the Epirus coastal GNSS stations and station PAXO in the Ionian Sea is equivalent to ~ 50% of it or 4.
8 and Mw = 3. 9, respectively (Tab. 1). The moment tensor solutions of all four events indicate NW-SE reverse faulting in agreement with the regional, compressional tectonics (Tab. 1). For the mainshock, two moment tensor calculations are included in Tab. 1. The first one is based on the rapid manual solution (Fig. 3a ) provided by NOA a few minutes after the earthquake occurrence. The 2 nd solution of the mainshock is based on the relocated determination of its hypocentre for the needs of the present study (Fig. 3b ). The calculation of the focal mechanism solutions is based on a waveform inversion methodology employing the ISOLA point source inversion software (  [19] ; see Fig. S1  for details on the quality of waveform fit). The crustal velocity model used for the relocated focal mechanism solution calculation was published by  [20].
available on one of the two catalogues. In total, a database of 281 events was constructed for the period between 1 March and 1 May 2020 in the study area. After several tests with different velocity models (e. g. [20] ), we adopted of the 1-D P-wave velocity model of  [21]  for the region of northwest Greece (Table  2 ), which produced adequate results in terms of travel-time residuals and focal depth distribution. We determined a constant ratio of Vp/Vs=1. 74 using the  [22]  method, also considering the root mean square (RMS) deviation curve with variable Vp/Vs, which presents a wide minimum for Vp/Vs between 1. 71 and 1. 75. The mean RMS error is 0. 367 s (Fig. 2a ) while the average location errors are ERX = 0. 54 km, ERY = 0. 73 km and ERZ = 2. 7 km (Fig. 2b ). Although the azimuthal gap is relatively small for most events (mean gap = 121°; Fig.
This creates links between strongly correlated events and reduces errors due to arrival-time reading inconsistencies. We acquired waveform data from stations of the Hellenic Unified Seismological Network from the National EIDA node (http://eida. gein. noa. gr/ ), hosted at GI-NOA. The relocation procedure was performed using two sets of iterations, the first with stronger a priori weights on catalogue data and the latter with higher weights on the cross-correlation data. A total of 270 events were successfully relocated (Fig. 3 ). The relocated focal depths are mainly distributed between 3 and 11 km. The Mw=5. 6 mainshock's relocated focal depth is estimated at 6. 4 km; however, it should be noted that there are significant uncertainties in the absolute focal depths due to the unavailability of data from near-field stations that cannot be corrected by double-difference relocation.
Geodetic data inversion: Picking quarter of fringes On the two above interferograms we extracted numerically by manual picking the pixels constituting the fringe with values 32, 96, 160 and 224. On the descending interferogram (see Tab. 4) we selected 86 values among 247, and on the ascending interferogram (see Table  5 ) 86 among 289. As expected, there are less pixels for the larger displacements as this corresponds (by definition) to smaller areas. On the descending interferogram (Fig. 5 ), the zero value of the interferogram is very well constrained due to the high coherence of the interferogram. We assume that the zero value is the average zero counted in the triangle Parga -Igoumenitsa -Paramithia (see Fig. 4  for locations). This assumption is justified by the non-detectable offset at the position time-series of the GNSS station GARD (Gardiki) which is located in the SW side of the tringle (see Fig.
Tectonic strain and the determination of the deformation zone west of Kanallaki We analyzed new GNSS data of the Greek permanent stations in Epirus and north Ionian Sea (Corfu and Paxoi islands; Tab. 8). The GNSS stations belong to the NOANET geodetic network  [41, 42] , the Hexagon SmartNet and the Uranus commercial network (see Fig. 1  for locations). The processing was made with the Precise Point Positioning (PPP) strategy  [43]  by means of the GIPSY/OASIS II software (ver. 6. 4) developed by the Jet Propulsion Laboratory (JPL; http://gipsy-oasis. jpl. nasa. gov; [44] ). We used the JPL final orbits (flinnR) and clocks, absolute antenna calibrations, random walk troposphere estimation, and the FES2004 ocean loading model. The tectonic velocities and uncertainties retrieved from the analysis of the time series are in Tab.
Acknowledgments: We thank  Efthimios Lekkas ,  Efthimios Sokos ,  Hélène Lyon-Caen ,  Nicolas Chamot-Rooke ,  Ioannis Kassaras ,  Ioannis Karamitros  and  Christos Papaioannou  for discussions. We thank  ESA ,  Geohazards Lab and Terradue  for providing access to  Geohazards Exploitation Platform (GEP)  for InSAR cloud processing. GNSS data were provided by  NOANET, Hexagon SmartNET and Uranus (Tree) networks of Greece. Seismic Waveform data were sourced from the corresponding ORFEUS EIDA node operated by the  National Observatory of Athens  (eida. gein. noa. gr). We thank the  NOA  analysis team for their phase data. We used data from the  HL (Institute of Geodynamics, National Observatory of Athens , doi:  10. 7914/SN/HL ),  HP (University of Patras , doi:  10. 7914/SN/HP ), which is cooperating certain stations jointly with the  Charles University in Prague, HT (Aristotle University of Thessaloniki , doi:  10.
Giuliani et al. [72]  and Uher et al. [79]  proposed a new chemical classification diagram for gem corundum based on the different types of primary corundum deposits worldwide (see  [40, 80] ). It used a database of 2000 EMPA analyses of ruby and sapphire that were obtained under the same analytical conditions. The FeO + TiO2 + Ga2O3 versus FeO-Cr2O3-MgO-V2O3 diagram in Figure  17  uses: (1) the FeO content to discriminate between iron-poor rubies in marbles and iron-rich rubies in M-UMR and (2) the second discriminator between ruby and sapphire is the addition to (Y-axis parameter) or subtraction from (X-axis parameter) FeO of trace elements associated preferentially with sapphire (TiO2 and Ga2O3) or ruby (Cr2O3, V2O3, and MgO). The fields of the different gem corundum deposits are: for rubies, (R1) marble; (R2) John Saul mine-type; (R3) M-UMR; (R4) metasomatites; for sapphires, (S1) syenitic rocks; (S2) metasomatites; and (S3) alkali-basalt and lamprophyre.
Finally, the chemical diagram permits a clear separation with limited overlap of the main types of deposit found worldwide. Giuliani et al. [72]  and Uher et al. [79]  proposed a new chemical classification diagram for gem corundum based on the different types of primary corundum deposits worldwide (see  [40, 80] ). It used a database of 2000 EMPA analyses of ruby and sapphire that were obtained under the same analytical conditions. The FeO + TiO  The chemical diagram provides sufficient discrimination to distinguish between the different types of corundum deposits for the following reasons: (1) the database contains more than 2000 EMPA analysis representative of all of the types of primary deposits and (2) the magmatic sapphire domain (S1) is defined by the geology and chemistry of corundum.
0584802 × (TiO2 -0. 0274651)/0. 0539087 + -0. 439517 × (V2O3 -0. 0102233)/0. 0111099 The discriminating factors F1 and F2 calculated for the different types of sapphire deposits (known classes) with their respective centroid for each class are as follows: The chemical diagram provides sufficient discrimination to distinguish between the different types of corundum deposits for the following reasons: (1) the database contains more than 2000 EMPA analysis representative of all of the types of primary deposits and (2) the magmatic sapphire domain (S1) is defined by the geology and chemistry of corundum. The sapphires are hosted in syenitic rocks or occur as megacrysts in syenitic xenoliths carried by alkali basalts. Most of the sapphires in placers linked to the erosion of alkali basalts (domain S2) overlap the domain S1.
The difference in composition between the standards and the analyzed corundum has led to some uncertainties in the data generated by the different laboratories. The Gemmological Institute of America laboratory developed matrix-matched corundum standards of ruby and sapphire and the standard deviation of the analyzed ruby became negligible and therefore can be compared with a database of stones with known provenance  [92]. The application of this analytical protocol to ruby made it possible to confirm the geological classification of gem corundum (ruby and pink corundum) for (1) Fe-poor ruby hosted in marble and (2) Fe-rich ruby in M-UMR (Figure  20 ). The geographic determination is not based on the Cr content of ruby because it appears by experience that it is not useful for origin certification  [11].
The Gemmological Institute of America laboratory developed matrix-matched corundum standards of ruby and sapphire and the standard deviation of the analyzed ruby became negligible and therefore can be compared with a database of stones with known provenance  [92]. The application of this analytical protocol to ruby made it possible to confirm the geological classification of gem corundum (ruby and pink corundum) for (1) Fe-poor ruby hosted in marble and (2) Fe-rich ruby in M-UMR (Figure  20 ). The geographic determination is not based on the Cr content of ruby because it appears by experience that it is not useful for origin certification  [11]. The discrimination for Fe-rich rubies in M-UMR is based on the contents of V-Mg-Fe as shown in Figure  20  for deposits in Mozambique, Madagascar, and Thailand/Cambodia.
Acknowledgments: The authors want to thank the Editor of Minerals and  Guest Editors ,  Frederick Lin Sutherland  and  Khin Zaw , for invitation to contribute in a special issue on " Mineralogy and Geochemistry of Ruby ", and for their valuable suggestions. We are also thankful to four anonymous reviewers for improving the text by pertinent and constructive comments on the article. The authors want also to thank  D. Schwarz ,  E. Le Goff ,  C. Simonet  for their discussion and collaborations on the scientific topic. G. G. wants to thank the  Institut de Recherche pour le Développement (IRD, France)  and the  French CNRS  and the  Unversities of Lorraine and Paul Sabatier (CRPG/CNRS-Université de Lorraine  and  GET/IRD-Université Paul Sabatier)  for academic and financial support for research on the geology of gems over the past 30 years.
Sampling Specimens were collected during 16 international campaigns at sea from 1998 to 2017 (ACE, ANDEEP-3, ANDEEP-SYSTCO, ARGOS, CEAMARC 2007-2008, JR144, JR179, JR262, JR275, JR15005, MD208, MUSORSTOM 10, Poker 2, PS77, PS81 and PS96). The available specimens cover a wide distribution within the Southern Ocean (Fig. 1 ), including the Patagonian shelf, the South Sandwich Islands, South Georgia, South Orkney, the Shag Rocks, Kerguelen, Crozet and the Antarctic continental shelf (Adélie Land, Amundsen Sea, Antarctic Peninsula and Weddell Sea). A total of 171 specimens from these locations were included in the analysis. In order to increase the taxonomic and geographical scope, in addition to the phylogenetic resolution, 20 additional genetic sequences (see Genetic Data below) from specimens outside the Southern Ocean were added to the dataset (i.
morphological identification A total of 124 Southern Ocean individuals (preserved in ethanol or frozen) were identified morphologically by the authors using original descriptions (e. g. Sladen, 1882; Koehler, 1908) , identification books  (Clark, 1962; Clark & Downey, 1992; McKnight, 2006)  and contemporary scientific literature  (Villier et al. , 2004; Gale, 2018). Subsequent to genetic analyses (see Genetic Data below), an a posteriori morphological investigation was carried out to look for new characters to differentiate species when new species delineations and synonymies were suggested by genetic data. Finally, the taxonomy of the family was synthesized and made available online, by building an interactive identification key through the Xper 3 portal (Fig. 2 ). Xper 3 is a Web portal with an easy-to-use interface that allows multiple access points (the key can be started using any character;  Vignes-Lebbe et al.
genetic data A fragment of the mitochondrial gene COI was sequenced (601 bp) for the 191 individuals. These genetic sequences were obtained through laboratory work in our institutes (80 individuals; see protocol below), through our private Barcode of Life Data System project (BOLD; 94 individuals) or mined from public BOLD projects (17 individuals). DNA extractions were performed on one tube foot (podium) per sample and were based on the salting-out protocol of  Sunnucks & Hales (1996). The amplification step was performed using the forward primers 'F-COI-PTE-28' (5′-GCTGGAATGATTGGAACTGC-3′) or 'LCOech1aF1' (5′-TTTTTTCTACTAAACACAAG GATATTGG-3′) and the reverse universal primer 'R-HCO2198' (5′-TAAACTTCAGGGTGACCAAAAAA TCA-3′;  Folmer et al. , 1994). Each polymerase chain reaction (PCR) mix (25 μL) included 12.
5 μL of a VWR Mastermix (2. 5 units of VWR Taq polymerase, 0. 4 mM of each dNTP and 1. 5 mM of MgCl 2 ), 10. 5 μL of molecular water, 0. 5 μL each primer (10 μM) and 1 μL of the DNA extract. The PCR conditions consisted of 35 cycles for each of the three temperature steps [30 s at 95 °C (denaturation), 30 s at 48 °C (annealing) and 30 s at 72 °C (elongation)]. These cycles were preceded by 2 min at 95 °C and followed by 10 min at 72 °C. EXOSAP purification (incubation at 37 °C for 15 min followed by another at 80 °C for 15 min) was done before sending the PCR products to the MACROGEN sequencing service. Sequence editing and alignment were done using the software geneiouS  (Kearse et al. , 2012). The absence of a stop codon in the sequence was checked in the same software in order to exclude the presence of nuclear pseudo-genes.
partitionfinder 2 (Bayesian information criterion;  Lanfear et al. , 2016)  was used within the CIPRES portal  (Miller et al. , 2010)  to select the most suitable substitution models (i. e. TRNEF+I+G for codon position 1, HKY+I+X for codon position 2 and TRN+I+G+X for codon position 3). A Bayesian phylogeny was subsequently produced using  BEAST v. 1. 8. 4 (Drummond & Rambaut, 2007)  within the CIPRES portal. Based on a previous phylogeny using multiple genes, Remaster gourdoni  Koehler, 1912  was used as the outgroup  (Linchangco et al. , 2017). Parameters of the analysis were as follows: partitioned dataset, Yule process tree prior, Markov chain Monte Carlo of 100 × 10 6 generations sampled every 10 000 trees. tracer v. 1. 6 was used to ensure an appropriate effective sampling size (ESS all > 200).
treeannotator v. 1. 8. 4 was used to find the most likely tree, which was visualized in figtree v. 1. 4. 3 (tree. bio. ed. ac. uk/software/ figtree). Node support was assessed through posterior probability (PP), with values < 0. 75 not being retained and collapsed into polytomies  (Huelsenbeck & Rannala, 2004). Moreover, the software denSitree v. 2. 2 was used to verify the potentiality of competing topologies among the set of trees  (Bouckaert, 2010). Three different methods of species delimitation were used to propose primary species hypotheses: one distance based [automatic barcode gap discovery (ABGD);  Puillandre et al. , 2012]  and two tree based [Bayesian Poisson tree process (bPTP;  Zhang et al. , 2013)  and generalized mixed Yule coalescent (GMYC;  Fujisawa & Barraclough, 2013) ].