dataesr/scientific-paragraphs-categorization huggingface dataset:
Data availability statement. Input data and scanning results are available on a Zenodo archive: https://doi. org/10. 5281/zenodo. 7966559. This includes Météo-France thermal index, ERA5 data averaged over WRAF regions, CMIP data used for the detrending, WRAF data used for the analysis, and date vs. duration matrices of estimated 1 and 0 for the three methods (calendar, annual-maxima and -minima) and all regions. R scripts for computing the scanning procedure and visualizing the results are available on GitHub: https://github. com/jlncttx/CRT23/. Figures and Tables can also be reproduced on the interactive application: https://jlncttx. shinyapps. io/CRT23app/. APPENDIX A.
Our procedure is not without limitations, particularly because applying it in such a generalized 354 and exhaustive way requires use of simple and fast methods. A first remark concerns the long-term 326 327 328 # Reg ID Region name Year Dates 1/ 1 1/ 0 1 / 0 Heatwaves 10. 6. 1. 1. 3 west DR Congo 2022 Nov 25 -Dec 24 630 [110 to Inf] 1 [1 to 1] 0. 0016 [0 to 0. 0094] DR Congo = Democratic Republic of Congo, EEA = European Economic Area, USA = United States of America. 348 procedure can provide additional method for the climate monitoring of weather events in a warming 349 world. Applied globally, it ensures extreme events are identified objectively, independently of the 350 populations concerned or the media coverage. This can help the event attribution community both 351 by providing objective lists of events to be studied in dedicated annual reports, without selection 352 bias, and by building reference databases of extreme events on which climate models and statistical attribution methods can be confronted.
Excitation force prediction Based on the open-source BEM software NEMOH  (Babarit and Delhommeau, 2015; Kurnia and Ducrozet, 2023) , the excitation forces exerted on the floating body of interest are represented. The first-order wave loads on the floating platform structure are studied based on a mesh with 1872 panels as shown in Fig. 9. The mesh was carefully chosen after a proper convergence study. Since the geometry of the structure is axisymmetric with a circular cross-section floating on the ocean surface and the wave field is confined to the propagation at limited angles with the 𝑥-axis, the motion of the body mainly occurs in the surge force 𝐹 𝑥 , the heave force 𝐹 𝑧 , and the pitch moment 𝑀 𝑦 degrees of freedom (DOFs). Fig. 10  illustrates the magnitude and phase of the complex frequency response function and corresponding impulse response function in the time domain for the three DOFs at full scale.
Even when several geophysical datasets are taken into account to infer the most probable crustal models, the uncertainty on mantle heat flow value can reach 15 to 20%  [Jaupart et al. , 2015]. In addition, when the temperature dependence of thermal properties  [Clauser and Huenges, 1995, Whittington et al. , 2009]  is not considered, the inferred crustal temperatures may be strongly underestimated  [Braun, 2009]. Apart from these uncertainties in the context of a thermally conductive regime, the occurrence of fluid flow in permeable rocks (advective or convective regimes) may strongly disturb the isotherms that would have been inferred from a purely conductive regime. For example, the uprising of crustal fluids through permeable fault zones may induce the formation of kilometer-sized positive thermal anomalies exceeding several tens of °C [e.
Numerical model The numerical model is a 2D-block consisting of two compartments of the basement with a depthdecreasing homogeneous permeability. A fault zone composed of one 10 m-thick core zone with a constant permeability K c , surrounded by two damage zones with a constant permeability K d , separates the two compartments. The choice of a constant permeability K d may be questionable since it may depend on the tectonic regime. However, based on the Scibek database [2020], we estimate an average permeability of fault zones around 10 -14 m 2 , whatever the tectonic regime. We thus fixed this value to allow fluid circulation within damage zones for all experiments. The thickness of the total fault damage zone (DZT, two half damage zones) is tested for the values DZT = 50, 300, and 1000 m.
The main geometrical parameters for faults able to host geothermal systems are: (i) a damage zone thickness ≥ 100 m, (ii) a minimum displacement of 100-150 m and (iii) a kilometric scale fault. These parameters are illustrated in Figure  12 , where a damage zone thickness of 600 m is chosen. The database of  Scibek [2020]  contains numerous information on the permeability of fault zones around the world, associated with fault zone parameters available: protolith, kinematic, length, displacement, damage zone thickness. Despite the important number of referenced sites (511 sites), it remains incomplete and spatially distributed in a heterogeneous way. We have sorted the database according to the 3 main fault geometrical criteria to select the sites that can be potential targets for geothermal exploration.
Potential geothermal systems in European fault zones At the scale of Europe, fault geometrical parameters applied to the databse of  Scibek [2020]  highlight 40 fault zones with a favorable geometry for hosting geothermal systems. We also added three crustal fault zones that have been previously mentioned in this study (i. e. , the Pontgibaud and Têt fault systems in France, and the fault zone of Larderello in Italy). Fault kinematics are represented in Figure  13a. The maps in Figure  13  show the spatial distribution of geothermal power plants and the selected fault zones with their kinematics (Figure  13a ) and with their associated permeabilities (Figure  13b ). Some countries do not contain any new data (Germany, Poland) but this is only due to the lack of geometrical data in the database for these sites.
For example, the Unterhaching fault zone [Germany, site number 101. 1 in  Scibek, 2020]   The site number comes from the database. DZ = Damage zone. "Bulk" refers to data that cannot be relocated in fault core or damaged zones. The first 7 lines correspond to geothermal systems for which power production is indicated. permeability of 10 -13 m 2 , but there is no information on the fault length, displacement or the damage zone thickness. Consequently, these maps must be considered as a first step to define new potential targets for geothermal exploration. The maps in Figure  13  highlight that only a few fault zones currently host exploited geothermal reservoirs, but some of them control the location of several power plants. This is the case for the Menderes Massif (Turkey) where at least 45 power plants are located close to the low-angle normal fault systems with a total capacity of 1450 MWe.
The identified new sites tend to show some similarities even though they are located in different tectonic contexts. Further, these maps show that all tectonic contexts may be interesting, in particular the extensional regime represented by normal faults. However, this may also be due to a bias in the incomplete database. Our selection, based on purely geometrical criteria, shows that fault permeabilities range from 10 -15 to 10 -12 m 2 , a favorable range for high-temperature geothermal systems. Based on these observations and criteria, we suggest that the geothermal potential in Europe is still underestimated.
Perspectives for geothermal exploration in fault zones Beside being heterogeneous, the  Scibek [2020]  database lacks numerous permeability data of European fault zones. Consequently, Figure  13  should not be considered as a predictivity map since several additional features must be taken into account before being usable to predict the presence of an exploitable geothermal system. Indeed, information on fault zone geometry and permeability data should be combined with the regional tectonic regime, the local stress field and the surrounding topography. In addition, it is important to recall that the permeability database of fault zones in Europe is not exhaustive, (since in constant evolution). We however believe that our study can help geothermal exploration towards a more efficient targeting, where permeability enhancement techniques would not be necessary.
We focused our study on thermal anomalies greater than 150 °C at a depth lower than 4 km. It must be noted that the recent study by  Lund et al. [2022]  indicates that "electric power from geothermal energy is now being produced from resources showing the main faults permeabilities from the database of  Scibek [2020]  and geothermal systems. Permeabilities for the Larderello geothermal system and Pontgibaud system are from  Bertani and Cappetti [1995]  and  Duwiquet et al. [2021]  respectively. with temperatures as low as 90 °C, using the organic Rankine cycle process in binary power units". Consequently, our selection must be considered as a lower limit since temperatures around 100 °C at a depth of 1-2 km should be easily found in wide fault zones (Figure  8b ), thus increasing the number of fault zones that could be considered as promising targets for geothermal exploration.
Acknowledgements This research has been supported by the  GERES-FAULT  project (grant no. ANR-19-CE05-0043-01 ), GM acknowledges funding from the program TelluS of the  Institut National des Sciences de l'Univers, CNRS. Discussions with  Patrick Ledru  and  Vincent Bouchot  helped to improve the ideas developed in this study. We thank reviewers  Domenico Montanari  and  Christoph Wanner  for their positive and constructive reviews. We also thank  Olivier Fabbri  for additional suggestions that help to improve the final version of the manuscript.
Independent datasets from a variety of in-situ and remote-sensing instruments, such as ISMAR, are utilised. The overall goal is to determine whether we can combine the in-situ measurements to construct an atmospheric model that can succesfully replicate the large brightness temperature depressions and V-H differences measured from ISMAR. Thus, we perform polarised radiative transfer simulations using ARTS. The differences in brightness temperatures between those simulated using ARTS, and those measured by the airborne radiometer, ISMAR are analysed. To quantify the importance of utilising polarisation observations at microwave and submillimetre frequencies, we focus mainly on ISMAR polarisation measurements at 243 GHz, along with comparing a number of simulations and measurements at 664 GHz.
2a , and rain below it. As mentioned, we do not represent melting particles here, and assume a Marshall-Palmer distribution of rain beneath the ice cloud base. The distribution used here corresponds to a rain rate of 1 -2 mm/hr, estimated from the radar data shown in Fig. 1. As well as including a database of scattering calculations for realistic particle habits performed using the Discrete Dipole Approximation (DDA;  Eriksson et al. (2018) ), ARTS also accepts externally generated scattering calculations. This gives us the opportunity to generate particles specifically for this study, along with providing the flexibility to use an alternative scattering method for the calculations. These points are described in more detail in the following subsections. and 6 km, and dendritic aggregates lower in the cloud between 6 km and 2 km (i.
Acknowledgements. This work was supported financially by a studentship from the  Engineering and Physical Sciences Research Council (EPSRC)  and the  Met Office , along with support from  NERC  grant  NE/P012426/1. The authors would like to thank the research computing staff at the  University of Reading  and the ARTS radiative transfer community for their help with installing and using ARTS. We also thank those who contributed to the data collection. The BAe-146 research aircraft is operated by  Airtask  and  Avalon  and managed by the  Facility for Airborne Atmospheric Measurements (FAAM) , which is jointly funded by the  Met Office and NERC. The flight was funded by the  European Space Agency. We thank  Silke Groß  who also contributed to processing the 35 GHz radar data.
Acknowledgements The  Kilian Group  is grateful to the valuable comments, discussions and corrections provided by  Didier Bert  and two other, anonymous reviewers. We appreciate and deeply thank the editorial work of  E. Koutsoukos. The KG also thanks  V. Idakieva  for providing her stratigraphical data on Bulgarian sections. We are also appreciating the help of  E. Baraboshkin ,  J. Charollais ,  G. Delanoy ,  R. Enay ,  R. W. Gallois ,  B. Granier ,  V. Idakieva ,  L. Leroy ,  F. Owen ,  P. Rawson ,  M. Rogov  and  E. Schnebelen-Bulot  in the preparation of the memoires. OSZ was supported by  OTKA NKFIH K135309  grant, JAMB was supported by the  DGAPAeUNAM ,  PAPIIT IN108722  grant. The authors are grateful to the  Hungarian Natural History Museum  funding the Open Access possibility.
Geomorphological configurations of the coast It is necessary to identify characteristics of the coast that influence the different components of the surges. First, the analysis of storm surges computed from the national REFMAR database reveals that they are controlled not only by storm tracks but also by the width of the continental shelf and the presence of shallow waters. For example, during the 20year study period , storm surges hardly reached 1. 0 m along the coastlines of the southern Bay of Biscay and the eastern Mediterranean Sea, but exceeded 2. 0 m in the English Channel  (Dodet et al. , 2019). In shallow water, the wind effects can significantly dominate the effect of the atmospheric pressure, and the surge can be strongly amplified by the bathymetry along the coast  (Bertin et al.
Code availability The Delft3D-FM code is currently being made available in http://oss. deltares. nl. The WW3 model description is available in: https://polar. ncep. noaa. gov/waves/wavewatch/. The code applied for the non-stationary extreme value statistics  (Mentaschi et al. , 2016)  is available in: https://github. com/menta78/tsEva.
Data availability The global ESL data that support the findings of this study are available in the LISCoAsT repository of the JRC data collection (http://data. jrc. ec. europa. eu/collection/LISCOAST) though this link: http://data. jrc. ec. europa. eu/dataset/jrcliscoast-10012, with the identifiers: https://doi. org/10. 2905/jrc-liscoast-10012; PID: http://data. europa. eu/89h/jrc-liscoast-.
Acknowledgments The authors would like to thank Xavier Bertin, CNRS research director at the LIttoral ENvironment et Sociétés (LIENSs) laboratory for his comments about the manuscript and for sharing of water height and wave data from the national observation services ReefTEMPS and DYNALIT. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. All authors declare that they have no conflicts of interest.
g. , cost of the electric cable  [8] ) and boundary constraints (e. g. , minimum and maximum allowable distance between devices  [9]  or predefined reciprocal structure  [10] ). Genetic algorithms are a popular choice to handle such a complex multi-variate problem, since the dimension of the state vector to be optimized is normally too large for an exhaustive search  [11, 12]. In addition to layout optimization, recently attention has been drawn also on the energy-maximization control problem  [13]  of a farm, where centralized, distributed and decentralized approaches are shown to differ significantly and impact the overall productivity of the farm. An open access dataset has also been provided, related to a wave tank experimental campaign with up to 5 WECs  [14]. Besides renewable energy production, a secondary beneficial effect of a WEC farm is to contribute to coastal protection  [15] ; indeed, coastal erosion is becoming a growing concern, partly driven by the effects of climate change  [16].
The radiated potential is further related to the body's motions -the 𝑁 𝐷𝑂𝐹 Degrees of Freedom (DoFs) -through the Response Amplitude Operator (RAO) of the 𝛿-th degree of freedom. A boundary value problem is defined, and is solved with the BEM solver Capytaine  [34] , the Python implementation of NEMOH, developed at Ecole Centrale de Nantes, France  [35]. For the analysis of the power extraction, the WEC is equipped with a PTO system, which typically exhibits complex nonlinear behavior  [36]  due to the implementation of sophisticated control strategies to maximize power output  [37]. However, for frequency domain analysis it is often acceptable to linearize the PTO  [38] , so that the superposition principle holds, allowing for simplification as a spring-damper system. The equation of motion  [39]  for the displacement 𝜁(𝜔), implementing the PTO model, is: [-𝜔 2 (M + A) + i𝜔(B + B 𝑃 𝑇 𝑂 ) + (C + C 𝑃 𝑇 𝑂 )]𝜁 = F, ( 3 ) where M is the body mass matrix, A denotes the added mass matrix, B the radiation damping matrix, C the matrix of hydrostatic and gravitational restoring coefficients, and F represents the external excitation forces, defined as the sum of diffraction and Froude-Krylov forces  [40].
Alvinellid worms are a family of endemic and closely related species from deep-sea hydrothermal vents in the Pacific and Indian Oceans. These annelid worms, sister group to the Ampharetidae, occupy a wide range of ecological niches, some of which include the most thermotolerant marine animals described to date such as the Pompeii worm Alvinella pompejana, and other species living at much lower temperatures such as Paralvinella grasslei or Paralvinella pandorae. The phylogeny of this family has not yet been studied extensively. It is, however, a complex case with conflicting molecular phylogenies, the main question being the monophyletic or polyphyletic character of the genus Paralvinella. We carried out a comprehensive study of the phylogeny of this family using the best molecular data currently available from RNAseq datasets.
91) by  Stiller et al. on the basis of several hundred orthologous genes derived from transcriptomic datasets  (Stiller et al. , 2020). However, other molecular data support the monophyly of the genus Paralvinella. Thus, the same study by Jollivet and Hourdez proposes a second phylogeny, based on a set of 278 orthologous transcripts, in which the genus Paralvinella remains monophyletic and P. p. irlandei is only basal to the other species of Paralvinella  (Jollivet and Hourdez, 2021). This last phylogenetic work was in agreement with an earlier study by  Jollivet et al. which proposed, based on enzyme isoforms similarities, that the species P. p. pandorae, P. p. irlandei and P. unidentata form a group within Paralvinella and that the genus Paralvinella is monophyletic  (Jollivet et al. , 1995).
The phylogenetic relationship between the three Nautalvinella species and the Alvinella species is therefore a key to understand the phylogeny of the Alvinellidae. Here, we propose a new molecular phylogeny of the family Alvinellidae based on orthologous genes derived from RNAseq datasets, notably improved by a new sequencing of the species P. unidentata and other species from both the western Pacific and the Indian Ocean. The phylogeny therefore includes all the described species of Alvinellidae species, with the exception of P. p. pandorae, and the rare species P. dela and P. bactericola for which no exhaustive molecular data exist to date. This phylogeny is rooted with species of the sister group Ampharetidae, as well as more distantly-related species of Terebellidae and the coastal pectinariid worm Pectinaria gouldii , in accordance with the currently accepted phylogeny of the Terebelliformia worms  (Rousset et al.
Animal Collection, Sequencing and Assembly Transcripts of A. pompejana were predicted from the genome assembled at the chromosomal level by R. Copley (NCBI accession number PRJEB46503) with the Augustus BRUN ET AL. webserver  (Hoff and Stanke, 2013). The software was first trained on cDNA sequences provided by the MPI that contained previous A. pompejana EST assemblies obtained from a Sanger sequencing (Genoscope project, see  Gagnière et al. for details (Gagnière et al. , 2010) ). The prediction was performed on scaffolds of more than 60k bases (95. 8% of the assembled genome). The resulting coding sequences were filtered with Kraken v. 2. 0. 9 and then Transdecoder v. 5. 5. 0 to ensure data homogeneity among all final transcriptomes. Transcriptome reads for the species P. gouldii, Anobothrus sp.
, Amphicteis gunneri, Amphisamytha calrdarei and Hypania invalida were downloaded from the NBCI SRA database (accession numbers SRR2057036, SRR11434464, SRR11434467, SRR11434468, SRR5590961)  (Kocot et al. , 2016; Stiller et al. , 2020). Total RNA extraction from flash-frozen tissue were performed with Trizol. Libraries of P. gouldii were sequences with Illumina HiSeq, libraries of Anobothrus sp. , A. gunneri and A. carldarei were obtained with Illumina Hiseq 4000, and Illumina Hiseq 2500 was used for H. invalida. An EST library was previously obtained for the species P. sulfincola in the framework of a Join Genome Initiative project (NCBI accession number PRJNA80027), led by P. R. Girguis and S. Hourdez  (Girguis and Lee, 2006). The animals were collected on the Juan de Fuca Ridge during the jdFR oceanographic cruise in August and September 2008, with the submersible Alvin on board of the R/V Atlantis.
Search for orthologous genes and Bioinformatic Processing Orthologous sequences were determined from the assembled transcriptomes using Orthograph v. 0. 7. 2  (Petersen et al. , 2017). Following the recommendations of Orthograph, a reference database of 1997 orthogroups (OG) was first constructed from the ODB9 database  (Zdobnov et al. , 2021). These OGs correspond to single copy genes in all lophotrochozoan species available when downloading ODB9 (Lottia gigantea, Crassostrea gigas, Biomphalaria glabrata, Capitella teleta, Helobdella robusta). Then, each Terebelliformia transcriptome was blasted against these OGs with Orthograph to identify orthologous genes. These steps attempted to identify all orthologous genes present in Terebelliformia that are expected to be single copies. The results of these ortholog identification steps are detailed in Supplementary data Table  1.
We then obtained the following datasets: 1. a set of 966 orthologous genes, in nucleotides, and present in at least 20 transcriptomes (with the constraint that P. p. irlandei must be present for each gene); 2. a set of 478 orthologous genes, derived from dataset (1) and translated in amino acids. These genes are found in at least 20 transcriptomes (with the constraint that P. p. irlandei , which had the less populated transcriptome must be present for each gene), and were filtered to reduce amino-acid composition biases between species; 3. a set of 895 orthologous genes, encoded in nucleic acids and concatenated into a supergene. This set of genes derives from the set of 966 genes (1), but with additional constraints. Sequence alignments must contain at least the same gene from 20 transcriptomes, within each alignment sequences shorter than 25% of the total length of the alignment are deleted, and aligned gene fragments of less than 100 nucleotides between two gaps are considered unreliable and deleted.
The resulting supergene contains 594,101 aligned nucleotide sites (P. p. irlandei being the least represented species with 288,184 sites). Here, we give priority to the quality of alignment and completeness of individual sites over the total number of genes; 4. a set of 385 orthologous genes, translated in amino acids and concatenated into a supergene. This set of proteins derives from the first set of 478 amino-acid sequences (2), with the same additional constraints as for dataset (3), and aligned gene fragments of less than 30 amino acids between two gaps are considered unreliable and deleted. The resulting supergene contains 96,432 aligned residues (P. gouldii being the least represented species with 45,945 sites), giving priority to the quality of alignment and completeness of individual sites over the total number of genes; 5.