dataesr/scientific-paragraphs-categorization huggingface dataset:
Second, one could use a compiled programming language and rely on already available efficient implementations of likelihood computation for models of molecular evolution (in popular softwares such as BEAST or RevBayes). Third, a genome-wide analysis can be done in two steps. A first step would consist in rapidly locating spikes affecting multiple loci thanks to a distance-based method, similarly as done by  Tamura et al. (2012). The second step would be locus-specific and use an improved version of the MCMC presented here.
Inference on simulated data We performed tests of the inference method on simulated datasets under known parameter values, and assessed our ability to retrieve those parameters using our inference protocol. Because the pa-21 rameter space is huge and each run of the MCMC takes time, we restricted ourselves to manually chosen parameter values, and varied one parameter at a time (Table  1 ). For each parameter combination, (λ, d, ν, α, β, κ), we used our code to simulate one dataset (a reconstructed spiked tree, and an alignment evolving on it), and estimated the marginal posterior distribution of the parameter under scrutiny. We fixed f = 1 in all these analyses. We fixed the time of origin 10 units of time in the past, and simulated sequences of length 2 kb. On each dataset, the MCMC is run for 10 6 generations, and a burn-in of 3 10 5 generations is discarded to estimate the posterior probability.
Gaps and codons containing undefined bases were removed from the alignments. After correcting for synonyms (supplementary table  S1 ), calibrated trees were downloaded from the timetree database (http://www. timetree. org/) (Kumar et al. , 2017). We assessed the sampling fraction of each family, using taxonomic information from the Reptile Database  (Uetz et al. , 2019) , from which we deduced the global sampling fraction used in our analyses (parameter f ). The final data set (alignments and corresponding timetrees) comprised 46 sequences of 348 bp (of which 286 sites were variable) for SVSP and 53 sequences of 477 bp (of which 347 sites were variable) for CRISP. Additionally, we downloaded 37 R35 (Orphan G protein-coupled receptor R35) sequences of 519 bp (of which 281 sites were variable) from GenBank (supplementary table  S3 ).
The R35 sequence alignment was performed with ClustalW2  (Larkin et al. , 2007)  implemented in BioEdit  (Hall et al. , 2011)  and then manually refined. We used our model of molecular evolution with spikes to infer the spiking pattern of each gene (CRISP, SVSP and R35). Because we studied coding sequences, we added the possibility to infer the molecular evolution parameters (α, β and κ) independently at each codon position in our code (Supplementary material). To reach convergence we performed and combined 4 runs of 10,000,000 23   The red dot is the median of the posterior, and the black line represents the 95% envelope of the posterior. Simulated trees in these datasets displayed between 12 and 66 tips and the alignments were 2 kb long. Figure  4 : Spike detection accuracy. For a simulated tree with 32 tips and 4 spikes we report (a) the number of these spikes that are detected by the method (true positives) and (b) the number of spikes that are inferred although they did not occur in the simulation (false positives).
A. 3 Structure of the code The code used in this study is freely available in the GitLab repository https://gitlab. com/MMarc/spikebased-clock/. It is written in Python and organized in the following core / accessory / test files. Core files are: nt. py contains all functions handling nucleotides, sequences, and alignments. evolmol. py contains the description of the model of molecular evolution used here, namely, K80. evoltree. py contains all necessary functions to simulate molecular evolution along a tree, or compute the probability density of an alignment having evolved along a tree. tree. py contains functions simulating birth-death trees and computing the probability density of birthdeath trees. spike. py contains functions for simulating spikes along a tree, as well as moving spikes according to different schemes during the MCMC implementation.
43 mcmc. py is probably the most important file, or at least the one that people might be the most interested in modifying. It contains two MCMC implementations: the first one considering that all nucleotides along the sequence evolve identically, and the second one considering that the first, second and third position of a codon evolve with different parameters. The initialization, moves, and priors could be changed according to the problem under study. Accessory files are: graphics. py contains a few graphic functions to display spikes along trees, and to graphically analyze the MCMC outputs. export. py which allows one to average spikes at each node, over the posterior. Test files are: try_inferencesOnSimulations. py to run a MCMC on a simulated dataset. CRISP_ordered. fasta the alignment of CRISP sequences.
) and(3). Using the parameter values used for the simulations N = 2, 000 bp, µ = 0. 08 per bp per My and L = 3 My (average depth of spikes in the simulations) predicts the following threshold values (taking κ = 0. 04 in the computation of 0 ) κ 0 = 0. 02 and 0 = 0. 15, which have the same order of magnitude as the empirical values κ0 = 0. 05 (actual inference is a little worse than predicted) and ˆ 0 = 0. 25 (actual inference is a little better than predicted). In the snake dataset studied, the sequence length and the substitution rate estimated are equal to N = 477 and µ = 2. 73 10 -3 per My for CRISP and N = 348 and µ = 2. 04 10 -3 per My for SVSP. For a typical branch length of this phylogeny, say L = 10 My, these values correspond to the same detection threshold of spike amplitudes for the two loci equal to κ 0 = 7.
try_CRISP_3pos. py to run a MCMC on the CRISP dataset. 44 B QUANTIFYING THE ABILITY TO DETECT SPIKES In this section we aim to give a rule of thumb on the model parameters to indicate when the effect of spikes can be distinguished from the stochasticity of clock-like substitutions and from temporal variations of the molecular clock. Let us focus on a single branch of length L and assume as in the main text that the molecular clock M on this branch is equal to µ = α + 2β plus some random variation eµ, where e is uniformly distributed in [-, + ] (which is equivalent to assuming uncertainty on branch length, as done in Material & Methods). If we assume the presence of one single spike on this branch (either at the mother node or inside the branch), then the number of mutations accumulated on the branch is the sum of S and C, where S is the number of mutations due to the spike and C the number of mutations due to the clock.
ACKNOWLEDGMENTS The authors are grateful to  Todd A. Castoe  for providing them with the venom gene alignments. They thank  Nicolas Lartillot ,  Tanja Stadler ,  Guillaume Achaz ,  Marie Manceau ,  Grégory Nuel ,  Ana C. Afonso Silva ,  Leandro Aristide ,  Laure Ségurel ,  Richard Durbin  and  Nicolas Vidal  for fruitful discussions on the topic of the paper. AL, MM and JM thank the  Center for Interdisciplinary Research in Biology (CIRB, Collège de France ) for funding. AL, HM and  JM thank the LabEx MemoLife for funding  (project " Genomics of species diversification ").
The resulting signal-to-noise ratio S/N varied between 110-170, with the exception of the fourth spectrum (S/N 25). We aimed for the S/N higher than in previous PUCHEROS and CORALIE observations in order to search for signatures of the third body, but we have found nothing conclusive (see Section 3. 4). Data reduction and spectra extraction were performed on-site with the dedicated pipeline  (Tokovinin et al. 2013) , and barycentric corrections to time and velocity were calculated with the bcvcor task of the rvsao package under IRAF. The RVs were calculated with our own implementation of the TODCOR method  (Mazeh & Zucker 1994) , for which we used two synthetic ATLAS9 template spectra: T eff = 6300 K, v rot = 25 km s -1 for the primary, and T eff = 4700 K, v rot = 20 km s -1 for the secondary.
3. Using the values of M Aa and M Ab , associated with the 12 https://github. com/casaluca/bolometric-corrections quantity f (M B ) in Table  2 , we also determined the mass of the third body. We found that M B = 0. 871±0. 020 M , which corresponds to a minimum value obtained by considering i AB = 90 •. As explained in Section 3. 4, we then attempted to search for signatures of the third body in CHIRON spectra with no success. A possible consequence is that the third body is itself a binary system with two low-mass stars of, for example, 0. 45 M each. From our analysis, we argue that V1200 Cen is actually a quadruple star system with an outer period of 180. 4 days instead of 351. 5 days. Understanding the formation of close binaries in quadruple star systems represents a major issue in stellar astrophysics (see Hamers 2019, and references therein), which is beyond the scope of this paper.
CESTAM stellar models We have also fitted the two stars using the CESTAM stellar evolution code  (Marques et al. 2013; Morel & Lebreton 2008; Morel 1997). Models were computed using the OPAL2005 equation of state  (Rogers & Nayfonov 2002)  and the NACRE nuclear reaction rates  (Angulo et al. 1999). We have used the LUNA collaboration reaction rates for 14 N-burning  (Imbriani et al. 2005). Convection is treated using the mixinglength theory (Böhm-Vitense 1958) with a mixing length given by αH P. The value of α that calibrates a solar model computed without diffusion is α = 1. 64. We have used the solar mixture of  Asplund et al. (2009)  in this work. We adopted the OPAL opacity tables  (Iglesias & Rogers 1996)  calculated with this solar mixture, complemented, at T < 10 4 K, by the Wichita opacity data  (Ferguson et al.
ACKNOWLEDGEMENTS Based on data collected with Solaris network of telescopes of the  Nicolaus Copernicus Astronomical Center of the Polish Academy of Sciences. This paper includes data collected by the TESS mission, which are publicly available from the  Mikulski Archive for Space Telescopes (MAST). Funding for the TESS mission is provided by  NASA's Science Mission directorate. This research made use of Photutils, an Astropy package for detection and photometry of astronomical sources (Bradley et al. 2019). This work has made use of data from the  European Space Agency (ESA) mission Gaia  (https://www. cosmos. esa. int/gaia),processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www. cosmos. esa. int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the  Gaia Multilateral Agreement.
This research has made use of  NASA's Astrophysics Data System Bibliographic Services , the SIMBAD database, operated at  CDS, Strasbourg, France  and the VizieR catalogue access tool,  CDS, Strasbourg, France. The original description of the VizieR service was published in Ochsenbein et al. (2000). We acknowledge support provided by the  Polish National Science Center (NCN)  through grants.
When considering the combination of other phenomena, such as earthquakes, landslides or inundations, the SYNER-G (Systemic Seismic Vulnerability and Risk Analysis for Buildings, Lifeline Networks and Infrastructures Safety Gain, www. vce. at/SYNER -G) Project, funded by European Union's Seventh Framework Programme (EU FP7), is a forerunner in the treatment of the combined events  (Pitilakis et al. 2014). Of course, this topic of the damages due to the combined events has already been studied in the literature; however, the approaches used are more theoretical or propose a framework for how to consider the cascade or domino effects, and are rarely implemented in a software package or applied to a real case study, as is proposed in this paper. The Bayesian treatment of the cascading effects is modish and the advances proposed by this approach are valuable; however, most often they remain theoretical or applied only to network infrastructures.
To overcome this debate, we chose to use the HAZUS guidance throughout this paper for characterizing the intensity measure, the building typologies and the damage scale, even if the software is conceived as such that, without any additional development, other terminologies can be applied in our research. The HAZUS (2017) choice is explained by the fact that earthquake and tsunami terminologies are self-consistent and by the fact that this document is the most recent one (November 2017), and can be considered as the most up-to-date development (Fig. 1 , left). Kircher and Bouabid (2014)  describe new functions for determining the probability of damage to buildings and essential facilities due to tsunami inundation (flood) and tsunami lateral force (flow) hazards, and for combining the damages due to these hazards with that due to earthquake shaking (i.
e. for evaluation of damage and loss due to a local tsunami). The new building damage and loss functions were developed as part of a FEMA-funded project to develop a Tsunami Model for incorporation into the HAZUS Loss Estimation Technology. The Tsunami Model uses the same model building types, occupancy classes and building damage states as those of the Earthquake Model, descriptions of which may be found in the HAZUS technical manuals for earthquakes  (FEMA-HAZUS 1999)  and the Advanced Engineering Building Module  (FEMA-HAZUS 2004). This version of HAZUS (HAZUS 2017) is able to run two types of damage analysis: both near-source (earthquake + tsunami) and distant-source (tsunami only). In this paper, we are interested in the combination of the earthquake and tsunami effects, called "near-source" analysis by HAZUS.
Damaging historical events have been reported (e. g. SISFRANCE, BRGM 2018; SISFRANCE is the database of historical earthquakes felt in French territories). Moreover, the tsunamis of the French West Indies are mainly associated with regional earthquakes (e. g. Lambert and Terrier 2011), even if some teletsunamis (also called a transoceanic tsunami) were reported (e. g. Zahibo and Pelinovsky 2001; Lambert and Terrier 2011) , in particular the tsunami induced by the great 1755 Lisbon earthquake. A teletsunami is a tsunami that originates from a faraway source, which is generally thousands of kilometres from the area of interest  (Yu et al. 2011). In this study, we are paying attention to tsunamis induced by regional significant earthquakes. Two large destructive thrust interplate earthquakes occurred in the area: the 11 January 1839, east of Martinique Island, and the 8 February 1843, east of Guadeloupe Island (e.
Seismic hazard: source characteristics and intensity measures Two earthquakes are considered: interplate earthquakes offshore Martinique and Guadeloupe (Fig. 2 ). Large historical events were reported in 1839 and 1843 offshore Martinique and Guadeloupe, respectively. Though they are generally associated with megathrust ruptures, no large tsunami were reported (e. g. Bernard and Lambert 1988 or Hough 2013). Nevertheless, source hypothesis from  Feuillet et al. (2011)  for these events are inspired from macroseismic data and active faults analysis. Both earthquakes are localized offshore, in the Atlantic Ocean, to the East of Martinique and Guadeloupe Islands. The epicentre of the 1843 earthquake is located to the west of Guadeloupe and the 1839 earthquake is located to the west of Martinique (Fig.
The site effects have been established during French Government projects that funded several years of H/V measurements and soil investigations first, for some communes  (Bertil et al. 2009a; Roulle et al. 2010)  and subsequently, for the entire territory  (Sedan et al. 2008  for the methodology,  Bertil et al. 2009b  for Guadeloupe and  Belvaux et al. 2013  for Martinique). Depending on the hazard intensity measure (IM) parameter used for the damage calculation (e. g. acceleration for HAZUS or EMS98 intensity for RISK-UE level 1 2001  -Milutinovic and Trendafiloski 2003) , the acceleration can be converted to intensities. The calculation of the intensities for our simulations also provides the ability to check them with the historical information. Figure  3  compares the Armagedom simulation results in terms of intensities with that described by the SISFRANCE historical events database, which is an abundant and reliable database, and is the reference historical database in France (SISFRANCE, BRGM).
Tsunami hazard: propagation and submersion To calculate the tsunami hazard parameter, which is the maximum moment flux, HAZUS uses the median value of the maximum inundation height, H (also called the water depth or flood depth, that is, the sea surface elevation minus the topography), and the median value of the maximum velocity of the water, v. We use the inundation height grids and flow velocities grids calculated based on numerical simulations involving modelling the tsunami source, propagation and inundation. The tsunami hazard data include inundation grids provided from an external numerical tsunami hazard model (Le  Roy et al. 2017; Poisson et al. 2009 ) that corresponds to a Level of Analysis 3 according to the HAZUS description. Tsunami generation is classically modelled with  (Okada 1985)  formulation.
For some areas, extensive field inventories were performed; for others, extrapolations of the obtained data to the other communes were performed. The typologies were classified considering the local construction mode and local vulnerability aspects. Hence, the assessment of the vulnerability is based on local field inventories that took weeks to months to be performed, which corresponded to Level 2 of the HAZUS methodology. The total number of census blocks is 2950 for Martinique and 2054 for Guadeloupe. The spatial repartition of these census blocks is presented in Fig. 5. For each census block, the following information is provided: typologies, range of construction years, number of houses, number of dwellings, surface, density and type of occupation. In Fig. 5 , we represented the density of each area classified as a function of the number of houses per hectare.
The earthquake vulnerability is governed first by the earthquake-resistant design for both European and American approaches, and second by the construction material (wood, RC, masonry). In addition to the construction material, the assessment of the construction mode (e. g. cast-in-place, prefabricated) is also important. Finally, thanks to these data acquired during the French programmes, the buildings are classified in the 36 model building types of the HAZUS Tsunami Model, which are the same as those of the HAZUS Earthquake Model  (FEMA 2011). For a coherence between the studies, we kept the "local name typologies" as a first column of Table  2  (named "Type CDRS") and we observed the corresponding HAZUS Typologies and RISK-UE typologies. The double assessment of the vulnerability allows us to use, for the calculation of the buildings damages, either the RISK-UE or the HAZUS methodologies, or to use one.
Earthquake and tsunami damage calculation For the earthquake damage calculation, we can apply either the RISK-UE methodology, LM1 (empirical method) and LM2 (mechanical method)  (Milutinovic and Trendafiloski 2003; Giovinazzi and Lagomarsino 2004) , or the HAZUS methodology  (FEMA 1999). Both of them are well known and are not detailed in this paper. Considering the historical database of intensities (SISFRANCE, BRGM), the field inventory data that we have and the experience acquired on the validation of the simulated damages with observed damages  (Douglas et al. 2015; Boutaraa et al. 2018) , we decided to apply RISK-UE methodology LM1 (the one based on relation between the intensity, the vulnerability index and beta damage distribution) for earthquake damage calculation. The decision to use RISK-UE methodology LM1 is also supported by studies made by others teams, for example  Lestuzzi et al.
For tsunamis, the building damage states are defined differently from one study to another and from one region to another. Among all the studies, three damage state definitions related to the tsunami as being the most adequate, the most used and therefore documented are (1) the Global Earthquake Model (GEM); (2) FEMA-HAZUS methodology; and (3) Japanese Ministry of Land Infrastructure Tourism and Transport. Eguchi et al. (2013)  in their study, "HAZUS Tsunami Benchmarking, Validation and Calibration", using the data after the 2011 Japan tsunami, mapped the damage states used in Japan into categories that are used by the HAZUS methodology (Fig. 6 ). As our area of study is the French West Indies and the building characteristics are closer to the American structures than those constructed in Japan, we use the damage state definitions given by the HAZUS methodology.
The measured frequencies follow the reduction in the rigidity of the structures due to the damages occurred; the damages are different from one structure to another. The red, orange and green colours of this table can be associated, for an exemplification aim, with the red, orange and green points of the capacity curve. In order to apply a general approach for all the structures, to compute the residual capacity of a mainshockdamaged building to withstand an aftershock (or another lateral solicitation as is the case SD is structural damage; N-SD is non-structural damage of the tsunami flow) we used the tool SPO2IDA  (Vamvatsikos and Allin Cornell 2006). SPO2IDA provides a direct connection between the static pushover (SPO) curve and the results of incremental dynamic analysis (IDA). Therefore, for the purpose of calculating the A y and A u parameters for the building that already reached a certain limit state, LS i , we use a practical tool called SPO2IDA, which is capable of converting static pushover curves into 16%, 50% and 84% IDA curves using empirical relationships from a large database of incremental dynamic analysis results.
Conclusions The relationship between the number of damaged structures and earthquakes alone and earthquake-and-tsunami cascade events was investigated in this paper from informatics, practical and realistic viewpoints. The database for buildings and soil responses are based on field investigation campaigns performed during several projects funded by the French Government. Several practical novelties are applied to the combined earthquake-tsunami damage scenario. First, the acquisition of each intensity measure for all the time of the event is primordial, since the maximum sea surface elevation and the maximum water velocity are not necessary in the same time in the same spatial cells. Hence, this information allows us to stick as close to the phenomenon as possible, instead of using median values of the intensity measure parameters.
R(τ ) = T -1 t=0 rt+1 = T -1 t=0 r(x t , u t , x t+1 ) (24) This iterative scheme can be seen as follows: τ n ∼ P (τ |θ n ) (25) D n = D n-1 ∪ {τ n , R(τ n )} (26) θ n+1 = argmax θ Ĵ(θ|D n ) ( 27 ) where θ 0 is randomly determined or initialized to some value, D 0 = ∅ and Ĵ(θ|D) means calculating Ĵ(θ) once the models f and r are learned using the dataset of trajectories and rewards D. θ n+1 = argmax θ Ĵ(θ|D n ) 10: end procedure Model-based policy search follows the generic policy search algorithm (Algo. 1) and implements COLLECTSTRATEGY, MODELSTRATEGY and UPDATESTRATEGY (Algo. 4). The main axes of variation are: (a) the way INITSTRATEGY is defined (the most usual approaches are random policy parameters or random actions), (b) the type of models used to learn f and r, (c) the optimizer used to optimize Ĵ(θ|D n ), and (d) how are the long-term predictions, given the models, performed (i.