dataesr/scientific-paragraphs-categorization huggingface dataset:
Best Practices for Field Measurement of CBD Are Important Future investigations of CBD should include precise topographic contexts for the boulders (via differential GPS or quantitative photogrammetry), connections to offshore bathymetric profiles, clear articulation of the available wave data and understanding of whether it represents significant wave height or individual wave heights, and geochronologic control where possible. Some studies currently incorporate some or all of these elements, but we propose that they should be standard practice for all field analysis of CBD. In addition to fully characterizing the topographic and geomorphic context of CBD, studies should aim to determine the local wave climate, in terms of decadal and centennial significant wave height, with statistical analysis of millennial recurrence intervals for maximal sea states, the likely H max on decadal, centennial, and millennial time scales, a consideration of the effects of wave period and storm surge, and an evaluation of the potential for amplification over the local bathymetric profile.
g. ,  Armaroli et al. , 2012)  and coastal vulnerability maps (e. g. ,  Kantamaneni et al. , 2019)  is becoming imperative. Understanding the extremes of storm behavior-now and in past centuries-will help us better prepare for the storms of the future, and including dynamic coastal processes in both short-and longterm hazard planning is essential  (Barnard et al. , 2019). CBD provide pinning points for the elevations and distances achieved by high-energy seawater incursions. Storm-flooding data points from CBD can go beyond the limitations of the instrumental record and should therefore be viewed as a cornerstone archive for understanding long-term coastal risk and vulnerability. A fundamental step is to decode the relationship between clast size, flow velocity, and the heights of associated waves so that we can (a) properly test whether uncategorized CBD worldwide are records of storminess rather than tsunami and (b) use CBD to help us understand the nature of storm wave activity at coasts.
It is equally important to reexamine-through a properly calibrated hydrodynamic lens-CBD that have been attributed to tsunami based on boulder size and local wave climate. The consequences of storm deposits being wrongly attributed to tsunami are substantial. First, incorrect data relating to event energy, runup distance, and timing are assimilated into tsunami hazard evaluations. Second, those same data then fail to be incorporated into storm hazard models. Building models from inappropriate datasets undermines both forward planning and, potentially, public trust in the underlying science. It is therefore of the first importance that the scientific community be aware of this problem. We must work to test existing interpretations, revising them if necessary, and apply more robust approaches moving forward.
ACKNOWLEDGMENTS This paper resulted from discussions at the XWaves 2018 conference (Les Treilles, Tourtour, France) https://lestreilles. hypotheses. org/1093. The authors gratefully acknowledge support from the Fondation des Treilles, which hosted the conference that brought together this international multi-disciplinary group of observational geoscientists and theoretical modelers. We thank Jelena Janjić for providing high-resolution versions of wave model maps from her doctoral thesis and Laura Cooke for reducing data from the Killard wave buoy.
, 2000; C. Martel pers. com. )  were used as standards. Calibration curves were determined by plotting the H 2 O content of standards against their measured 16 OH -/ 16 O -. For profiles, glasses with H 2 O contents determined from spot analyses were used as standards and calibration curves constructed as above. Both the FTIR and spot SIMS results were used to estimate H 2 O concentrations "by difference" (BD). To do so, glasses analyzed by IR and SIMS (Table  S1  and Fig. S1 ) were analyzed by electron microprobe and their analytical totals (after corrections of the alkali) plotted as a function of their glass H 2 O contents. For each microprobe session, empirical calibrations relating the summation deficiency (100 -analytical total) with the glass H 2 O content were constructed from either the IR or the SIMS H 2 O concentration data ("by difference"-IR and "by difference"-SIMS), and applied to estimate the concentration of H 2 O in experimental glasses.
32) in our dataset (charge 47-3a, Table  6 ). Concentration profiles in glass away from alkali feldspar interfaces have been also obtained for H 2 O (Fig. 10 ). H 2 O concentrations have been determined by difference ("by difference"-SIMS) for the same three crystal-bearing T = 60°C and T = 120°C charges. For the T = 120°C-td = 552h charge, results have been duplicated by SIMS. In all cases, H 2 O concentrations were found to increase near the alkali feldspar interface. In the T = 60°C charge, the interface melt H 2 O concentration is ~ 7. 6 wt%, vs. 6. 3 wt% away from alkali feldspar and 6. 5 wt% in the far-field melt. The high SiO 2 glass in the hollow alkali feldspar has a H 2 O concentration of 7. 1 wt% (Table  6 ). In the T = 120°C-td = 120h charge, the H 2 O concentration at the interface reaches 8 wt% (vs.
ACKNOWLEDGEMENTS Assistance by  O. Rouer  on the electron microprobe, by  A. Lecomte  on the scanning electron microscope (SCMEM-UMR 7359 GeoRessources,  Université de Lorraine ) and by  A. Gurenko  and  N. Bouden  on the secondary ion mass spectrometry ( CRPG-UMR 7358 ,  CNRS-INSU, Université de Lorraine ) are gratefully acknowledged. E. Le Moing  and  F. Savoie  ( ISTO-UMR 7327 ,  Université d'Orléans ) helped with the use of the cold-seal pressure vessels. Downloaded from https://academic. oup. com/petrology/advance-article-abstract/doi/10. 1093/petrology/egaa054/5837683 by  INFU BIBLIO  PLANETS user on 20 May 2020.
ACKNOWLEDGMENTS This work was supported by the  CNRS programs "Physique et Chimie du Milieu Interstellaire (PCMI) " co-funded by the  Centre National d'Etudes Spatiales (CNES)  and  "Programme National de Physique Stellaire" (PNPS). Part of the calculations were performed using HPC resources from  GENCI-[CINES/IDRIS ] (grant N o 2010040883) and work stations at the  Centre Informatique of Paris Observatory. This work was also granted access to the HPC resources of MesoPSL financed by the  Region Ile de France  and the project  Equip@Meso  (reference  ANR-10-EQPX-29-01 ) of the programme Investissements d'Avenir supervised by the  Agence Nationale pour la Recherche.
Moreover, the comparison with bulk sensitive results is a nontrivial task. In this field, resonant inelastic soft x-ray scattering (RIXS) is likely to offer an important contribution, made possible by the recent progress in instrumentation  [40]. For instance, state-ofthe-art RIXS can be performed with a combined energy resolution of ∼ 30 -40 meV at the Cu L 3 edge, which facilitates studies of high-energy phonons ( > ∼ 30 meV). For detailed investigations, a further increase of the resolution is needed, which is a realistic prospect in the next three to five years. What is needed in this context is a well defined procedure for extracting quantitative information about the EPC from the available RIXS data, preferably in a model independent way. Determining the EPC from RIXS data was first proposed by Ament et al.
A recent remarkable work has also reported the first application to nSrIrO 3 /mSrTiO 3 multilayers  [47]. For the low-Z 3d oxides, data on Ti L edge are also available  [48, 49]. From a conceptual point of view, state-of-the-art RIXS research on the EPC has proceeded along two main lines: i) the search for a simplified universal scheme allowing experimentalists to address a variety of cases without detailed calculations; ii) the development of more specific treatments that exploit numerical computation. While both approaches are useful and cross fertilize each other, in the following we focus on the first one. Specifically, we introduce innovative ways of using the theory by Ament et al. [41]  and identify some scaling laws with a wide range of application. The proposed methods are then employed on the cuprate Nd 1+x Ba 2-x Cu 3 O 7-δ (NBCO).
V. DISCUSSION Here, we focus on the experimental results for NBCO since the methods used to recover the EPC from RIXS spectra have been already discussed. Nevertheless, these two aspects are connected so that the discussion of the results on NBCO will also clarify the limits of the methods. The momentum dependence of the EPC in the parent compound, plotted in Fig. 11 , is fitted with simple trigonometric functions. The coupling to the buckling branch scales as cos(πh) (red dotted line) and the coupling to the breathing branch as sin(πh) (blue dashed line) (see Appendix A). Once again, we stress that these data may contain averages of unresolved branches. It is remarkable that such simple rules fit the data well, especially for the breathing mode whose error bars are smaller. This result is important because the simple dependence of M/Γ on the momentum is theoretically obtained from models that consider only nearest neighbor interactions.
The amplitude of the trigonometric functions has been adjusted by tuning the scaling factor so that: M Γ breath = 0. 45 sin(πh), (8) M Γ buckle = 0. 98 cos(πh). These results demonstrate that RIXS provides easy and direct access to the momentum-dependent EPC. The analysis of the RIXS data of NBCO-AF and the internal consistency of the results obtained with different methods demonstrate that our model involving the starting Hamiltonian [Eq. (1) ] and Einstein phonons is useful to study high energy phonons in undoped cuprates. It is remarkable that the intensity of the in-phase buckling branch is high and has a strong EPC; this is consistent with the large static buckling in the system, which is known to enhance the coupling to the bond-buckling phonons  [3, 75]. Until now, we have been using a strictly local perspective, where both the phonon and electron degrees of freedom are localized.
While this approach produces good agreement with experimental data, as shown in Fig. 11 , it is important to also consider what happens when itin-M/Γ erant description of the electron states is used instead. Interestingly, in the RIXS studies of EPC, the theoretical results turn out to be quite similar in the two approaches. The comparison is shown in Fig. 15 , where the experimental data are also reproduced (the calculations are presented and compared in Appendix A). At least in this case the sensitivity to the electron states description is rather modest. This observation has profound implications on our work since it legitimates the use of the same theoretical tools in treating AF compounds and doped superconducting cuprates. The limits of applicability to other systems will have to be assessed with further work, since the results depend on a delicate combination of many factors, such as electronic screening, excitonic effects and time scales.
Note that the EPC strength is proportional to the square root of the RIXS intensity. The best fits to the data obtained in the two limiting cases of local (thick lines) and itinerant (thin lines) electron models are shown for comparison. In the latter case, the band dispersion is taken from Ref. 77. The two approximations yield similar results and describe the the data fairly well, with a small advantage to the local electron picture close to the X point of the BZ. We summarize here the procedures used to recover the phonon components from the RIXS spectra. These rather technical issues are collected here to improve the flow and cohesion of the main text. Nevertheless, the content of this Appendix must be considered as an integral part of the work. We consider the benchmark RIXS spectrum shown in Fig.
ACKNOWLEDGMENTS RIXS data were collected at the beam line ID32 of the ESRF using the ERIXS spectrometer jointly designed by the  ESRF  and the  Politecnico di Milano. This work was supported by the  ERC-P- ReXS  project ( 2016-0790 ) of the  Fondazione CARIPLO  and  Regione Lombardia , in Italy. R. A. is supported by the  Swedish Research Council (VR)  under the project " Evolution of nanoscale charge order in superconducting YBCO  nanostructures". S. J. is supported by the  National Science Foundation  under Grant No. DMR-1842056. J. v. d. B. acknowledges financial support from the  DFG  through the  Würzburg-Dresden Cluster of Excellence on Complexity and Topology in Quantum Matter -ct. qmat ( EXC 2147 , project-id 39085490) and through  SFB 1143  (project-id 247310070).
, 2013 (Kalabokas et al. , , 2015;; Doche et al. , 2014). The present study focuses on the influence of tropospheric subsidence on surface ozone concentrations, especially during spring and summer months over the western Mediterranean area. In extension to previous work, it is based on the analysis of 10 years of ozone and other air pollution measurement data  (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015)  as well as measurements of natural radionuclide tracers at surface level, which can be used as tracers of transport and photochemical and removal processes. These data are collected at the JRC-Ispra site, located in the pre-alpine area in northern Italy but also located relatively close to the western Mediterranean. In addition, we used meteorological maps, back trajectories and IASI satellite ozone data for a better understanding of the relative importance of the contributions of the different sources of ozone, especially the role of the vertical transport in the troposphere.
Conclusion High boundary layer concentrations of 7 Be are used as indicator of the influence of free tropospheric air, in which 7 Be activity is high due a cosmogenic source. 210 Pb activity is an indicator of accumulation of surface emissions and their reaction products and it reaches its highest levels during periods with stagnant air conditions. Radioisotope and humidity data from the Ispra station show that local peaks in 7 Be/ 210 Pb frequently are coinciding with local minima in specific humidity, consistent with the hypothesis that these peaks are found in situations with a strong impact of tropospheric influence to the boundary layer. Comparison with ozone measurements shows that these peaks in some occasions coincide with ozone peaks but more frequently ozone peaks coincide with peaks in 7 Be activity.
Acknowledgement The authors would like to acknowledge the following people:  S. Dos Santos  and  J. -P. Putaud  for meteorological data and aerosol physics data. G. Manca for 222 Rn data. F. Lagler  and  J. -P. Putaud  for the help with the ozone and NOx data. The authors also acknowledge that a small part of the material in the present paper has been used in ref. Jensen et al. , 2017 (Figure 1). Acknowledgement is also made for the composite weather maps, which were provided by the  NOAA/ESRL Physical Sciences Division, Boulder, Colorado , from their website at http://www. cdc. noaa. gov/. The authors also acknowledge the  NOAA Air Resources Laboratory (ARL)  for the provision of the HYSPLIT transport and dispersion model and/or READY website (http://www. ready. noaa. gov)used in this publication.
geo. uzh. ch/en/units/h2k/Services/HBV-Model. html) as described in refs  [50] [51] [52]. For the gauged rivers, we modelled daily runoff based using mean water temperature and precipitation from adjacent meteostations. The data for reproducing the water discharge at key sites were taken from hydrological yearbooks and automatic information system of State monitoring of water bodies  [53]. The daily air temperature and precipitation were taken from Russian Hydrometeocenter (URL: http://aisori. meteo. ru/ClimateR; [44] ). The calibration of model parameters demonstrated that the HBV model adequately reproduces the seasonal dynamics of runoff (quality criteria of 0. 75 to 0. 90). The uncertainties of modelled discharge at ungauged rivers stem from several factors. First, there is uncertainties in characterizing watershed boundaries for the very flat, but poorly resolved, WSL territory.
Sequence Analyses and Phylogenetic Reconstructions The sequences were edited in Geneious 8. 1. 8 (Kearse et al. , 2012)  and overlapping fragments merged into consensus sequences. We compared our sequences with the NCBI databases using BLAST  (Altschul et al. , 1997)  to check for sequence contaminations  (Vrijenhoek et al. , 2009). The NCBI database did not contain COI sequences from Xylophagaidae and the similarity hits targeted COI sequences of unrelated bivalve and gastropod molluscs (max. 70% sequence similarity). COI sequences were translated into amino acid alignment with code 5 for invertebrate mitochondrial genes and checked for stop codons in order to avoid pseudogenes. NCBI comparisons of large and small rRNA subunit sequences revealed highest similarities with species of Xylophagaidae and Teredinidae (max.
98% for 18S rRNA, 84% for 28S rRNA). We imported our sequences in Mesquite 3. 2  (Maddison and Maddison, 2019)  and included NCBI sequences of Xylophagaidae, Teredinidae, and Pholadidae (Supplementary Table  S3 ). All sequences were aligned using MAFFT and then manually edited, trimmed and cleaned from ambiguous positions. The final alignments included 388 bp (COI), 1353 bp (18S rRNA), and 1104 bp (28S rRNA). All new sequences are deposited on GenBank (Supplementary Table  S3 ). Genetic diversity was evaluated as the number of segregating sites (S), using the MEGA software version 6  (Tamura et al. , 2013)  and uncorrected pairwise distances with PAUP * v. 4. 0a161  (Swofford, 2003). Maximum likelihood (ML) and Bayesian inference (BI) analyses of the molecular data phylogenetic trees were calculated separately for each gene COI, 18S rRNA and 28S rRNA, using RAxML v.
8. 2. 10 (Stamatakis, 2014) and MrBayes v. 3. 2. 6  (Huelsenbeck and Ronquist, 2001) , respectively. Analyses of concatenated COI+18S rRNA+28S rRNA, partitioned by gene, were also calculated with RAxML and MrBayes. For the BI analyses, the best-fitting evolutionary model for each gene was estimated with the software package Iq-Tree 1. 6. 12 (Chernomor et al. , 2016)  using the Akaike information criterion (AIC). GTR+F+I+G4 was the best fitting nucleotide substitution model for each of the genes. BI analyses were run twice, starting from random trees, with four chains running simultaneously (two cold and two heated). Chains were run for 10 6 generations for 18S rRNA and 28S rRNA and 10 7 generations for COI and the concatenated data, sampled every 1,000 generations and, after verifying that stationarity had been reached, 25% of the generations were discarded as burn-in.
The ML analyses were performed using the GTR+G evolutionary model, following the recommendations in the software author. Support values for the ML analyses were generated by 100 bootstrap pseudoreplicates. We used sequences from Mya arenaria Linnaeus, 1758, Mya truncata Linnaeus, 1758 and Varicorbula limatula Conrad, 1846 [here reported as Varicorbula disparilis D'Orbigny, 1853 as in NCBI database] and the Teredininae Lyrodus pedicellatus   Quatrefages, 1849 and Bankia carinata Gray, 1827 as outgroups. Trees were visualized in FigTree v 1. 4. 2 (Rambaut, 2006). A median-joining haplotype network based on COI sequences was constructed in PopArt  (Leigh and Bryant, 2015)  for the species that produced a minimum of 15 sequences, i. e. , X. dorsalis, Abditoconus brava, and X. atlantica.
The species of Abditoconus were united in clade 5, while those of Spiniapex were in clade 6, and those of Xyloredo in clade 7. A single terminal, supposedly a Xylopholas from the Gulf of Mexico, represented by GenBank sequences (Clade 8, 0. 9 pp, 58% bp), was isolated from all other Xylopholas. This situation is unclear and could possibly result from misidentification of the specimen. Re-collection and examination of the voucher may be needed to solve this in the future. S3  for accession numbers). Xyl: node of Xylophagaidae; Ter: node of Teredinidae. Colored circles and associated numbers represent the geographic and depth distributions of the species in this study; circle colors as in Figure  1. In summary, the monophyletic and well-supported xylophagaid clades correspond to six genera Xylonora gen.
Shiptime for cruise POS402 was granted by the German Research Foundation (DFG) through grant "MENEZKART". CR was funded by the People Programme (Marie Curie Action IOF to CR) of the European Union's Seventh Framework Programme (FP7/2007-2013) under the "DeepFall" project http://deepfall-project. eu; https://twitter. com/DeepFall_Proj (REA grant agreement N. PIOF-GA-2013-628146); AN-J was funded through DiWOOD; CB was funded by the DFG Cluster of Excellence "The Ocean in the Earth System" at MARUM (University of Bremen), a European Research Council Advanced Grant (BathyBiome, Grant 340535) and the Max Planck Society.
ACKNOWLEDGMENTS We would like to thank the chief scientists, captains and crews and the teams of ROV Victor 6000 ( IFREMER, France) ,  ROVs MARUM Quest 4000 and Cherokee  ( MARUM, Bremen, Germany ),  ROV Isis  ( NOC Southampton, United Kingdom ), and  ROV Genesis  ( Renard Centre of Marine Geology, Belgium ) for their help during the following cruises: DOSMARES (NW Mediterranean canyons) with the  Spanish RV Garcia del Cid; BIOCANT (Avilés Canyon)  with the  Spanish RV Sarmiento de Gamboa ; MEDECO (2007,  Eastern Mediterranean ),  MoMARDream-Naut  (2007) and MoMARDream-08 (2008, both to Rainbow hydrothermal vent field), (https://doi. org/10. 17600/7030060 )and BIOBAZ (2013,  Menez Gwen  hydrothermal vent field) with the  French RV Pourquoi Pas ?  BIONIL/M70-2  ( 2006 ,  Eastern Mediterranean ) with the German RV Meteor; HOMER/MSM13-3 (2009,  Eastern Mediterranean ) with the German RV MARIA.
S. MERIAN; ARKXXII/1b (2007) and ARKXXIV/2 (2009, both to Haakon Mosby mud volcano) with the  German RV POLARSTERN ;  MENEZKART/POS402  ( 2010 ,  Menez Gwen  hydrothermal vent field) with the German RV POSEIDON; JC-10 (2007, Mercator mud volcano,  N-Atlantic ) with the  British RRS James Cook ;  64PE284  (2008, Meknès mud volcano,  N-Atlantic ) with the Dutch RV Pelagia;  B09/14  (2009, Mercator and Meknès mud volcanoes) with the Belgian RV Belgica. Wood colonization experiments in the Lacaze-Duthiers Canyon were deployed with the RV Minibex (COMEX). Material from the Morocco mud volcanoes was collected within the Chemeco (Monitoring colonization in chemosynthetic ecosystems) from the  European Science Foundation  under grant  EURODEEP/0001/2007  and  FTC (Fundação para a Ciência e a Tecnologia ) project; we thank  Dr.
127 0. 138 0. 147 0. 166 0. 131 0. 13 0. 144 Abditoconus heterosiphon 0. 055 0. 043 0. 067 0. 124 0. 056 0. 066 0. 052 Xylonora muraokai NP 0. 080 0. 074 0. 038 0. 139 0. 014 0. 048 0. 066 Xylonora zierenbergi 0. 079 0. 074 0. 045 0. 142 0. 034 0. 032 0. 066 Xyloredo nooi SWAtl 0. 102 0. 086 0. 077 0. 136 0. 069 0. 075 0. 029 Xyloredo nooi NZ 0. 102 0. 086 0. 077 0. 136 0. 069 0. 075 0. 016 Xylopholas crooki 0. 11 0. 101 0. 095 0. 134 0. 082 0. 088 0. 082 (A) Uncorrected p distances (mean ± standard deviation) are represented above the diagonal for COI (bold) and below for 28S rRNA sequences; average and maximum within-lineage divergences are included; (B) Uncorrected p distances between the 28S rRNA sequences of species analyzed in this study and previously published species (see Supplementary TableS3for accession numbers).