dataesr/scientific-paragraphs-categorization huggingface dataset:
4 Modeling the kinematics of deformation of the West Andean fold-and-thrust belt. The geological inferences on the style of deformation, shortening and timing of deformation are further explored in a forward kinematic model of the WAFTB (Figure  7 ). We use here the formalism for tri-shear folding  [Erslev, 1991]  as folding is in our case interpreted mostly as fault-propagation folding. We use the code FaultFold Forward v. 6 freely available from http://www. geo. cornell. edu/ g e o l o g y / f a c u l t y / R W A / p r o g r a m s / faultfoldforward. html [Allmendinger, 1998]. Trishear modeling of folding simulates triangular zones of distributed deformation at the tip of propagating faults. In our model approach, folding is calibrated by seven parameters: the propagating fault ramp angle, the coordinates of the propagating fault tip, the slip on the fault, the trishear angle (i.
Acknowledgments Work supported by a PhD grant attributed to  M. Riesner  by the Ministry of higher education and research (MESR), and funded by  ANR  project  MegaChile  (grant  ANR-12-BS06-0004-02 ) and LABEX  UnivEarthS  project ( Sorbonne Paris Cité , Work Package 1). We thank  Daniel Carrizo  and  AMTC (Univ. de Chile)  for organizing and funding helicopter fly over the WAFTB. The kinematic modeling was made using FoldFault FORWARD v. 6 freely available from http://www. geo. cornell. edu/g e o l o g y / f a c u l t y / R W A / p r o g r a m s / faultfoldforward. html[Allmendinger, 1998]. This manuscript benefitted from the constructive reviews of  R. W. Allmendinger ,  V. A. Ramos  and of an anonymous reviewer. This is IPGP contribution number ****.
This technique was originally developed for the analysis of solutes in pure water, which is frozen in the experimental capsules and analyzed via laser-ablation ICP-MS. In the case of COH fluids, an immiscible mixture of water and non-polar gases is expected at the investigated P, T conditions  17  (inset in Supplementary Fig. 1e ). The cryogenic technique, operating at approximately -35 °C, only keeps water in a solid state. Therefore, the other volatiles (including CO 2 ) are lost when the capsule is opened for analysis. Consequently, the solute contents retrieved by ICP-MS pertain to the aqueous part of the bulk COH fluid only (Supplementary Table  3 ; other details in Methods section). In Fig. 2 , we report the solubility data of quartz (SiO 2 -COH system) and forsterite + enstatite (MgO-SiO 2 -COH system) at 1 GPa and 800 °C, where SiO 2 molalities have been obtained by correcting the concentration of the internal standard (Cs) on the basis of the measured fluid XCO 2 (Supplementary Fig.
However, since the inner capsule contains a mixed COH fluid instead of pure water, the oxygen fugacity in the inner capsule will be lower compared to that fixed in the outer capsule. The fugacities of oxygen and hydrogen fixed in the outer capsule by both NNO and FMQ were calculated employing Perple_X  59  (http://www. perplex. ethz. ch) using the thermodynamic data set of Holland and Powell  60  revised by the authors in 2004 and the Perple_X EoS n. 16 (H-O HSMRK/MRK hybrid EoS) (Supplementary Table  2 ). Subsequently, we calculated the speciation of the graphite-buffered COH fluid in the inner capsule for fH 2 fixed by both NNO and FMQ through thermodynamic modeling using (i) the software package Perple_X 59 (based on Gibbs free energy minimization) and the EoS of Connolly and Cesare  45  (Perple_X EoS n.
The furnace design includes a pilot hole in the base part that permits screwing the reactor with a hex key while placed in the furnace. Openings on the top of the reactor allow the carrier gas (ultrapure Ar) to flow inside it and to generate vent or vacuum conditions. The presence of O-rings ensures a tight seal. The reactor is connected to a QMS by a heated line (80 °C) to avoid condensation of water on the metal tubes. The pressure conditions in the line and in the reactor are monitored through high-resolution sensor gauges ( ± 1 mbar precision). The temperatures of the line, reactor and furnace are monitored with Ktype thermocouples. Line and reactor pressures and temperatures are recorded by a Eurotherm Nanodac data recorder with PID control. The internal volume of the reactor was calibrated against the distance h between the basal and the top part.
Analyses were performed using a 193 nm ArF GeoLas Pro excimer laser system coupled to an ELAN DRCD-e quadrupole mass spectrometer at University of Bern. We analyzed the diamond trap for  24  Mg,  25  Mg,  26  Mg,  29  Si,  62  Ni,  133  Cs,  195  Pt, and 197 Au, using a 60 µm beam diameter, ~13 J/cm laser fluency, and 5 Hz repetition rate. Data were acquired in blocks of up to ~10 individual sample analyses bracketed by three analyses of the standard NIST SRM610, placed in the ablation chamber with the sample. Background was taken for ~50 s and the sample signal, on the diamond trap or on the solid residue, was collected for ~20 s. LA-ICP-MS data reduction employed the SILLS software  62  and in-house spreadsheets to calculate solute concentrations, employing rigorous limit of detection filtering  63  for each element and each measurement individually.
Acknowledgements Authors are indebted to  A. Risplendente  for the assistance at scanning electron microscope and electron microprobe. M. Merlini  is acknowledged for the characterization of the experimental materials by X-ray diffraction. Funding provided by the  Italian Ministry of Education, University and Research (MIUR)  program  PRIN2012R33ECR. S. T. , C. T. , D. S. and S. P. acknowledge support from the  Deep Carbon Observatory (DCO).
83) with the NCP calculated from the seasonal DIC drawdown  54. Assumption of steady-state. Under steady-state or quasi-steady-state, NCP approximates carbon export out of the mixed layer because the inventory change of organic carbon (POC + DOC) in the mixed layer is negligible compared to NCP. In the Southern Ocean, DOC production is a small fraction of NCP  55, 56. In order to assess whether the assumption of steady-state is valid in our study region, we estimated the change in POC inventory over the days prior to ship sampling. To that end, we first estimated the time-derivative of chlorophyll between the time of sampling and 8 days earlier using MODIS ocean color data at 8 days 9 km resolution. We then converted Chl to POC using an empirical relationship derived from in situ Chl and POC (bottle measurements) data measured at the Palmer LTER (see Supplementary Fig.
Diatom species were identified by morphological characterization and 18 S rRNA gene (rDNA) sequencing. DNA was extracted with the DNeasy Plant Mini Kit according to the manufacturer's protocols (Qiagen). Amplification of the nuclear 18 S rDNA region was achieved with standard PCR protocols using eukaryotic-specific, universal 18 S forward and reverse primers. Primer sequences were obtained from  67  and are as follows: 18AF 5′-AACCTGGTTGATCCTGCCAGT-3′ and 18BR 5′-TGATCCTTCTGCAGGTTCACCTAC-3′. PCR products were purified using either QIAquick PCR Purification Kit (Qiagen) or ExoSAP-IT (Affymetrix) and sequenced by Sanger DNA sequencing (Genewiz). Sequences were edited using Geneious Pro 5. 6. 4 software and BLASTn sequence homology searches were performed against the NCBI nucleotide non-redundant (nr) database to determine species with a cutoff identity of 98%.
42 Oil PlanApo N objective lens. Valve apical length (AL), transapical width (TW), and pervalvar height (PH) dimensions were estimated with Scion Image software (http://scion-image. software. informer. com; June 2015). Diatom biovolumes were calculated according to  71  where pennate diatoms were modeled after elliptic prisms and centric diatoms were modeled after cylinders. Network analysis. All OTUs were used in the initial dataset. The rare taxa, i. e. OTUs appearing less than three times in at least 20% of the samples, were removed from the dataset. The OTU abundances were then standardized to the median sequencing depth. The dataset was then divided into two equally sized subsets based on their NCP/POC values ≥ or ≤ the median NCP/POC. For each subset the correlations between OTUs and the p-values were computed using the SparCC method  42  , which was specially designed for compositional data.
The resulting correlations with magnitude >0. 75 and with p-values >0. 05 were selected to construct networks for each subset. The two networks were visualized using Cytoscape v3. 4. 0  72. In Cyoscape, OTUs are represented as nodes. Correlations are displayed as edges with positive relationships in orange and negative ones in blue. Network properties were computed using the 'Network Analysis' function in Cytoscape, including diameter, density, clustering coefficient, characteristic path length, etc. The topological parameters for each node were also calculated, such as node degree (the number of edges linked to each node), betweenness centrality, and closeness centrality. Other statistical analyses. Forward stepwise regression was performed in JMP statistical discovery software from SAS. To reduce the number of regressors in the stepwise regression, which increase the possibility of collinearity and over-fitting, only the top 20 most dominant OTUs were included in the analysis.
Acknowledgements This work was supported by  NSF   OPP-1043339  to Cassar,  NSF   PLR-1440435  to Ducklow ( Palmer LTER ) and  NSF   OPP-1341479  to  Marchetti. This work was also in part (NC and YL) supported by the  "Laboratoire d'Excellence" LabexMER  ( ANR-10-LABX-19 ) and co-funded by a grant from the  French government  under the program " Investissements d' Avenir ". The authors thank  Oscar Schofield  for providing chlorophyll data,  Duke IGSP  for sequencing the DNA samples, and  Kuan Huang  for discussion. The authors are grateful to all the scientists, scientific support personnel and the officers and crew on ARSV L. M. Gould  for collecting samples and shipboard assistance.
Optical correlation images We use optical correlation images of the ground displacement from  Ayoub et al. (2009). Maps of ground displacement are made using 14 pairs of aerial photographs acquired before and after the earthquake. Cross-correlation is performed to derive horizontal co-seismic displacements in the vicinity of the fault. Pre-earthquake photographs were acquired during the summer 1989 while post-earthquake were acquired during the autumn 1995. The footprint of each pair is slightly less than 10 × 10 km 2 and the data set covers almost the entire surface rupture of the fault (Figs  2  and 7a ). Because of their near-field coverage, optical data can finely constrain shallow slip in our models. However, as pointed out by  Kaneko & Fialko (2011) , near-fault observations may include inelastic effects that can bias slip estimates assuming linear elasticity.
Bayesian sampling We use a Bayesian approach to obtain the full posterior probability density function (PDF) of the slip distribution given the observations and uncertainties. According to the Bayes-Laplace theorem, we write the posterior PDF as: p(m|d obs ) ∝ p(m) exp - 1 2 (d obs -Gm) T C χ -1 (d obs -Gm) (1) where m is the model vector, p(m) is the prior distribution, d obs is the data vector, G is the Green functions matrix, and C χ is the misfit covariance describing both data and forward prediction uncertainties. We compute the Green's functions for a semi-infinite stratified elastic medium using the EDKS software  (Zhu & Rivera 2002)  To sample the model space we use AlTar, a parallel Markov Chain Monte Carlo (MCMC) algorithm based on the CATMIP formalism  (Minson et al. 2013). Using multiple MCMC chains in parallel, Al-Tar initially samples the prior PDF, p(m), and then slowly increases the information brought by the data until it samples the posterior PDF.
A C K N O W L E D G E M E N T S We are grateful to J. P. Avouac and F. Ayoub for providing the optical images correlation observations. We also thank Y. Fialko for sending us his co-seismic slip model. This study contributed from fruitful discussions with Sarah Minson, Lijun Zhu, Michael Aivazis and Gilles Peltzer. Some GPUs used for this research were donated by the NVIDIA Corporation. This work was supported by the Initiative d'Excellence (IDEX) funding framework (Université de Strasbourg) and the CNRS PICS program (Zacharie Duputel). This work was also funded by NSF grant 1447107 awarded to Mark Simons. We thank the Editor, Martin Mai, and two anonymous reviewers for their constructive comments, which helped improve this manuscript.
Introduction In his systematic revision of the species of Nassariidae,  Cernohorsky (1984)  treated 16 taxa as junior synonyms of Nassarius (Hinia) pauperus  (Gould, 1850)  (as "Hima"). All these nassariids are rather similar and the small morphological differences were interpreted by  Cernohorsky (1984)  as representing intraspecific variation. Kool & Dekker (2006 , 2007)  discussed, in parts 1 and 2 of this ongoing review, whether many of these synonyms should not be considered valid species. DNA data obtained from live specimens collected during several MNHN expeditions were used here as evidence to support species hypotheses originally based solely on morphological features. Kool & Dekker (2006 , 2007)  defined some informative morphological characters for the species included in the Nassarius pauperus complex (often as "pauper-complex").
Acronyms Sequence cleaning and alignment was done by using Codon Code Aligner software. GenBank accession numbers for all the sequences obtained are included in Table  1. We compiled a dataset of sequences available for several closely related species, identified in a phylogenetic tree, based on a large dataset of Nassariidae  (Galindo et al. 2016)  to compare with our new species hypotheses. The analysis involved 89 COI sequences: 72 of them belong to the Nassarius pauperus complex, 16 sequences to other species of Nassariidae and one to a distant outgroup. The Automatic Barcode Gap Discovery (ABGD) method using the default parameters  (Puillandre et al. 2012b ) was employed. It automatically detects, when present, a threshold (the barcode gap) in the pairwise distribution of the genetic distances calculated between each pair of specimens.
Results A comprehensive dataset on the Nassarius pauperus complex was gathered. For COI, 72 partial sequences were unambiguously aligned without gaps; 244 sites were variable positions, of which 204 were parsimony informative. For 28S, 51 sequences of the first subunit were successfully amplified. The 28S tree supported all the species hypotheses evidenced by COI. The resulting trees, constructed after the analyses of COI and 28S markers separately (Fig. 1A-B ), are in general characterized by strong support values (posterior probability, PP) of deep and terminal nodes. The Nassarius pauperus complex was recovered as a monophyletic group (PP = 1). Branch lengths (sequence divergences), similar to those found for other major clades within Nassariinae (i. e. , Phrontis  Adams & Adams, 1853 , Nassarius, Tritia Risso, 1826 and Naytia Adams & Adams, 1853) , support our taxonomic decision to consider this clade as a separate genus.
Our results are also consistent with what has been observed in other nassariids: the intraspecific variability is about 1. 9% among species of Nassarius  (Kool & Galindo 2014 ) and ranges from 1. 1% to 2. 5% within species of Tritia  (Couceiro et al. 2012; Couceiro et al. 2007; Simon-Bouhet et al. 2006). In general, K2P genetic distances between gastropod species span from 4. 2% to 5. 9%  (Li et al. 2010; Kantor et al. 2012; Fedosov et al. 2014; Lorenz & Puillandre 2015). The absence of a discrete barcode gap in a dataset can be explained many ways. In this case, it can be related to poor intraspecific replication within some species, i. e. , there is only one sequence each representing R. paupera and R. tringa. The trees (Fig. 1A-B ) reveal the existence of several lineages, with, so far, no morphologically recognizable characters (i.
Acknowledgements As sources of material used in this paper, we want to highlight in particular the following expeditions: MONTROUZIER 1993 to New Caledonia; PANGLAO 2004 to the Philippines; SANTO 2006 to Vanuatu; and  PAPUA NIUGINI  to the Madang District of Papua New Guinea. They were sponsored by the  Total Foundation , the  Stavros Niarchos Foundation , the  Prince Albert II of Monaco Foundation ,  Entrepose Contracting and Fondation EDF. In the field,  Y. Kantor ,  N. Puillandre ,  E. E. Strong  and  M. C. Boisselier  specifically preserved mollusk samples for molecular sequencing. Another source of sample material is the series of cruises to New Caledonia, Fiji, Tonga and the  Solomon Island as part of the Tropical Deep-Sea Benthos  programme (Bouchet et al. 2008), and also  Bertrand Richer de Forges' Programme Lagon  (material collected by  Richer de Forges  in 1995).
G. Marani  built and has managed the Geographic Information System for the biodiversity of  Nassariidae. M. Caballer  is thanked for photographing the holotypes as part of the  E-RECOLNAT   ANR-11-INBS-0004 ,  MNHN program  and  S. Pont  ( SEM-EDS ) for securing the electronic microscopic images. This project was supported by the " Bibliothèque du Vivant" network , funded by the  CNRS-MNHN-INRA-CEA (Genoscope) , the  'Service de Systématique Moléculaire'  ( UMS 2700 CNRS-MNHN ), and the deep-sea studies developed in the  French-Taiwanese TF-DeepEvo ANR-NSC  project ( ANR 12-ISV7-0005-01 ). Thanks to  B. A. Marshall  and an anonymous reviewer for their comments, which helped to improve the manuscript.
The main data sources for TRMM-TMPA 3B42V7 are infrared GOES-W (Geostationary Operational Environmental Satellite-West), GOES-E (East), GMS (Geostationary Meteorological Satellite), Meteosat-5, Meteosat-7, and NOAA-12 geostationary satellites, as well as the passive microwave radiometers of the TMI/TRMM (TRMM Microwave Imager), SSMI/DMSP (Special Sensor Microwave Imager/Defense Meteorological Satellite Program), AMSU/NOAA (Advanced Microwave Sounding Unit/National Oceanic and Atmospheric Administration) and AMSR-E/Aqua (Advanced Microwave Scanning Radiometer-EOS) low orbit satellites. During the last ten years, the TMPA algorithm has undergone three important updates to incorporate data from new sensors into the algorithm  [22]. TRMM-TMPA 3B42V7, the research version, is available approximately two months after observation.
Local Assessment Figure  6  shows the rBIASs and rRMSEs for the 23 validation daily SPP series considered individually. The rBIASs and rRMSEs are obtained after comparing the precipitation estimated from TRMM-TMPA 3B42V7 and daily rain gauge measurements (black), and the precipitation corrected with the QM method and daily rain gauge measurements (grey). Figure  5a  shows that the global rBIAS is worse after the QM correction. Without correction, the average of the rBIAS of the 23 daily SPP series is -3% against -25% after the QM correction. For the rRMSE, Figure  5b  shows a very slight improvement of only 1% for the QM-corrected data. This result shows that for the Guiana Shield, the TRMM-TMPA 3B42V7 SPP provides a reasonably good estimation of precipitation on the global scale. The rBIAS degradation of the QM-corrected data indicates that this method is not applicable to large spatial scales.
Acknowledgments: The research leading to these results has received funding from  Fonds Européen de Développement Régional (FEDER-Guyane / PHEUS  Project). We acknowledge  Météo France  and  Agência Nacional de Àguas  for providing the daily precipitation data. Finally, special thanks to the original producers of all evaluated precipitation products for providing free downloadable precipitation products. We would like to thank  Editage  (www. editage. com)for English language editing.
Scan parameters were as follows: voltage = 135 kV; current = 300 pA; exposure: 333 ms; isotropic voxel size of 0. 1095 mm. Data were reconstructed using datos|x reconstruction software (Phoenix|x-ray, release 2. 0), then exported into a 16-bit TIFF image stack of 1010 virtual slices in transverse view. Materialise Mimics Innovation Suite software version 18 was utilized for the 3D reconstructions.
ACKNOWLEDGMENTS The authors thank two outside reviewers for their insightful comments and suggestions for improving the paper. Miguel Garcia  (MNHN) prepared the scan used in this analysis. Carole Burrow  provided valuable information concerning "acanthodian" spine morphology and ter¬ minology J. G. M. received a  George Frederic Matthew Research Grant  from the  New Bruns¬ wick Museum (Saint John, New Brunswick, Canada)  to examine the material. A. R and J. S. S. D. were supported by postdoctoral fellowships funded by the  Herbert and Evelyn Axelrod Research Chair in Vertebrate Paleontology at the AMNH. A. B. was funded by the  Richard Gilder Gradu¬ ate School at the AMNH.
Missing Information on Ties Such ties are essential, yet they are not made at many tide gauges around the world, primarily because tide gauges and GNSS equipment are operated by different national agencies. These agencies do not accept making the ties as being their responsibility, in spite of this issue being raised with them many times by international sea level and GNSS programs, including the Global Sea Level Observing System (GLOSS) of the Intergovernmental Oceanographic Commission (IOC). Figure  1  illustrates the problem. It shows tide gauge locations around the world for which a permanent GNSS station nearby (closer than 1 kilometer) has been identified in the Système d'Observation du Niveau des Eaux Littorales (SONEL) data bank at the University of La Rochelle in La Rochelle, France.
Consequently, the rates recorded by the different techniques can be used to validate each other. For example, altimeter and tide gauge data can provide estimates of land movement that can be compared with those of GNSS data. Similarly, tide gauge and GNSS data can be used to calibrate altimeter measurements. Researchers have made such comparisons of rates using different techniques for many years [e. g. ,  Wöppelmann and Marcos, 2016]. However, an implicit assumption is always that the level of the land on which the tide gauge is located is moving in the same way as the land under the GNSS and that there is no differential movement between them. Such an assumption may be reasonable where the two sensors are not far apart and are located within the same parcel of land. However, it becomes more problematic when the two sensors are farther apart, when they are installed on dissimilar substrates (e.
Falling Between the Cracks Why has it been so difficult to make the ties and include them in sea level and GNSS data banks? One reason might be a lack of scientific appreciation for the importance of this activity. Most researchers consider only the rates of change of sea and land levels, measured by the tide gauge and GNSS, respectively, to be important. They seem to be happy enough to assume that the intervening land is relatively stable, so the same land movements occur at both locations, but this assumption cannot be made in long-term studies, for example, within the context of validating new satellite radar altimetry missions aimed at climate sea level applications. Scientists engaged in the relatively new field of WHSU are also disadvantaged by the lack of ties. Tide gauges and navigational satellite equipment are commonly separated by several meters to a kilometer or more.
Sampling procedures and analysis Sampling campaigns were conducted in September (rainy season) and November (dry season) 2014 at the five gauging stations. Physico-chemical parameters were automatically recorded at the interval of 1 min during 24h for each sampling campaign: pH, turbidity, salinity, chlorophyll a by the sensor YSI6920 (YSI, USA); temperature and dissolved oxygen (DO) by a HOBO sensor (USA). These sensors have been calibrated with standard solutions before each measurement campaign. All solutions used for calibration should be at ambient temperature to ensure quality of calibration and all data must be entered on the documents. In parallel of in-situ measurement, river water samples were hourly collected for analysis of other water quality variables (TSS, DOC, POC, and alkalinity) during 24h.