dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2006). These efforts to make, assess, and fully document the additional DTMs were unfortunately cut short by the end of Huygens mission funding. At that time, all of the source data products needed to build DISR DTMs were in preliminary and rapidly changing states. Radiometric and cosmetic (compression artifact removal and sharpening) processing of the images had not been finalized, so the versions of the images used were later superseded and never archived. As noted by  Archinal et al. (2006) , the cameras were geometrically recalibrated but their optical parameters never published. Only a preliminary estimate of the Huygens descent trajectory was available to constrain the camera position for each image, with no prior information about camera pointing. The version of the Huygens trajectory archived in the PDS differs from both the version used as input for the USGS-DTM and the photogrammetrically adjusted camera positions.
As a result, the geometry of stereopairs could only be reconstructed with limited accuracy, so that elevations are relative rather than absolute. The lack of a priori position and pointing information also meant that there was no way to identify potential stereopairs more efficiently than by visual examination of the images. This limited both the effort to map additional areas and the ability to improve the quality of a DTM by using multiple overlapping images. Finally, attempts to use the automatic image matching module of SOCET SET were unsuccessful because of the relatively low signalto-noise level and the extremely small size of the DISR images. The USGS-DTM was thus generated by visually identifying remarkable features. This process restricts the resolution of the DTM because areas that do not contain mappable features have been filled by interpolation.
, 2013; Perron et al. , 2006). These discrepancies may result from the difficulty of controlling the images (i. e. , improving the knowledge of camera positions and pointing given the limited starting data that were available) described above. As a result, it is likely that the overall USGS-DTM is not properly leveled, and because it was produced from overlapping stereopairs, the apparent dome could be the result of different leveling errors on the two sides. The limited resolution of the manually produced DTM also confounds efforts to assess the complete geometry of the stream courses. All theses reasons led us to revisit the topographic mapping of the Huygens site. In addition to investigate the apparent errors in the USGS-DTM, we will take advantage of recent advances in the processing of the Huygens data and the stereoanalysis softwares to generate a significantly improved DTM and, ultimately, to map a larger area of the landing site with additional stereopairs.
We will also fully document our data sources, methodology, and final products so that others can reproduce or extend our work. Since the USGS-DTM realization, recent post-processing of the DISR images were performed (Figure  3 ) to correct both for the radiometric and geometric distortions  (Karkoschka et al. , 2007; Karkoschka & Schröder, 2016). A re-estimate of the navigation data (SPICE kernels) is also available  (Charles, 1996; ESA SPICE Service, 2019). The new DTM, hereafter called the IPGP-DTM, was built using MicMac, a free and open source photogrammetry software  (Pierrot-Deseilligny & Paparoditis, 2006; Pierrot-Deseilligny & Clery, 2011; Bretar et al. , 2013). MicMac applies a shape-from-motion (SfM) algorithm to generate large point clouds. To manipulate the Huygens images, which were originally not intended for photogrammetric reconstruction, a tailor-made reconstruction procedure was required.
In an early version of the DISR dataset, the decompressed pixel values were rounded to the nearest integer before applying an inverse square root, which led to a significant information loss. The new image processing has corrected these errors and removed the residual radiometric artifacts (e. g. ,  Karkoschka et al. , 2007; Karkoschka & Schröder, 2016; Karkoschka, 2016). Indeed, the standard decompression scheme produced images that consist of certain spatial frequencies in each 16×16 pixel block with noticeable boundaries between adjacent blocks. In many images, artifacts generated by the compression were more apparent than real features on the surface of Titan. That problem was fixed by smoothing high spatial frequencies  (Karkoschka et al. , 2007). The method was recently improved by  Karkoschka and Schröder (2016)  who use a lower degree of smoothing so the new images display significant radiometric and geometric differences compared to those used to build the USGS-DTM  (Tomasko et al.
The position and orientation of the Huygens probe during the descent were first computed by the Huygens Descent Trajectory Working Group (DTWG). The positions are given with an uncertainty of the order of 0. 24 • in longitude, 0. 17 locity of the probe during the descent were generated using data from the DTWG  (Kazeminejad & Atkinson, 2004; Kazeminejad et al. , 2011). They were computed by numerical integration of the equations of motion, providing the position of the probe in spherical coordinates with respect to the Titan centered fixed frame, together with the altitude derivative with time. The finite difference method provided good results for the velocity vectors thanks to the high time resolution of the data. Finally, a polynomial interpolation was performed between data-points for the creation of the kernel.
For the generation of the Camera Kernel (CK) that contains the attitude of the probe, thus the pointing direction of the cameras, the body angles of the probe were reconstructed with the geometry derived from the DISR images provided by  Karkoschka et al. (2007). Lastly, in order to smooth the evolution of the data points, the spin rate from housekeeping data was introduced in the calculations and used to write another CK which implements the actual angular rate with the exact attitude of the probe at each moment of shooting. The Frame Kernel (FK) and Instrument Kernel (IK) that complement the CK have been defined according to the standard fixed frames and parameters of the probe provided by the Huygens User manual.
IPGP-DTM construction using MicMac The MicMac because it allows a large degree of freedom in the sensor models and in the 3D reconstruction strategies, which makes it a relevant tool for our application. Since the images and the geometries of acquisition are not optimal, it is important to control the parameters at each stage of the reconstruction. MicMac also incorporates a correlator that proved to be more reliable and robust than in other photogrammetry softwares  (Rosu et al. , 2015). Another important issue is that any user can reproduce the IPGP-DTM. Regarding our particular dataset, we developed a specific workflow. Indeed, we are in a particular case at a crossroads between two typical scenarios: • the "architectural" scenario, which tries to reconstruct a complex structure and usually deals with different focal lengths of the same camera in order to capture all the details of the studied structure.
• the "drone" scenario, where images are acquired by a short focal length camera onboard a drone with inaccurate GPS data. Theses two scenarios can be easily handled by MicMac following a classical pipeline (Figure  5 ). Yet, our dataset is a mix of the two scenarios with different focal lengths and imprecise navigation data. Moreover, the parallax of our images is small and we are working with two different cameras. We therefore could not apply an existing workflow and had to develop an entirely new procedure for this particular dataset (Figure  5 ). This workflow can be extended to any case where the camera configuration is complex (low parallax and overlap, imprecise navigation data, no ground control points, etc. ). Batch commands can be run from a command line and the three main steps of the photogrammetric reconstruction (homologous points search, absolute orientation, and depth map construction) are divided into 6 sub-steps corresponding to different commands (Figure  5 ).
If not, this step does not converge. However, a first estimation of the position of the optical center and the orientation of the optical axis is carried out during this stage using the images. This step is not essential to compute the final orientation but necessary for MicMac to calculate the absolute orientation. -12-©2020 American Geophysical Union. All rights reserved. manuscript submitted to Earth and Space Science Then, the absolute orientation is determined in two steps. The first one aims to compensate between the relative orientation and the positions provided by the SPICE kernels, which means that it applies a 3D homothety (rotation, translation, and scaling) to the pre-existing relative orientation. This first step is necessary in order to switch to field coordinates because no pre-existing cartography is at our disposal.
We also masked pixels with a correlation score lower than 0. 5, the reference threshold used in MicMac (in SOCET SET, it equals 0. 4, as documented in the source code and the user guide). The resulting mask is applied to Fig. 9  and 10. Nevertheless, despite these adjustments, the resulting IPGP-DTM presents a global tilt of ∼9. 5 • (measured in Figure  11  (a), see Supplementary Information S5), which leads to an improbable configuration: the dark lakebed is higher than the bright hills  (Tomasko et al. , 2005; Perron et al. , 2006; Karkoschka & Schröder, 2016)  and the rivers, the mouth of which is located in the dark lowlands, rise up the slope. This overall inclination is due to improperly addressed photogrammetric problems. Indeed an intrinsic mathematical indeterminacy affects the global orientation of the IPGP-DTM plane.
Determination of the IPGP-DTM tilt The last step of the workflow consists in finding the overall inclination of the IPGP-DTM. As no other topographic data derived from the Cassini mission can help constrain the global tilt of the IPGP-DTM, a new strategy should be adopted. The USGS scientists fixed this problem by setting the elevation of lakebed in the USGS-DTM to zero, assuming that there is no global slope. To avoid making any prior assumption concerning the global inclination, we determined the tilt using morphological information and river routing. Routing is commonly used in hydrology to determine the natural route taken by a liquid over a given topography. Ideally, a liquid flowing on the IPGP-DTM should choose the same path as the one followed by the rivers seen in the images. Thus the idea is to compare this routing with the actual location of the rivers  (Tomasko et al.
, 2011). Their large extent (more than 500,000 km 2 ) and the proximity of one of them to the Huygens landing site (about nearly 50 • to the west) sign that recent rains may occur in this region. The strategy therefore consists in i ) rotating the IPGP-DTM produced with Mic-Mac along the x-axis and y-axis, from -20 • to +20 • with a 1 • step; ii ) calculating the routing using the Matlab TopoToolBox  (Tarboton, 1997; Schwanghart & Scherler, 2014) ; and iii ) comparing it to a river mask produced using the orthorectified mosaic (Figure  7 ). To minimize misinterpretation, three masks were manually drawn by different operators and we kept their intersection as the final one. For this comparison, we only focused on the major rivers to the right of the scene (outlined in red in Figure  7 ), leaving aside the shorter and stubbier rivers to the left that are not discernible enough.
Conclusion New investigation of the topography around the Huygens landing site has been successfully carried out. We developed a new strategy that could overcome the high complexity of the dataset, unusual even for planetary data, and provided a fully documented and reproducible workflow. This procedure could be apply in situations with such a complex dataset. For instance, it could be applied both to poorly known and hard-to-reach -22-©2020 American Geophysical Union. All rights reserved. -23-©2020 American Geophysical Union. All rights reserved. img/transect_comp_Malt. pdf -25-©2020 American Geophysical Union. All rights reserved. manuscript submitted to Earth and Space Science.
manuscript submitted to Earth and Space Science terrestrial areas (i. e. , Antarctica) and to archive data from former planetary missions (i. e. , Voyager, Galileo, etc. ). Besides a new strategy, the article provide a new DTM with a higher spatial sampling and a more reliable topography since it is much less interpolated than the previous product. This DTM offers new opportunities for investigating the topography of fluvial landscape at Titan's equatorial region with an unprecedented resolution. It could bring new insights on Titan's landscape formation mechanisms by quantitatively characterizing the morphometry of these rivers and the topography of their associated drainage basins.
Acknowledgments The authors thank  Chuck See  for providing the re-processed DISR images. They also thank the reviewers for their valuable comments and advice. MicMac software can be downloaded for free (https://micmac. ensg. eu/index. php/Accueil)and the SPICE kernels are publicly available (https://doi. org/10. 5270/esa-ssem3np). The DTM and other products resulting from this work are available on https://doi. org/10. 5270/esa-3uja374.
Material and methods To investigate the TEC variations caused by the 2010 Mw 7. 8 Mentawai and Banyaks earthquakes, we analyzed 15-s data from 29 and 25, respectively, continuous GNSS stations of the SuGAr network that were in operation on the day of each earthquake (Fig. 2 ). We analyzed the GNSS data for the week centered on the day of each earthquake to obtain the ionospheric perturbations before, during, and after the events. We calculated the TEC by applying a method similar to the one described by Calais and Minster  26. To obtain a more accurate measure of the apparent distance between a satellite and receiver, we used the carrier phase (L1 & L2), neglecting the less precise pseudo-range measurements (P1 & P2): where, f 1 and f 2 are, respectively, the corresponding high and low GPS frequency and TEC is the total electron content measured in TEC units (1 TECU = 10 16 el/m 2 ).
We detected and corrected the cycle slips using the program Ninja within the GPS-Inferred Positioning System and Orbit Analysis Simulation Software (GIPSY-OASIS) version 6. 2  27. As a consequence of the integrated nature of TEC, the observed ionospheric perturbations result from a large range of altitudes from the satellite to the receiver. However, the main contribution to the observed TEC variations is located around the height of the maximum of ionosphere ionization (the F2 layer). For this study, we fixed the altitude of the F2 layer at 300 km, which can be considered as the average altitude for day and night for the Equator. The intersection of the line of sight between each GNSS satellite-receiver pair at this altitude is termed the ionospheric pierce point (IPP), which we use to spatially visualize the observed TEC perturbations.
Values of uplift are provided by the US Geological Survey (USGS, https ://earth quake. usgs. gov/earth quake s/) resulting from finite fault, calculated using Okada-style deformation codes  29. We highlight that the ITPI is a more accurate way to estimate the ionospheric perturbation as it is calculated in the spectral domain and it is consequently free of eventual pass-band filter applied to CID. Tsunami warning response to the two Mw 7. 8 Mentawai and Banyaks earthquakes. We analyzed two M w 7. 8 earthquakes (Fig. 2 ) that occurred in 2010 along the Sunda megathrust (Indonesia): The 6 April Banyaks earthquake  18, 19  and the 25 October Mentawai earthquake  7, 20, 21. Although they had the same magnitude, only the Mentawai earthquake produced an anomalously large tsunami. The Banyaks earthquake ruptured a deeper portion (20-30 km) of the megathrust, producing relatively small uplift of the seafloor and thus only a small tsunami (max water height: 44 cm, max run up: 6 m, source NOAA database).
Acknowledgements Some of the results presented here are reported in the PhD thesis of  Dr. Fabio Manta  (https ://hdl. handle. net/ 10356 /10757 7 ), archived by  Nanyang Technological University, Singapore. We are grateful to the many scientists and field technicians who have kept the SuGAr network in operation. These include  Paramesh Banerjee ,  Iwan Hermawan ,  Danny Natawidjaja ,  Jeffrey Encillo ,  Imam Suprihanto ,  Dudi Prayudi , and  Bambang Suwargadi. SuGAr GPS data are available for download from ftp://ftp. earthobser vator y. sg/Sugar Data. This research was supported by the  National Research Foundation Singapore  under its  Singapore NRF Investigatorship scheme  (Award No. NRF-NRFI05-2019-0009 ) and by the  EOS  and the  National Research Foundation Singapore  and the  Singapore Ministry of Education  under the  Research Centres of Excellence initiative.
These particles are also added in the salt water that is injected to generate the vortices. A green light laser beam is then used to illuminate the particles in planes crossing the vortices. The top view camera is used to record the movement of the particles with a frame rate of 1 Hz. Two frames of the video sequences are used to estimate the particle displacement using PIVlab  (Thielicke and Stamhuis 2014)  or Flow Manager (Dantec Dynamics c ) softwares. Each image is subdivided in 32 pixels interrogation windows to calculate the instantaneous velocity fields as a function of time at the rate of 1 field per second.
Acknowledgments This work has been carried out in the framework of the  Labex MEC  Project  410  (No. ANR-10-LABX-0092 ) and of the A* MIDEX  Project (No. ANR-11-IDEX-0001-02 ), funded by the " Investissements d'Avenir" French Government program  managed by the  French National Research Agency (ANR). The authors also acknowledge support from the  American Physical Society's International Research Travel Award Program (IRTAP). We also thank for their financial support, the  University of Guadalajara  and  Aix Marseille Université  for the fundings " Appel à Projets Actions Internationales "  2016. A. O. E. acknowledges  CONACyT  for his scholarship.
Results Transmissivity increase of the hydrogeological system (aquifer and aquitard) over 12 years and over geological ages. Aquifer transmissivity can be determinated from earth tide analysis  9, 17, 27, 28, 38  , considering the time lag (phase shift) between the tidal dilatation of the aquifer and the water level response in the well  6. Geologic or topographic heterogeneity may affect the tidal response of an area  39  , but these effects did not vary over the duration of our study 10 , and should not affect the phase lag evolution. We use Baytap08 software  40  to calculate, by period of 31 days with an overlay of 15 days, the phase shift of the water-level response to M2 tidal component of earth tides (Fig. 3a ). Significant changes in the phase of the tidal responses are observed following the five earthquakes, with values ranging from -17° to + 34°.
Tidal response of a leaky aquifer. We first use Baytap08 software  40  , a modified version of Baytap-G  67  , to calculate the phase shift and amplitude ratio of the water-level response in the Galion borehole to M2 tidal component of earth tides. Water level data were divided into 31 days spans with an overlap of 15 days. Input data are presented in Fig. 2 : hourly water levels, hourly barometric pressure at the nearest meteorological station (10 km www. nature. com/scientificreports/ NE), and hourly ocean tide fluctuations at the Fort-de-France harbor, re-projected to the Atlantic coastline of the island. The frequency analysis of each dataset is available in SI appendix Fig. S5. The tidal response of a leaky confined aquifer model  43  consists of an aquifer with a transmissivity T confined above by a semi-confining aquitard with a permeability, k and a thickness, b.
) comes from the BRGM piezometric monitoring network of Martinique, set up since 2005 as part of the European Water Framework Directive and is funded by the French Ministry of Environment and BRGM. Data are available online: https ://ades. eaufr ance. fr/. The borehole national reference is BSS002NNZL (1175ZZ0154/NF4). Two sensors have used both with millimetric resolution. OTT Thalimedes from 2005 to 2014, a float operated shaft encoder with integrated data logger, and SEBA Dipper-PT data logger, from 2014 to 2019, a ceramic pressure sensor, with integrated air pressure compensation tube. Public reports of felt earthquakes in Martinique by the OVSM-IPGP observatory are available online: https ://volca no. ipgp. fr/marti ) = T 0 e -γ △σ (t) and knique s. htm. Historical earthquakes database is available online: https ://sisfr ance.
Acknowledgements The authors thank all of the BRGM hydrogeologists and technical teams who contributed to the Martinique water level monitoring network since 2007. Zheming Shi  is thanked for his advices concerning the parametrization of  Baytap08. Faiza Boulahya  is warmly thanked for compiling Baytap08 on BRGM calculation server and for the development of an extraction script. The  Volcanological and Seismological Observatory of Martinique (OVSM-IPGP)  is thanked for the access to their monitoring data via "volobsis". The authors also thank  Anne Lemoine ,  Didier Bertil ,  Clara Levy  (BRGM) and  Hideo Aochi  ( BRGM & ENS ) for fruitful discussions.
Ikeya (1981)  based on the previously published articles  (Ikeya, 1975; 1978). The ESR dating paper by  Yokoyama et al. (1981a)  addressed some of the main problems such as uranium concentration variations, U-series disequilibrium (escape of radium and radon), water content and alpha/beta effectiveness, k-value, for which an analytical device was built according the description of  Zimmerman (1971). Several values ranging between 0 and 1 were measured for k for three bones. Yokoyama et al. (1981a)  experimentally determined a k-value of 0. 084 for the bones from Arago. Grün and Katzenberger (1994)  measured later a k value of 0. 13±0. 02 for enamel sample. At this time, the dose values, D E , were calculated using a linear extrapolation with 5-6 data points and the obtained values varied from sample to sample by a factor of 10 implying a wide spread in the ages of the human bearing layers.
Acknowledgements I would like to thank the three reviewers who have contributed to improve this paper. Since 1980, we have collaborated with many prehistorians, the list would be too long to be reproduced here, but I want to thank them all warmly for giving access to their sites. I thank also  Jean-Pierre Quaegebeur ,  Concèle Léger  and  Roland Bibron  from  CEA, France , who were the first of Yokoyama's collaborators to begin this paramagnetic adventure. Georges Valladas taught to me how to prepare quartz grains in his great simplicity!I think often to him. I am particularly grateful to  Jacques Labeyrie  and  Henry de Lumley  accepting me in their lab. We have been working with  Jackie Despriée  for more than 25 years and he is the collaborator that everyone wants to have. Thank you  Jackie!Jean Michel Dolo  helped us for the questions of artificial irradiations and became a good friend also.
Statistical Analysis SPSS software version 25 (IBM) was used for statistical analysis. For the RGRs of fresh weights, one replicate in 4 • C_Dark was excluded due to a technically erroneous measurement (hence the total N = 15, n = 3 in the treatment of 4 • C_Dark and n = 4 in the other three treatments). For the other parameters, each treatment had four biological replicates. A two-way ANOVA was used to test the effects of temperature and light conditions on growth and photochemistry. Prior to analysis, all data were tested for the normality by the Shapiro-Wilk test and the homogeneity of variances by the Levene's test. Since the data of RGRs failed to comply with the homogeneity of variances, a non-parametric test (Mann-Whitney U test) was used to test the effects of temperature and light conditions, respectively.