dataesr/scientific-paragraphs-categorization huggingface dataset:
The reliability of these measurements was tested and assessed through different quality control procedures, as well as through comparisons with available historical datasets. This dataset is available through an unrestricted repository at https://doi. org/10. 25704/b200-3vf5, where NetCDF files including different elaboration levels (from 0 to 2) and documentation are easily accessible. This multiparametric dataset is expected to be particularly beneficial to oceanographic studies focusing on the characterisation of the hydrographic and biochemical structure of the Western Mediterranean at all spatial scales. In fact, the presence of AW (at different modification stages), LIW and WMDW, as well as their interannual variability, can be observed and analysed, as reported by  Aulicino et al. (2018).
They included part of the presented dataset in their multiplatform analyses, stressing the usefulness of repeated glider monitoring in combination with altimetry and numerical simulations. Still, these observations already proved their contribution to the analyses of the mesoscale and sub-mesoscale processes in the study region  (Cotroneo et al. , 2016)  whose study needs to be based on an appropriate high-resolution in situ dataset in order for these data to possibly be coupled with satellite remote sensing data. Then, we believe that the ABACUS glider dataset represents a valid unrestricted product which could partially fill the lack of information in the AB, and a valuable tool for improving, together with similar information collected in the framework of other AUV projects, our knowledge about the dynamics of the Western Mediterranean and its physical and biochemical characteristics at different spatial scales.
The synergy between multiple glider surveys and other data sources, i. e. satellites, models, coastal radars, buoys and drifters, possibly including advisable occasional classical oceanographic cruises, could represent the best strategy to be implemented. As for the AB, the ABACUS monitoring activities are expected to be repeated and enhanced during the coming years, taking into account the lessons learned through this study. From 2017 we have enlarged the ABACUS network and conducted more glider missions per year in order to monitor both seasonal and interannual variability along the Mallorca-Algerian coast transect.
Acknowledgements. The ABACUS 1 missions (2014) were supported by the Joint European Research Infrastructure network for Coastal Observatories (JERICO) TransNational Access (TNA) third call (grant agreement no. 262584). The research leading to ABACUS 3 (2016) was supported by the European Union's H2020 Framework Programme (h2020-INFRAIA-2014-2015) (JERICO-NEXT grant agreement no. 654410). Additional EU funding (PERSEUS grant agreement no. 287600) is acknowledged. The activities described in this paper were developed in the framework of the Italian Flagship Project RITMARE. Ananda Pascual wishes to acknowledge support from the PRE-SWOT project (CTM2016-78607-P) funded by the Spanish National Research Program. The SOCIB Data Server hosts ABACUS data which are available at https://doi. org/10.
Comparison of results from this study with previous work The present study funded by ESA in support of its PROSPECT package follows an earlier study into the effects of sublimation on the isotopic fractionation of water ice also carried out in the same laboratory in Lyon, using the same glass vacuum line and elemental analyser for D/H isotopic analysis. The results from this previous study have already been published  (Lécuyer et al. , 2017) , so it is useful to place the current dataset into context by comparing it with this earlier work. resistance wire heating a much larger section of the glass vacuum line than did the earlier study, which results in more water vapour being removed from the system before it can build up to such a level near the water ice sample that it begins to refreeze back down onto the sublimating ice and reach a steady cycle of loss and retrapping.
C. Electronuclear Reaction Third, electrons are able to trigger some nuclear reactions. The so-called electronuclear process has a threshold around some tens of megaelectronvolt and is able to produce some energetic recoil elements with enough energy to trigger some upsets. The electronuclear reactions are closely connected with the photonuclear process. Within the equivalent photon approximation, the flux of energetic photons can be folded with the photonuclear cross sections to estimate the electronuclear cross sections. The nuclear reactions induced by energetic photons (>10 MeV) have been widely studied by the nuclear physics community and some cross-sectional databases exist  [13] ,  [14]  for many materials. In this paper, the GEANT4  [8] ,  [9]  toolkit has been used to estimate the electronuclear cross sections.
The GEANT4 photonuclear and electronuclear databases were established using the different methods described in  [15]  and  [16]  which include the proposed parametric models. To simulate final states for electronuclear reactions, GEANT4 uses the Bertini cascade  [17]  at low energies and the FRITIOF precompound model  [18]  at high energies, where the photon is converted to π 0. In the energy range studied in this paper, the Bertini cascade is applied. GEANT4 has also been used to study the nature and the energy distributions of the recoil nuclei. This study has been performed over a wide energy range that goes from some megaelectronvolts up to some gigaelectronvolts. Fig. 3  shows some total electronuclear cross sections calculated with GEANT4 for different target materials (Z = 14, 22, 29, and 74).
A. Monte Carlo Toolkit The GEANT4 library (v10. 2)  [8] ,  [9]  has been chosen to simulate the transport of the incident electron and secondary particles generated in nanometric volumes. GEANT4 is a C++ toolkit assembled by an international collaboration for describing radiation interaction with matter. We have developed some applications to investigate the problematics presented in this paper. The calculations of the energy deposited by incident electrons, in small volumes having dimensions representative of sensitive volumes of devices of latest generation, have been performed. The MicroElec module of GEANT4  [22]  has been chosen to model the transport of electrons down to some electronvolts. The interest of this model is that electrons are generated and transported down to 16. 7 eV allowing creation (almost) in its entirely of the generated cascade.
We have developed two applications. The first one samples the population of recoil ions of electronuclear and photonuclear reactions (nature, direction, energy,. ). A database of the characteristics of the recoil ions has been established for several material targets. The second application simulates the energy deposited by the recoil particles in a sensitive volume. This task can be performed for nuclear recoil coming from nuclear reactions and secondary electrons produced by means of inelastic electron/electron interactions.
In addition, these measurements complement the characterization upon indentation of the SLBs with the already established F b procedure, as in one force-separation cycle both sets of data can be recorded. Most importantly, we evaluated the influence of the underlying substrate on the tube growing force, comparing the tube growth from deposited vesicles and SLBs (on silicon and mica). Following this approach, we were able to assess the contribution of the different substrates on the membrane mechanics, in a specific environment, and we prove that the SLB model represents an intermediate scenario between a free membrane (bleb) and a cytoskeleton supported membrane. This approach contributes to better understand and improve SLBs as models for biomembranes and may assist during the design of cutting-edge substrates and platforms to mimic different circumstances on the cytoskeleton-membrane arrangement.
Acknowledgements We acknowledge financial support from the  Generalitat de Catalunya (AGAUR ,  2017 SGR 1442 ),  Spanish Ministry of Economy and Competitiveness (MINECO)  and  FEDER  ( CTQ2015-66194-R MINECO/FEDER ) and  CIBER-BBN (FlexQSskin)  projects, and  Instituto de Salud Carlos III , through " Acciones CIBER ". The  Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBERBBN)  is an initiative funded by the  VI National R&D&I Plan   2008-2011 ,  Iniciativa Ingenio 2010 ,  Consolider Program ,  CIBER Actions  and financed by the  Instituto de Salud Carlos III  with assistance from the  European Regional Development Fund. We are also grateful to  Pau Gorostiza  and  René Fábregas  for fruitful discussions, and to  J. Antonio Duran  and  Blai Barberà  for technical assistance.
Endomicroscopic measurements at different laser pulse durations. Two fluorescent dyes, Rhodamine B (Sigma-Aldrich) and Fluorescein (Sigma-Aldrich), both dissolved in water, were used as standards to validate their spectral shapes and lifetimes values with theory or data found in literature, prior to tissue measurements. For each standard, a drop of aqueous dye solution yielding a concentration of 10 -6 M was placed on a microscope slide and positioned as shown in Fig. 7(a). For all measurements, the average laser power at the sample was 30 mW with a beam size of 0. 1 mm and the excitation wavelength was 800 nm. Measurements were taken at pulse durations ranging from 40 fs to 150 fs. The lifetime decays were fitted to a mono-exponential decay function using the FluoFit software from PicoQuant and the characteristic lifetime value of each dye was extracted.
For the ex vivo fluorescence measurements, the fixed tissue samples were placed in the sample holder, and the same measurement variables as used for the fluorescent dyes were employed; the mean power of 30 mW with the range of pulse durations for the 800 nm excitation. For each pulse duration, and for each region of interest (ROI) of the sample, the time-resolved fluorescence lifetime decay profiles were collected and analyzed using FluoFit software to extract the lifetimes of four endogenous fluorophores: NADH, FAD, Lipopigments, and Porphyrin I. The fluorescence spectra, on the other hand, were first smoothed and then spectrally decomposed using a custom MatLab script to recover fluorescence spectra of these individual fluorophores including Porphyrin II. Per measurement, five ROIs were selected.
Multi-modal imaging with the multiphoton microscope Instrumentation. A multiphoton imaging platform for small animals (PIMPA) comprising the multi-modal multi-photon microscope (Leica TCS SP8 MP, Leica Microsystems, Wetzlar, Germany) and controlled through Leica's acquisition software is the key instrument. The same Mai Tai Ti:Sapphire tunable laser source (690-1040 nm) equipped with an automated dispersion compensation unit was used. The maximum available power varied from 1. 8 to 2. 4 W for the different wavelengths. The laser pulse can be tuned between 70 fs and 300 fs at a fixed repetition rate of 80 MHz at the output of the cavity. A water-immersion objective was used (HCX IRAPO L 25x NA 0. 95), and the field of view at a fixed focal depth was 433 µm by 433 µm for a working distance of 1.
85 mW and 1. 96 mW when the excitation wavelength was 800 nm and 890 nm respectively. The two wavelengths, 800 nm and 890 nm, were chosen for optimal TPEF and SHG detection respectively. The same wavelengths were used for FLIM as well. Prior to ex vivo measurements, the power at the objective for different pulse durations was measured. An acquisition of two-photon imaging of the samples required 500 ms, while FLIM required an acquisition time of 2-3 s per sample and the excitation pulse duration varied from 120 fs to 340 fs. TPEF and SHG images were analyzed on ImageJ, while fluorescence lifetime data collected at 448 ± 20 nm and 520 ± 30 nm were combined and fitted to a two-exponential decay function using the Symphotomie software provided by PicoQuant. For each tissue sample, five ROIs were chosen for fluorescence lifetime analysis at each pulse duration.
Acknowledgements This work is supported by  PhysiCancer in Plan Cancer  with  "MEVO" and "IMOP" grant , by  CNRS  with the  "Defi instrumental" grant , by  Ligue Nationale Contre le Cancer (LNCC)  and the  Institut National de Physique Nucleáire et de Physique des Particules  ( IN2P3 ). This work was done in the PIMPA Platform partly funded by the  French program  " Investissement d' Avenir " run by the  "Agence Nationale pour la Recherche"  (grant " Infrastructure d'avenir en Biologie Santé- ANR-11-INBS-0006 ").
gsfc. nasa. gov/iaufwg/history/IAU_1982_resolution_c1. html). Therefore, FITS is one of the standard formats implemented in the VO. FITS data storage is compatible with the PDS archiving specifications so that FITS files can be embedded in PDS data sets. FITS format is supported by a large number of open libraries and software tools, developed in numerous languages. The reference C and Fortran library, CFITSIO (https://heasarc. gsfc. nasa. gov/docs/software/ fitsio/fitsio. html), is maintained by the NASA's High Energy Astrophysics Science Archive Research Center, and it comes with a number of interfaces for other languages  (C++, C#, Perl, Python, MatLab, etc. ). Independent libraries are available, for example, in JAVA, go, Python, R, IDL, and many other languages (a nonexhaustive list is available at https://fits.
gsfc. nasa. gov/fits_libraries. html). Software tools for visualization and analysis make use of those libraries or implement their own, having different levels of maturity and option completeness (see https://fits. gsfc. nasa. gov/fits_viewer. html). FITS is already capable of being used as a standard formatting for most data products commonly used in planetary surface investigations. In particular, the Multi-Extension FITS schema proposes an easy way to store inhomogeneous digital information  (reflectance, calibration data, vector, table data, etc. )  in the same file, each with corresponding metadata, as well as multidetector imagery (e. g. , from  HiRISE, McEwen et al. , 2007)  or hyperspectral cubes with geometry information (e. g. , from CRISM,  Murchie et al. , 2007 , or OMEGA, Bibring et al.
, 2005, instruments). FITS has been already chosen to distribute data from, for example, Hayabusa AMICA and NIRS cameras (http://darts. isas. jaxa. jp/planet/project/hayabusa/index. html), all Akatsuki cameras (http://darts. isas. jaxa. jp/planet/project/akatsuki/index. html; except the Lightning and Airglow Camera), and the Dawn Framing Camera (https://sbn. psi. edu/pds/archive/dawn. html) data. Some Rosetta data, from NAVCAM and OSIRIS cameras, are distributed in FITS format at the ESA Planetary Science Archive (http://psa. esa. int). In addition, many PDS3 data sets in the Small Bodies Node are archived and distributed as FITS files with PDS3 labels. However, solar system imagery data have been traditionally described using terrestrial-based geospatial descriptions and remote sensing formats.
This is particularly true for planetary surface investigations. Engineers and cartographers working in the first spatial missions were more familiar with Earth observation techniques and standards than the astronomy one. Furthermore, the standardization of the spatial references in FITS dates back to the 2000s, when planetary surface research habits had already been installed. In small bodies investigations, where astronomers and planetary scientists have worked together for longer, FITS format is already more popular. With the impressive increasing of raster data from planetary missions, the efficient automatization of data processing is an issue. Metadata, historically optimized for archiving, are not always ready for efficient processing. FITS metadata schema can be a solution to this problem.
To be more efficiently used in planetary surface investigations, FITS metadata must be thoroughly mapped to planetary geospatial concepts. Then, they must be extended in order to take into account the size of the reference body and orientation as standardized by the IAU Working Group on Cartographic Coordinates and Rotational Elements (WGCCRE). This group reports triennially  (Archinal et al. , 2011)  on the preferred rotation rate, spin axis, prime meridian, and reference surface for planets and satellites ensuring that cartographic endeavors are effectively comparable. In the framework of the Virtual European Solar and Planetary Access (VESPA; http://europlanet-vespa. eu/;  Erard et al. , 2018)  workpackage of the EuroplanetRI2020 (http://www. europlanet-2020-ri. eu/) project an extension to FITS metadata (GeoFITS) has been proposed (https://voparis-confluence.
Planetary Surface Proposed Convention To facilitate surface investigations, data taken of a planetary surface should be radiometrically calibrated and orthorectified (when topographic data are available) into a well-known map projection as required by Geographical Information Systems (GIS) applications. In general, GIS applications excel in planetary data set integration and interoperability even though some have historically been anchored to Earth's spatial description. Often, robust interoperability in GIS applications is achieved by using the Geospatial Data Abstraction Library (GDAL; http://www. gdal. org), released by the Open Source Geospatial Foundation. GDAL is essentially Earth and Space Science 10. 1029/2018EA000388 a format translation library written in C++ for geospatial raster and vector data and, fortunately, it also offers basic support for the FITS format, however missing a FITS metadata dictionary.
FITS WCS Keywords and Their Recommended Use in Planetary Surface Context In this section WCS FITS keywords are inserted in the planetary surface context. When possible, corresponding PDS4 and EPN-TAP definitions are added for archiving and distribution standardization purposes. 1. RADESYS. Name of the inertial reference frame with respect to which the coordinate system is defined. Standard FITS defaults this keyword to ICRS. This is applicable to planetary data too as long as the planetary coordinate system parameters, that is, the rotational elements, are defined with respect to ICRS. This is the case starting from the 2003 WGCCRE report  (Seidelmann et al. , 2005). Before the 1982 WGCCRE report  (Davies et al. , 1983)  the inertial system was FK4, after it was FK5. 2. EQUINOX. The value field contains the equinox in years for the celestial coordinate system in which positions are expressed.
Standard FITS defaults this keyword to J2000. This is applicable to planetary data starting from the 1982 WGCCRE report  (Davies et al. , 1983). Before 1982 the standard equinox was B1950. 3. WCSAXES. Number of axes in the WCS description. The value of WCSAXES may exceed the number of raster pixel axes. WCSAXES is, for example, generally set to 2 in two-dimensional rasters, it could be set to 3 if an additional time or filter dependency is added to the coordinate description. 4. WCSNAME. Name of world coordinate descriptions (e. g. , body-fixed rotating-ocentric-ographic, nonrotating, inertial). EPN-TAP provides similar information through the spatial_coordinate_ description parameter. 5. CRPIXn. Location of a reference point along axis n, in units of the axis index. The reference point value do not need to lie within the actual data array.
7. CRVALn. Value of the coordinate specified by the CTYPEn keyword at the reference point CRPIXn. 8. CDi_j. The ij linear transformation matrix (rotation, skewness, scaling) defining the intermediate world coordinates. Earth and Space Science 10. 1029/2018EA000388 This keyword will assure compatibility with standard GIS softwares. Note. GIS = Geographical Information Systems. a Note that International Astronomical Union Working Group defines a mean radius for each Solar System body. When this Mean Radius is used in projection definition, the three keywords A_RADIUS, B_RADIUS, and C_RADIUS, must be set to the same value of the defined Mean Radius. 9. PCi_j. The ij linear transformation matrix (rotation, skewness) defining the intermediate pixel coordinates (to be used with CDELT keywords). 10.
EPN-TAP standard also provides with a target_name parameter. Notice that PDS4 and EPN-TAP also ask for a target_type attribute, which must be specified from an enumerated list. 15. ORIGIN. It contains string identifying the organization or institution responsible for creating the FITS file. No clear correspondence for this reserved FITS keyword is available in PDS4. This is because PDS4 is focused on referencing the authors of the data collection and its metadata curation, not the data producer itself. Yet the content of the ORIGIN keyword can be inserted in a PDS4 comment. 16. REFERENC. It contains a character string citing the bibliographic reference where the data are first described. It is recommended that either the Astrophysics Data System bibliographic databases (http://adswww. harvard.
TAB projection is implemented in the Calabretta WCSLIB (http://www. atnf. csiro. au/people/mcalabre/WCS/wcslib/), available in all major linux distribution. As an example of nonprojected planetary data we have converted in FITS format some data acquired by the imaging spectrometer OMEGA on-board of Mars Express. OMEGA unprojected and uncalibrated data (level1b) are distributed by ESA Planetary Science Archive  (Besse et al. , 2018). Their structure is described in the OMEGA Experiment Archive Interface Control Document (ftp://psa. esac. esa. int/pub/mirror/MARS-EXPRESS/ OMEGA/MEX-M-OMEGA-2-EDR-FLIGHT-V1. 0/DOCUMENT/EAICD_OMEGA. PDF). OMEGA rasters are equally sampled all over the field: we use them to exemplify TAB description without indexing. In addition, as geometrical description depends on the observation filter, this allows us to distribute a file for each filter, containing science and geometry data.
The spectral cubes have been converted from Band Interleaved per Line to Band Sequential in order to make them easily understandable when visualized using standard FITS viewer (as ds9 in Figure  2 ; the output result can be downloaded at the address https://github. com/cmarmo/convertofits/releases/download/v1. 0-beta/orb0413_1. IR1. fits. gz together with the python script used for conversion https://github. com/cmarmo/convertofits/blob/master/omega2fits. py). The wcsware tool (available in the wcslib-utils package in Fedora distribution, in the wcslib-tools in Debian) had been run on the output file, validating the WCS structure and checking the ability to convert to (wcsware -w) and from (wcsware -x) pixel and planetary surface coordinates.
Akatsuki Imaging Data The Venus Climate Orbiter Akatsuki(http://akatsuki. isas. jaxa. jp/en/) is a JAXA spacecraft dedicated to the study of the Venus atmosphere. Akatsuki imaging data are already distributed in FITS format. Geometry information is distributed in two different cubes of data, containing, respectively, values at the center of the pixel and at the lower left corner of the pixel. Tabular coordinate representation allows us to gather geometry in one table together with the described raster. In addition to that, in Akatsuki images Venus is sometime far from completely filling the field: tabular representation avoids to store unnecessary data. In that case, coordinate indexes are necessary to identify which pixels contains the spatial information (The output result can be downloaded at the address https://github.
com/cmarmo/convertofits/releases/download/ v1. 0-beta/ir1_20160415_070351_097_l2b_v10_out. fit. gz together with the python script used for conversion https://github. com/cmarmo/convertofits/blob/master/akatsukil2b. py). Again, we used wcsware to validate the WCS structure and to test pixel to world/world to pixel coordinate conversion. Even though TAB projection is not fully implemented in FITS visualization tools, this representation has the advantage to store the detector geometrical information together with physical quantities measured by the detector itself in a standardized way.