dataesr/scientific-paragraphs-categorization huggingface dataset:
Comparing the ANTA to the widely used algorithm published by  Dogliotti et al. (2015) , higher detail was resolved in the nearshore area of Herschel Island Qikiqtaruk and shows the potential of this tuned algorithm for arctic nearshore waters. In this study, the first turbidity-reflectance relationship specifically calibrated to Arctic nearshore environments is presented. It can be applied to a series of operating and historic satellite sensors. It is shown that improvements were made for identifying turbid filaments and sediment pathways along-and offshore when comparing it to globally used turbidity algorithms. The applicability of the ANTA in other Arctic nearshore environments was also clearly demonstrated, however, careful verification of the results is recommended due to scarce validation dataset availability.
Acknowledgments USGS and  NASA  are acknowledged for Landsat imagery. ESA is acknowledged for Sentinel 2 and 3 imagery. We thank  Bernard Gentili  for his help when processing TriOS RAMSES data and  Maeve McGovern  for his involvement in field and lab work in Adventfjord. We acknowledge the support of  Deutsche Forschungsgemeinschaft (German Research Foundation) and Open Access Publication Fund of University of Potsdam.
Funding This publication is part of the  Nunataryuk  project. The project has received funding under the European Union's  Horizon 2020 Research and Innovation Program  under grant agreement no. 773421. K. P. K. was financially supported by a Ph. D. stipend by the  University of Potsdam  ( PoGS Potsdam Graduate School ) and a short-term stipend by the  German Academic Exchange Service (DAAD). I. N. was funded by the  HGF AI-CORE ,  ESA CCI + Permafrost , and  NSF Permafrost Discovery Gateway (NSF  Grants  #2052107  and # 1927872 ) projects. BJ was funded by the  European Space Agency (ESA)  as part of the  Climate Change Initiative (CCI)  fellowship ( ESA ESRIN/ Contract No. 4000l3376l/2l/I-.
Temporal Aspects of Sounds Unit repertoires are not easy to create, especially because of the variabilities of the unit features, even for repetitive units emitted by the same singer. Therefore, manual annotations of acoustic datasets, even by experts trained to detect and classify units, showed inter-annotator variability for different reasons, and in particular due to the subjectivity of the analysis  (Leroy et al. , 2018). The automatic approaches clearly help to better describe these songs. A very large panel of methods were proposed, for example, based on the information entropy  (Suzuki et al. , 2005) , on a threshold on the Fourier coefficients  (Mellinger, 2005) , on the extraction of the edge contour  (Gillespie, 2004) , on the analysis of the mel-frequency cepstral coefficient (MFCC)  (Pace et al.
Data Collection In their study of humpback whale songs,  Payne and McVay (1971)  conclude that "the function of the songs is unknown. " However, because singers were recorded during breeding seasons, it was firstly assumed that songs could be linked with mating activities, as interactions between females and males, and/or between males. Up to now, the role of these songs is not totally clear and still under investigation. It is the same for the time structure and the meaning of its evolution over the years. Therefore, acoustic playbacks on humpback whales should be done with high caution. In any case, this kind of experiment has to be done by experts, with marine mammal observers (MMOs) on boats and following the rules of protection and respect of the cetacean species. Therefore, this project done during the humpback whale breeding season in July-August 2018 off La Réunion Island (Indian Ocean) followed strict ethics rules, especially based on the charter of responsible approach of marine mammals  (Region Réunion, 2017).
Therefore, from each detected unit, a total of 74 acoustic features were automatically computed from the time and spectral representations (see the mathematical definition of these features in  Malfante et al. , 2018)  (Table  3 ). All implementations were taken from the Librosa toolbox  (McFee et al. , 2020) , the audio_analysis software package  (Lerch, 2012) , and the pyaudio analysis toolbox  (Giannakopoulos, 2015). The t-distributed stochastic neighbor embedding (t-SNE) was implemented to enable the representation and visualization of the feature space (van der Maaten and Hinton, 2012) using the Scikitlearn Python package  (Pedregosa et al. , 2011). The aim of using t-SNE was to explicitly show the similar and dissimilar sounds from the CSEs and the units based on these acoustic features (Table  2 ).
-For underwater gesture sensing, two wrist-worn inertial measurement units [9-degree-of-freedom (DoF) inertial measurement unit (IMU) Bitalino R-IoT with wired serial connection to the computer, 100 Hz] and one underwater tablet (Valtamer Alltab 4. 0 with wired connection to the computer). The two IMUs allow to finely capture continuous gestures via the built-in accelerometers, gyroscopes, and magnetometers. As such, arm posture (orientation angles), attacks (impulses), and slow arm or forearm movements can be used to initiate and continuously modify sounds, while the tablet with its touchscreen surface allows for preselection of sound classes. This interface can be played underwater by a diver-musicianexperimenter such that a gesture can be associated with a specific type and profile of sound that is produced by the sound synthesis software.
Next, we present our refined continuous ocean sediment ε Nd distributions, including ε Nd at the continental margin and across the sea floor (Section 3). We then provide our proposed combination of both datasets and include a discussion about the final boundary conditions, acknowledging the limitations in our approach, and propose the use of these gridded maps as a first step towards a deeper interrogation of the sources and sinks of oceanic Nd, including the possibility of a benthic flux (Section 4). The final ε Nd maps clearly highlight where there is a wealth and conversely a dearth of Nd measurements, and where those measurements may or may not be representative of the wider oceanographic setting, thereby providing a useful guide for future data acquisition efforts. Furthermore, our methods are reproducible, and we provide full documentation of the protocol to facilitate updating the distributions with new measurements.
Updated database and compilation of published ε Nd An extensive and updated (relative to  Jeandel et al. , 2007)  database of ε Nd values measured on both terrestrial and marine sediments was initially obtained from  Blanchet (2019). This database was built incorporating published Nd values from an extensive literature review, external contributions and retrieval from the SedDB database and includes 1,529 observations. We then identified areas where known additional published data could be added to the database and where observational data was spatially limited, having the potential to impede/bias interpolation across the globe. Notably, we prioritised detailed publications with numerous observations taken around key regions of deep-water formation in the North Atlantic and addressing data scarcity, particularly in the Pacific, Indian and Southern Ocean.
Through co-author contribution and a collective community effort to put forward relevant published datasets, the initial database was expanded to reach a total of 5,107 data points, including 2,671 present day and Holocene rock, river and marine sediment observations, thus capturing a much greater level of spatial detail in the overall larger quantity of constituent data (Fig. 1  and Supplementary Table  S1 ). This was achieved first from extensive literature review, adding relevant observations particularly covering the Southwest Atlantic, the Bering Sea, the Southern Ocean, and West Africa. We then added further detail in the Southern Ocean, focusing along the Antarctic coastline, notably in West Antarctica, the Antarctic Peninsula and surrounding the Ross Sea  (Cook et al. , 2013; Mikhalsky et al.
, 2013; Mikhalsky et al. , 2006; Pierce et al. , 2011; Roy et al. , 2007; Simões Pereira et al. , 2018; van de Flierdt et al. , 2008; Walter et al. , 2000). This Southern Ocean compilation also includes a collection of 34 new (i. e. hitherto unpublished) measurements; see Supplementary Text S1 and Table  S2  for information on the collection/measurement techniques. Our compilation of published and new Southern Ocean data is focussed on marine detrital measurements that could be used as an indicator of the ε Nd signal eroded from neighbouring continental rock and also provides measurements from sediments directly in contact with seawater. We obtained even more modern and Holocene detrital measurements from sediments in the Arctic, eastern North Atlantic, West Atlantic, Gulf of Alaska and the Indian and East Pacific Ocean from the global compilation of detrital ε Nd that accompanied the large-scale acquisition of seawater and geologicarchive ε Nd performed by  Tachikawa et al.
(2017). Additionally, we include data from a recent global core-top compilation published by  Du et al. (2020) , whom investigated recent changes to Global Overturning Circulation from authigenic and sedimentary ε Nd records, covering particularly the North-West and South-West Atlantic, the Indian and Central Equatorial Pacific Ocean. Finally, we included marine pore fluid ε Nd from three sites in the eastern North Pacific  (Abbott et al. , 2015b; Abbott et al. , 2015a). The database, including the full dataset of ε Nd and associated metadata table is reported in Supplementary Table  S1  and the database will be stored on the GFZ data repository (see Data Availability).
Data selection The primary aim of this first phase of work is to define as accurately as possible the modern isotopic signatures of the continents surrounding the oceans and continental margins on a global scale. To achieve this aim, we filtered the entries in our new, comprehensive database (Section 2. 1) to only include samples from the Holocene (specifically 11. 7 ka to present) as well as the New Southern Ocean samples, which in some cases may be older, yet still provide appropriate ε Nd for our study (as explained in Supplementary Text S1). We include present day (P) samples defined from 1 ka to present or from the upper 1cm/top-core sediment, and Holocene/Marine Isotope Stage 1 (MIS1) samples ranging from 11. 7 -1 ka. This is because we are most confident that the measured values falling within these depositional age ranges are representative of the modern continental ε Nd interacting with seawater.
This yielded a total of 1,078 observations, which came from three broad sample types: river sediment samples, which deposit on the continental shelf and slope; Holocene marine sediments collected along given margins; and geological material outcropping close to an oceanic margin expected to be weathered. We explain this choice in more detail in Supplementary Text S2. All the discrete continental data extracted through this filtering process are reported in Supplementary Table  S3  and are displayed in Fig. 2a. Cook et al. , 2013; Mikhalsky et al. , 2013 , Mikhalsky et al. , 2006; Pierce et al. , 2011; Roy et al. , 2007; Simões Pereira et al. , 2018; van de Flierdt et al. , 2008; Walter et al. , 2000. White crosses: this study). We acknowledge the potential for bottom ocean currents to transport fine-grained sediments to sites distal from their sources  (Gorsline, 1984) , and this may have a local/regional control on the ε Nd passed on to the overlying water column  (Jeandel et al.
3a   (Blaser et al. , 2016; Du et al. , 2016; Wilson et al. , 2013). It is hypothesised that detrital sediments interact with pore water on long timescales (hundreds to thousands of years), in large part compensating for slow reaction kinetics and therefore enabling detrital sediment to exert a significant influence on the ε Nd of pore water  (Du et al. , 2016). Furthermore, detrital sediments provide a direct measurement of the sediment ε Nd in contact with pore water, albeit in the absence of quantifying exactly the reactive Nd phases. We therefore filtered the updated Nd database to identify marine core-top pore water and detrital sediment ε Nd and used this compilation to produce a best estimate of the global distribution of seafloor ε Nd. Similar to the continental compilation, only core-top sediments (i.
For example,  Bayon et al. (2002)  presented a robust chemical procedure for separating the detrital material into decarbonated sediment residuals and specific detrital size fractions, resulting in reduced or no loss of specific phases. Within our database, decarbonated and detrital fraction observations are much more abundant, and as such, these samples are also deemed suitable for inclusion in this dataset alongside bulk sediment digests and pore-water samples, allowing for a more global representation of direct ε Nd measurements covering various seafloor lithologies. We recognise that under current practical constraints, there is no unique/ideal solution for our sample selection. To use only pore water and bulk sediment fractions would limit the number of observations to too few for producing a useful broad scale representation of the seafloor ε Nd source.
Interpolation of seafloor ε Nd map Once an extensive compilation of suitable discrete detrital and pore water ε Nd observations were obtained, the points were then interpolated globally to produce a spatially continuous ε Nd signature of seafloor sediments in contact with bottom water. Again, the aim here is to broadly characterise the signature of seafloor sediments, providing a best estimate of global ε Nd based on the available [and limited] dataset. Our map thus may not capture localised features and variations. Adopting the assumption that dominant seafloor lithology types at least partially describe the major sedimentary source and characteristics of detrital ε Nd , we used a high-resolution gridded map characterising the major lithologies of seafloor sediments in the world's ocean basins  (Dutkiewicz et al.
2b , but can be accessed by downloading the high-resolution vector datasets accompanying this study (Supplementary Dataset S1). Australia  (Ehlert et al. , 2011). In our continental ε Nd representation, north-eastern and eastern Australia and Tasmania display a relatively homogenous signal with Cenozoic and Mesozoic rocks dominating, and thus yielding values of around -8 to -6. The presence of Proterozoic to Archean units in north-western Australia and southern Australia provide two relatively spatially constrained regions of quite unradiogenic ε Nd  (-20 to -15). Antarctica displays a high degree of spatial heterogeneity, this heterogeneity has been observed previously in studies documenting the variability of Antarctic sediment sources using 40 Ar/ 39 Ar ages and bulk < 63 μm Sm/Nd isotopes  (Roy et al.
However, we note that the deep Atlantic Ocean is the most data sparse region in our database, especially in the open South Atlantic. Further data acquisition in this area could alter our results. The Mediterranean region is data rich, due to the detailed wealth of published observations gathered by  Blanchet (2019)  in addition to detrital measurements accompanying the data presented by  Tachikawa et al. (2017). The Mediterranean Sea is mainly characterised by an unradiogenic sediment signal of -11, consistent with the majority of observations here, with an exception being in the east of the basin, located north of Egypt, at the mouth of the Nile River. Here, multiple observations range from -5 to -2 and the area is broadly characterised by an ε Nd signal of -3. These higher values trace the delivery of radiogenic sediments by the Nile Rivers to the Eastern Mediterranean from Cenozoic volcanic plateaus of the Ethiopian Highlands  (Fielding et al.
Combined representation of the ε Nd signal at the sediment-water interface In this study, we have presented an updated compilation of current measurements of a range of possible sources of Nd isotopes to the ocean, and we have used this new synthesis to produce a spatially continuous dataset of seafloor and continental margin ε Nd. In so doing, we provide suitable data products to facilitate a step-change in our ability to address outstanding questions concerning marine Nd cycling (e. g. through new conceptual or three-dimensional ocean modelling) and a methodology for reproducing/adapting our results. The possible existence of a benthic flux of Nd to overlying waters, or simply a less spatially constrained boundary exchange at the sedimentwater interface than has previously been adopted in most modelling studies  (Arsouze et al.
, 2009; Arsouze et al. , 2007; Gu et al. , 2019; Rempfer et al. , 2011)  brings forth the requirement for global mapping of seafloor ε Nd. We undertook this exercise, utilising all of the available data that we are aware of at the time of writing to produce our final, spatially continuous distribution (Fig. 3b ). However, we acknowledge that we may have missed some sites, and we hope that when spotted, others will contribute these to the continually evolving database first published by Blanchet (2019) (see Data Availability). There are most certainly underrepresented regions in our compilation of measurements notably, huge swathes of the open Atlantic Ocean, deep Pacific, and southern Indian Oceanwhich we hope may become better represented in time (notwithstanding the practical difficulties associated with very deep ocean sampling), thus enabling a more thorough capturing of the spatial distribution of seafloor ε Nd.
Furthermore, as research continues, it may become more practical to further filter the available data to use only the most suitable sediment sources (ultimately, pore waters or specifying precisely the labile Nd fractions; see discussion in Section 2. 3. 1, above). Nonetheless, it is a testament to the hard work of the wide research community that so many observations do already exist, enabling us to produce our best estimate of seafloor ε Nd from these data. The final step is to bring the two data products together, and Fig. 4  shows our combination of the continental margin and seafloor ε Nd distributions. This dataset can be considered to be our best estimate of the global distribution of ε Nd at the entire sediment-water interface to date. To produce this final characterisation of global seafloor sediment ε Nd distributions, we used the continental ε Nd map extrapolated to where sediment thickness ≥ 1000 m, and the remaining sediment regions are represented using the seafloor ε Nd map.
proximity to the East Pacific Rise). We were able to achieve this improvement by refining the spatial variability around Antarctica compared to earlier work using a larger compilation (as discussed Section 4. 2) and by including additional marine detrital observations in the South Pacific. The presented seafloor ε Nd maps therefore provide a considerable improvement upon previous simplified linear extrapolation methods. Our key ambition in this regard is to enable users ease of access to appropriate boundary conditions and thus to facilitate future improved model ε Nd representation. By doing so, we hope to have empowered the community to progress our understanding of sediment-water interaction of Nd and further to build upon this established database, incorporating further understanding of the sediment ε Nd distributions and its role in governing the Nd characteristics of seawater.
Modelling applications and future work We envisage that one of the major applications of our new ε Nd distributions will be for designing/implementing the boundary conditions required for Nd-isotope models. Such models could range in complexity from relatively simple box-models to full complexity general circulation models. What all have in common, is the need for pre-defined Nd sources. With the emergent (but still debated) benthic flux hypothesis, future models will require knowledge of the ε Nd of seafloor sediment to be able to constrain a benthic flux and model the non-conservative processes involved in marine Nd cycling. The new datasets presented in this study are therefore useful for further modelling applications like the research undertaken by  Pöppelmeier et al. (2020b)  in exploring sedimentary Nd sources.
5 • × 0. 5 • ) gridded maps of the continental and seafloor detrital ε Nd are provided in Supplementary Dataset S1 and S2, the maps are also available in vector format, and so can be accessed at different spatial resolutions to suit specific user applications. These observations thus form the basis of exploring the benthic flux hypothesis in numerical models in order to understand and quantify its potential role in controlling the marine distribution of Nd isotopes, working towards solving the 'Nd paradox'. These data products have been designed to facilitate more modelling and sensitivity studies, with a future aim of coordinating a Nd isotope enabled model intercomparison study. In closing, appropriate to current understanding of sedimentary Nd sources, we chose to represent the dominant ε Nd signal using lithology and sediment types to inform the origin, age distribution and environment of sediment particles in contact with the ocean, as a first order approach to quantifying the sediment reactive Nd signal.
Summary and conclusion The important role of sediment-water interaction in governing oceanic Nd sources and sinks is widely accepted. However, the detail of these processes remain some of the least understood aspects of marine Nd cycling. The updated compilation of published and new sedimentary ε Nd measurements from the continental margins and deep ocean presented here build upon the work of  Jeandel et al. (2007) , extending the remit of the previous study to include measurements from pore waters and deep seafloor detrital samples in order to improve the characterisation of global ε Nd distributions at the entire sediment-ocean interface. Thus, our new continuous, global, gridded datasets provide the opportunity to explore the non-conservative sedimentary processes that control global Nd cycling.
Acknowledgements SMR was funded by the  Natural Environment Research Council (NERC)   SPHERES Doctoral Training Partnership  (grant number:  NE/ L002574/1 ). We thank  April Abbott ,  Jianghui Du  and  Andy Ridgwell  for informative discussions while undertaking the work. We are grateful to two anonymous reviewers for prompt and helpful comments that improved the manuscript, and to  Karen H. Johannesson  for swift editorial handling.
Data availability The presented database of ε Nd measurements, along with our global, gridded datasets and all input files for reproducing the maps are available at: https://doi. org/10. 5518/928. The ε Nd database will also be made publicly available on the GFZ data repository (https://datase rvices. gfz-potsdam. de/panmetaworks/showshort. php?id=escido c:4094893). Please contact Cécile Blanchet (blanchet@gfz-potsdam. de) for additional data. In addition to the ε Nd data, the input files include the Continental Geological Base Map, as used by  Jeandel et al. (2007) , which was an earlier version obtained from http://pyroxene. ens. fr/spip labocnrs/spip. php?rubrique67; GlobSed: Global Sediment Thickness Map (currently also available from http://earthdynamics. org/dat a/GlobSed); and the Seafloor Lithology Map (currently available from ftp://ftp.
The results concluded that the heterogeneity of thin beds in lithofacies is dependent on porosity and permeability with input dataset. According to the final model, cross-bedding sandstone (CBS), hummocky cross-stratified sandstone (HCSS) and trough cross-bedding sandstone (TCBS) show good reservoir quality due to high porosity ranging from: 25. 6% to 20. 4% and, 19. 3%e14. 5%, and permeability ranging from: 74. 03 mD to 66. 84 mD and, 64. 86 mD to 21. 01 mD. In contrast, massive to weak laminae sandstone (MWLS) and bioturbated sandstone (BS) show fair to poor reservoir quality, caused baffling of surrounding mud sediments in the reservoir lithofacies. Results also revealed that LiDAR based VOM with petrophysical properties can significantly reduce the risk and minimize the cost of reservoir modeling in petroleum industry.