dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2019 ; O'Neill et al. , 2017 ; Tewarie et al. , 2019a ; Vidaurre et al. , 2018a ; Zhu et al. , 2020 ). According to self-paced motor task, results showed that all SS methods have successfully extracted one or more significant network that involve strong connectivity between sensorimotor regions ('Mot'). For HCP data, a similar sensorimotor network was revealed among significant components in all SS methods except for SOBI, PSAUD and Kmeans. Integrated regions in this network mainly include nodes from central and parietal gyrus. The sensorimotor network is strongly coherent with the task  ( Melnik et al. , 2017 ; Yousry, 1997 )  since it requires both movement (through button press or hand movement) and tactile response (as the subject will feel the button or fingers tape). The effect of right-handedness of all participants of self-paced dataset is also revealed by the presence stronger implication of sensorimotor nodes from the right cortex relative to the left one as revealed by the sphere sizes and connections in Fig.
3. It is noteworthy to mention the existence of a network that highlighted significant connections in the visual lobe in JADE for self-paced button press task and most SS methods for HCP task. This network was previously noticed by Oneill et al. studying the same button press task  ( O'Neill et al. , 2017 ). This can be interpreted as a cross modal synchronization between visual and sensorimotor cortex as previously studied  ( Bauer et al. , 2020 ). Regarding temporal evolution, it is clear that all networks modulate significantly with the exact button press time for self-paced task. Differently, the temporal variation related to HCP motor task takes an oscillatory shape, which was also reported by other studies dealing with the same dataset  ( Vidaurre et al. , 2018a ; Zhu et al. , 2020 ).
, 2017 )  that used FastICA algorithm and little difference was observed for the overall results. Second, we should point that not all these components are necessarily essential, especially in the case of simple tasks as motor tasks. To this end, we followed the approach of the null distribution based on sign flipping algorithm  ( Hunt et al. , 2012 ; O'Neill et al. , 2017 ; Winkler et al. , 2014 ; Zhu et al. , 2020 )  to select only components whose temporal dynamics significantly modulate with the task. In this way, we ensure that brain dynamics relative to the studied behavioural tasks can be summarized and described by the retained components through an automatic way that allows us to objectively compare the SS methods performance. In addition, the fact that this technique is a purely data-driven procedure that does not require any prior hypothesis or conditions manipulation makes it likely adapted to the specific examined dataset.
Future works should therefore investigate more about this methodological approach in the framework of cognitive tasks, in addition to resting state experiments. Also, it is crucial to seek more methods to use or combine with the applied technique in order to have more robust basis for significant components selection. It is noteworthy to report that null distribution-based technique was applied uniformly for all SS methods, thus our main objective of comparison was built on a unified evaluation framework. Third, we used the same pipeline supported by the previous studies dealing with the same dataset (cortical parcellation, source reconstruction, functional connectivity metric and source leakage correction, frequency bands and sliding window settings)  ( Kabbara et al. , 2019 ; O'Neill et al.
For this reason, we followed the work of  ( Tewarie et al. , 2019b )  to estimate dynamic functional connectivity by taking sample by sample time series rather than windowed aggregated samples using the Instantaneous Amplitude Correlation (IAC). This high temporal resolution measure of FC has shown great sensitivity to genuine fluctuations in functional connectivity applied in the same context of our study. It would be interesting to test data-driven windows approach in this context using the recurrence plots of the amplitude envelopes as in  ( Tewarie et al. , 2019b )  instead of averaging trials in dataset 2 to reduce heavy dFC matrices. It could be also tested against fixed sliding window approach as for datasets 1 and 3. Concerning frequency bands, it was crucial to preprocess each dataset in its appropriate bandwidth.
The SOBI and Kmeans algorithms showed the weakest performance among tested methods. CoM2, PSAUD and PCA showed promising results in working memory task, revealing the formation and dissolution of multiple networks that relate to semantic processing, pattern recognition and language as well as vision and movement. At the subject level analysis, ICA methods using high statistical order (JADE, InfoMax, CoM2 and PSAUD) outperform other methods. Our main message is that researchers should be aware to select the appropriate SS methods and other related parameters (epoch length, task complexity and dataset size) when analyzing dynamics of behavioral tasks.
Acknowledgement This work was financed by the  Rennes University and the Institute of Clinical Neuroscience of Rennes  (project named EEGCog). The study was also funded by the  National Council for Scientific Research (CNRS) in Lebanon. The authors would also like to thank the the  Lebanese University , the  Lebanese Association for Scientific Research (LASER)  and  Campus France ,  Programme Hubert Curien CEDRE (PROJECT  No. 42257YA ), for supporting this study.
Code availability Codes supporting the findings of this study are available in the link ( https://github. com/judytabbal/dynbrainSS. git ). All analysis codes necessary to produce the results here were performed in MATLAB software, using FieldTrip Toolbox http://www. fieldtriptoolbox. org for data segmentation, filtering and source reconstruction steps, EEGLAB toolbox for some SS methods as JADE, InfoMax and SOBI and other MAT-LAB implemented functions as detailed and provided in the previous link. A graphical user interface is made freely available allowing other researchers to test the methods on our (or their) simulated and real data.
Data analysis Faunal composition for a similarity analysis was compiled from literature data and direct observations for the fossil assemblages Castillo, La Venta, Makaraipao, Castilletes marine, Loyola-Mangan, Rio Acre, Solimões-Pebas, Urumaco, Utuquina, Pirabas, Cantaure, Ituzaingo, Rio Yuca, Fitzcarrald, and Contamana (Supplementary Table  S1 )  (Cione et al. 2000 (Cione et al. , 2009;; Lundberg et al. 2010; Bogan et al. 2012; Aguilera et al. 2013a,b; Cione & Azpelicueta 2013; Tejada-Lara et al. 2015; Antoine et al. 2016; Azpelicueta & Cione 2016; Ballen & Moreno-Bernal 2019). We compiled an initial set of Miocene fossil fish fauna and later limited the analysis to those faunas that had a sampling size equal to or larger than the one herein described, in order to avoid uncertainty due to low sample size.
Therefore, the faunas used in the analysis were reduced to La Venta (12. 0 Ma), Makaraipao (15. 0 Ma), Rio Acre (7. 9 Ma), Urumaco (8. 0 Ma), Ituzaingo (7. 5 Ma), Fitzcarrald (12. 8 Ma), and Contamanta (11. 0 Ma). An analysis with the full dataset provided a similar pattern as described here (Supplementary section S1). Modern faunal similarity was measured using a continental-wide database of curated, voucher-based presence/absence records of fish species in each of the hydrographic regions of South America  (Dagosta & Pinna 2019). Faunal similarity and resampling nodal support values were measured using the binary method with average distance as implemented in the pvclust package v. 2. 2-0  (Suzuki et al. 2019 ) in R v. 3. 4. 4 R Core Development Team (2018). We chose the binary method because we have presence/absence instead of abundance data and because of the asymmetry with respect to absences.
Resampling nodal support measures AU and BT were calculated with the pvclust::pvclust function; although both measures are reported, AU are more reliable than BT as a measure of relative support in hierarchical clustering  (Suzuki et al. 2019). The same method of clustering was applied to both the Miocene and modern datasets. Additional correlations between 5 similarity, geologic age, and geographic proximity were calculated using the packages vegan and sf  (Pebesma 2018; Oksanen et al. 2019 ) (Supplementary Section S3). Extant occurrences were downloaded from the SpeciesLink and GBIF databases (DOI links https://doi. org/10. 15468/dl. 6glxkb, https://doi. org/10. 15468/dl. d33vwn, https://doi. org/10. 15468/dl. 67lq6f, and https://doi. org/10. 15468/dl. 9aryay) and specific data cleaning procedures carried out (Supplementary section S2).
Mapping was carried out in QGIS v. 3. 4. 12 (QGIS Development  Team 2019). Image edition and processing was carried out in GNU image manipulation program (GIMP) and Inkscape. The raw data and scripts are available both in zenodo (doi:XXXXXXXXXXXX) and https://github. com/gaballench/makaraipao. Preserved crown with median portion of middle pterygoid ridge approaching.
Faunal similarity Continental fossil faunas of Miocene age have long been recognized in South America. Earlier studies based on the fossil mammal assemblage have consistently shown more similarity between the Acre and Urumaco faunas, whereas the older La Venta fauna has been shown to have a distinctive mammal fauna  (Cozzuol 2006; Latrubesse et al. 2010; Carrillo et al. 2015). Cozzuol (2006)  found the Acre and Urumaco faunas to be most similar to each other than to the Mesopotamian and the La Venta fauna, while the latter was found to be the most dissimilar of all. Carrillo et al. (2015)  suggest complex faunal patterns in time and space on the basis of more numerous faunal units and a richer dataset than the earlier study by  Cozzuol (2006). Their analyses indicate that the La Venta fauna clusters with the Fitzcarrald fauna and to a lesser degree with Collon Curá, while Urumaco is most similar to Acre and the Mesopotamian in agreement with  Cozzuol (2006).
ACKNOWLEDGEMENTS We thank  Jaime Escobar  and  Natalia Hoyos  ( MUN, Universidad del Norte ) for allowing access to fossil specimens from the  Castilletes Formation  and also for their hospitality during a visit to their institution. Carlos DoNascimiento (IAvH) and  Saúl Prada  (MPUJ) granted access to collections under their care. John Lundberg  and  Mark Sabaj  ( ANSP ) allowed us to study the ichthyological collections under their care. The  Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)  is acknowledged 20. CC-BY-NC 4. 0 International license available under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (which this version posted June 21, 2021.
Methods. We implemented a temperature-gradient model to interpret the disk IR continuum emission, based on a multiwavelength dataset comprising a broadband spectral energy distribution (SED) and VLTI H-, L-, and N-bands interferometric data obtained in low spectral resolution. Then, we added a ring-like component, representing the carbonaceous L-band features-emitting region, to assess its detectability in future higher spectral resolution observations employing mid-IR interferometry. Results. Our temperature-gradient model can consistently reproduce our dataset. We confirmed a spatially extended inner 10 au emission in Hand L-bands, with a homogeneously high temperature (∼1700 K), which we associate with the presence of stochastically heated nano-grains. On the other hand, the N-band emitting region presents a ring-like geometry that starts at about 10 au with a temperature of 400 K.
6 and 11. 3 µm and suggested that the emission at 8. 6 and 11. 3 µm extends out to larger radii than the N-band dust continuum emission. Boutéraon et al. (2019)  spatially resolved the ∼ 3. 3 µm and ∼3. 4 µm features down to a distance of 30 au from the central star. Those two features originate from C-H bonds associated with aromatic rings and aliphatic chains, respectively. They also showed that the 3. 3/3. 4 µm band ratio does not change significantly with the distance from the star. Since aliphatic grains are expected to be more fragile against UV processing (e. g. ,  Acke et al. (2010) ), that suggests a replenishment and a regeneration of those grains to maintain the strength of the 3. 4 µm band, relative to the 3. 3 µm band, as we approach the star. Based on a multiwavelength dataset, the aim of our study is to provide a consistent view on the radial structure, down to the au-scale, and basic physical properties of the material responsible for the IR continuum emission in the inner disk region around HD 179218.
Moreover, we aim to provide first constraints on the spatial distribution of aromatic carbon nano-grains, through the 3. 3 µm feature, in the inner 1-10 au region. Finally, in the perspective of future MATISSE observations in medium spec- tral resolution (R ∼ 500), synthetic L-band visibilities are produced to assess further the feasibility of detection of carbonaceous nano-grains in the 1-10 au region. The paper is organized as follows: Section 2 summarizes the new observations with VLTI/MATISSE which complement the existing data obtained with two other VLTI instruments, MIDI and PIONIER. Section 3 describes a geometrical modeling of the MATISSE data, followed by a temperature-gradient modeling of our multiwavelength dataset. In Section 4 we investigate the presence of the carbonaceous features in the obtained low spectral resolution MATISSE data and provide the limits on the detection of carbonaceous nano-grains based on synthetic medium spectral resolution MATISSE data.
MATISSE observations One snapshot of HD 179218 in low spectral resolution in L-band was observed with MATISSE on March 24, 2019 with the small AT quadruplet giving 6 simultaneous uv points. The corresponding baseline lengths ranges from 7 to 25 m. The N-band flux of HD 179218 (∼ 10 Jy) is lower than the sensitivity limit of MA-TISSE with ATs for absolute visibility measurements (∼ 15 Jy), therefore no N-band photometry was acquired. Since chopping is only performed during that step, no L-band data with chopping was acquired either. As a consequence, the L-band thermal background emission was removed using sky measurements done at the beginning of the observation (a few minutes apart). Table  1  gives an overview on the observations. We reduced the data with the version (1. 5. 0) of the standard MATISSE data reduction pipeline.
The data reduction steps of MATISSE are described in  Millour et al. (2016). We obtained six dispersed L-band absolute visibilities, three independent closure phases (out of four closure phases in total) and four total flux measurements. In the study presented here, we aim to measure the dust IR continuum emission and to assess the limits of the detection of the carbonaceous features. A detailed study of the brightness asymmetries suggested by the MATISSE closure phases will be carried out in a future study. For now, we refer to Appendix B for a first modeling of the MATISSE closure phases performed in the frame of our temperature-gradient model. Considering our primary goal of this study, we thus focused on the visibilities and total flux for which two calibration procedures were applied: -The calibrated visibilities were obtained by dividing each raw visibility measurement of HD 179218 by the instrumental visibility measured on the associated interferometric calibrator observed just after.
-The calibrated total photometric fluxes were obtained by multiplying the ratio of the target-to-calibration-star raw fluxes, measured by MATISSE at each wavelength, followed by multiplication by the absolute flux of the corresponding calibrator. Both routines were performed using python tools of the MA-TISSE consortium. The interferometric and spectrophotometric calibrator was selected from Mid-infrared stellar Diameters and Fluxes compilation catalog (MDFC), a calibrator catalog for mid-infrared interferometric observations  (Cruzalèbes et al. 2019 ). In Fig. 1  in light blue curves visibilities are shown as a function of wavelength for different baselines. Since the MA-TISSE L-band visibility at the shortest baseline (B proj ∼ 7 m) is already rather low (around 0. 4), and even lower for larger baselines, it suggests a spatially extended L-band emitting region.
MIDI data The calibrated MIDI N-band visibilities from  Menu et al. (2015)  were taken from the Optical interferometry Database (OiDB  Haubois et al. 2014)  of the Jean-Marie Mariotti Center 3  (see Appendix C for the MIDI observation log). Decommissioned in 2014, the MIDI instrument  (Leinert et al. 2003 ) combined the light from two telescopes of the VLTI in the mid-infrared (MIR) (8-13 µm) with two spectral resolutions (R = 30 and 230). The HD 179218 low spectral resolution MIDI data consist of 27 observations with baseline lengths ranging from 10 -90 m (see Appendix C). As shown in Fig. 3  (upper right corner), the MIDI visibilities show characteristic sinusoidal modulations at the longest baselines (∼50 to 85 m), which are reminiscent of an object having a brightness distribution with sharp edges like a uniform disc, ring or a binary system with two unresolved components.
PIONIER data The calibrated PIONIER  (Le Bouquin et al. 2011 ) H-band visibilities were also taken from OIDB. The PIONIER interferometric observations (see Appendix C for the PIONIER observation log) were carried out using the 1. 8 m auxiliary telescopes (AT) of the VLTI with a four-telescope recombiner operating in H-band (1. 55-1. 80 µm). The three AT configurations provide different baselines in the range 10-140 m. In Fig. 3  at the bottom left, we see a series of inclined lines. Each line corresponds to a uv point, which is dispersed in the six wavelenght channels. The top of each line corresponds to the short edge of the H-band while the bottom of each line corresponds to the long edge of the H-band. The dispersed H-band visibilities are rather low and do not vary with spatial frequency.
Photometric observations The visible and IR broadband SED used in our temperaturegradient modeling is shown in Fig. 2  (dotted black line) and interpolated measurements in Fig. 3  (bottom right panel, dotted blue line). The SED is based on various photometric measurements taken from the VIZIER 4  database. For most of the photometric measurements, the error bars are ∼ 5-6%. We thus assumed a typical 5% error for all the interpolated data points. For sake of comparison, we also considered the high-resolution MIR Spitzer spectrum, taken from the Spitzer archive 5  and SWS spectrum from the ISO archive 6. The ISO SWS data presented here is before normalization of each individual spectral segments and with the regions of overlap intact. The observed SED was de-reddened using the visual extinction A V = 0.
Model description To model more accurately the radial structure of the disc, we applied a temperature-gradient model to a multiwavelength dataset that includes NIR and MIR interferometric data and an IR broadband SED. With such a temperature-gradient (and surfacedensity) model, we can take into account the fact that different radial disk regions will emit at different wavelengths, with different temperatures, and different optical depths along the line of sight. Such model aims to reproduce the emission from the disk surface as seen in the IR. Here, the circumstellar emission is produced by a geometrically flat temperature-gradient dusty disk that has temperature and surface density radial profiles given by: T r = T in r r in -q , ( 9 ) Σ r = Σ in r r in -p , ( 10 ) where r in is the inner radius, T in -temperature at the inner radius and Σ in is the dust grain surface density in g/cm 2 at the inner radius respectively; and p and q, the surface density and temperature power-law exponents, respectively.
(2014) : V λ, disc (B p (i, θ)) = 2π d 2 1 F λ (0) r out r in B λ (T r )ε τ J 0 2π λ B p (i, θ) r d rdr, (17) B λ (T r ) the Planck function, and d the distance to the object. From that temperature-gradient description, we built a twocomponent disk model with the aim to reproduce, in a consistent way, the complete dataset comprising the IR broadband SED, the PIONIER H-band, the MATISSE L-and the MIDI N-band visibilities.
g. size, hydrogenation state, structure) as a function of the distance from the star. Probing those grains at such close distances from the star and such small scale is a unique opportunity to study the photo-induced fragmentation of large hydrogenated amorphous carbon grains (containing aliphatic structures) along with the dehydrogenation and destruction processes of carbon grains. Notably, identifying clearly where the C-H induced features start in HD 179218's disk will be key. Interestingly, a complete nondetection of those features in the future MATISSE data would point toward very efficient dehydrogenation processes and/or the presence of another dominant refractory species like iron. What is at stake is a better understanding of the physical conditions under which solid carbon can survive in the terrestrial planet-forming regions of discs.
Moreover, local photo-fragmentation of larger carbonaceous grains could play a significant role in the regeneration of nano-grains. -First constraints could be provided on the presence and location of aromatic grains from the existing low resolution MATISSE data. Indeed, we found that the MATISSE data are not compatible with the presence of aromatic grains in close proximity to the star (closer than about 1 au). The perspective of such a study is a better understanding of the physical conditions under which solid carbon can survive in the terrestrial planet-forming regions. To this end, we simulated MATISSE L-band visibilities in medium spectral resolution to assess the feasibility of detection and detailed characterization of the aromatic (3. 3 µm) and aliphatic (3. 4 µm) band emitting regions in the inner 10 au.
Acknowledgements. MATISSE is defined, funded and built in close collaboration with  ESO , by a  consortium composed of French (INSU-CNRS in Paris and OCA in Nice) ,  German  ( MPIA, MPIfR and University of Kiel ),  Dutch (NOVA and University of Leiden), and Austrian (University of Vienna ) institutes. The  Conseil Départemental des Alpes-Maritimes in France , the  Konkoly Observatory and Cologne University  have also provided ressources for the manufacture of the instrument. This work has been supported by the  French government  through the  UCAJEDI Investments  in the  Future  project managed by the  National research Agency (ANR)  with the reference number  ANR-15-IDEX-01. We acknowledge  Université Côte d'Azur  for the PhD funding of  E. Kokoulina  via the program " Center For Planetary Origin " ( C4PO ).
The surface is modelled using the 6-m-resolution SPC/OLA v34 shape model composed of triangular facets and derived from a combination of stereophotoclinometry and laser ranging  35  ; its pole orientation 9,10 is J2000 ecliptic longitude 69. 92° and latitude -83. 45°. The observation geometry for each spot and time of the day (i. e. , ephemerides of the OSIRIS-REx spacecraft and the asteroid) is computed using the spiceypy Python-wrapper for the SPICE Toolkit. The kernel files are directly sourced from the SPICE kernels produced by the mission. For each observation geometry, we build the local set of facets of Bennu's topographic model by drawing concentric circles (with radius ranging between 0 and that of the OTES spot and centred at the spot's centre) and by drawing radial vectors with origin in the spot's centre and length between 0 and the spot's radius.