dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions The reduction in the budget of generating reference labels is essential in remote sensing applications, which are also important to monitoring and implementing SDGs goals. It increases the efficiency of generating land-cover and land-use maps from datasets spanning large geographical extents. To this end, two unsupervised domain adaptation methods, namely, DANN and D-CORAL, are evaluated on a case study focusing on historical panchromatic orthomosaics. According to the conducted experiments we can conclude that unsupervised domain adaptation is not sufficient to generate accurate land-cover maps, however, when combined with a limited amount of reference data it can greatly reduce the labelling effort when compared to a standard supervised learning approach. While long-term baseline studies can benefit from exploiting available archives of historical panchromatic orthomosaics, the challenge of creating adequate reference data for each of the dates remains.
This study implies that the use of real-world datasets beyond standard benchmarks highlights a limitation of the state-of-the-art approaches. In addition, the availability and use of multiple, high quality, real-world datasets would serve to test the effectiveness of the proposed approaches. In summary, future works will focus on exploiting a highly specific domain knowledge to address the shift between source and target domains. professional flatbed scanner, at a resolution of 1500 dpi, and saved in a raw uncompressed 16-bit unsigned (unit 16) tiff format. Subsequently, the digital versions of the photographs are preprocessed to obtain a homogenized dataset comprising photographs with the same dimensions and the center of perspective localized at the center of the image. Ground control points (GCPs) are deduced from salient points such as buildings and road intersections that have been preserved to date, and the coordinates sourced from existing geodetic surveys, and recent images and digital elevation models of the cities having a meter to sub-meter scale spatial resolution.
The photogrammetric processing workflow is carried out using Agisoft Metashape Pro (https://www. agisoft. com/ (31 January 2018)) that entails: (1) photo alignment, (2) addition of GCPs, (3) tie point filtering, (4) Optimization of the camera calibration based on the two previous steps, (5) dense matching using the cloud compare software (https://www. danielgm. net/cc/ (31 January 2018)), (  6 ) dense point cloud denoising through filtering and subsampling, (7) DEM production, (8) Orthomosaic production and accuracy assessment. The final productions are georeferenced uint16 GeoTIFF orthomosaics having a horizontal georeferencing accuracy of 10. 8 m and 13. 9 m for Goma-Gisenyi and Bukavu (area of interest only), respectively (Figures  A1  and A2 ; Tables  A1  and A2 ). This limited georeferencing accuracy is related to the limited number of GCPs, their non-ideal distribution in the orthomosaics and the poor quality of the camera calibration.
The orthomosaics used in this work cover the urban areas of Goma-Gisenyi and Bukavu and generated by the Royal Museum for Central Africa (RMCA) as described in Smets et al. ,  [34]. The historical aerial photographs archived at RMCA are scanned using a professional flatbed scanner, at a resolution of 1500 dpi, and saved in a raw uncompressed 16-bit unsigned (unit 16) tiff format. Subsequently, the digital versions of the photographs are preprocessed to obtain a homogenized dataset comprising photographs with the same dimensions and the center of perspective localized at the center of the image. Ground control points (GCPs) are deduced from salient points such as buildings and road intersections that have been preserved to date, and the coordinates sourced from existing geodetic surveys, and recent images and digital elevation models of the cities having a meter to sub-meter scale spatial resolution.
The photogrammetric processing workflow is carried out using Agisoft Metashape Pro (https://www. agisoft. com/ (31/01/2018)) that entails: (1) photo alignment, (2) addition of GCPs, (3) tie point filtering, (4) Optimization of the camera calibration based on the two previous steps, (5) dense matching using the cloud compare software (https://www. danielgm. net/cc/ (31/01/2018)), (  6 ) dense point cloud denoising through filtering and subsampling, (7) DEM production, (8) Orthomosaic production and accuracy assessment. The final productions are georeferenced uint16 Ge-oTIFF orthomosaics having a horizontal georeferencing accuracy of 10. 8 m and 13. 9 m for Goma-Gisenyi and Bukavu (area of interest only), respectively (Figures  A1  and A2 ; Tables  A1  and A2 ). This limited georeferencing accuracy is related to the limited number of GCPs, their non-ideal distribution in the orthomosaics and the poor quality of the camera calibration.
In 2011, the circular-section fiber was replaced with octagonal-section fiber in the fiber link to improve the stability of the spectrograph illumination  (Perruchot et al. 2011; Bouchy et al. 2013) , and the pre and post upgrade data have distinct characteristics. This work, therefore, distinguishes two SOPHIE datasets, labeled SOPHIE and SO-PHIE+, depending on whether the spectra were taken before or after this SOPHIE upgrade.
Radial velocity analysis We use the Yorbit software  (Ségransan et al. 2011; Bouchy et al. 2016)  to fit the Keplerian RV signal induced by a companion. Yorbit uses a genetic algorithm to produce starting values for a Levenberg-Marquardt optimization, which in turn provides the priors for a Markov chain Monte Carlo (MCMC) estimation of the error bars following  Díaz et al. (2014). The first step of the RV data analysis is to identify significant periodic signals in the data. This is done by computing the Generalized Lomb-Scargle (GLS) periodogram algorithm of the RV measurements  (Zechmeister & Kürster 2009). In the case of giant planet survey targets, we then estimate the false-alarm probabilities (FAPs) of the tentative signals through a bootstrap permutation of the data. The GLS periodogram is however known to fail for the signals induced by companions in highly eccentricity orbits  (Zechmeister & Kürster 2009).
For two of the stars (BD+631405 and HD 331093), we, therefore, used the Plan-etPack software to compute Keplerian periodograms  (Baluev 2013a,b). We ran its kpow command for a range of orbital periods with a frequency step of 0. 01 and an upper limit on eccentricity. The latter is needed to control the computational cost, as the closer emax approaches unity, the longer is the computational time. When a significant period is identified, the RVs are first fit using a single Keplerian orbital model initialized at that period. The following parameters are varied while fitting the single Keplerian model: P the orbital period, K the RV semi-amplitude, e the orbital eccentricity, ω the orbital argument of periastron, T p the time of passage through pericenter, γ S and γ S + the RV offsets for SOPHIE and SOPHIE+ datasets, respectively.
It accounts for the systematics in the Gaia DR1 catalog and distinguishes between stars belonging to the TGAS (Tycho-Gaia Astrometric Solution) and the secondary subset of the DR1 catalog  (Lindegren et al. 2016; Kiefer et al. 2021). For the targets in the TGAS dataset, the inputs to the 5-parameter fit include a 24-years older Tycho-2 or HIPPARCOS-2 astrometric point in addition to 14 months of Gaia measurements, leading to an improved proper motion accuracy. Targets in the secondary dataset Table  4 : Detected orbits with Gaia astrometric excess noise ε DR1 >0. 85 mas. All sources belong to the primary dataset of Gaia DR1. When the 3-σ upper-limit on the orbital inclination is above 89. 5 • , the constraint on the companion true mass is handled as an upper-limit. Source   2021 )). Here we additionally impose that the secondary contributes no more than 10% of the total luminosity since the systems we study are single-lined spectroscopic binaries.
a sin i a phot I c M c,true ∆V MCMC (mas) (mas) (mas) (mas) ( • ) (M ) Acceptance 1-σ 3-σ 1-σ 3-σ 1-σ 3-σ 1-σ 3- Out of 26 targets studied in the present paper, 25 targets figure in the DR1 catalog, with HD 211961 as the sole exception. Table  A. 7 summarizes for those 25 stars the DR1 inputs to GASTON. For targets in the TGAS (respectively secondary) dataset of the DR1, the reported value of ε DR1 is considered significant beyond noise, if above 0. 85 mas (resp. 1. 2 mas)  (Kiefer et al. 2021). Targets with ε DR1 above these thresholds can lead to, but does not guarantee, a true mass measurement from an allowed orbit inclination range that excludes 90 •. Targets with ε DR1 below the thresholds cannot be distinguished from noise, so can only provide an upper-limit (lower-limit) on the mass (inclination).
BD+450564 BD+450564 is a K1 type star with mass 0. 81 ± 0. 07 M and logR' HK of -4. 98 ± 0. 11. It was only observed after the SOPHIE upgrade and the final dataset has 14 SOPHIE+ RV measurements. Its GLS periodogram (Fig. B. 1) has a clear peak around 300 days, with a FAP below 0. 1%. The Keplerian fit of the 14 RVs has a period of 307. 8 ± 1. 5 days and a semi-amplitude of 47. 7 ± 2. 8 m s -1 , and it corresponds to a minimum mass of m sin i = 1. 36 ± 0. 12 M J. The orbit of BD+450564 b is quasicircular, with e = 0. 12 ± 0. 06. Due to the low (and possibly null) eccentricity, we fit for the time of possible transit instead of the time of periastron. The 3. 3 m s -1 dispersion of the RV residuals is consistent with the typical uncertainty of the RVs. No significant astrometric orbit is detected in HIPPARCOS data.
BD+550362 BD+550362 is a K3 type star with mass of 0. 91 ± 0. 10 M and logR' HK = -5. 11 ± 0. 12. Its 22 RV measurements were all obtained after the SOPHIE upgrade. The GLS periodogram (Fig. B. 1) shows two peaks around 260 and 2000 days with FAPs below 0. 1% and 1%, respectively. We tested three models for this target: k1 (one-planet Keplerian), k1d2 (one-planet Keplerian and a quadratic drift), and k2 (two-planet Keplerian). An Ftest comparison of the k1 and k1d2 models reveals that the k1d2 model gives a better fit than the k1 model with confidence of 96% (F-value = 24. 3). The F-test comparison of the k1d2 and k2 models finds no significant improvement for the k2 model (F-value=3. 8, Probability= 84. 5%). The k2 model fits the shorter period planet well, but its orbital parameters for the longer period planet are very uncertain because our data do not sample its period well.
BD+631405 BD+631405 is a K0 type star with a mass of 0. 82 ± 0. 08 M and has low magnetic activity (logR' HK = -4. 93 ± 0. 13). Its 16 RVs were all obtained after the SOPHIE spectrograph upgrade. Figure  B. 2 shows both a GLS periodogram and a Keplerian periodogram of those velocities. We produced the Keplerian periodogram using the kpow command of the PlanetPack package for orbital periods between 3-1500 days with a frequency step of 0. 01 days -1 and an emax=0. 91 upper limit on the eccentricity. The GLS periodogram has no obvious peak, but its Keplerian counterpart shows a clear one around 1200 days. A one-planet Keplerian fit of the RVs finds a highly eccentric orbit (e = 0. 88 ± 0. 02) of period 1198. 5 ± 60. 8 days. The semiamplitude, 186. 0 ± 14. 9 m s -1 of the Keplerian fit corresponds to a planet with minimum mass, m sin i = 3.
This is qualitatively expected from Gaia DR1 only covering ∼1/6 of the orbit (HD 76332 is not part of the TGAS dataset), but none of the GASTON simulations, whatever the mass of their companion, could produce a Gaia DR1 astrometric excess noise above ε=1. 55 mas. We note that HD 76332 has a duplicate source and that duplication may be the sign that something went wrong during the reduction for this specific source. For non-TGAS sources, the GASTON simulations fit the proper motion through the orbital motion observed with Gaia and we suspect that the best explanation for this discrepancy is an inaccurate proper motion fit in the DR1. If not fitting for the proper motion, GASTON leads indeed to I c within 40-70 •. We adopt the HIPPARCOS result as the best estimation of HD 76332 B's true mass.
HD 26596 has a stellar companion in an eccentric orbit (e=0. 4) at 890 days and a minimum mass of 121 ± 7 M J. To 3σ confidence, GASTON derives an upper limit of < 0. 19 M for the true mass and the HIPPARCOS analysis derives a range of 0. 23-0. 43 M. This source again has a duplicate in the DR1 database, and we suspect that its Gaia astrometric excess noise is underestimated. We therefore again prefer the HIPPARCOS confidence range for the mass of this companion to its likely underestimated GASTON upper limit.
5: Parameters of the HIPPARCOS astrometric observations. A in the last column indicates an orbit determination. The table is divided in three parts to distinguish CJs, BDs, and SCs, after the RV analysis (from top to bottom). TableA. 6:Updated parallax and proper motion values and the astrometric orbit parameters (I p , Ω) for 8 sources with significant orbit detections. Table A. 9: Companion HD 76332 B, whose RV orbit is incompatible with Gaia astrometric excess noise. The minimum and maximum ε that we were able to simulate for this secondary dataset source is given as ε simu,min and ε simu,max. Figure B. 2: Generalized Lomb-Scargle (GLS) periodogram (on left) and Keplerian periodogram (on right) of the RVs for the eccentric CJs, BD+631405 b and HD 331093 b. The two dashed black lines in GLS periodogram represent the 10% and 1% false alarm probability in ascending order.
Acknowledgements. We thank the  staff of Haute-Provence Observatory  for their support at the 1. 93 m telescope and on SOPHIE. This work is based on observations made with SOPHIE in the context of the program " Recherche de Planétes Extra -solaire " (PI:  I. Boisse ,  F. Bouchy ) and the  Programme National de Physique Stellaire (PNPS) , in particular the two programs " Recherche et caractérisation de planètes géantes avec SOPHIE " (PI :  G. Hébrard ) and " Exploring the Brown Dwarf Desert around FGK stars in the Solar neighborhood " (PIs:  F. Kiefer , IDs:  2017B_PNPS008 ,  2018A_PNPS008 ,  2018B_PNPS013  ;  S. Dalal , IDs:  2019A_PNPS008 ,  2020A_PNPS004 , 2020B_PNPS DALAL). F. K. acknowledges support by fellowship grants from the  Centre National d'Etude Spatiale (CNES)  and from the  Paris-Science-Lettre (PSL) University.
This work was also supported by the  PNPS of CNRS/INSU  co-funded by  CEA  and  CNES. X. B. , X. D, T. F. & L. M. acknowledge funding from the  French National Research Agency (ANR)  in the framework of the  Investissements d'Avenir program  ( ANR-15-IDEX-02 ), through the funding of the " Origin of Life " project of the  Univ. Grenoble-Alpes. E. M. acknowledges funding from the  French National Research Agency (ANR)  under contract number  ANR-18-CE31-0019  (SPlaSH). MH acknowledges support from  ANID -Millennium Science Initiative -ICN12_009. N. A. -D. acknowledges the support of  FONDECYT  project  3180063. This work was supported by  FCT -Fundação para a Ciência e a Tecnologia  through national funds and by  FEDER  through  COMPETE2020 -Programa Operacional  Competitividade e Internacionalização by these grants:  UID/FIS/04434/2019 ;  UIDB/04434/2020 ;  UIDP/04434/2020; PTDC/FIS-AST/32113/2017 & POCI-01-0145-FEDER-032113 ;  PTDC/FISAST/28953/2017 & POCI-01-0145-FEDER-028953.
C. Pressure measurements with VISAR A VISAR has been used to measure the rear-free surface velocity of pure aluminum (99. 9%) target immersed under water. As material parameters (density, elastic stiffness, etc. ) are well-known for pure aluminum, hence the plasma pressure obtained from shock waves measurement is very precise. Thus, through the temporal velocity profile of the rear surface, one can calculate the related rear pressure. Then, Finite Element simulations of the specimen response are used to calculate the attenuation of the shockwave during its propagation. A Johnson-Cook rheological model was used with the commercial Finite Element code Abaqus, as presented in previous work. 17 fterall, one can extract the plasma pressure (at the front face of the specimen) from the rear shock wave pressure measured by adding the known attenuation, for the given used thickness.
2011 ). On the contrary, another study that investigated IL-6 in an Asian HCC cohort showed that pretreatment IL-6 values with a cut-off of 4. 58 pg/mL are correlated with overall survival after sorafenib, with high pretreatment levels associated with a poor prognosis  (Shao et al. 2017). SORAfenib in combination with local MICro-therapy guided by gadolinium-EOB-DTPA-enhanced MRI (SORAMIC, EudraCT 2009-012576-27, NCT01126645) is a prospective, phase II, randomized, controlled study in HCC patients with three study arms. In the palliative arm of the study, HCC patients were randomized to sorafenib treatment either alone or combined with Y90 radioembolization (RE), and the addition of RE treatment failed to improve survival compared to sorafenib monotherapy  (Ricke et al. 2019). This exploratory post hoc analysis of the palliative arm of the SORAMIC trial aimed to explore the predictive value of baseline IL-6 and IL-8 in patients with advanced HCC receiving sorafenib monotherapy.
Statistical analysis All statistical analyses were performed using R statistical and computing software, version 3. 5. 0 (http:// www. r-proje ct. org). Categorical variables were reported as counts and percentages, and continuous variables as means and standard deviations. Correlations were evaluated with Chi-square and Fisher's exact tests, and a t test was used to compare two groups. We used the receiver-operating characteristic (ROC) curve to determine the cut-off values for IL-6 and IL-8 that could produce the highest sensitivity and specificity to predict individual survival shorter than the median overall survival. The Kaplan-Meier method was used for estimates of overall survival, and the log-rank test was used to compare survival groups. Cox regression models were used to assess the effects of cofounding factors on overall survival.
g. ,  Solan et al. , 2004; Thrush et al. , 2006; Queirós et al. , 2013). Species were scored for each trait modality based on their affinity using a fuzzy coding approach  (Chevenet et al. , 1994) , where multiple modalities can be attributed to a species if appropriate, and allowed for the incorporation of intraspecific variability in trait expression. The information concerning polychaetes was derived primarily from  Fauchald and Jumars (1979)  and  Jumars et al. (2015). Information on other taxonomic groups was obtained either from databases 3 of biological traits, publications  (Caine, 1977; Leblanc et al. , 2011; Rumbold et al. , 2012; Jones et al. , 2018)  and publications listed in Supplementary Appendix 1. (Costello et al. , 2015; Martini et al. , 2020).
SubT Subtidal species Ordination of the functional trait data was done using a Fuzzy coded multiple Correspondence Analysis (FCA)  (Chevenet et al. , 1994). Then, a hierarchical clustering analysis based on the Ward algorithm  (Ward, 1963)  was carried out using Euclidean distances  (Usseglio-Polatera et al. , 2000)  to define homogeneous functional groups comprising species with similar biological trait associations. The frequencies of the modalities of each trait were calculated in order to visualize the biological profiles of identified functional groups. Partitioning of Taxonomic and Functional β Diversity Regional differences in diversity (β diversity) were estimated from presence-absence data using  Sørensen's (1948)  dissimilarity. For each pair of cores, taxonomic β diversity and its two components, turnover and nestedness, were computed using the Baselga partitioning scheme  (Baselga, 2017; Schmera et al.
hyperborea  (Teagle et al. , 2018). While communities associated with holdfasts were fairly variable throughout the study area, six sites collected in northern and southern Scotland (Boreal province) were distinct from six sites in northwestern Wales and Southern England, supporting partitioning within the Boreal/Northern European Seas province. In honeycomb worm assemblages, differences in Boreal and Boreal-Lusitanian regions were mainly driven by the occurrence or absence of M. edulis and potential hybrids of M. edulis × M. galloprovincialis in the two studied regions. Given the morphological similarities among the three taxa, identification to the species level was uncertain in UK1 and UK4, with most identifications being kept to the genus level. This may partly explain the similarity among the Scottish and southern England sites in our dataset.
ACKNOWLEDGMENTS The authors would like to thank  Céline Cordier ,  Mickael Vasquez , and  Anthony Knights  for assistance with field collections. The authors would also like to thank  Maïwenn Lescop ,  Gautier Sourimant , and  Jean-Dominique Gaffet  for their help with sorting through reef samples and measuring worms. This study forms part of the  REEHAB (REEf HABitat)  project (www. honeycombworms. org).
FUNDING This work was supported by the  Total Foundation  (Grant No. 1512 215 588/F, 2015 ). AM and AC were funded by  Ph. D. grants from  Ifremer ,  Region Bretagne , and the  ISblue  project (the  Interdisciplinary graduate school for the blue planet ,  ANR-17-EURE-0015 , co-funded by the " Investissements d'Avenir" program ).
Flow Cytometry Analysis Immunostaining for RPE-specific markers were performed using the IntraPrep Permeabilization kit (Beckman Coulter, Brea, CA) as per the manufacturer's instructions. Primary antibody concentration was 1 μg/1 million cells for mouse anti-PMEL17 (Abcam, Cambridge, MA), mouse anti-RPE65 (Abcam). Goat anti-mouse conjugated to Alexa 647 (Invitrogen, Carlsbad, CA) was used as a secondary antibody. Nonspecific, species-appropriate isotype control was included in all flow cytometry experiments and stained cells were analyzed using a C6 flow cytometer (Accuri, Ann Arbor, MI). Further histogram analyses were performed using FloJo software.
RNA-Seq and Data Processing First-strand cDNA synthesis was performed with 195 ng total RNA using anchored oligo-dT and SuperScript III First-Strand Synthesis SuperMix (Thermo Fisher Scientific). Second strand cDNA synthesis was performed using RNase H, DNA polymerase I, and Second Strand Buffer (Thermo Fisher Scientific). Double-stranded cDNA was purified using DNA Clean & Concentrator-5 (Zymo, Irvine, CA). Library preparation was performed using the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA). Libraries were cleaned using Agencourt AMPure XP beads according to manufacturer's instructions (Beckman Coulter). Libraries were evaluated by the High Sensitivity DNA Kit on the 2100 Bioanalyzer. They were then multiplexed and sequenced on an Illumina HiSeq with 50 bp paired-end reads.
Biological Pathway and Upstream Regulator Analysis Pathway analysis was performed using ingenuity pathway analysis (IPA) (Qiagen, Redwood City, CA). Transcripts that were identified to be differentially expressed during RPE-EMT compared with untreated monolayers with a greater than 2-fold change and a P value of less than 0. 05 were input into IPA and KEGG for bioinformatics analysis using gene IDs. Differentially expressed transcripts were analyzed in IPA using core analysis followed by a comparison analysis between dissociation time course and TGF-β/TNF-α concentration. Datasets were assessed for prediction of canonical pathways and upstream regulators. 24.