dataesr/scientific-paragraphs-categorization huggingface dataset:
A limitation could be also find due to the underestimation of the multi-scattering processes in the case of a recent snow-fall that could therefore not be considered yet by using as input the yesterday's LSA-SAF satellite surface albedos. Finally, a restriction is applied in the look-up-table for aerosol properties to sun zenith angles smaller than 85 degrees. This is required as the radiative transfer model, and the MDSSFTD algorithm itself, are not well suited for extreme zenith angles. In conclusion, this restriction disables the data availability under twilight conditions (  > 85 degrees). For the MSG/SEVIRI platform this occurs in wintertime over high latitude regions.
Material and methods We designed a retrospective unicentric study. We reviewed data from patients who underwent CLN resection with or without porta hepatis disease resection, within upfront or interval complete CRS in the frontline treatment of advanced epithelial OC between January 2008 and December 2015. Patients were classified in two groups according to CLN status. Univariate and multivariate analyses were conducted. Survival rates were estimated using Kaplan-Meier method.
2. 1. Patients and study design A computer-generated search of our institution patient database was carried out to retrospectively identify all patients who underwent CLN resection with or without PH disease resection, within upfront or interval complete CRS in the frontline treatment of advanced (FIGO stage IIIC-IV) epithelial ovarian, fallopian or primary peritoneal cancer between January 2008 and December 2015 at the French Comprehensive Cancer Center, Institut Claudius Regaud -Institut Universitaire du Cancer de Toulouse, France. Institutional Review Board approval was obtained from our center.
Due to the proximity of the nodes at the base of the mesentery and the retroperitoneum, mesenteric lymph nodes metastasis could spread into the retroperitoneum and ascend along the paraaortic or aortocaval group  [28]. On the other hand, CLN involvement was associated with PALN involvement. In fact, in our study, all the patients with positive CLN had PALN involvement. Among the patients with CLN involvement, the 71% (12/17) had more than four positive PALN. Our results are biologically plausible as drainage from paraaortic nodes immediately below the left renal vein to the CLN has been demonstrated  [29]. Lymphadenectomy in ovarian neoplasm (LION) randomized trial (NCT00712218) aimed to evaluate the impact on overall survival of systematic lymphadenectomy in patients with OC stage IIB-IV undergoing complete PDS with pre and intraoperatively clinical negative lymph nodes.
Ion cyclotron range of frequencies (ICRF) wave propagation is calculated theoretically for tokamak conditions and for linear magnetized plasma device IShTAR which is dedicated to the RF sheath studies. Only the slow wave (SW) mode of ICRF waves can propagate and be studied in IShTAR. Therefore it is possible to decouple the role of the different ICRF modes in the RF sheath effects. Numerical simulations of the ICRF SW are done in COMSOL in the framework of the existing cold plasma modelling package RAPLICASOL and the SW is for the first time modelled in 3D. To date, RAPLICASOL existed as a 3D wave coupling modelling approach which targets the fast wave (FW). Plasma is implemented as a material with manually assigned physical properties and a perfectly matched layer (PML) is used to absorb the wave energy.
The existing simulations of the ICRF waves are focused on the FW mode that can deliver power to the hot plasma core. Method of Moments code TOPICA  [4]  and Finite Element solver RAPLICASOL  [5] [6] [7]  evaluate the distribution of the field of the fast wave and introduce artificial modification (vacuum layers) to the density profile in order to avoid the lower hybrid (LH) resonance, which results in the absence of the conditions suitable for the SW propagation. Other simulation tools exist as well, for example an attempt to model the physics of ICRF antenna fields together with plasma-surface interactions using a finite-difference timedomain approach  [8]. Lower-Hybrid antennas working in close frequency range are modelled using Finite Element code TORIC  [9, 10]  (which is also used for ICRF modelling) or COMSOL-based LHEAF  [11].
In this work it is attempted to achieve understanding of the SW propagation in order to further study its influence on the RF sheath. In addition, the SW is important because it is able to carry a part of the power emitted by ICRF antennas and this power can be further deposited in unwanted locations of the plasma, instead of its delivery to the plasma core. The simulations are done in 3D using the simulation tool RAPLICASOL developed in the commercial software COMSOL. The modelling approach presented in this paper consists of 2 main parts: implementation of collisionality and accurate resolution of the specific SW structure. Previous works has encountered difficulties with the SW resonance layer because (a) they did not include sufficient collisionality leading to singular or near-singular fields at the resonance, and (b) because they sought to resolve the 'wavelength' rather than the true spatial scale of the SW resonance cone structure.
Plasma implementation and testing in COMSOL In the scope of this work COMSOL models have been developed for wave-plasma interaction studies by relying on the main principles of RAPLICASOL [5-7]: • Plasma is simulated as a dielectric medium with dielectric tensor derived in the cold plasma approximation; • Perfectly matched layer (PML) is used to absorb the wave energy and replace infinite (or simply big) regions of wave propagation and absorption; • Simulations are done in 3D using COMSOL RF module  [26]. PML was first suggested in 1994  [27]  and since then is commonly used to imitate the outgoing propagating wave without any reflection on the interface. It is built-in in the COMSOL software, however the functionality is rather limited and makes it suitable for usage only with standard dielectrics.
The presented simulation work shows that the SW in the shape of a resonance cone is not a purely backward wave and in fact can be absorbed by the same PML as the forward elliptic FW in the toroidal direction z (section 4. 4). Furthermore, it was observed in our simulations that the SW and FW absorbtion regions are usually spatially separated in the modeled conditions. It will be demonstrated below that for the SW only the toroidal PMLs are crucial, while the radial PML is intended to absorb the FW. It means that both waves can be propagating and coexist in one simulation domain. COMSOL software provides an opportunity to plot the direction of the Poynting vector and the distribution of the power absorption, so this way the correctness of the chosen stretching function coefficients is double-checked in the performed simulations.
Conclusions A complex ICRF waves study for IShTAR is performed. The wave equation solutions are applied to the IShTAR conditions and it is seen that only the SW mode can propagate and be studied in IShTAR, so the present work is fully focused on this mode. The existing modelling package RAPLICASOL for the FW propagation in cold plasma has been extended to include the SW. In IShTAR, same as in the given ASDEX Upgrade tokamak example case, the parallel electric field has significant values only for the slow wave and mostly at very low densities; the propagating SW has the shape of a resonance cone. This proves that the conditions in IShTAR are relevant for studies of the physics of the RF sheath caused by the SW in tokamaks. In experiments in Ar, densities up to 5 × 10 16 m -3 at the radial location of the antenna limiters are achievable in the present state of the device  [3].
Our study is mainly based on a dataset that includes physical (velocity, temperature, salinity) and biogeochemical (oxygen, nitrate, turbidity and chlorophyll) parameters measured by sensors attached to an autonomous underwater glider. A significant number of data were acquired that allow us to analyze the high variability in physical and biogeochemical parameters in the Mauritanian upwelling system in a very detailed view and with much better statistics then obtained from ship-based observations. Our study also devotes attention to the role of the pelagic processes close to the benthos in contributing to the local oxygen and nitrate structure. Benthic lander observations with novel lab-on-chip technology reported high nitrate and nitrite variability on timescales of less than 40 h for our working area  (Yücel et al.
, 2015). As underwater glider for the water column, the high-resolution lander-based time series observations highlight the advantage of new technology in revealing variability that can not be captured by traditional observing methods. However, ship-based profile and bottle data allowed us to carry out high-precision reference data as well as to collect an array of parameters so far not accessible from autonomous instrumentation. Based on the observational data at hand we aim to decompose and identify drivers for remote (via transport) and local (biogeochemical cycling) variability in oxygen and nitrate. This includes estimating local microbial particle-associated oxygen respiration as well as the possible role of DOC as microbial substrate. The paper is structured as follows. In Sect. 2 the observational datasets, including data processing and calibration procedures as well as methods are described.
Observational datasets, data processing and methods In June 2014 the research cruise Meteor 107 (M107) was carried out off Mauritania in the framework of the interdisciplinary collaborative research center SFB 754 "Climate-Biogeochemistry Interactions in the Tropical Ocean" funded by the Deutsche Forschungsgemeinschaft (DFG). The multiplatform experiment was carried out following a cross-shelf transect near 18 • N (Fig. 1 ;  Yücel et al. , 2015; Gier et al. , 2017). In this study we analyze and interpret physical and biogeochemical glider-based measurements of one Slocum glider (IFM13) deployment in combination with ship-based profiles and bottle data. Following the SFB 754 data policy and the spirit of open-access science all datasets associated with this publication  (Dengler et al. , 2019; Engel, 2018; Kiko et al.
Ship-based velocity, sensor and nutrient measurements The ship-based instrumentation included a vessel-mounted acoustic Doppler current profiler and a pumped Sea-Bird SBE 9plus CTD system, equipped with double sensor packages for temperature, conductivity (salinity) and oxygen, and with single sensors for chlorophyll fluorescence and turbidity. In total 62 CTD stations were carried out along the 18 • N transect between 8 and 27 June 2014. The CTD was mounted on a 24-bottle General Oceanics rosette system used to collect discrete water samples for analysis of salinity and various biogeochemical parameters. From the observational data we calculated conservative temperature ( ), absolute salinity (S A ) and potential density anomaly (σ ) using the Thermodynamic Equation of Seawater 2010 MATLAB Toolbox Version 3.
04  (McDougall and Barker, 2011). The salinity of bottle samples was measured on board R/V Meteor with a Guildline Autosal 8 model 8400B salinometer and used to calibrate the CTD conductivity sensor. The calibrated salinity measurements have an accuracy of 0. 002 g kg -1. The CTD oxygen sensor (SBE 43) was calibrated with the Winkler titration oxygen measurements of discrete water samples obtained from the rosette  (Winkler, 1888; Grasshoff et al. , 1983). Considering the scatter of the calibrated oxygen measurements an accuracy of 2. 5 µmol kg -1 from the oxygen concentrations was determined. In total 835 bottle samples along 18 • N were analyzed for this study for nitrate and nitrite using a QuAAtro autoanalyzer (Seal Analytical) on board. The nutrient data were used for sensor intercalibration (Sect.
2. 5) and to characterize the upper-shelf nutrient distribution where no glider measurements were available. See also  Yücel et al. (2015)  and  Fiedler et al. (2016)  wherein parts of the nutrients dataset were already published. The horizontal circulation was observed with two vessel-mounted acoustic Doppler current profilers (Ocean Surveyor with 38 and 75 Hz). Here we focus on the upper 250 m of the water column and thus only make use of the 75 kHz instrument. The bin size was set to 8 m and the ping rates for both were 2-3 s. The first reliable depth bin is centered at 18 m depth. Water track and amplitude calibration was performed as described in  Fischer et al. (2003). 2. 2 Underwater vision profiler, particle abundance and particle-associated respiration rate estimation An underwater vision profiler 5 (UVP5;  Picheral et al.
, 2010)  was mounted on the General Oceanics rosette and operated during downcast dives to obtain full depth particle size spectra (0. 06 to 26. 8 mm equivalent spherical diameter, ESD). Microbial particle-associated respiration rates (PARRs) were calculated according to  Kalvelage et al. (2015)  for particle sizes between 0. 06 and 10. 64 mm ESD as a function of particle size (ESD, mm), ambient temperature and oxygen concentration. The empiric relationship of particle size and oxygen respiration (r = 1. 8417×ESD 1. 8 nmol h -1 ) is based on a dataset close to the study area in the northern Mauritanian upwelling systems  (Iversen et al. , 2010). The relationship published by  Kalvelage et al. (2015)  well describes the lowerbound of the data shown in Fig. 8c  of  Iversen et al. (2010). The upper bound can be well described by the relationship r = 5.
Glider-based measurements The Slocum G2 underwater electric glider (IFM13) was operated from 12 to 27 June 2014 and did six sections of roughly 68 km each. The glider was programmed to dive to a maximum depth of 300 m. The glider was equipped with a pumped CTD and an Aanderaa optode was mounted on the tail of the glider to measure concentrations of dissolved oxygen. Data processing and calibration of salinity and oxygen measurements followed the procedures described and cited in  Thomsen et al. (2016). The glider was equipped with a Satlantic Deep SUNA nutrient sensor measuring nitrate and nitrite, named NO x following  Yücel et al. (2015). The configuration and data processing of the SUNA was done as described in  Karstensen et al. (2017). For the IFM13 deployment we linearly corrected the SUNA NO x measurements by the following function: NO x (calibrated) = 1.
625 = 138O 2 /16 NO x ) -is considered. The normalization of the nonconservative parameters is described in  Hupe and Karstensen (2000)  in their Sect. 3. 1. As we are interested in the local remineralization (and respiration), we used source water types based on the dataset at hand (see Table  1 ) and considering potentially youngest NACW and SACW guided by maximum oxygen and minimum NO x concentration within the nearby (±0. 04 • C/S A ± 0. 02 g kg -1 ) space (Fig. 2c, d ). In this way the OMP method will provide us with the local respiration and remineralization signals in the observational data. Note that the main difference between the AOU method and the OMP method is the reference frame: the AOU methods is based on the assumption that the regional AOU and NO x fields are created from bulk respiration/remineralization of the reference profile.
During the rest of the deployment, the poleward velocity reduced to values between 0 and 10 cm s -1. Despite the lower velocities it still seems that the poleward velocities were leading the changes in oxygen. This analysis suggests a strong modification of typical water mass signals, such as typically high concentrations of oxygen in SACW, are altered at the shelf due to locally enhanced respiration. Finally, although our observations suggest a relationship between increasing oxygen concentrations after periods of enhanced northward flow, no increase in SACW fraction is observed pointing to a complex interplay between physical and biogeochemical processes. In the following section we will investigate these highturbidity waters close to the seabed in more detail using UVP5, CTD sensor and bottle data to investigate the distribution and composition of the organic matter.
Discussion In this study we investigate remote and local drivers of oxygen and nitrate variability off Mauritania in June 2014 using physical-biogeochemical glider-based observations in combination with ship-based profile and bottle data. Our data reveal different types of O 2 and NO x anomalies driven by a combination of remote (primarily the transport of SACW in the boundary current system) and local (organic matter remineralization) processes. Our particle-related respiration rate estimates are enhanced in the upper oxycline close to the shelf break and near the seabed (Fig. 8c ). Brandt et al. (2015)  found diapycnal oxygen flux divergences just below the mixed layer of similar magnitude as the estimated oxygen respiration of about 1 µmol kg -1 day -1. This suggests that the high oxygen consumption in the upper water column near the shelf off Mauritania might be largely balanced by diapycnal oxygen fluxes.
Acknowledgements. Special thanks goes to the captain and the crew of  R/V Meteor  for their support during the M107 cruise. We further thank the authorities of Mauritania for the permission to work in their territorial waters. We thank  Bettina Domeyer ,  Anke Bleyer ,  Ulrike Lomnitz ,  Regina Suhrberg ,  Sven Trinkler  and  Verena Thoenissen  for the nutrient analyses. We thank  Ruth Flerus  for the water sampling on board. We thank  Ruth Flerus  and  Jon Roa  for the dissolved organic matter analyses and  Christian Begler  for preparing and carrying out the glider deployment and the navigation. We thank  Hela Mehrtens  and the whole GEOMAR data management team for their important work and for supporting us with publishing the datasets. This study is a contribution of the  Sonderforschungsbereich 754  " Climate -Biogeochemistry Interactions in the Tropical Ocean ", subprojects  B6 ,  B8  and  B9 , which is supported by the  German Research Foundation.
Code and data availability. The CTD sensor and nutrient bottle data can be downloaded freely at https://doi. org/10. 1594/PANGAEA. 860480 (Krahmann et al. , 2016)  and https://doi. org/10. 1594/PANGAEA. 885109 (Sommer and Dengler, 2018) , respectively. The glider data can be accessed at https://doi. org/10. 1594/PANGAEA. 877388 (Krahmann et al. , 2017). The underwater vision profiler (UVP) data can be accessed at https://doi. org/10. 1594/PANGAEA. 885759 (Kiko et al. , 2018). The organic matter dataset can be accessed at https://doi. org/10. 1594/PANGAEA. 896321 (Engel, 2018). The vessel-mounted acoustic Doppler current profiler (ADCP) dataset can be accessed at https://doi. org/10. 1594/PANGAEA. 897534 (Dengler et al. , 2019). According to the SFB 754 data policy (https://www. sfb754. de/de/data, last access: 1 March 2019), all data associated with this publication are published at a world data center (https://www.
Reverse Transcription quantitative real time PCR (RT-qPCR). cDNA synthesis was obtained by reverse transcription (RT) of 1 µg of total RNA using High Capacity cDNA Reverse Transcription Kits (Applied Biosystems, Foster City, CA, USA) according to the manufacture's suggestions. RT-qPCR was performed using iQ SYBR Green Supermix protocol (Bio-Rad Laboratories, Milan, Italy). Each PCR amplification was carried out in 15 µL reaction volume containing 25 ng of cDNA, 1x iQ SYBR Green Supermix, and 250 nM gene-specific sense and anti-sense primers. Reactions were run on a Bio-Rad iQ5 real-time PCR detection system (iCycler IQ5 software, version 3. 1; Bio-Rad) together with two reference genes. The list of the primers description and sequences were shown in Supplementary Materials. Flow cytometry of CSC markers.
The presence of CSC surface marker antigens was detected using antibodies CD90/THY1 (Stem Cell Technologies, Vancouver, BC, Canada), CD133/PROM1 (Miltenyi Biotec GmbH, Bergisch Gladbach, Germany), and CD44 (Abcam, Cambridge, UK). Flow cytometric analysis was performed immediately on a FACSCalibur flow cytometer (Becton Dickinson, NJ, USA). A total of 10,000 events were analyzed per sample. Data were presented as a mean for at least three independent experiments. Immunofluorescence of CSC markers. For mouse liver tissues, after de-paraffinization with xylene and rehydration with gradual concentration of ethanol, antigen retrieval was performed by microwave heat in sodium citrate pH 6. 0. The autofluorescence background of paraffin tissues was quenched by combination of photo bleaching and Sudan Black B dye  54.
Acknowledgements The authors thank the support of  Dr. Stebel ,  Dr. Barbetta , and  Dr. Zarattini  ( animal facility, University of Trieste ) and the group of  Prof. Bulla  ( Department of Life Sciences, University of Trieste ) for the reagents for HABP staining. BA was supported by a fellowship the  Italian Association  for the Study of the Liver (AISF), SI by a fellowship from the  Istituto Italiano di Cultura ,  Jakarta  and  Fondazione Italiana Fegato ,  CHCS  by the  University of Trieste. This study was supported by the project  297   Nutrizione e Salute  ( 2012-2014 ) 'Dalla nutrigenetica alla nutraceutical' of the  Italian Ministro dell' Istruzione, dell' Università e della Ricerca  ( Art. 13 D. LGS 297/99 ) and in part by an in-house grant from  Fondazione Italiana Fegato.
Following  Peters et al. (2018) , for a token sequence s i ,. , s j , we compute the span representation s (s i ,s j ),l at layer l by concatenating the first (h s i ,l ) and last hidden vector (h s j ,l ), along with their element-wise product and difference. We randomly pick 3000 labeled chunks and 500 spans not labeled as chunks from the CoNLL 2000 chunking dataset  (Sang and Buchholz, 2000). As shown in Figure  1 , we visualize the span representations obtained from multiple layers using t-SNE  (Maaten and Hinton, 2008) , a non-linear dimensionality reduction algorithm for visualizing high-dimensional data. We observe that BERT mostly captures phrase-level information in the lower layers and that this information gets gradually diluted in higher layers. The span representations from the lower layers map chunks (e.
We evaluate each layer of BERT using ten probing sentence-level datasets/tasks created by  Conneau et al. (2018) , which are grouped into three categories. Surface tasks probe for sentence length (SentLen) and for the presence of words in the sentence (WC). Syntactic tasks test for sensitivity to word order (BShift), the depth of the syntactic tree (TreeDepth) and the sequence of toplevel constituents in the syntax tree (TopConst). Semantic tasks check for the tense (Tense), the subject (resp. direct object) number in the main clause (SubjNum, resp. ObjNum), the sensitivity to random replacement of a noun/verb (SOMO) and the random swapping of coordinated clausal conjuncts (CoordInv). We use the SentEval toolkit  (Conneau and Kiela, 2018)  along with the recommended hyperparameter space to search for the best probing classifier.
As random encoders can surprisingly encode a lot of lexical and structural information  (Zhang and Bowman, 2018) , we also evaluate the untrained version of BERT, obtained by setting all model weights to a random number. Table  2  shows that BERT embeds a rich hierarchy of linguistic signals: surface information at the bottom, syntactic information in the middle, semantic information at the top. BERT has also surpassed the previously published results for two tasks: BShift and CoordInv. We find that the untrained version of BERT corresponding to the higher layers outperforms the trained version in the task of predicting sentence length (SentLen). This could indicate that untrained models contain sufficient information to predict a basic surface feature such as sentence length, whereas training the model results in the model storing more complex information, at the expense of its ability to predict such basic surface features.