dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGEMENTS We are grateful to  M Cardon  from the  'Stress and Cancer ' lab, at the  Institut Curie , as well as  R Leclere ,  E Martel ,  M Richardson  and  A Nicolas  from the experimental pathology platform for help and advice. We acknowledge  O Mariani  from  CRB Institut Curie  for her help in preparing RNA samples from patient tumors. We are grateful to all members of the animal facilities of  Institute Curie  for their helpful expertize. SL was supported by funding from the  Fondation ARC. The experimental work was also supported by grants from the  Institut National de la Santé et de la Recherche Médicale (Inserm)  and the  Institut Curie. FMG's laboratory is labelized by the  Ligue Nationale Contre le Cancer (LNCC). We are very grateful to the  LNCC, Institut Curie and Inserm  for providing their support these last years.
Finally, one can avoid manual remeshing to track the air/ice interface by using adaptive mesh refinement and penalization method around the Level-Set interface. In such framework the use of wall functions may be useful to model the turbulent boundary layer. Future work will investigate these concepts. In a previous paper  (Pena et al. (2015) ), a three-dimensional icing code has been developed and validated in the NSMB (Navier-Stokes-Multi-Block) flow solver. The icing code implemented consists of an Eulerian droplet transport equations and an iterative Messinger model. A mesh deformation algorithm previously implemented in NSMB was used to track the ice/air interface through time for multi-steps ice accretion simulations. In this paper, a novel approach for tracking the ice/air interface using the Level-Set method is introduced and the feasibility of the approach is demonstrated.
Numerical method and governing equations The icing code is developed in the Navier-Stokes solver NSMB (Navier-Stokes-Multi-Block)  (Vos et al. (1998) ). NSMB is a numerical software solving the Navier-Stokes equations via finite-volume. NSMB is a structured multi-block code parallelized in MPI that includes numerous numerical schemes and turbulence closures (URANS, LES, Hybrid approaches as Detached Eddy Simulation and DDES), several high-order spatial discretization schemes and remeshing techniques. Chimera grids and Immersed boundary method are available as well. The code was initially developed by EPFL (Lausanne, Switzerland), KTH (Stockholm, Sweden), AEROSPA-TIALE, SAAB and CERFACS (Toulouse, France) and is now used and upgraded by CFS Engineering (Lausanne, Switzerland), ICUBE (Strasbourg, France), EPFL, ETH (Zurich, Switzerland), TU (Dresden, Germany), IMFT (Toulouse, France) and Ecole Polytechnique de Montreal (Montreal, Canada).
Thermodynamic Modeling To calculate the properties of the ice and the liquid water film on the exposed body one need to solve the mass and energy conservations. The input to the equations are the wall shear stress τ wall and the heat transfer coefficient h c evaluated by the flow solver NSMB, the collection efficiency β and the droplet velocity field u computed by the droplet module. The PDE icing model implemented in the NSMB flow solver is based on the Messinger model  (Messinger (1953) ). The Mass and energy conservation equations are solved for each cell located on the wall. Radiation is neglected in the energy conservation equation as it accounts for a very low contribution in most icing cases. According to  Beaugendre et al. (2003)  the system of equation writes :          ∂ρ w h ∂t + ∇.
The variable φ is defined as φ : (V x Φ, V y Φ, V z Φ), S is the right hand side and Ω the volume of the cell. The right hand side part is treated explicitly breaking the unconditional stability of the implicit scheme. It will be shown that this method is still able to handle large timesteps at the cost of higher numerical dissipation. The system of three equations is solved with preconditioned BiGSTAB. The whole process is parallelized with MPI. At the end of the single step calculation, the Level-Set interface, i. e. the contour zero Φ = 0 is extracted by the post processing software Tecplot R. If a multilayer icing calculation is desired, the output contour can be directly used as geometry input for a mesh generator program. The main objective of the framework currently developed in NSMB is to avoid remeshing by using penalization method and wall functions in such case the wall is modelled by a forcing term inside the flow and droplet equations.
In despite of the different type of method used by LEWICE and NSMB-ICE a good agreement is obtained. The collection efficiency against the distance from the stagnation point is compared with LEWICE in Fig. 8. The collection efficiency peak is β = 0. 72. In a glaze configuration there is no direct correlation between the collection efficiency and the instantaneous mass of ice per second distributions. As less ice forms near the stagnation point, the remaining water film flows on the surface as runback and freezes downstream mainly on the top of the leading edge. The convergence of the thermodynamic module is plotted in Fig. 9. A L2-Residual drop of ResL2 = 10 -11 is achieved in less than 10s of CPU time. The spurious oscillations of temperature residual during the first steps are due to the change of the type of surface (from dry type to wet type).
, 2011; Inoue et al. , 2014; Keenan et al. , 2014a; Peichl et al. , 2014; Toomey et al. , 2015). A loosely organised global phenocam network is emerging with regional networks including the PhenoCam Network  (Richardson et al. , 2009a)  and the National Ecological Observatory Network (NEON) in the USA  (Keller et al. , 2008) , the EUROPhen network in Europe  (Wingate et al. , 2015; Brown et al. , 2016) , the Phenological Eyes Network (PEN) in Japan  (Nasahara and Nagai, 2015) , and most recently, the Australian Phenocam Network  (Brown et al. , 2016). These networks provide support for phenocam data collection and sharing in the wider scientific community and are a platform for the development of open data and data sharing standards. Phenology information can also be derived from satellite remote sensing imagery.
Insights from existing phenocams To demonstrate the utility of phenocams for monitoring in situ vegetation phenology in Australian ecosystems, we calculated GCC from image data sets from four contrasting ecosystems in Australia: Cow Bay (AU-Cow, Fig. 2 ; site 1), Howard Springs (AU-How, Fig. 2 ; site 2), Tumbarumba (AU-Tum, Fig. 2 ; site 3), and Whroo (AU-Whr, Fig. 2 ; site 6). We used R software (R Core Team, 2013) to extract and calculate chromatic coordinates (Eq. 2) from phenocam images collected between the hours of 10:00 and 16:00 at local site time (i. e. UTC + 10:00 or 9:30 h). Temporal coverage varied for each camera, so we analysed all available images within the 10:00 to 16:00 time frame and calculated a daily average value of GCC, RCC, and BCC.
Data standardisation and sharing Standardisation and quality control in phenocam data collection is essential to support cross-site and cross-ecosystem comparisons. There is a clear need for standards in measurement in Australia, with a wide range of phenocam hardware currently in use. Brown et al. (2016)  provide recommendations for improving phenocam datasets and improving comparability between sites, including maintaining metadata and data management standards (i. e. image naming, FOV, camera settings) for all camera-based data registering all publicly available phenocams with a regional phenocam network making datasets available online wherever possible. Analysis of some of the datasets revealed that camera quality and installation issues (i. e. sun glare, inappropriate image acquisition times, power consumption) play a role in data quality.
However, the single greatest challenge was found to be changes in data quality and characteristics over time that limit or prevent automated analysis. In particular, changes in the FOV over time due to intentional or unintentional reorientation of the camera create a major obstacle to the collection of a sufficiently long time series and to automated data analysis. Slight or gradual changes can be dealt with through additional image co-registration efforts, but they can be arduous and reduce the area effectively available for analysis. Solid mounting of the camera and, when necessary, accurate realignment after removal (i. e. for maintenance) or unintentional reorientation can help alleviate such issues. Maintaining a consistent FOV is critical. For all but the most homogeneous environments, the FOV of the phenocam is the dataset.
Conclusions We see considerable potential for the developing Australian Phenocam Network. Existing infrastructure, supported by TERN, will assist in the establishment of this network, the implementation of more phenocams around the country, and the standardisation of data collection, analysis, and sharing. The Australian Phenocam Network would also provide valuable data for monitoring networks such as OzFlux, Su-perSites, AusPlots, and eMAST. Currently, there are only a small number of continuously operating phenocams in Australia, with even fewer uploading data to the Australian phenocam website. Expansion of the currently sparse distribution of Australian phenocams will help improve our understanding of the diversity of phenological strategies employed by Australian ecosystems. Combined with satellite remote sensing techniques, phenocams can improve our ability to quantify and predict the functioning of Australia's ecosystem within the Earth system.
Data availability The Australian phenology map (Fig. 2 ) was constructed using freely available  MODIS EVI data (2000 -2012)  obtained from the Oak Ridge National Laboratory Distributed Active Archive Center (https://daac. ornl. gov/MODIS/). The eddy covariance data used in this manuscript are also freely available from the OzFlux data portal (http://ozflux. org. au). Howard Springs flux data are provided to this database by  Beringer (2013a)  and Whroo data by  Beringer (2013b). Likewise, the phenocam data are freely available through the recently formed Australian Phenocam Network (https: //phenocam. org. au).
Acknowledgements. First and foremost, the authors would like to acknowledge the  Australian Centre for Ecological Analysis and Synthesis (ACEAS)  for their support of a workshop aimed at developing a Phenocam Network in Australia, held on Stradbroke Island in March 2014. Support for collection and archiving of some of the data used in this paper was provided through the  Australian Government Terrestrial Ecosystem Research Network (TERN)  (http://www. tern. org. au)facilities ACEAS,  AusCover, SuperSites, OzFlux , and eMAST. Part of the data was also funded via  Australian Research Council  grants  DP0772981  and  DP130101566. J. Beringer  is funded under an  ARC   Future Fellowship  ( FT1110602 ). T. F. Keenan acknowledges support from a  Macquarie University   Research Fellowship. Tumbarumba cameras were funded by a  Re-establishment Grant 2013  from the  University of Technology Sydney: "Setup of a phenocam network on some key Australian ecosystems" (N.
The underlying mechanism for recruitment of the FANCD2-FANCI complex itself to the ICL is currently unclear. Whereas the structure of the mouse homologues has been reported  8  , to date there is no structural information on the human FANCD2-FANCI complex. Here, we present a cryo-EM structure of the full-length human FANCD2-FANCI complex, demonstrating the existence of a novel Tower domain. The Tower domain is required for recruitment of the complex to ICLs in vitro and in vivo. We also demonstrate, for the fist time, a direct interaction between the FANCD2-FANCI complex and a DNA structure resembling a replication fork stalled at an ICL. Finally, we present data firmly establishing that the FANCD2-FANCI complex needs to be bound to DNA, to be efficiently monoubiquitinated. Several FA disease-causing mutations lie within the Tower domain, thus we have uncovered the molecular basis for the disease in these patients.
2a ), and purified the complex of this protein (FANCD2DTower) and FANCI (Fig. 2b ). The highly purified FANCD2DTower-FANCI heterodimer was subjected to cryo-EM, resulting in a structure at 20 Å resolution clearly missing the Tower domain, but otherwise similar to the full-length structure (Fig. 2c, d ). These data are further confirmed by docking the mouse crystal structure, where we have removed the C-terminal 305 amino acids onto the cryo-EM structure of the FANCD2DTower-FANCI complex (Supplementary Fig. 2b ). The Tower domain is important for the FANCD2-FANCI complex. Given the striking position of the Tower domain, we decided to determine whether this domain is functionally important to the FANCD2-FANCI complex, and to the FA pathway. We stably expressed exogenous full-length FANCD2 or FANCD2DTower in patient-derived FANCD2-deficient PD20 cells (Supplementary Fig.
EM and 3D image processing. Negatively stained freshly prepared full-length FANCD2-FANCI was applied to glow-discharged, carbon-coated grids and allowed to adsorb for 15-60 s. Specimen was then stained with 2% uranyl acetate. Vitrified full-length FANCD2-FANCI and FANCD2DTower-FANCI was prepared on glow-discharged carbon-coated quantifoil grids. Specimen were imaged at a nominal magnification of 30,000 Â with a 2 k Â 2 k Gatan CCD camera (corresponding to a pixel size of 3. 5 Å at the specimen level) in a JEOL 2100, LaB 6 operating at 200 kV. A preliminary full-length FANCD2-FANCI 3D model was calculated using the RCT  9  and the WEB and SPIDER software package  22. For this first 3D model, 4,082 pairs of particles of full-length FANCD2-FANCI were picked from 80 tilt pair images recorded at 50°and 0°.
Refinement of the 3D volume obtained from the RCT method was done using images from frozen, hydrated, fulllength FANCD2-FANCI. In all, 5,058 particles were selected after using Roseman's algorithm  23  in SPIDER  22  procedure, and subsequently manual selection in WEB  22. Defocus was determined using CTFTILT  24. 3D classification and refinement were carried out in RELION  25  , with 25 iterations of 1 class and 4 classes 3D classification. For the FANCD2DTower-FANCI complex, frozen particles were selected using Roseman's algorithm  23  in a SPIDER  22  procedure, with the previous frozen, hydrated, full-length FANCD2-FANCI structure, and then manually screened using the EMAN  26  program Boxer. In all, 8,547 particles were selected from 71 micrographs with a defocus range of 3-5. 2 mm. Defocus was determined using CTFFIND3 (ref.
24). Refinement was carried out using EMAN  26  software package. The frozen, hydrated, full-length FANCD2-FANCI structure was used as the starting model and refined against the FANCD2DTower-FANCI particles. At each iteration, particles with bad cross-correlation values were temporally removed, and intermediate volume was band-pass filtered between 10 and 150 Å. For the resolution limit estimation of 3D-reconstruction volumes, two independent reconstructions were carried out and compared in reciprocal space using increasing shells with the FSC (Fourier shell correlation) technique. Visualization of 3D-density map was done in UCSF Chimera  27. Preparation of interstrand crosslinked DNA substrates. The DNA oligos were annealed in a buffer containing 10 mM Tris-HCl pH 7. 5, 100 mM NaCl and 1 mM EDTA.
Live-cell imaging. EGFP-fused wild-type and mutant FANCD2 or mCherry-fused UHRF1 cDNA were inserted into the pOZ vector as described above. Live-cell imaging were carried out with an OLYMPUS IX81 microscope connected to PerkinElmer UltraView Vox spinning-disk system equipped with a Plan-Apochromat 60 Â /1. 4 oil objective using Volocity software 6. 3 for image capturing. EGFP was excited with 488-nm laser lines. Throughout the experiment, these cells were maintained at 5% CO 2 , and 37 °C using a live-cell environmental chamber (Tokai hit). Confocal image series were typically recorded with a frame size of 512 Â 512 pixels and a pixel size of 139 nm. For localized DNA-damage induction, cells were seeded in glass-bottom dish (MatTek) and sensitized by incubation in DMEM supplemented with 10% fetal bovine serum and 20 mg ml À 1 TMP for 30 min at 37 °C.
Microirradiation was performed using the FRAP preview mode of the Volocity software by scanning (each irradiation time was 100 ms) a pre-selected 3-5 stripes (50 Â 3 pixels) within the nucleus 10-60 times with a 405-nm laser set to 100% laser power. The EGFP and mCherry intensities at micro-irradiated sites were quantified using ImageJ with Fiji, and normalized by their intensities before microirradiation. Cell fractionation and whole-cell lysate. Collected cell pellets were permeabilized with CSK buffer containing 200 mM NaCl, 10 mM PIPES, 300 mM Sucrose, 1 mM MgCl 2 , 1 mM EDTA and 0. 5% Triton X-100 on ice for 10 min. CSK fraction (supernatant) and nuclear pellet were separated by centrifugation at 900g at 4°C for 10 min. Nuclear pellet was processed the same way as whole-cell lysate described below.
Acknowledgements We thank both members of the  Cohn laboratory  and  Johannes Walter  for reading and discussing the manuscript, and  Helen Walden  and  Patrick Sung  for help with establishing the in vitro monoubiquitination assay. We thank the  FARF repository  for the PD20 cell line. We are grateful to staff at the  Micron microscopy facility  for excellent help and support. This work was supported by grants  UF100717  and  ALRXNV0  from the  Royal Society  (to M. A. C. ), grant  103/789  from  The Fell Fund  (to M. A. C. ), grant  C5255/ A18085  from  Cancer Research UK (CR-UK)  through the  CR-UK Oxford Centre  (to M. A. C. ), grant  MR/N021002/1  from the  Medical Research Council  (to M. A. C. ), The Medical Research Fund  (to M. A. C. ), the  Taiwanese Government  (to C. -C. L), a  Goodger Scholarship  (to C.
Voice sample and Up Series We analysed the voices of all 10 men who took part in the British television documentary the Up Series  [31]. All were born in England in the year 1956 and were audio-video recorded for the series once every 7 years from age 7 to 56. [31]. In addition to 10 men, the Up Series also followed the lives of four British women, however, due to this small and unrepresentative sample, data from these women were not included in this study. The original aim of the documentary, in 1964, was to get a glimpse of England at the turn of the millennium, at a time when 'the shop-stewards and executives of the year 2000 are now seven years old'  [32]. The directors chose children from various socio-economic backgrounds. Each episode of the Up Series features interviews in which the participants of the documentary are asked to discuss their personal and professional lives, their values and aspirations, and to share their opinions on a range of topics.
g. changes in relative hormone levels  [7, [13] [14] [15] ) that could in turn have an indirect effect on vocal production. While there is some evidence of lower testosterone levels in married versus unmarried men and among those with children versus those without (see e. g. [42] [43] [44] ), it remains unclear whether this reflects between-individual differences or within-individual fluctuation in androgen levels. The potential influence of social life events on vocal production warrants investigation using a larger longitudinal dataset. The Up Series documentary included four women; however, this sample size was too small to be sufficiently representative. Replication studies should, therefore, include women to test whether individual differences in F0 also emerge before puberty among females and should include infants as well as post-menopausal/andropausal adults in order to determine whether individual differences in trustworthiness, and even impacts political and economic decision-making  [45].
Molecular barcoding of fish We used the QIAamp DNA Mini Kit (Qiagen), per the manufacturer's instructions, to perform DNA extraction. The 5 region of the cytochrome oxidase I (COI) mitochondrial gene was amplified with the primers FishF1 (5 -TCAACCAACCACAAAGACATTGGCAC-3 ) and FishR1 (5 -TAGACTTCTGGGTGGCCAAAGAATCA-3 )  (Ward et al. , 2005). PCR reactions were performed in 20 µl, containing 1 ng of DNA, 1x CoralLoad PCR buffer, 3 mM MgCl 2 , 66 µM of each dNTP, 0. 15 µM of each primer, and 0. 5 units of Taq DNA polymerase (Qiagen). The amplification protocol was 4 min at 94 • C, followed by 40 cycles  We used CodonCode Aligner version 3. 7. 1 software (CodonCode Corporation, Dedham, MA, USA) to edit sequences, which were 670 bp in length, compared them to the GenBank database content with BLAST, and deposited them in GenBank under accession numbers KT023566, KT023567, KT023568 and KU739501-KU739517.
The terminology for different parts of the male quadriloculate organ and the vagina is that of  Justine (2007a). We scanned drawings and used Adobe Illustrator software (version CS5) to refine lines and in some cases to add colour fill to better graphically differentiate structural elements. Museum abbreviations used are as follows: MNHN, Muséum National d'Histoire Naturelle, Paris; BMNH, Natural History Museum, London.
Trees and distances A tree was constructed from all available COI sequences of species of the genus Hyporthodus, including sequences already available in GenBank and our new sequences. The tree was inferred using Maximum Likelihood method. The best evolutionary model for the data set was estimated in MEGA7  (Kumar, Stecher & Tamura, in press ) under the Bayesian Information Criterion (BIC) to be Hasegawa-Kishino-Yano model  (Hasegawa, Kishino & Yano, 1985)  with a discrete Gamma distribution (HKY + G). The tree was computed in MEGA7, with 100 bootstrap replications. A tree inferred from the same data, using the Neighbour-Joining method  (Saitou & Nei, 1987)  and evolutionary distances computed using the Kimura-2 parameter  (Kimura, 1980)  with 1,000 bootstrap replicates, was also constructed with MEGA7.
Identification of fish hosts, Haifa grouper When we began our study, no sequence of H. haifensis was available in GenBank, and identification of our first COI sequences via BOLD yielded confusing results, probably because of sequences in the database derived from misidentified specimens. We obtained COI sequences for one specimen from Tunisia (now deposited in the MNHN collections) and two additional specimens from Libya, and the three sequences were identical or very similar (1 bp difference); sequences were also identical or very similar (1 bp difference) to three sequences of H. haifensis (KJ709537, KJ709538 and KJ709539) recently added to GenBank  (Landi et al. , 2014) , from off Sicily, i. e. , geographically close to Tunisia and Western Libya. We conclude with certainty, from identical COI sequences and convergent morphological identification, that our fish specimens belong to the species H.
Comparison of barcode sequences from Hyporthodus species We obtained 8 and 9 COI new sequences from H. niveatus and H. nigritus, respectively. In both cases, these sequences were similar to or identical with sequences deposited under the same names in GenBank. A ML analysis (Fig. 1 ) produced distinct branches for the species H. octofasciatus, H. haifensis, H. acanthistius, H. niveatus, H. nigritus and H. flavolimbatus; H. ergastularius and H. septemfasciatus were not well resolved, but this might be due to misidentification of some sequences, as previously suggested  (Schoelinck et al. , 2014) ; a NJ bootstrap analysis produced the same tree topology (Fig. 1 ). With the exception of the two latter species, all species, and especially H. haifensis, H. nigritus and H. niveatus, were each in separate clades with high support (100%).
COI sequences of monogeneans We obtained COI sequences of P. sulamericanus from H. haifensis from off Tunisia and Libya. The closest sequence in GenBank according to BLAST was from P. cyanopodus  Sigura & Justine, 2008 (Schoelinck, Cruaud & Justine, 2012) , a parasite from Epinephelus spp. in the South Pacific. The sequences differed by 17. 6% (Kimura-2 parameter distance). Since no sequence of P. sulamericanus from the Americas was available, no further comparison was possible.