dataesr/scientific-paragraphs-categorization huggingface dataset:
Data collection We collected data using focal sampling  [40] , maintaining a balanced record of focal samples across individuals. We video-recorded focal individuals (15 or 30 min, depending on the site and visibility) using two Panasonic HC-V770 Camcorders with two external Sennheiser unidirectional microphones (MKE-400). Overall, we collected 1298. S1 ). During focal samples, we recorded data on proximity, socially directed approaches and social interactions (grooming and play). We collected proximity data using 5 min scan samples, determining the identities of nearest neighbours (at arm's-length distance) to the focal individual and identities of the other group members present in the vicinity. We continuously recorded socially directed approaches, i. e. whether the focal individual approached another group member or was approached by one, but only if their outcome was positive (resulting in a social interaction or contact sitting) or neutral (resulting in proximate sitting).
Social bond and rank difference To compute the social bond between partners, we used an inverse proxy referring to the social affinity or social bond strength between partners, the dyadic composite sociality index (DSI)  [41, 42]  using the 'socialindices' package in R (  [43]  https://github. com/gobbios/socialindices). The values of the DSI scale can range from 0 ! 1. Lower DSI values indicate weaker bonds, and higher DSI values indicate stronger bonds. Our DSI computation included the measures of partners' duration of grooming and play, their proximity rates (i. e. royalsocietypublishing. org/journal/rsos R. Soc. Open Sci. 8: 211121 having been in arm reach distance) and their approach rates (i. e. focal having approached the partner or the partner having approached the focal). As the San Diego bonobos were not always let out as one coherent group on the same day, we additionally controlled for observation time and co-residency of dyads for this group.
The social indices R package (  [43]  https://github. com/gobbios/socialindices) contains all the functions used to perform this analysis. The DSI was computed after (2. 1) (e. g. [34] ), where d includes the numbers/duration of behaviours chosen to select the index (as described above), f ixy indicates the rate/duration of behaviour i for the dyad xy and f i denotes the mean rate/duration of that behaviour i considering all dyads of this sample  [41]. DSl xy ¼ P d i¼1 f ixy= f i d : ð2:1Þ To compute rank differences, we computed Elo-ratings  [44, 45]  for individuals of each site using the 'EloRating' package in R  [46]. Elo-ratings rely on the outcomes of agonistic interactions between partners and depend on the sequence in which interactions take place over time. Undecided outcomes were counted as a disadvantage to higher ranked individuals.
Video coding We coded joint actions using the computer software ELAN v. 5. 2  [48]. We focused on the interruptions of ongoing joint actions of play and grooming, or mixed activities (switching from grooming to play in the same interaction or vice versa). The interruption duration was coded from the moment of suspension until the resumption of the joint action (see electronic supplementary material, figure  S3 ). The moment of suspension corresponded to the moment all movements typical of the activity stopped. For grooming, it corresponded to the cessation of all hand or mouth movements performed to groom the partner's body. For play, suspensions corresponded to the cessation of play-related movements (rough-and-tumble contact play, chasing) and play-related signals (play-faces, laughter).
For this dataset, we excluded events that were out of sight (N = 3), and only considered interruptions occurring during grooming or play, caused by external causes (N = 1052)-i. e. we excluded internal perturbations that were initiated by subjects themselves ( partner break). Of these, we further excluded N = 40 external interruptions occurring during mixed activity types due to limited sample size (i. e. less than or equal to 10 interruptions in bonobos; see electronic supplementary material, table  S4 ). Thus, model 1 involved N = 1012 data points.
Acknowledgements. We thank  Adrian Baumeyer  at  Basel Zoo ,  Dean Gibson ,  Mike Bates  and  Kim Livingstone  at  San Diego Zoo ,  Emmanuel Le Grelle  and the  Conservatoire pour la Conservation des Primates at La Vallée des Singes ,  Antoine Joris  and  Marielle Vandenbunder-Beltrame  at  La Réserve Africaine de Sigean , and all the dedicated animal keepers, for letting us conduct our observations at their sites, and for providing invaluable support during the study periods. We are also grateful for the help of our trained research assistants  Cindy Maslarova  and  Laura Perrenoud. Additionally , we thank  Martin Götz  for discussions and input regarding Bayesian statistics, and  Quentin Gallot  for his assistance with the inter-rater agreement coding. royalsocietypublishing. org/journal/rsos  R.
1 eV. First, a survey spectrum was performed using a pass energy of 187. 85 eV to identify all the elements present on the surface. Afterwards, narrower scans with a range of 20 eV were acquired using a pass energy of 23. 5 eV to accurately identify the chemical state of each element and to perform quantitative analysis using PHI Multipack software. The contribution of the background was approximated by the Shirley method and Wagner sensitivity factors (corrected for the transmission function of the apparatus) were used for the calculation of the atomic concentrations. An Argon ion beam was used to sputter the DLC surfaces at an angle of 45°. The ion beam was accelerated at 250 V with a current density of 120 nA mm -2. We sputtered the surfaces for 5 min. The corresponding sputter depth is ~0.
EDX (80 mm² silicon drift detector from Oxford Instruments) was used for local chemical analysis (spectra or elemental maps). The ta-C(66) thin foil was analysed using a FEI Titan ETEM G2 electron microscope operated at 300 keV and equipped with a Cs image aberration corrector. To avoid contamination prior to the analysis, the samples were plasma-cleaned with Argon for 30 s. Compositional analyses were conducted in TEM mode with an energy dispersive X-ray spectrometer (SSD X-max 55 mm² from Oxford Instruments). Contact mechanics calculations. Elastic-plastic contact of two rough DLC surfaces were modelled by using experimental AFM topography maps with discrete height profiles h x;y over a scan area of 20 × 20 μm 2 (including 512 × 512 data points). Local contact pressures p x;y and elastic displacements u x;y were calculated under an external normal pressure of 210 MPa (equal to a maximum cylindrical Hertzian contact pressure used in our experiments) using the PyCO code developed by Pastewka and co-workers.
Acknowledgements The authors gratefully acknowledge funding by the  BMWi  within the project  PRO-METHEUS. Part of the simulations was performed on the computational resource ForHLR II funded by the  Ministry of Science, Research and the Arts Baden-Württemberg and DFG ("Deutsche Forschungsgemeinschaft"). Computing time was granted by the  John von Neumann Institute for Computing (NIC)  and provided on the supercomputer JUWELS 65 at  Jülich Supercomputing Centre (JSC)  within projects  HFR04  and  HFR09. The authors acknowledge the  Consortium Lyon Saint-Etienne de Microscopy (CLYM)  for the access to the electron microscopes and funding by the  European Union  within the  Auvergne-Rhône-Alpes region FEDER  project,  PLATEFORME TRIBLOGIE MOTEURS.
Code availability The density-functional tight-binding calculations were performed using the open-source software Atomistica. The source code is available under GNU GPL v2 at http://www. atomistica. org. The density-functional theory calculations were carried out using the open-source software CP2K. The source code is available under GNU GPL v2 at https:// www. cp2k. org. The contact mechanics calculations were carried out using the opensource software PyCo. The source code is available under MIT license at https://github. com/ComputationalMechanics/ContactMechanics.
Thirdly, 'sequence-based prediction' describes a new family of methods in which growing catalogs of defined TCR:antigen combinations are used to train machine learning algorithms to predict specificity directly from TCR sequences  12, 13, 14   (Bagaev et  al. , 2020; Fischer et al. , 2020; Tong et al. , 2020). These have great potential to enable generalizable decoding of the repertoire, especially as the training datasets grow, however they do not yet enable the confident assignment of specificities within deep repertoires using TCR sequences alone. Here, we develop an alternative approach to decoding TCR repertoires. In this method, rare T cells are clonally expanded by antigens of interest in culture, subjected to bulk TCR sequencing, and clonal frequencies are analyzed using a similarity-based clustering approach to identify and organize families of antigen-responsive clonotypes against the majority of irrelevant sequences.
Following the incubation time, cells were washed three times in 1X BD Permwash and resuspended in BD stabilizing fixative (BD Biosciences) diluted 1:3. All analysis plots were pre-gated on live (using Live/Dead stain) and singlet events. Cells were analyzed with a FACSCanto II or an LSR Fortessa (BD Biosciences). Data was analyzed with FlowJo® Software.
Significance was assigned to each cluster by determining the frequency with which clusters containing the same number of members, and a greater or equal mean frequency, were observed within 1000 random trials. Random trials used 1000 nonspecific TCR clonotypes (of the corresponding chain), each assigned a frequency from the clonotype shortlist being tested, and clustered as described above. Clusters were considered significant at p<0. 01 (i. e. , <10 occurrences in the random trials). Clonotypes from significant clusters detected across all TCRdist thresholds were combined into a single master clonotype list and reclustered at the maximum threshold of 50 for final output. All code used for these analyses will be made available at https://github. com/TGenNorth/TCR_framework. git.
Acknowledgments We thank the  Luminex core at Baylor Scott & White Research  for performing the cytokine detection experiments and the  Biotechnology core at Baylor Scott & White Research  for developing the vaccine reagents. A Roche Collaborative Research Grant to the  Baylor Scott & White Research Institute  supported the initial development of anti-CD40 antibodies with enhanced agonist potency, and the  Vaccine Research Institute  via the  ANR-10-LABX-77  grant funded the rest of the work.
Glycolysis and oxidative phosphorylation at rest: the interest of measuring the oxygen-glucose index (OGI) The same research group measured CMRO2 and CMRGlc with PET in 33 normal right-handed adults in the resting awake state. They estimated OGI by dividing relative CMRO2 by relative CMRGlc in every voxel and calculated a whole-brain molar ratio of 5. 32, significantly inferior to 6, a value corresponding to a full oxidation of glucose  (Vaishnavi et al. , 2010). The other main observation was that the brain exhibits strong regional variations in OGI. However, there is no consensus about the heterogeneity of OGI in the human brain. The analysis of a same datasets (CMRO2 and CMRGlc measured in the brain of 13 adults) provided opposite conclusion with either uniform OGI  (Hyder et al. , 2016)  or robust regional differences within gray matter  (Blazey et al.
ACKNOWLEDGEMENTS G. B. received grants from the  Centre National de la Recherche Scientifique (CNRS) , the  Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA) ,  Agence Nationale de la Recherche  ( ANR 2011 MALZ-0003 ),  Association France Alzheimer ,  Fondation de France ,  Fondation Alzheimer  and  Infrastructure de Recherche translationnelle pour les Biothérapies en Neurosciences (NeurATRIS   ANR-11-INBS-0011 ). J. P. B. is funded by the  Agencia Estatal de Investigación  ( PID2019-105699RB-I00 / AEI / 10. 13039/501100011033  and  RED2018-102576-T ),  Instituto de Salud Carlos III  ( CB16/10/00282 ),  Junta de Castilla y León  ( CSI151P20  and  Escalera de Excelencia   CLU-2017-03 ),  Ayudas Equipos Investigación Biomedicina 2017 Fundación BBVA and Fundación Ramón Areces.
A database describing the atmospheric radiation was presented in a previous work  (Hubert & Cheminet, 2015). It was built thanks to Geant4 (version 9. 4. 2) simulations of extensive air showers, with the models of the standard QGSP_BIC_HP reference physics user list (i. e. , Quark Gluon String with Precompound-Binary Intranuclear Cascade-High Precision cross sections from ENDF-VI library). These simulations allowed determining the number of secondary CR (neutron, proton, muon, and electron) energetic spectra per kinetic energy unit per area per primary particle. Altitude is handled by the database itself while the geomagnetic coordinates and the solar modulation of GCRs need a post processing step. Considering the galactic and solar CRs, the nuclear transport code (Geant4) can be used to simulate the extensive air showers and their impacts on the atmosphere  (Cheminet et al.
, 2013; Hubert & Aubry, 2017; Hubert & Cheminet, 2015). Air showers were described thanks to databases containing all the details of secondary particles including types, energies and angular properties. Moreover, altitude ranges from the ground to 45 km are considered. The implementation of the quantity magnetic rigidity is useful as particles with the same rigidity R, charge sign and initial conditions have identical trajectories in a static magnetic field. The rigidity R is defined as R = pc/Ze, where p is the momentum, c is the speed of light and Ze is the charge of the CR particles. The cutoff rigidities and the asymptotic directions have been introduced to specify the geomagnetic effects on CRs and to determine the CR spectral characteristics and the anisotropy near Earth but outside the magnetosphere from CR measurements at ground (neutron monitors, muon detectors) or by space-based detectors within the magnetosphere.
02 × 10 10 3. 1 × 10 9 7. 65 × 10 8 (GLE 5, X 5 = 8, η = 1, 2, 4, 8)(GLE 69, X 69 = 48, η = 1, 2, 4, 8) Abbreviations: GLE, ground-level enhancement; SEP, solar energetic particle. aimed at comparing the calculated ambient dose equivalents with flight measurements in quiet solar conditions. The exact paths of each campaign flight not being available, it was necessary to consider the standard deviations translating the path diversity of each investigated route. Realistic flight paths were extracted from the Eurocontrol Demand Data Repository (DDR) (Eurocontrol). Databases contain more than 25,000 flight paths operated from March 7th to 9th, 2019. Each path was described as a sequence of 4D values (date, universal time (UT), longitude, latitude, and geometric altitude). The date and the UT allow determining the solar potential from neutron spectrometer measurements  (Hubert, 2016; Hubert, Vernetto, et al.
, 2019)  or from NMs  (Ghelfi et al. , 2017; Maurin et al. , 2015). Comparisons presented in  Hubert and Aubry (2017)  showed a good adequacy of the calculations with the measurements. To expand the validation of the GLE model and the above mentioned Geant4 database, CR variations measured and calculated during the GLEs 5 and 69, and solar modulation during Forbush decreases were proposed.
Modeling of 774/775 CE and 993/994 SEP Events In the case of past events, the only known parameters are the event-integrated fluences issued from environmental archives. It is therefore essential to propose a hypothesis to describe the GLE time profile as well as the anisotropy function. Analyses consider data acquired during two well-known GLEs recorded during the modern era: GLE 5 and GLE 69. The formalism described by Equations 1 and 2 was used to calculate the differential SCR energy spectrum and the anisotropy function. Two additional parameters were introduced: First, X k which is a scaling factor relative to the recorded fluence spectrum and allowing to reach the past event characteristics. Second, another scaling factor η that is applied to the time profile of the GLE k (with k = 5 or 69).
Analyses of the Ambient Dose Equivalent considering 3 days of Air Traffic In this part, all flights are considered, not just Paris-New York, but also much longer flights including those to the US West Coast and East Asia, which can reach fairly high latitudes. Thus, a database containing flights operated during 3 days (March 7-9, 2019) of air traffic was used, which represents approximately 25,000 flights. Ambient dose equivalents were calculated for each flight, and according to several values of parameters (X, η). Figure  3  and Figure  4  present the calculated ambient dose equivalent in µSv for all flights taking off between March 7th and 9th, with flights referenced by their departure times. In addition to the quiet conditions presented in Figure  3a , several solar events scenarios were considered: the GLE 69 (b), the GLE 5 (c), and the 774/775 CE SEP event according to several descriptions: (X 69 , η = 1) in Figure  4a , (X 5 , η = 1) in Figure  4b , (X 69 , η = 4) in Figure  4c  and (X 5 , η = 4) in Figure  4d.
Analyses of Ambient Dose Equivalent as Function of the SEP Occurrence Probability Additional to the energetic characteristics of SEP, assessment of the occurrence probability of extreme SEP events is crucial for the modern space-based technological activities. These occurrence probabilities are investigated by using direct measurements for events that occurred during the modern era, and extended using the method of cosmogenic isotopes for past events. In the first case, the probability of SEP events was investigated as a function of the integral fluences of E > 30 MeV protons determined from measurements onboard the two satellites IMP-8 and GOES and from Greenland ice-core data for the prespace era  (Miroshnichenko et al. , 2014). Nevertheless, data issued from Greenland ice core were dismissed because they actually describe the comingled statistics of biomass burning in North America (and to a lesser extent, Eurasia), with plume transport and deposition events over central Greenland  (Wolff et al.
The ACFJ and the PEGASUS consortiums complement, for the rest of the world, data issued from the NOAA (National Oceanic and Atmospheric Administration) in the US for several decades. To illustrate the impact of altitude changing during an extreme solar event, simulations were performed considering the Seattle-Paris and the Dubai-Dallas flights described in the Part 3. 5. Results show that the dose level can be halved by reducing the cruise altitude by around 5,000 feet (∼1,500 m). A decreasing of the flight altitude by 4,000 feet, which must be done in consultation with air traffic control, leads to a decrease of the ambient dose equivalent of 1. 65 and 1. 57 factors for the Seattle-Paris and the Dubai-Dallas flights (operated with a Gulfstream V and a Boeing 77-200 airplanes, respectively).
eurocontrol. int/ddr). However, it is possible to build a realistic path database in using data accessible in https://flightplandatabase. com (particularly for detailed analyses applied to Seattle-Paris and Dubai-Dallas flights). All data needed to model air showers in Geant4 are detailed in  (Hubert et al. , 2015). The Geant4 open-source tool is accessible in http://geant4. web. cern. ch/. To perform calculations, the following models were used: standard QGSP_BIC_HP reference physics user list (i. e. , Quark Gluon String with Precompound-Binary Intranuclear Cascade-High Precision cross-sections from ENDF-VI library). The physical properties of the Earth atmosphere (pressure, temperature, chemical composition and density) are available in the International Standard Atmosphere (ISA: Atmosphere type, International Standard Organization, norm ISO 2533:197).
Data Availability Statement According to the particle type, for the dose equivalent conversion coefficients are included in these studies  (Pelliccioni, 2000;  Ferrari et al. , 1997a Ferrari et al. ,  , 1997b Ferrari et al. ,  , 1997c;; Sato et al. , 2007 Sato et al. , , 2011)). Data supporting realistic flight paths used in this work are available in the Eurocontrol Demand Data Repository, only with licensing, and.
The numerical integration of the Navier-Stokes equations is carried by an in-house solver using a fully implicit Finite-Element Method. The time integration is performed with an iterative Newton-Raphson-like approach. The chosen time step of 0. 1 corresponds to about 1% of the characteristic shedding period. The method is third order accurate in time and space and employs a pseudo-pressure formulation. The solver has been employed in recent fluidic pinball investigations for reduced-order modeling  (Deng et al. 2020; Noack et al. 2016 ) and for control  (Ishar et al. 2019). We refer to  Noack et al. (2003 Noack et al. ( , 2016) )  for further information on the numerical method. The code is accessible on GitLab on email request. The initial condition for the numerical simulations is the symmetric steady solution.
In this approach, we no longer consider a population but the database of all the individuals evaluated so far. Thus, we no longer need the replication and elitism operators of MLC. This choice is justified by the fact that we want to learn as much as possible from what we already know and avoid reevaluating individuals. To perform the crossover and mutation operation, individuals are selected from the database thanks to a tournament selection. A tournament selection of size 7 for a population of 100 individuals is used in  Duriez et al. (2016). That means that for a population of 100 individuals, 7 individuals are selected randomly and the among the 7, the best one is chosen for the crossover or mutation operation. For gMLC, as the individuals are selected among all the evaluated individuals, the tournament size is properly scaled at each call to preserve the 7/100 ratio between the tournament size and the size of the database.
This subspace is initialized by selecting N sub individuals. Two ways to build the subspace after the Monte Carlo process are listed below: • Choose the best individual: select the best N sub individuals evaluated so-far in the whole database. • Individuals near a minimum: select the best individual evaluated so-far and the N sub -1 individuals closest to the best one. The first approach has the benefit to comprise several minima candidates, whereas the second one is bound to lead to a minimum in the neighborhood of the best individual and relies on a given metric. Once the subspace is built, the next steps are similar to the downhill simplex method. As subplex and simplex are essentially the same algorithm applied to different spaces, we will not designate them differently. Following the situation, downhill subplex may call 1 (only reflection), 2 (expansion or single contraction) or N sub + 1 (shrink) times the cost function.
Several iterations of downhill subplex are repeated until at least N G individuals are generated. In this study, the same number of individuals generated with the evolution phase and the downhill subplex phase is chosen to balance exploration and exploitation. If the stopping criterion is reached, the most efficient individual in the database is given back. Otherwise, we restart a new cycle by generating new individuals with a new evolution phase, combining and modifying individuals derived by evolution and downhill subplex. However, the individuals built thanks to downhill subplex are linear combination of the original N sub individuals. These new individuals do not have a matrix representation which is necessary to generate new individuals with genetic operators in the exploitation phase.