dataesr/scientific-paragraphs-categorization huggingface dataset:
However, application of the same model to an independent test set (right column) here yields an accuracy of 0. 25 (would tend to 0. 5 over larger test sets); (iii) mistaking the objective: if, for each time bin, one counts the true positives (TP), true negatives (TN), false positives (FP) and false negatives (FN), one obtains a 0. 85 accuracy due to the dataset being unbalanced. This misses the fact that we are interested in cases of mainshocks being preceded by some signal, not of no signal not followed by a mainshock. In comparison, the true positive rate (TPR) is here only 0. 38. variables, and mistaking the objective. In this respect, almost none of the reviewed studies split data between a training set and an independent test set (Tab. 1). Flexible, high-variance, machine learning models will tend to overfit the data without stringent constraints, out-of-sample tests and corrections for model flexibility.
Although these theoretical frameworks and others will provide directions to follow in data exploration and model validation, they do not form the core of the GEFS, which is data-oriented and theoretically agnostic. In this second case, the main challenge is the creation of a large database for data analytics and forecasting. Data types include satellite images, in the range of tens to hundreds of Gb per source for a couple of years of recordings, navigation satellite data, in the range of several Tb per provider, other satellite data (e. g. DEMETER dataset is eight Tb in size), ground station data such as earthquake catalogs, geoelectric or air ionization time series, etc. (in Mb-Gb range per source and/or region). This means that the GEFS database will enter in the Big Data category, with everything that this entails in terms of data processing in volume, variety and speed of execution.
Quantitative analysis Analysis of the overall preparedness used descriptive statistics in SPSS V. 25. We explored the data to identify distribution of responses, trends and outliers. Data were first analysed with descriptive statistics using proportions for categorical variables. Analysis of the survey was primarily descriptive to discover differences between settings, geographical locations to compare how prepared organisations were and what issues arose as the pandemic progressed. Correlation was assessed using Spearman's rho test. Correlational analysis looked for relationships in key areas, such as perceived safety, access to PPE, ability to raise concerns and intention to leave as well as geographical differences across the UK. A probability below 0. 05 (p<0. 05) was considered to be a significant difference.
, 2018). The partitions were selected by Partition Model  (Chernomor, von Haeseler, & Minh, 2016). For BI we performed a model-based Markov chain Montecarlo-based phylogenetic analysis using MrBayes v3. 2. 2  (Ronquist et al. , 2012)  through Cipres Science Gateway  (Miller, Pfeiffer, & Schwartz, 2010) , treating each DNA region (rbcL, rsp4 gene, rps4 IGS, and trnL-trnF) as separate partitions. An evolutionary model for each DNA region was selected in jModelTest 2  (Guindon & Gascuel, 2003; Darriba et al. , 2015) , using the Bayesian Information Criterion  (Schwarz 1978 , Table  1 ). Each analysis consisted of two independent runs with four chains performing 50,000,000 generations, sampling one tree every 1,000 generations. For the BI and ML, GenBank sequences of Polypodium vulgare L. were used as the outgroup.
Divergence times estimations Divergence times were estimated with the software BEAST 2. 5  (Bouckaert et al. , 2019)  through the CIPRES Science Gateway  (Miller et al. , 2010). The data matrix was partitioned among the four markers and assigned the GTR model of substitution for the rps4 gene, rps4 IGS, and trnL-trnF intron+IGS, and the HKI model for the rbcL gene. The trees and clock models were linked. In the absence of reliable fossil for the ingroup, we used time estimations from the large-scale study on the time diversification of leptosporangiate ferns by  Testo and Sundue (2016)  for node calibration. We used calibrations for the following nodes with the respective ages: campyloneuroid clade + Adetogramma + Serpocaulon = 55. 84 ma; campyloneuroid clade = 49. 54 ma; Campyloneurum + Niphidium = 45.
64 ma; Campyloneurum = 35. 28 ma; Microgramma = 26. 73 ma; Niphidium = 5. 97 ma. We assigned a normal distribution for all calibrated nodes. We used an uncorrelated lognormal clock, and the birth-death tree prior, with the relative extinction rate set to 0. 5 and speciation set for 1. 0. Parameters and priors were set using BEAUti  (Drummond et al. , 2012). A starting tree topology was specified based on the resulting majority-rule Bayesian tree, using the package ape  (Paradis & Schliep, 2019)  in R (R Core Team, 2019) to match branch lengths to units of time specified for BEAST analysis. Two Markov chain Montecarlo runs were conducted using 5 × 10 7 generations with parameters sampled every 5,000 steps. Results from both BEAST runs were analyzed to confirm that stationarity, convergence, and effective sample sizes (ESS) were sufficient for all parameters using Tracer 1.
Acknowledgments: This work was supported by  FAPEMIG (Fundação de Amparo à Pesquisa do Estado de Minas Gerais)  through grant  CRA-APQ 01599-10 ,  CNPq  ( Conselho Nacional de Desenvolvimento Científico e Tecnológico)  through grants  478723/2010-5  and  563568/2010 , and for productivity grants, all attributed to AS, and the ATM " Biodiversité actuelle et fossile" of the Muséum national  d'Histoire naturelle (2012) attributed to SH. CNPq also provided research scholarships to TEA (grant numbers  555226/2010-7  and  202160/2011-4 ). We thank the  Coordenacão de Aperfeicoamento Pessoal de Nível Superior (CAPES)  for financing the 1st Scientific Publication Workshop of  Programa de Pósgraduação em Biodiversidade  through the  PROCAD-AM  grant  88887. 200472/2018-00. We would like to thank the  Muséum national d'Histoire naturelle de Paris, France (MNHN) , the  Service de Systématique Moléculaire (SSM -MNHN ) and  Céline Bonillo  for the support and help.
CONCLUSIONS The extensive sampling of Microgramma presented here supports the monophyly of the genus as currently circumscribed. Our results indicate that a considerable part of the broad morphological variation observed in the genus is homoplastic, as well as ecological interactions such as ant-association. The young age we found for the African lineage of Microgramma (15 Ma) corroborates a long-distance dispersal event from South America to Africa and reinforces its important role in the floristic relationships between South America and Africa. We already submitted the sequences to GenBank and the accessions will be added as soon as they are sent.
F. Proton acceleration The proton beam accelerated from the target backside was characterized in energy and angle using a combination of widely accepted methods, namely a radiochromic films (RCF) stack  23  and a Thomson parabola spectrometer  24. We used various target materials (plastic and metal) of thicknesses decreasing from 30 µm down to 0. 8 µm. 6] [27]. Indeed, for relatively thick targets as explored here, target normal sheath acceleration (TNSA) is expected to be the dominant ion acceleration process  [28] [29] [30] [31]  , with wellassessed characteristics (acceleration along the target normal, known scaling with laser intensity, known variation of beam divergence with energy). For this commissioning experiment, we focused only on an acceleration regime governed by TNSA, to be able to compare our results with the extensive collection of experimental data on TNSA gathered over the past two decades.
V. ACKNOWLEDGMENTS The authors would like to thank all teams of the laboratories which contributed to the success of the facility, that is all the CILEX consortium, which was established to build Apollon. This work was supported by funding from the  European Research Council (ERC)  under the European Unions  Horizon 2020 research and innovation program  (Grant Agreement No. 787539 , project  GENE-SIS ), and by Grant  ANR-17-CE30-0026-Pinnacle  from  Agence Nationale de la Recherche. We acknowledge, in the frame of the  GENESIS  project, the support provided by  Extreme Light Infrastructure Nuclear Physics  ( ELI-NP) Phase II , a project co-financed by the  Romanian Government and European Union  through the  European Regional Development Fund , and by the project  ELI -RO -2020 -23  funded by  IFA (Romania) , to design, build and test the neutron detectors used in this project, as well as parts of the OTR diagnostic.
The Oto score was published in 2007 by the Melbourne group  7  and consists of five parameters largely corresponding to traditional standard donor criteria. Notably, paO2/FiO2 (arterial partial pressure of oxygen/fraction of inspired oxygen) ratio is perceived most important and the variable is given double weight. An adaptation of the Oto score was presented by Smits et al. based on multicenter data from Eurotransplant (ET). 8 This ET score added a donor history variable, introduced separate classes for missing values, and removed the double weight on the paO2/FiO2 ratio. Grimm et al. were the first to propose a scoring system based on both donor and recipient factors (MALT score). Derived from the United Network of Organ Sharing (UNOS) data, it aimed to predict 1-year mortality after lung transplantation.
| Donor and recipient data A list of all lung donors offered to the lung transplant program at the Medical University of Vienna was provided by the ET organization. Detailed data for all organ offers were retrieved from the official ET donor registry. Perioperative as well as postoperative follow-up data for transplanted recipients (group III) were obtained from our institutional databases. Primary graft dysfunction (PGD) at different time points was assessed according to 2016 ISHLT guidelines. 12 diological assessment for grading PGD was provided by trained chest radiologists of the Department of Biomedical Imaging and Image-guided Therapy of the Medical University of Vienna.
Histological Characterization of Human Coronary Thrombi Thrombi from 84 patients who underwent primary percutaneous coronary intervention were harvested from the occluded coronary artery segments. Recanalization was performed with 0. 014" guide wires, followed by thrombectomy with Export Advance, Eliminate. Retrieved material was fixed with paraformaldehyde, embedded in paraffin, and sectioned, and sections were processed for immunohistochemistry to detect platelets using an antibody against CD42b. The images were acquired with a bright-field light microscope, Nikon Eclipse Ni (Nikon, Paris, France), captured using a Nikon Digital Sight DS-Ri 1 camera and the option grab large images of the Nikon NIS-Elements software (Nikon). The platelet density was measured using the Bersoft Image Measurement software.
Institutional Review Board Statement: The analysis of intracoronary thrombi of patients was conducted in accordance with institutional and governmental guidelines and was approved by the ethical committee of the institution that participated in this study, and patient material/data were registered in the Fribourg STEMI (ST elevation myocardial infarction) Fast Track Registry (EVALFAST). Informed Consent Statement: Data in the EVALFAST registry were collected retrospectively from 2008 and prospectively from 2010 onwards. Only patients with a diagnosis of STEMI and having given their written consent were included. Data Availability Statement: All data are available in the article or supplementary material.
The survey period was limited to  days so as not to violate the capture-recapture closure assumption  (Kery & Royle, ). Individuals of the focal species were identified based on their unique coat patterns, using the open-source pattern recognition software Hotspotter  (Crall et al. , ) , and then verified manually. We selected our sampling occasions to stretch across midnight (from .  to .  the following day) as all our study species are predominantly nocturnal, with sampling occasions set to -day periods. We constructed spatial capture histories for all the identified individuals for the  sampling occasions. As we did not obtain images of both flanks of all individuals, we estimated density first by excluding individuals for which we only had leftflank images, and then by excluding those for which we only had right-flank images, and compared the results.
We used a maximum likelihood modelling approach to fit spatial capture-recapture models to estimate population densities of the four species. Models were implemented using the package secr . .  in R . .  (R Development Core Team, ). Density was estimated within the state space, which consists of an explicit spatial region within which sampling occurs. This area includes the trapping grid and a buffer zone, to ensure that the activity centres of all individuals potentially exposed to sampling would be included in the buffer area  (Kery & Royle, ). We used the number of days a camera station was active (i. e. trap-nights) as a variable in the detection process. We examined the effect of varying the buffer size (- km, with .  km increments; Supplementary Fig.  ) to test its influence on predicted density estimates, using buffer sizes that were sufficiently large to include all activity centres of individuals exposed to trapping.
Acknowledgements We thank  Earthwatch  through the  Neville Shulman Award , and  Nelson Mandela University , for funding;  Marc Engler ,  Annie Casey ,  Nadine-Josie Holmes ,  Jessica Jones ,  Chris Duff ,  Anasthasia Sanchez De Launay ,  Maya Broadbank ,  Sarah Marsh ,  Max Hargreaves ,  Aaron Eastwood , and  Joe Jacobs  for assistance with camera-trap image classification and fieldwork; Platjan landowners for permission to access their properties;  Markus Jebsen ,  Riley De Charmoy Bouchet ,  Syanne Kirby , and the  Limpokwena Nature Reserve  for their hospitality during data collection; and a reviewer and the Editor for their constructive feedback.
Transmission Electron Microscopy (TEM) The exosomes were fixed overnight at 4 • C in 2. 5% glutaraldehyde/0. 1 M sodium cacodylate buffer solution and were subsequently treated with 1% OsO 4 /0. 1 M sodium cacodylate buffer. Ethanol solutions at an increased concentration were used for dehydration and then fixed in epoxy resin (EPON™, Hexion, Houston, TX, USA). Ultramicrotome was used for the preparation of ultrathin (LKB, Stockholm, Sweden) which was stained with heavy metal solutions (1% uranyl acetate and 1% lead citrate) and analyzed by TEM (Tecnai G12, FEI Company, Hillsboro, OR, USA) at an acceleration voltage of 100 kV. The image acquisition was performed by a video camera (Tietz, Tietz Video and Image Processing Systems GmbH, Gauting, Germany) and an imaging software (TIA, FEI Company, Hillsboro, OR, USA) [49].
Spectral analysis can both recognize autofluorescence as a specific signal and as a defined color, to provide accurate results. Spectral deconvolution (unmixing calculation) was carried out using SP6800 software (1. 6. 1. 7136 version). All data were exported as FCS3. 0 and analyzed using Kaluza Flow Cytometry software 1. 2 version (Beckman Coulter, Brea, CA, USA).
Analytical Ultra Centrifugation Analytical ultracentrifugation  [31]  was performed in a ProteomeLab XL-1 centrifuge (Beckman) using an AN-60TI rotor (Beckman) at 20 • C. Four hundred µL of purified rAAV8-γSGC were loaded into each sample cell. A first set of runs (absorbance and interference measure) was performed at 3000 rpm in order to set the wavelength of analysis and the laser position properly. Absorbance and interference monitoring were performed at 16,000 rpm from 2 h to 2 h 30 min. Data were collected using ProteomeLab software (Beckman) and treated with Sedfit software. Runs were performed against a reference rAAV8 production produced without any transgene.
The baculoviruses were passaged on Sf9 cells cultured in flasks to reach ten serial A critical point is the genetic stability of the baculoviruses during the amplification of virus stocks and their ability to conserve the transgenes of interest. To investigate the genetic stability of the baculovirus genomes, we performed viral passages starting with viral stocks amplified for two passages following plaque purification of the baculovirus clones. The baculoviruses were passaged on Sf9 cells cultured in flasks to reach ten serial passages. At passages 4, 7, and 10, qPCR analysis were performed on either baculovirus DNA polymerase gene, AAV rep and cap genes and on the ITR region of the rAAV transgene to measure the baculovirus and rAAV titers when the Monobac was used. Two data sets are presented for each baculovirus constructs.
Acknowledgments: We are thankful to assistance provided for animal work by  Marie Liabeuf  and  Béatrice Marolleau. We would like to thank  Christophe Georger  for histological work;  Jean-Baptiste Boucheteil  and  Cyril Luc  for performing the analytical ultracentrifugation experiments; and  Jeanette Isabell Zanker ,  Aubrey Bailey  and  Marjut Köylijärvi  for proofreading of the manuscript.
Recently it was demonstrated that this problem can be overcome by using a two stage indexation method  [22, 23]. In this method, the pat-terns are first indexed with the matrix templates, masked with the matrix template solution, and subsequently indexed with the precipitate phase templates. Our initial trials showed that the conventional method of NBED data collection utilizing the ASTAR system (NanoMegas) was insufficiently sensitive to detect the faint G-phase reflections. Reliable indexing of the diffraction patterns of small precipitates with complex crystal structure requires electron detection with the highest possible resolution and dynamic range. Hence, diffraction pattern data was collected with the fast (up to 384 frames/s) TemCAM-XF416 pixelated CMOS detector (TVIPS). A comparison of data collected with the ASTAR and TVIPS systems is given in supplementary materials.
The precipitates were 10-20 nm in diameter, enriched in Si, Ni, Ti and Mn, and depleted in all other alloying elements. No other irradiation induced phases were found in this steel, making this material ideally suited to study G-phase. Electron transparent samples for TEM investigations were prepared via focused ion beam cross-section lift-out in a SCIOS 2 HiVac (Thermo Fisher Scientific) using a final cleaning at 2 kV. The NBED data was collected using a camera length of 80 cm and a convergence angle of approximately 0. 5 mrad. A map of 260 × 200 scan positions was collected with a step size between 1-2 nm. The region of interest was tilted slightly away from a 110 zone axis so that only few matrix reflections would be strongly excited. The raw data from the camera was converted to the. BLO file format compatible with the ASTAR software (NanoMegas) using a custom tool  [28]  and analyzed with methods and tools described in refs.
In the dataset described here, the camera length is large for the matrix phase resulting in few matrix reflections in each pattern; this may increase uncertainty in determining the matrix orientation. Furthermore, a more quantitative estimate of the angular resolution might be obtained via automated parameter studies; an enabling solution is being developed within the Pyxem library  [31]. FCC to BCC transformations tend to be associated with irrational interface planes containing an invariant line along an irrational lattice vector which can be predicted from lattice parameter ratios  [33]. If it is assumed that the G-phase unit cell represents 4 × 4 × 4 BCC unit cells and the ratio a f cc /a bcc = 3. 6/(11. 5/4) = 1. 25, plate-shaped morphologies with near KS relationship and an invariant line close to 1 7 8 in the FCC lattice (or 111 in the BCC lattice) are expected.
of G-phase precipitates of 10-20 nm in size detected using three different methods. a) A TEM DF image by using a {006} G-phase reflection. Due to the different orientation variants, some of the precipitates are not visible in this image. b) STEM-EDX showing particles rich in Si and Ni and depleted in Cr and Fe. c) The same is observed in APT and also shows that the particles are enriched in Ti and Mn. The Fe and Cr ion maps are not shown. 20 2 Illustration of the indexing procedure and exploration of the dataset. a) A diffraction pattern from the matrix with the best fit template superimposed as white circles. Additional anomalous spots and the direct beam are also circled in cyan and green respectively. b) A diffraction pattern showing additional diffraction spots originating from edge on Frank loops.
Acknowledgements We acknowledge funding through  BiGmax  (https://www. bigmax. mpg. de/), the  Max Planck  research network on big-data driven materials science. This work was in part supported by the  U. S. Department of Energy, Office of Nuclear Energy  under  DOE Idaho Operations Office  Contract  DE-AC07-051D14517  as part of a  Nuclear Science User Facilities experiment. We want to acknowledge SCK-CEN and the  MYRRHA  project for supplying the material, the staff at MIBL for assisting with the ion irradiations, and Dr. X. Zhou for the valuable discussion.
21 3 21 of G-phase precipitates of 10-20 nm in size detected using three different methods. a) A TEM DF image by using a {006} G-phase reflection. Due to the different orientation variants, some of the precipitates are not visible in this image. b) STEM-EDX showing particles rich in Si and Ni and depleted in Cr and Fe. c) The same is observed in APT and also shows that the particles are enriched in Ti and Mn. The Fe and Cr ion maps are not shown. 20 2 Illustration of the indexing procedure and exploration of the dataset. a) A diffraction pattern from the matrix with the best fit template superimposed as white circles. Additional anomalous spots and the direct beam are also circled in cyan and green respectively. b) A diffraction pattern showing additional diffraction spots originating from edge on Frank loops.
E. Data Acquisition System The ILL instrument control group put together the acquisition system in 2018 for the purpose of the first experimental campaign. A 16 channels charge sensitive preamplifier card (developed by ILL) shapes the signals of the16 3 He PCs. They are then fed to two synchronized digitizers (CAEN V1724, 8 channels, 14 bits 100 MS/s Flash ADC) housed in a VME crate. The digitizers run a real time digital pulse processing embedded program (CAEN DPP-PHA) to process the data flow, detect events and output their arrival time and energy (i. e. the pulses' amplitudes). Raw data buffers are stored into binary files in "list mode" for further data processing. The crate houses a third CAEN acquisition card (V1751) to record monitoring signals from the beam shutters. An optical fiber links a monitoring computer to the VME crate.
B. Filtering parameters of the 3 He proportional counters After the preamplifier stage, signals issued by the 3 He PCs were digitized, processed and filtered by the DPP-PHA (which stands for Digital Pulse Processing, Pulse Height Analysis) algorithm implemented in the CAEN V1724 digitizers. The overall quality of the measurements is directly linked to the parameters of the filtering algorithm (see Tab. II). The parameters used for data taking are listed in Tab II. The signal threshold, triggering pulse processing, was tested individually for each channel. This trigger threshold (TT) has a role of discriminating the pulses from the fluctuations of the baseline (statistical and/or parasitic signals). If the TT is too low, many non-physical events are processed and recorded: that generates additional pile up and dead time.