dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis All statistical analyses were performed in R version 4. 0. 2. We defined the time to clearance as the time to the first recorded CT value equal to 40 with right censoring at the last recorded value if all values were less than 40. We compared the survival curves of the COVID-19 vaccinated individuals and the unvaccinated individuals using the log-rank test (as implemented in the R package survival ). For models 1-2 of viral clearance we considered CT values of 40 (∆CT of 0) as left censored. The likelihood of the model parameters θ given the data is thus equal to 0 -∞ f (x|θ), where f (•|θ) is the model likelihood. Bayesian hierarchical models were coded in stan and fitted using Hamiltonian Monte Carlo with the rstan package  [17]. For model 2, to avoid label switching across the parameters A 0 , B 0 and α, β, we used the ordered vector type.
Consistent with the previously published analysis of the same dataset  [2]  and other separate data  [13] , the single exponential model suggested a faster clearance rate in the vaccinated compared with the unvaccinated subjects (p=0. 05 comparing random effect terms for the slope coefficient α). As measured by the AUC estimated until day 5, day 7, or day 14, the log-linear model estimated larger reductions in AUC in vaccinated relative to unvaccinated individuals than the bi-exponential or the spline regression models (Figure  2 ). The virological endpoint most commonly used in COVID-19 clinical trials is the time to viral clearance (a model-free measure, although the exact definition of this measure varies across trials). Time to clearance as a summary statistic is 'inefficient' because it is dependent on the initial viral load; it does not borrow information across time points; and it only uses the noisy estimate of when the viral load first reaches the lower limit of detection.
Sample size estimation Previous work has estimated that sample sizes of approximately 500 patients per arm are required for clinical trials evaluating differences in time to viral clearance as primary end-points  [11]. We postulated that by estimating the rate of clearance directly from daily serial viral load measurements, necessary sample sizes could be reduced substantially. By estimating the rate of clearance (even under a mis-specified model) information is borrowed across the serial viral load measurements, thereby resulting in a gain in efficiency relative to the standard approach of estimating the time to clearance. To explore this, we simulated data under the posterior predictive distribution   of model 2 (bi-exponential decay) fitted to the NBA dataset. We assumed effect sizes equal to 30% and 50% increases in the population clearance rate parameters of the model.
Acknowledgments This research was funded, in whole or in part, by The  Wellcome Trust. A CC BY or equivalent licence is applied to author accepted manuscript arising from this submission, in accordance with the grant's open access conditions. NJW is a  Principal Research Fellow  funded by the  Wellcome Trust  ( 093956/Z/10/C ). JAW is a  Sir Henry Dale Fellow  funded by the  Wellcome Trust  ( 223253/Z/21/Z ).
4c ). Dioxygen has no access to heme d via the solvent accessible channel to heme b 595 because heme d itself blocks a deeper penetration of substrates to the active site. In E. coli bd-I, another long substrate channel for oxygen on the opposing side was described, leading from CydB to heme d on CydA  21, 22. A similar channel is also present in bd-II, leading from AppB to Glu99 on AppC (Fig. 4b ). However, this channel seems to have a smaller diameter, in particular due to the methyl group of Ala100 on AppC that narrows the channel diameter approximately by one fourth. At the homologous position, the bd-I features a Gly residue that widens the channel. To further analyze the geometry of the putative oxygen channels of both oxidases, we probed the radii with the program Caver 3. 0  42. The analysis of the derived models revealed radii of 1.
Excess detergent was removed by an addition of a 40-fold mass excess BioBeads (SM-2 resin, BioRad, Feldkirchen, Germany) and further incubation of 3 h at 4 °C under stirring. Excess amphipols were removed by size exclusion chromatography (Superose 6 Increase 10/300 GL, GE Healthcare), equilibrated in 20 mM MOPS, 20 mM NaCl, pH 7. 0. Peak fractions were pooled and used for further analysis. For cryo-EM the samples were supplemented with 1 μM aurachin D prior to placing them onto the cryo grids. Cryo-electron microscopy and data analysis. Glow-discharged cryo grids were prepared with 2. 5 µL protein solution (5. 6 mg/mL) on R1. 2/R1. 3 Quantifoil holey gold grids. Grids were incubated for 45 s and blotted for 6. 5 s prior to plunging into liquid ethane and flash-frozen using a Vitrobot (FEI Company).
Cryo-EM recordings were made at the EM Facility at the Rudolf Virchow Center, Würzburg, Germany, with a Titan Krios G3 (Thermo Fisher Scientific) equipped with a Falcon III direct detector. Micrographs were taken at 300 kV with a ×75,000 magnification and a calibrated pixel size of 1. 0635 Å. Movies with 47 frames each were collected automatically with EPU at an exposure time of 74. 99 s and a total electron exposure of 79 e -/Å 2. The final data set contained 1836 movies with a targeted under-focus between 1. 4 and 2. 4 µm (Supplementary Table  1 ). All movies were dose weighted and motion-corrected with Motioncorr 49 , CTFs were determined using CTFFIND-4. 1  50. Convolutional neuronal network-based particle picking of all micrographs was conducted with crYOLO 51 using the provided general network.
The remaining particles were further refined and purged from residual artifact particles with a 3D classification on the initial model to a subset of ~40,000 particles. The respective 3D class was taken as model for a 3D auto-refinement (in several rounds, later with an imposed C2 symmetry). The remaining ~40,000 particles were 2D classified and the resulting class averages were used as template for another round of particle picking. These new particles were again 2D and 3D classified, and the resulting 120,000 particles were used for a final 3D autorefinement with following post-processing imposing C2 symmetry to a resolution of 3 Å. The cryo-EM map was taken for protein modeling in COOT 0. 8. 9. 1  53. The homologous bd-I structure (PDB: 6RX4) was fitted into the map as starting model and mutated to the respective sequence.
All steps were conducted at 30 °C. The reaction chamber was filled with 2 mL buffer (20 mM MOPS, 20 mM NaCl, 0. 003% LMNG, pH 7. 0), 10 µL DTT (1 M) and 5 µL duroquinone in ethanol (100 mM) and incubated for 1 min. 10 µL bd-II in LMNG buffer (2 mg/mL) were added to start the reaction. After 2 min, the reaction was inhibited by adding various amounts (1-300 nM) of aurachin C and aurachin D, respectively. The enzymatic activity was corrected for the non-enzymatic activity that was about 5% of the entire activity. Each data point was measured in triplicates. The standard deviation of each measurement is provided. Dynamic substrate channel analysis. As starting point for substrate channel analysis, a conformational ensemble was obtained for both E. coli bd-I and bd-II through molecular dynamics (MD) simulations with the programs of the Schrödinger software Suite 2021-1 (Schrödinger LLC, NY).
First, the cryo-EM structures of bd-I (PDB ID: 6RX4) and bd-II were prepared with PrepWizard 55 by adding missing hydrogen atoms, adjusting bond orders and formal charges of smallmolecule ligands. PROPKA  56  was used to generate the ionization states of polar amino acids at pH 7. 0. The structures were energy-minimized using the OPLS4 force field 57. MD simulations were carried out with Desmond 58. The optimized structures were embedded in POPC membranes within orthorhombic periodic boundary systems and solvated with TIP3P water molecules, while neutralizing the charge of the systems with counter-ions. After an equilibration protocol, the production of MD simulations was conducted for 100 ns in an NPT ensemble at 300 K regulated by a Nosé-Hoover thermostat and a Martyna-Tobias-Klein barostat.
Data availability The cryo-EM maps have been deposited in the Electron Microscopy Data Bank (EMDB; https://www. ebi. ac. uk/emdb) under the accession number EMD-13048. The atomic model has been deposited in the worldwide Protein Data Bank (wwPDB; https:// www. wwpdb. org/) under accession number 7OSE. For structural alignments, the PDB entries 5DOQ, 6RKO and 6RX4 were used. Source data are provided with this paper.
Contaminants in groundwater are a major issue worldwide. Temporal trends of such occurrences in French groundwaters were evaluated for several active substances of pesticides belonging to different chemical classes, to identify key factors explaining groundwater contamination. Our study relied on exploitation of a French national database (ADES, created in the mid-1990s and remarkable for the available data, including over 88 million analyses). Temporal changes in the frequency of exceeding a reference value of 0. 1 µg/L for several substances were determined at yearly and monthly scales. Such trends were examined by distinguishing different periods according to changes in regulations (new approval, withdrawal, or dose reduction), and were combined with data on effective rainfall as a proxy for groundwater recharge, on aquifer lithology, and on sales of active substances as a proxy for actual applications.
, 2005) , environmental data such as the hydrogeological setting  (Fonseca et al. , 2019; Mas et al. , 2020) , or the hydrodynamic context  (Lapworth et al. , 2006). In most cases, however, the number of observations is relatively small and generally concentrated in a small enough geographic area for drawing site-specific conclusions. We, however, propose to examine-at a national scale and using multi-year monitoring data since the mid-1990s-the evolution of groundwater quality in France. This evolution may be due to changes in pesticide use as driven by regulatory evolution, but also to changes in the hydrogeological and climatic context. As far as we know, this is the largest dataset ever used for this type of exercise.
Groundwater-quality database In France, since the mid-1990s, the Ministry for the Environment has set up a national open-access database coordinated by the French Geological Survey (BRGM) on groundwater, called ADES (https://ades. eaufrance. fr/). This base contains data from sanitary and environmental monitoring networks, covering both quantitative (groundwater levels) and qualitative aspects. Today, it contains over 88 million water analyses from about 75,000 observation points. Launched in 2007 and fully operational in 2009, the monitoring networks were structured to answer the WFD objectives and its directive EC 2006/118 on "The protection of groundwater against pollution and deterioration". Creating these networks i) increased the number of analyses, ii) stabilized the number of monitored wells and iii) obtained a wider and patrimonial vision, earlier pesticide monitoring tended to focus on known or suspected contaminated areas.
Molecules studied The ADES database contains the results of concentration measurements for several hundreds of active substances. A selection was thus made of the most frequently quantified active substances in French groundwater. As the monitoring of metabolites is generally more recent and less homogeneous, we focused on the active substances for this review of data over a longer time span. Other criteria retained for covering different situations, included evaluation of national regulations (and thus of uses), chemical classes, and crops to protect. The main information is summarized in Table  1. We retained atrazine, metolachlor, isoproturon and chlortoluron, all frequently detected during a national campaign  (Lopez et al. , 2015). In addition, molecules with a similar use in cropping terms were selected as well, such as dimethenamid and acetochlor that are much used on maize, like metolachlor.
Pesticide and herbicide sales In France, since 2009 and following national regulations, all distributors of crop-protection products must declare their annual sales figures for nation-wide monitoring. These data are stored in the National Crop Protection Products Sales database (BNV-D). The information is available at a departmental (provincial) scale. A limit to using these data is set by the fact that sales are referenced by the municipality of the sales point. More recently, the referencing has changed to the municipality where the buyer is headquartered, which may differ from where a substance is actually used. It is thus clear that such data can only be used at a national or departmental scale, or over large surfaces, as using such data at a local scale may introduce a strong bias. Faced with such uncertainties on where the substances were used and possible geographical discrepancies between sales and actual use, we decided to aggregate the data by year for the whole of France in order to highlight the main trends.
A standard for groundwater bodies Groundwater bodies are the evaluation units of the Water Framework Directive; they are defined as a distinct volume of groundwater within one or several aquifers, their boundaries being based on hydrogeological criteria and, if necessary, anthropic pressures. Such groundwater bodies are defined by six types of hydraulic functioning (alluvial, sedimentary, volcanic edifice, intensely folded, basement, locally impermeable), by their condition (confined or unconfined) and by other attributes. Of the 589 groundwater bodies recorded in a 2013 French database, 117 are in an alluvial domain, 299 in a sedimentary environment, 1 in a volcanic edifice, 36 in folded rocks, 51 in a locally impermeable aquifer, and 85 in basement rocks. We examined the groundwater quality data by type of associated lithology, and-at the scale of specific water bodies-also in terms of surface crop types.
Similarly, even though the chlortoluron sales figures for 2009 and 2011 were higher than those for 2008, the frequency of exceedance was higher for the wettest year  (2008). Year 2017 stands out for its high frequency with respect to rainfall and sales. The two molecules isoproturon and chlortoluron have a similar leaching profile with a GUS index of 2. 6 and quite similar sales figures compared to other active substances; in this respect, it should be stressed that since 2004 only one or the other substance can be applied on a plot during a single year. Study of the entire dataset, however, does not show a clear structural trend as was seen for chloroacetamides, and other factors should be considered. Herbicides for wheat can be bought for application during sprouting, but are also used during tillering if required by the conditions.
Conclusions - We analysed monitoring data on groundwater quality in France at a national scale over a period of more than twenty years. This provided insight into the short-and medium-term impact of changes in regulations governing pesticide use (withdrawal, dose reduction, or new marketing authorization), on the frequency of exceeding the reference value of 0. 1 µg/L. The persistent exceedance of molecules in groundwater after withdrawal is probably related to a conjunction of several factors, such as (1) limited degradation of active substances within the unsaturated and saturated zones;  (2)  long transfer times in the unsaturated zone and a long residence time; and (3) the possible remobilization of active substances from the unsaturated zone-especially soil-over periods that may last several years.
Even though recent dose reductions for, e. g. , isoproturon and chlortoluron probably were beneficial in reducing substance transfer to groundwater, it is difficult fully to appreciate their impact on current concentrations just by working on data collected at a nation-wide scale. France can rely on a remarkable database regarding groundwater quality, but more local data on actual use are necessary for a reliable evaluation. Today, even though the national databases have been greatly enriched over the past decade, for fully understanding the real impact of mitigation measures it is necessary to collect, make available and cross-check new data. These spatialized data are particularly important for active substances applied on crops that are unequally distributed throughout France, and it would be pertinent to develop a similar approach that is aimed at a more local scale when data become available.
Acknowledgements The work at the origin of this paper was carried out in the framework of several projects, co-financed by the  French Office for Biodiversity  and the  BRGM , and more particularly of the  TRENDNAT  project. The authors thank  Nolwenn Croiset , who contributed to the initial work. H. M. Kluijver  translated and edited the original French version of the paper into English, and edited the revised version.
Plasmid construction and transformation of P. tricornutum The vector pPha-NR carrying the nitrate reductase promoter and the ble gene for zeocin resistance  (Chu et al. , 2016)  (GenBank accession number JN180663, kindly provided by Prof. P. Kroth), was used as backbone for all plasmid constructions. The DNA fragments used for gene fusion and cloning in the final constructs were amplified by PCR using Q5 DNA polymerase (New England Biolabs, Evry, France) under standard conditions. The primers are specified in Supporting Information Table  S1. The amplified fragments were assembled in the vector, previously digested with EcoRI and HindIII, by the sequence and ligation independent cloning (SLIC) method  (Jeong et al. , 2012). The genes coding for a (p)ppGpp synthetase (SYN) and an inactive mutant form (D275G) of this synthetase (SYN D>G ) were obtained by PCR, using plasmids described in  Sugliani et al.
(2016)  as templates. SYN corresponds to the (p)ppGpp synthetase RelA from E. coli (residue 1 to 386). To target the enzymes to the chloroplast, the genes were fused by PCR to the sequence coding for the bipartite targeting sequence of the chloroplastic gamma ATP synthetase of P. tricornutum (GeneBank accession number U29898) whose ability to target proteins to the chloroplast is well characterized  (Apt et al. , 2002; Liu et al. , 2016). A Kozak sequence (AAG) was included in the primer before the ATG translation start site to facilitate translation. The final constructions were used to transform cells by particle bombardment as previously described  (Falciatore et al. , 1999; Kroth, 2007). Full details of the transformation procedure are provided in Methods S1. Multiple independent transgenics lines were used for each construction in subsequent experiments.
Light microscopy and cell measurement Light microscopy images of live cells were taken using a Motic BA410 microscope equipped with a Moticam 1080 camera (Motic, Barcelona, Spain). Images were used to determine the length and width of individual cells using the MOTIC IMAGE 3 PLUS software after calibration of the microscope. For fluorescence microscopy, cells were incubated with the fluorescent dye AC202 as described in  Harchouni et al. (2018). Fluorescence was visualized in an epifluorescence microscope Eclipse 80i (Nikon) using the DAPI filter cube (excitation filter, 360BP40; emission filter, 460BP50). Images were acquired using MS ELEMENTS imaging software (Nikon, Melville, NY, USA). Images were merged using IMAGEJ software.
Mass spectrometry analysis Protein extracts (50 µg protein) from three SYN lines, two SYN D>G lines and one WT, on equal numbers of cells, were loaded onto a gel (SDS-PAGE) and the band from the stacking gel corresponding to the total proteins was excised and submitted to in-gel trypsin digestion for proteomic analysis as previously described  (Santin et al. , 2018) , with minor modifications. In parallel, total proteins were also separated to analyse the protein profile in the gel (Fig. S2 ). Tryptic peptide samples were quantified by a colorimetric peptide assay (Pierce, Thermo Fisher Scientific, Waltham, MA, USA) and aliquots of 200 ng were injected by LC-MS/MS. Two LC-MS/MS injections were performed per condition (technical replicates). Spectral data were processed for protein identification and quantification using the MaxQuant computational proteomics platform (v.
The major groups of proteins showing differential accumulation in SYN are listed in Table  1. Unexpectedly, many chaperones and co-chaperones showed higher levels of expression in SYN, and the chaperone heat shock protein 20 (HSP20; accession number B7G195) showed the greatest increase. The differentially expressed chaperones in SYN are encoded by nuclear genes and have predicted cellular localizations. Four chaperones, including HSP40 and one isoform of HSP90, contain the ASAFAP hexapeptide motif that predicts likely chloroplast localization  (Gruber et al. , 2015). Other chaperones have signal peptides for the secretory pathway without an ASAFAP motif, suggesting localization in the endoplasmic reticulum. Some chaperones, such as the Lon protease, which functions as both a chaperone and a protease, are predicted to be mitochondrial.
Acknowledgements This work was supported by the  Agence Nationale de la Recherche  ( ANR-15-CE05-0021-03 , SignauxBioNRJ) and the IJPB Plant Observatory technological platform. The IJPB is supported by  Saclay Plant Sciences-SPS  ( ANR-17-EUR-0007 ). LA thanks  Research England  for E3 funding. We thank  J. Bartoli  and  E. Bouveret  for kindly providing 13 C-ppGpp. Electron microscopy experiments were performed on the PiCSL-FBI core facility at the  IMM/IBDM , member of the  France-BioImaging national research infrastructure  ( ANR-10-INBS-04 ) and the authors are especially indebted to  A. Kosta ,  H. Le Guenno  and  F. Richard. Lipid analyses were performed at the  HelioBiotec platform (CEA Cadarache ).
We investigate the determinants of ICO campaigns' presence and success using data on 503 initial coin offerings (ICOs) from 60 countries that took place between 2015 and 2018. We took individual project perspective and country-wide perspective into account. Our findings show that expert ratings, insider retention, and resource-related signals, such as the number of team members and advisors, contribute positively to ICO funding success and post-ICO activity. Conversely, organizing presale and bonuses contribute negatively. Moreover, we established that countries' financial system development and ICO-related legal certainty boost the crypto-market. More importantly, we also document that countries' cultures foster ICO market development.
Country-level variables In the analysis of the country-level determinates, we retrieved data from ICObench and used three alternative dependent variables. The first dependent variable presents the number of ICOs in a given country. The second dependent variable reflects the number of Softcap reaches in a given country. The third and last dependent variable is the number of Hardcap reaches in a given country. To the best of our knowledge, the first dependent variable proxy provides the overall activity of ICOs in a given country. We hope that the results will shed some light on the ICOs' geographic dispersion presented in Figure  3. The second and third dependent variables are proxying for the ICOs' successes, which differ across. To include a wide country-level perspective to the research we employ set, financial system-related, legal system-related, national culture, and policy uncertainty proxies.