dataesr/scientific-paragraphs-categorization huggingface dataset:
3D maps of HA orientation in bone and mineralized cartilage obtained by XRDTT. Performing tensorial tomography analysis of the weakly textured HA002 diffraction data, we could for each voxel within the bone and mineralized cartilage region obtain the local preferred orientation of the unit cell c-axis of the HA crystallites. In the XRDTT reconstruction procedure (cf. "Materials and methods") a uniaxial texture model based on spherical harmonics was assigned to each sample voxel  40, 41, 56. The resulting orientational maps were 3D registered with the corresponding PPC-CT tomograms to relate the HA orientation maps to the bone and cartilage morphology. Co-registered PPC-CT and XRDTT data are shown in Fig. 3  for three intersecting and orthogonal cross-sections through the sample. Magnified views are provided to visualize the local preferred orientation.
This could be an adaption of the bone matrix due to the incorporation of cartilage canals into the ossification front  18, 64. In the recent article by Grünewald et al. 16  , they describe deviations between the XRD and SAXS based tomographic reconstructions, and speculate that the old truth of the crystallographic c-axis coinciding strictly with the long axis of the crystallites might need revision. Despite the coarse resolution and the low signal-to-noise ratio of our experiment, a possible explanation for the deviations we observe (cf. Fig. 4 ) is that similar mechanisms play a role. Deep into the bone, we observe that both the HA crystallite c-axis (from XRDTT) and the crystallite symmetry axis (from SASTT) appear to the directed towards the bone-cartilage interface, cf. Fig 4. Whereas a detailed assessment of the relation between the HA crystallite orientation and the spongiosa morphology was outside the scope of this study, a simple orientation analysis of the bone morphology based on the PPC-CT data is provided in the SI, S8.
Acknowledgements Federico H. Cova ,  Manuel Guizar-Sicairos  and  Ragnvald H. Mathiesen  are thanked for discussions regarding the scattering-contrast measurements and reconstructions. ESRF-The European Synchrotron is thanked for beamtime at ID15A through proposal LS-2810. We thank the  Research Council of Norway  for financial funding through FRINATEK (# 275182 ),  NANO2021  (# 272248 ) and its  Centres of Excellence funding scheme  (# 262644 ).
, 2016). However, a step is clearly picked up by quartz content showing another major rapid increase from ∼ 20 %-∼ 70 %, suggesting, together with δ 15 N, further drying and catchment erosion while TOC remains low (∼ 0. 5 %-∼3 %), and later recovery (∼ 12 %) (Fig. 8 ). Increased sediment input and drainage perturbation is also suggested by increased accumulation rates between the two steps before reaching steady deep lacus-   , 1996; Sites 522 and 744: Zachos et al. , 1996)  document successive glacial events: "late Eocene Event", EOT-1 and Oi-1 related to the Antarctic Ice Sheet  (Coxall and Wilson, 2011). (b) Agglutinated benthic foraminifera data at ODP Site 647  (Kaminski and Ortiz, 2014)  against the age model of  Coxall et al. (2018). (c) Lithostratigraphy, magnetostratigraphy and NGR data around the Eocene-Oligocene boundary in the CDB1 core.
At the end of this interval, the CDB1 core records for the first time a switch from obliquity to precession-eccentricity forcing at around the EOT-1 event. We thus potentially relate the obliquity-dominated interval to the instable phases of the incipient Antarctic Ice Sheet (AIS), whereas the onset of precession eccentricity dominance after EOT-1 would relate to a more stable, nearly coalesced AIS. These observations lead us to consider that obliquity variations preconditioned the EOT, either directly through AIS modulation or, preferably, via North Atlantic Deep Water formation. Data availability. The data set has been uploaded to a PANGAEA repository: https://issues. pangaea. de/browse/PDI-30098 (Boulila, 2021). Access is temporarily restricted but will be available at a later date. Supplement.
The supplement related to this article is available online at: https://doi. org/10. 5194/cp-17-2343-2021-supplement. Author contributions. The paper was conceived and planned by SB and GDN, in collaboration with all authors. SB carried out the cyclostratigraphic analyses. GDN conducted the paleomagnetic study. SB, GDN, BG, HB and JJC contributed to the interpretations of data and finalization of the paper. Competing interests. The contact author has declared that neither they nor their co-authors have any competing interests. Disclaimer. Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Acknowledgements. This work originated from a project (CYN-ERGY Project) funded by the BRGM, the AELB and the ADEME.
All the scientific crew is thanked for fruitful discussion. We thank the two reviewers and the editor Alberto Reyes for their constructive revisions. Financial support. Slah Boulila and Bruno Galbrun have been supported by ANR AstroMeso and ERC AstroGeo projects. Guillaume Dupont-Nivet has been supported by the Marie-Curie (CIG HIRESDAT and ERC MAGIC grants; grant no. 649081).
i. (Fig. 2d , Supplementary Fig. 6 ). Complementation of the ΔsopB bacteria with WT SopB, but not the catalytically inactive C462S mutant  31  , expressed from a low copy plasmid restored recruitment of GFP-Rab10 to invasion sites at 10 min p. i. (Fig. 2a, b ). These data suggest that Rab10 localization kinetics at S. Typhimurium invasion sites is delayed in the absence of SopB's lipid phosphatase activity. At later stages of invasion (30-60 min p. i. ), S. Typhimurium is localized to invaginated regions of the plasma membrane that subsequently undergo scission to generate SCVs containing the bacteria. These later stages of infection are identified as bacteria that become inaccessible to antibodies present in the extracellular medium (see model, Supplementary Fig. 7 ). We examined the localization of Rab10 to these bacteria during infection.
c Representative images of Henle 407 cells transfected with GFP-Rab10 and infected with WT, ΔsopD, and ΔsopBΔsopD mutant strains of Salmonella for 30 min. Inset shows invasion site and arrowhead denotes a Rab10 + tubule. Scale Bar, 12 μm. Data are representative of three independent experiments. d Quantification of GFP-Rab10 recruitment to bacteria from (c). Salmonella antibody staining before and after cell permeabilization was used to distinguish bacteria populations undergoing internalization, as described in the "Methods" section. In three independent experiments, bacteria (shown in red) that were inaccessible to extracellular antibody were scored for GFP-Rab10 localization in at least 50 invasion sites. Data are means ± S. E. M. Statistical analysis was performed with one-way ANOVA. e, f Quantification of the number of infected cells with GFP-Rab10 + tubules at 30 min post-infection following infection by the indicated strains.
In three independent experiments at least 50 infected cells were scored for the presence or absence of GFP-Rab10 + tubules. Data are means ± S. E. M. Statistical analysis was performed with a one-way ANOVA. SCV: Salmonella-containing vacuole; GFP: green fluorescent protein. Source data are included in source data file. in a manner that depended on Rab10 whereas Rab8A had only a minor role (Supplementary Fig. 11d ). Furthermore, Rab8A knockdown (confirmed by qRT-PCR) does not complement the membrane scission defect of ΔsopD mutant bacteria (Supplementary Fig. 11e, f ). Collectively, these data suggest that Rab10 is the relevant target of SopD during S. Typhimurium invasion. Rab10 localizes to invaginated regions of the plasma membrane during host cell invasion. Under conditions when plasma membrane scission was impaired (by infection by ΔsopB or ΔsopD mutant bacteria), we observed Rab10 retention at invasion sites.
A parent ion scan was performed using a resolving power of 60,000, then up to the twenty most intense peaks were selected for MS/MS (minimum ion count of 1000 for activation), using higher energy collision induced dissociation (HCD) fragmentation. Dynamic exclusion was activated such that MS/MS of the same m/z (within a range of 10 ppm; exclusion list size = 500) detected twice within 5 s were excluded from analysis for 15 s. For protein identification, Thermo. RAW files were converted to the. mzXML format using Proteowizard 62 then searched using X! Tandem  63  and Comet  64  against the Human RefSeq Version 45 database (containing 36113 entries). Search parameters specified a parent ion mass tolerance of 10 ppm, and an MS/MS fragment ion tolerance of 0. 4 Da, with up to 2 missed cleavages allowed for trypsin.
Acknowledgements J. H. B. holds the Pitblado Chair in Cell Biology. Infrastructure for the Brumell laboratory was provided by a  John Evans Leadership Fund grant  from the  Canadian Foundation for Innovation  and the  Ontario Innovation Trust. K. C. B. was supported by scholarships from the  Natural Sciences and Engineering Research Council of Canada  and an  Ontario Graduate Scholarship. V. M. D. was supported by fellowships from the  Canadian Institutes of Health Research , the  Hospital for Sick Children Research Training Centre  and is a recipient of the  L'Oreal-UNESCO Women in Science Award. We thank  Paul Paroutis  for help with confocal microscopy. This work was supported by operating grants from the  Canadian Institutes of Health Research  (FDN# 154329  to J. H. B, MOP# 119289  to B.
(b) Anemonefish monitoring We used wild-spawned, laboratory-reared, juvenile orange-fin anemonefish, Amphiprion chrysopterus, of one to three months of age from approximately 50 wild breeding pairs in the experiment. We collected eggs from natural nests in Moorea lagoon over three months which were hatched and reared in aquaria at CRIOBE (electronic supplementary material S1). After approximately 1-3 months, we photographed and weighed (±0. 01 g; Ohaus Scout Pro Portable Electronic Balance) 42 juveniles. We measured total length (TL: distance from tip of lower jaw to end of tail) and body height (distance from the pelvic fin and the start of the dorsal fin) (±0. 001 cm) from photographs using ImageJ software. We randomly placed individual juvenile anemonefish into each experimental anemone, either control (n = 24) or ALAN (n = 18) with no difference in length, height, or weight between treatments (electronic supplementary material S2).
(e) Statistical analyses We performed statistical analyses in R v. 4. 0. 4 [49]. We determined differences in illuminance (lux) and PAR (log10(x + 1)transformed) among sites and treatments (categorical variables) using linear mixed-effect models (LMERs), and replicate was added as a random effect with lunar phase and month as covariates. We fitted LMERs using the lmerTest package  [50] , while marginal (mR 2 ) and conditional (cR 2 ) R 2 were obtained with the package piecewiseSEM  [51]. In addition, we determined differences in maximum illuminance (lux) and PAR among sites and treatments using linear models (LM). We determined the effect of treatment and site on the probability of fish survival over time using a general linear model (GLM) with a binomial distribution. We fitted survival curves using the survminer package  [52].
We fitted LMERs to analyse the effect of treatment, site, period of treatment exposure (0-15 versus 15-20. 5 months), and initial fish height, length, and weight (log-transformed) on fish SGR (height, length, and log-transformed weight). We determined best-fit models using likelihood ratio tests, starting from the most complex model and subsequently removing non-significant interactions and explanatory variables via the lmtest package  [53] , and we used Tukey post-hoc tests to determine differences among groups via the 'emmeans' function in the emmeans package  [54]. royalsocietypublishing. org/journal/rspb Proc. R. Soc. B 288: 20210454.
Model selection is reported in electronic supplementary material, tables S5A, S6A, and S7A. H i , L i , and W i are the initial fish measurements at the start of the experiment, treatment is the light treatment (control versus ALAN), and site is field site. Exposure period refers to the two periods of treatment exposure (i. e. 0-15 months and 15-20. 5 months). mR 2 is the marginal R 2 , which describes the proportion of variance explained by the fixed factors alone. cR 2 is the conditional R 2 , which describes the proportion of variance explained by both fixed and random factors. Significant data are shown in italics. observed a negative, rather than a positive, impact of ALAN on growth which was 15%, 21%, and 51% lower in terms of height, length, and weight, respectively. Growth is a complex process influenced by many interacting physiological and ecological factors and their trade-offs  [55, 59]  and the observed lower growth may be due to negative effects on growth-related physiology.
Acknowledgements. We are enormously grateful to  Camille Vizon ,  Marie-Louise Elian , and  Ignacio Pita Vaca  for light intensity measures at night and for support in the lab and in the field during data collection;  Anne Haguenauer ,  Frederic Zuberer ,  Guillaume Iwankow ,  Frank Lerouvreur , and  Mathieu Kerneur  for help in the field;  Till Deuss  and  Robin Mannion  for anemonefish larval rearing. The Underwater LUX Sensor and SpectroSens2+ handheld logging metre was kindly donated to S. C. M. by  Skye Instruments Ltd  (http://www. skyeinstruments. com/coral-research-and-skyeinstruments/). We wish to thank  Sofitel Moorea Ia Ora Beach Resort ,  Manava Beach Resort & Spa Moorea , and  Intercontinental Moorea Resort & Spa  for their help and support in the field.
Sample size This observational study will be constituted by three groups: HFOT alone, NIV with standard oxygen, and NIV with HFOT, according to the strategy initially chosen by the clinicians. We assume proportions of surviving patients weaned from non-invasive strategies of oxygenation within day 14 of 50% in the NIV group and 65% in the HFOT group. There do not exist enough data to speculate on survival in the NIV associated with the HFOT group. Considering the proportions of patients receiving each strategy of oxygenation, 30% for HFOT, 60% for NIV with standard oxygen and 20% for NIV with HFOT (the total exceeds 100% to take account of the variability of the proportions), for a power of 80% and a type I error of 5%, for the relative hazard of 0. 65, the number of patients required is at least 70 in the HFOT alone group, 130 in the NIV with standard oxygen group and 40 in the NIV with HFOT group, that is, a total of 240 patients to estimate mortality hazard with precision of 1%.
In the event of a change in treatment strategy, the patient will be analysed in the originally initiated treatment group. All the analyses will be performed by the study statistician according to a predefined statistical analysis plan and using statistical software (SAS V. 9. 4 or R software). For statistical tests, a two-tailed p value of <0. 05 will be considered as indicating statistical significance. Analysis pertaining to the main criteria of evaluation Secondary endpoints will be compared between the three treatment groups by means of analysis of variance (or non-parametric method, if appropriate) for quantitative variables and by means of the χ 2 test (or Fisher's exact test) for qualitative variables. Predetermined subgroup analysis Subgroup analysis will be conducted to analyse outcomes in patients with and without hypercapnia and in patients with and without malignancy.
Data availability statement No data are available. Data will be handled according to French law. Coding participants will be done by recording the first letter of the name and forename, accompanied by a single study identifier indicating the order of participant inclusion, in order to store anonymised data in the electronic case report form. The sponsor will ensure that each study participant has given his/her consent for access to his/her personal data that is strictly required for quality control of the study. All investigators will have access to the final data set. Investigators will make available the documents and individual data strictly required for monitoring, quality control and audit of the study to persons having access to them, in accordance with the statutory and regulatory provisions in place (articles.
Our results provide bottom-up evidence for the idea that these categories are, at least to some extent, justifiably characterized in notional terms. This also demonstrates the utility of concreteness ratings for addressing issues that are relevant to cognitive linguistic theorizing. 2 Linguistic variables and concreteness: theorybased hypotheses In this study, we focus on English, and we investigate the following linguistic variables: part of speech, morphological structure, countability, and etymology. We selected these variables because they all allow making clear predictions for differences in the degree of concreteness based on existing linguistic theory, with special consideration of cognitive linguistic approaches. The following sections discuss each variable in turn, including the specific datasets that we use to operationalize each variable.
1) but also for words of other parts of speech. To test this hypothesis, we examined the most frequent suffixes of English: if the most frequent suffixes can be classed as abstractiontriggers, then there are chances that suffixed words are overall more abstract than non-suffixed ones. The MorphoLex database  (Sánchez-Gutiérrez et al. 2018 ) contains information on a set of derivational morphological variables for 68,624 complex words from the English Lexicon Project  (Balota et al. 2007). Such variables also include measures of suffix frequency. For our purposes, the relevant measure is morphological family size  (Schreuder and Baayen 1997) , that is, morphological type frequency defined as the number of word types in which a given morpheme, in our case a given suffix, is a constituent: "For instance, in the example {attendance, pleasance, pleasure, appearance}, the suffix -ance has a morphological family size of 3 {attendance, pleasance, appearance}, while the root -pleas-has a morphological family size of 2 {pleasure, pleasance}"  (Sánchez-Gutiérrez et al.
Moreover, we are interested in investigating whether the prediction made above (suffixed words being more abstract) extends to words with more than just one suffix, and whether abstractness grows as a function of the precise number of morphemes, i. e. , does abstractness increase monotonically when words become progressively more morphologically complex? It has been shown that word length correlates with abstractness (see  Lewis and Frank 2016; and  the experimental studies in  Reilly et al. 2012 Reilly et al. , 2017)) , and hence we want to further assess the extent to which morphological structure and length are independently associated with abstractness. Table : The most frequent English derivational  suffixes according to morphological family size (from https://github. com/hugomailhot/MorphoLex-en).
g. , apple) afford direct manual grasp, while mass ones referring to substances and aggregates (e. g. , water, sand) tend to require the intermediation of an instrument, such as a cup or a spoon  (De Felice 2015). Since graspability correlates with concreteness  (Pexman et al. 2019) , this may indicate that concrete mass nouns are relatively more abstract than concrete count nouns. For all these reasons, we expect mass nouns to be, on average, more abstract than count nouns. In our analyses, we use data from the Bochum English Countability Lexicon  (Kiss et al. 2016 ), a manually annotated database that addresses the issues discussed above, namely, that the count/mass distinction does not apply to nouns but to senses of nouns, and that a noun in a given sense can often be both count and mass.
As for the first issue, the database provides countability information for noun-sense pairs rather than for nouns, e. g. , matter 1 ('a vaguely specified concern') is annotated as count, while matter 2 ('that which has mass and occupies space') is annotated as mass. The second issue is addressed by the fact that each noun-sense pair is assigned to one of four distinct classes rather than to count or mass only, i. e. , count, mass, both count and mass, neither count nor mass. The database contains ≈11,800 noun-sense pairs that have been assigned to one of the four classes based on the answers that annotators gave to several syntactic and semantic questions about the usage of the noun-sense pair. For example, a nounsense pair is annotated as count only if the answer to "Can the noun-sense pair in its plural form appear together with more?" is "yes"  (Kiss et al.
The main dataset: concreteness ratings The main dataset of concreteness ratings comes from  Brysbaert et al. (2014)  largescale rating study, where 40,000 English word forms were rated for concreteness The linguistic dimensions of concrete and abstract concepts on a scale from 1 (= maximally abstract) to 5 (= maximally concrete). Over four thousand U. S. -resident native speakers of English participated in the study, with a wide range of ages and educational levels being represented. The instructions given to participants defined concrete words as those that "refer to things or actions in reality, which you can experience directly through one of the five senses", and abstract words as those that "refer to meanings that cannot be experienced directly but which we know because the meanings can be defined by other words"  (Brysbaert et al.
2014: 906). In using these ratings, we adhere to the idea that the concreteness/abstractness distinction is best characterized in terms of whether concepts are accessible to the senses  (Paivio et al. 1968 ). This is the most common way of operationalizing concreteness, but there are other operationalisations possible  (Dunn 2015). The concreteness ratings will be used as the main response variable (dependent variable) in all subsequent analyses, with different linguistic predictors as independent variables. It is important to state that the data quality of the concreteness measurements is not uniform. First, the concreteness ratings may be more volatile for rare words that are not known by a sufficient number of people. Because of this, we used word prevalence norms  (Brysbaert et al. 2016; Keuleers et al.
2015)  to restrict the dataset to only those words that are known by at least 95% of the population. This led to an exclusion of 10,266 data points (28. 5% of the full dataset). A second aspect of data quality relates to the variability of concreteness ratings across different participants. It is known that words at the extreme points of the concreteness continuum have lower standard deviations across raters  (Pollock 2018) , i. e. , raters agree more with each other for words that are clearly abstract or clearly concrete. There are multiple ways of entering standard deviations into the analysis. We decided to use weighted regression, where words with higher standard deviations (i. e. , more variability across participants) contribute less to the overall result. This way, we do not have to exclude words based on an arbitrary cut-off value (e.
Predictor datasets We consider the following variables presented in Table  2 , with predictions based on the discussion in Section 2. We use corpus-derived part-of-speech tags from the SUBTLEX movie subtitle corpus  (Brysbaert et al. 2012) , morpheme parses from MorphoLex  (Sánchez-Gutiérrez et al. 2018) , morpheme counts from the English lexicon project  (Balota et al. 2007) , countability data from the Bochum English Countability Lexicon  (Kiss et al. 2016) , and etymological data from the Oxford English Dictionary.