dataesr/scientific-paragraphs-categorization huggingface dataset:
Though we were broadly inclusive in analytic inclusion of confounding factors we cannot exclude some residual confounding. Our data included visits from 2011 to 2015, and the differences we found may have changed over time. Finally, even though our results are consistent with findings from national studies, given the single institution nature of our study the results may not be generalizable to other EDs especially general EDs as opposed to PEDs. In conclusion, we found that Black NH children and Hispanic children were less likely to receive an opioid analgesia when visiting the ED for a painful condition than White NH children, and at the same time were more likely to receive a non-opioid analgesia when presented with moderate or severe pain. Our data bring a new piece of evidence of racial/ethnic inequities that may reflect the effects of racial discrimination in the analgesic management of children in the ED.
The value given by the balance includes the weight of the liquid quantity and the capillary force. Hence, for a given capillary bridge, F exp cap can be calculated by F exp cap = ρV w -M where ρ is the density of water, V w is the actual water volume at the time of measurement, M is the output of the balance (and V w is calculated once the profile of the capillary bridge is recovered from image processing). A high resolution camera (BASLER acA4600 10 μm) was used to photograph the liquid bridges. The output images were processed using ImageJ and MATLAB software was used to recover the geometry data for the liquid bridge: the gorge radius y * , contact angle θ r , and contact radius y c. Some relevant horizontal views of different surface roughness levels are shown in Fig. 5.
Acknowledgments The authors acknowledge support from the  international research network GDRI-GeoMech  ( Multi-Physics and Multi-Scale Couplings in Geo-Environmental Mechanics ). The authors would also like to express their sincere gratitude to the  NEEDS program  for having supported this work. The research described was funded in part by the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie  grant agreement No. 832405  (ICARUS) and by the  French National Centre for Space Studies (CNES).
METHODOLOGY This research is based on the secondary data and a critical review of the published literature. The research papers, review papers, and books were searched from various sources, such as Scopus, Google Scholar, and individual journal websites, related to the performance of HFCW for the removal of selected types of EOCs (PhCs, PCPs, and SHs). The snowball sampling method yielded over 50 journal articles, which were further screened and used for the purpose of this research. The screening was carried out to check the quality of published data. Only peer-reviewed journal papers were selected for this research, which helped to ensure the reliability of given data. The selected studies have used generally accepted and reliable analytical methods such as solid phase extraction-gas chromatographytandem mass spectrometry (SPE-GC-MS/MS); SPE-(ultra) high performance liquid chromatography-diode array detector (SPE-(U)HPLC-DAD); liquid-liquid phase extraction-GC-micro electron capture detector (LLPE-GC-μECD); LLPE-(U)HPLC-MS/MS; and SPE-rapid resolution liquid chromatography-MS/MS (SPE-RRLC-MS/MS).
Instrumental detection and quantification limits described as limit of detection (LOD) and limit of quantification (LOQ) were in the range of 0. 00003-2. 6 μg L À1 and 0. 00006-10 μg L À1 , respectively. The samples were analyzed soon after the collection, as the storage time was less than one or two days in most of the cases. The selected studies contained the required information on most of the key parameters such as concentration of EOCs in influent and effluent waters, removal efficiency, chemical oxygen demand (COD), biochemical oxygen demand (BOD), hydraulic loading rate (HLR), and HRT. In this way, a global database was compiled containing information of 117 HFCWs (with several PhCs: 93; PCPs: 19; and SHs: 24) that were reported in 35 peer reviewed journal publications (that examined PhCs: 30; PCPs: seven; and SHs: five) with case studies from 12 countries (PhCs: 10; PCPs: six; and SHs: five) for the removal of PhCs, PCPs, and SHs (Supplementary materials 1: Tables  S1-S3 ).
Assemblies were then obtained with the SPAdes genome assembler version 3. 11. 1 (11) using the careful mode. Annotation of the Bradyrhizobium sp. sGM-13 and Bradyrhizobium sp. sBnM-33 genome sequences was performed using Prokka  (12). Coverage was calculated with SAMtools mpileup (13) on Burrows-Wheeler Aligner MEM algorithm (BWA-MEM) version 2-generated (  14 ) mapping of the paired-end reads. Information about the two draft genome sequences is listed in Table  1. The strains sGM-13 and sBnM-33 had average nucleotide identities (ANI; calculated over all coding sequences [CDS] as in https://img. jgi. doe. gov/docs/ANI. pdf) of 90. 99% and 88. 60%, respectively, in relation to the closest species, Bradyrhizobium retamae Ro19 (GenBank accession no. NZ_LLYA00000000. 1) and 89. 53% with respect to each other.
ACKNOWLEDGMENTS This work was financed by the  Partenariat Hubert Curien UTIQUE  project  17G0918 , a mobility grant ( Bourse d'Alternance)  from the  University of Gabès , and a doctoral partner scholarship from the  French Ministry of Foreign Affairs. A collaborative IDEEV ( Institut Diversité ,  Ecologie et Evolution du Vivant ) research grant to B. A. covered the sequencing costs. This work has benefited from a  French State grant  (Saclay Plant Sciences, reference no. ANR-17-EUR-0007 ,  EUR SPS-GSR).
Survey development and completion In line with the knowledge mapping methodological guidance produced by Ebener et al. [28]  the purpose of this exercise was to 'bridge the gap' in identifying the different health systems, i. e. , policy making, service provision and resources in relation to a traumatic birth; 'to understand how knowledge flows and where the assets and the gaps are' (p. 636). Ebener's five-stage knowledgemapping process was used  [28] , with the first stage 'acquire the data' involving a survey tool (see Additional file 1). The survey was devised by the authors, with collaboration from those who attended the meetings. The survey collected data in four main areas. First, 'country level data' comprised population level statistics including the number of inhabitants, number of births, and types of birth (setting, mode of birth) based on the most recent/verifiable data source; the number of maternity hospitals; and how the maternity system was funded.
A further question was included to capture whether women could be referred to specialist perinatal or mental health services. The last section captured whether there was any 'training' into traumatic birth for maternity professionals involved in perinatal care (i. e. , midwives, obstetricians, obstetric nurses). This included questions on: 1) training provided as part of the national/general basic professional training/pre-registration curriculum and; 2) national mandatory requirements for post-registration training. If yes, respondents were asked to detail which professions, and how 'much' training was provided. Similar to the examples of knowledge mapping detailed by Ebener et al. [28] , this work involved engaging stakeholders and local experts. Individuals from the COST action (referred to as stakeholders in this paper) who were willing to participate were asked to collect data in consultation with local experts who had national knowledge of maternity care, perinatal mental health provision and/or pre-or post-registration training (and to detail who these individuals were) in their country.
The stakeholders were asked to record any other comments (collected as part of their conversations with experts), which may be useful to help understand policies, practice, or training, in their country on the survey (see Additional file 1). As this knowledge mapping exercise involved mapping existing policies, services, and training provision, rather than any individual level or evaluation-based data, full ethics approval was not required. Data collection took place from March 2020 to February 2021. Stakeholders were issued with reminders (up to three) and asked to notify the authors if they were no longer able to collect the data.
Country level data Country level data from the 18 countries are presented in Country level data was based on the most recent available census, at the time of data collection. Some data were rounded to two decimal places. i The data used to calculate birth rate and ratio of maternity hospitals were sometimes collected for different reference years. j Care system: 1 = public care only; 2 = public and private care. k There were inconsistencies in how data was reportedsome provided the numbers of maternity hospitals, whereas others detailed the different levels of provision, i. e. numbers of maternity units, consultant led units, etc. from having a traumatic birth experience, they related only to physical trauma (i. e. , to reduce anal sphincter injury or stillbirth rate). Other stakeholders, such as those from Poland, reported on more general policies to improve birth outcomes and maternal wellbeing, such as "[ …] pre-birth education aimed at reducing anxiety associated with labour and early motherhood, but nothing […] that would specifically address the prevention of traumatic birth" (Poland stakeholder).
The strengths of this work are it is the first mapping exercise to explore whether there are any national guidelines, services, or training provision for women who have experienced a traumatic birth in different European contexts. Such evidence helps to identify promising practices, key gaps, and to inform future research priorities. The limitations relate to a lower response rate than intended. Not all European countries are represented in this data set, and while originally 23 countries agreed to participate, and despite calls for other country representatives, overall, only 18 were included. All the included countries have high income-status, and the evident gaps in these contexts would suggest the situation could be even worse in middle or low-income countries. The survey only collected information on what was available, rather than any individual level or evaluation-based data.
Acknowledgements This article/publication is based upon work from  COST Action  "Perinatal mental health and birth-related trauma: Maximizing best practice and optimal outcomes", supported by  COST (European Cooperation in Science and Technology). We would like to thank  Gülcan Tecirli  for her assistance in data collection in Turkey. COST After birth  Consortium Joan G. Lalor  (Professor in Midwifery, Director of Research) 4  Wilson de Abreu 5 Valérie Avignon 3 Barbara Baranowska 6 Pelin Dikmen-Yildiz 7 Wissam El Hage 8 Yvonne Fontein-Kuipers 9 Antje Horsch 2,3 Susan Garthus-Niegel 10,11,12 Ernesto Gonzalez Mesa 13 Eleni Hadjigeorgiou 14 Maria Healy 15 Figen Inci 16 Gözde Gökçe İsbir 17 Ljiljana Jeličić 18 Sigfridur Inga Karlsdóttir 19 Georgia Kontosorou 20 Patricia Leahy-Warren 21 Julia Leinweber 22 Sylvia Murphy Tighe 23 Ursula Nagle 24 Jenny Patterson 25 Jessica Pehlke-Milde 26 Mirjana Sovilj 18 Claire Stramrood 27 Gill Thomson 1 Anastasia Topalidou 1 Maria Węgrzynowska 6.
Study Design and Participants A multicenter prospective study was performed in six academic institutions, hospitals, and cancer centers in France. Patients with advanced melanoma, who underwent a somatic comprehensive genomic FoundationOne assay  9  (Foundation Medicine, Cambridge, MA) were prospectively included. Patients' clinicopathologic characteristics, tumor genomics results, and outcome data were collected. According to the location of the known primary melanoma, we allocated each patient to a group of sun-exposure pattern including chronically sun-exposed area such as head and neck, intermittently sun-exposed area such as trunk, arms, and legs, and sun-protected areas such as feet, soles, toes, genitals, mucosal, and uveal areas. Progression and tumor response to PD-1 inhibitors were assessed according to the RECIST guidelines version 1.
Pellet containing membranes was resuspended in hypotonic buffer containing protease inhibitors. Protein concentration was evaluated by BCA assay (PIERCE, Thermo Scientific, France) and blotted using SDS-PAGE basic protocol. Primary antibody incubation was performed overnight at 4°C (eIF5A, Abcam #32443; GLUT1, Abcam #ab54460; GLUT2, Cell Signaling #54460; hypusine-eIF5A,  13  ; β-actin, sigma # A5441) and then with adequate HRP-conjugated secondary antibodies (Jackson ImmunoResearch, Interchim, France) (30 minutes, 1:10000, RT). Detection was performed using Immobilon Western Chemiluminescent HRP Substrate (Millipore, Molsheim, France) and Fuji apparatus. Band intensities were evaluated using PCBas Software. Lactate dehydrogenase (#K2228, APExBIO, Clinisciences) and glyceraldehyde 3-phosphate dehydrogenase (#K680, BioVision, Clinisciences) cells content were evaluated using activity assay and following manufacturer's instructions.
Statistical analysis Data were analysed using GraphPad Prism 6 software. Calorimetry data were analysed using two-way ANOVA multiple comparison and activity using multiple t-test. Other data were analysed by Mann-Whitney (2 groups) or Kruskal-Wallis (more than 2 groups) test to assess statistical differences between experimental groups. Differences were considered statistically significant with p<0. 05. Data were displayed as scatter plot of independent values and group mean values ± SD.
Acknowledgments This work was supported by a grant  DPM 20121125559  from the  Fondation pour la Recherche Médicale (FRM) , a grant from the  Société de Réanimation de Langue Française (SRLF)  and a grant (project  KIRI ) from the  Agence Nationale pour la Recherche (ANR). The authors greatly acknowledge the  C3M Animal core facility  as well as the IRCAN Cytomed, Histology and Molecular and  Cellular Imaging  (PICMI) facilities that are supported by  "le Cancéropôle PACA", "la Région Provence Alpes-Côte d'Azur" and "le Conseil Départemental   06 ".
, 1991; Anadon et al. , 1996; Leng et al. , 1997a; Godin et al. , 2010; Tornero-Velez et al. , 2012; Ratelle et al. , 2015a; Ratelle et al. , 2015b; Willemin et al. , 2016). The global model aims at aggregating the exposures via different sources and routes, and at calculating the cumulative amount of the five metabolites from the four parent compounds. In this work, we estimated the exposure to deltamethrin, permethrin, cypermethrin, and cyfluthrin of the French ENNS cohort from the HBM data with our global model for pyrethroids. Given the estimated exposures, we assessed the risk related to three neurotoxic effects of the reconstructed pyrethroids' mixtures using the methodology on cumulative assessment groups of pesticides by EFSA (2019a).
Materials and Methods The proposed approach is based on the population and the HBM data of the ENNS cohort, the assessment of the pyrethroids' exposures using reverse dosimetry with PBPK modelling, and the assessment of the cumulative risk from the reconstructed exposures (Figure  2 ). questionnaires (with the consumption of several food groups like fruits, vegetables, cereals, meat and fish), were collected for each study participant. First morning voids were collected to measure the concentrations of the pyrethroids' metabolites.
These concentrations came from average food residue data measured in contamination control and food monitoring surveys carried out in France between 2007 and 2013. Only samples above the limit of quantification were used to compute the intakes. For each participant, we then obtained an individual ratio of his/her computed dietary intakes (PM/CYP ratio). To reconstruct the pyrethroids' exposures from the HBM data, we considered a continuous exposure via oral intake for each parent compound in order to reach a steady-state. The daily intakes for cypermethrin, cyfluthrin and deltamethrin were estimated from the HBM data, and the daily intake for permethrin was computed from the cypermethrin intake and the PM/CYP ratio. As no information was available on isomeric ratios of pyrethroids, the ratios usually observed in commercial formulations were used to compute the isomers' intakes, i.
There were no general trends for cis-DCCA and trans-DCCA. The model estimates of the concentrations under the LOQ were also checked in details (Figure  S2  in Supplementary Data). Precise estimates of the concentrations were obtained for cis-and trans-DCCA and 3-PBA in men, and for cis-DCCA in women. For trans-DCCA in women and DBCA and F-PBA in men and women, it was not possible to obtain, for most of the individuals, a precise estimate of the (unquantified) concentration as the 95% confidence interval was estimated between 0 and 0. 1 µg/L, that is the LOQ. The uncertainty was high for these metabolites. Nevertheless, for F-PBA, the estimated medians could differ between the individuals (from 0. 03 to 0. 07 µg/L with an outlier at 4. 5 µg/L for a woman). This outlier can be explained by discrepancies in the measured data for that woman: high concentrations of cis-DCCA and 3-PBA, and moderate concentrations for trans-DCCA.
g. , DBCA that is specific to deltamethrin). Several difficulties arose during the estimation process of the daily intakes from the biomonitoring data. The main one was that cypermethrin and permethrin share the same metabolites among the five measured in the cohort. It then would not have been possible to distinguish the part of the urinary concentrations of the metabolites DCCA and 3-PBA formed by one or the other of these compounds, and that would lead to the nonuniqueness of the intakes of cypermethrin-permethrin pair (i. e. , an infinity of solutions). To overcome that, a realistic weighted exposure ratio between permethrin and cypermethrin was calculated using the food diaries of the ENNS participants and food contamination data for France. Even though that approach is subject to uncertainties in the reporting and in the contamination data that were very sparse for pyrethroids (considering that most of the food samples were below the limit of quantification), an exposure ratio between these two compounds was calculated for each participant.
Conclusions In this article, we presented a method for interpreting HBM data in the context of the exposure and risk assessment continuum by the means of PBPK modelling. To our knowledge, this is the first time that reverse dosimetry using PBPK modelling has been used to estimate the cumulative exposure to pyrethroids' mixtures from their urinary metabolites' concentrations. Nowadays, many countries have established biomonitoring programs to assess the chemical exposure in populations which allows the building of large databases gathering biomarkers of exposure and individual information  (Alimonti et al. , 2011; Fréry et al. , 2011; Centers for Disease Control and Prevention, 2019; Health Canada, 2019). Several initiatives, like the HBM4EU project (www. hbm4eu. eu/) have been carried out at national and European levels to encourage the development of new technologies, tools and models to reduce the uncertainties in exposure assessment from such data.
Extraction of light curves from the TESS FFI We extract photometry from the TESS Full Frame Images (FFI) for all 15,405 stars in the target list, following the methods presented in  Nardiello et al. (2019). Briefly, this method models the TESS PSF, accounting for spatial and temporal variations to perform photometry and neighbour subtraction (for sources between 10 and 400 from the target star) where fields are crowded. We extract light curves from the FFI using the img2lc code presented in  Nardiello et al. (2015 Nardiello et al. ( , 2016)). The pipeline corrects for some systematic effects associated with the spacecraft, detector, and environment by modelling them using the co-trending basis vectors (CBVs) obtained by  Nardiello et al. (2020). As an example, this allows for reconstruction of the light curves where a pointing problem caused a systematic loss of flux in sector 1.
APOGEE also includes detailed element abundance information derived through the application of APOGEE Stellar Parameters and Chemical Abundances Pipeline (ASPCAP:  García Pérez et al. 2016 ) -which uses a specifically derived linelist  (Shetrone et al. 2015)  -to spectra of the NIR H-band taken using the twin (Southern) APOGEE spectrograph  (Wilson et al. 2019 ) on the 2. 5m Irénée du Pont telescope at Las Cumbres Observatory (LCO:  Bowen & Vaughan 1973). APOGEE spectra are then reduced and analysed using in-house pipelines  (Nidever et al. 2015; Jönsson et al. 2020). Red giants in the TESS-CVZs are specifically targeted within APOGEE via external program time through the Carnegie Institution of Science (PIs: Beaton, van Saders, and Teske). Information about these extra targets and more generally about APOGEE-2 targeting is presented in  Beaton et al.
(2020, in prep. )  and  Santana et al. (2020, in prep. ). Using the APOGEE abundances, we can make some initial insights into the connections between stellar age and element abundances in the Galaxy. We find that APOGEE-2 DR16 has 513 targets in common with our bright TESS-CVZ giants. The SkyMapper T eff and [Fe/H] generally agree well (within 1σ) with those derived by APOGEE, in the cases where both surveys returned these parameters. We use these spectroscopic and photometric stellar parameters to determine bolometric corrections in the J, H and K S band for each of the targets represented in all the relevant data sets. We use the bolometric-corrections code 2  , which applies methods described in  Casagrande & VandenBerg (2014). We then use this correction, in conjunction with the Gaia DR2 parallax information and the 2MASS photometry to determine the luminosity of each of the targets.
The lower two panels on the left hand side of Figure  7  show spectra of exemplar RC and Red Giant Branch (RGB) stars. Again here, oscillation modes are clearly detected in both stars. RGB and RC stars have been examined in detail in previous asteroseismic samples from e. g. CoRoT, Kepler and also in TESS. For this reason, our prior knowledge of their mode structure is good, facilitating their automated detection (peak-bagging) using the PBJam 5  code  (Nielsen et al. 2020, submitted). The = 0 and = 2 modes are cleanly detected and are shown by the red vertical lines in the inset panels. = 1 modes are visible in between the l = 0, 2 pairs, with clear evidence of mixed pressure and gravity modes visible within each order. While we do not make use of individual mode measurements in our analysis, this demonstrates that such analyses are inherently possible with TESS.
Our detection of rotational splitting in an RC star here is comparable in scale to initial measurements of red giants based on ∼ 500 days of Kepler data  (Beck et al. 2012). Finally, in Figure  9 , we demonstrate that the trend between stellar mass and ratio of the photospheric Carbon and Nitrogen abundances, [C/N], which is readily seen in APOKASC and other data-sets (e. g. Martig et al. 2016; Masseron & Gilmore 2015; Silva Aguirre et al. 2020) , is also broadly reproduced by our TESS-SCVZ results. Here, we use the subset of stars in our sample which have APOGEE spectra, that were re-analysed in PARAM with these tighter spectroscopic constraints. We compare with the dataset of  (Miglio et al. 2020) , which used a very similar analysis to derive stellar mass. The [C/N] has a relationship with mass in giant stars due to the first dredge-up (FDU) of material from the stellar interior as the star evolves away from the main sequence (e.