dataesr/scientific-paragraphs-categorization huggingface dataset:
Blood cell-type composition analysis The analysis of the blood cell-type composition was performed using the Houseman method  (Houseman et al. , 2012). The overall proportions of the different cell types were determined using the minfi package and the estimateCellCounts function  (Aryee et al. , 2014) , with the DNA methylation data as input. The proportions of CD4+ T cells, CD8+ T cells, B cells, Natural Killer cells, Monocytes and Granulocytes were then determined.
Epigenetic clocks and age acceleration calculations Six epigenetic clocks have been selected to calculate epigenetic ages: Hannum, Horvath, EN, GrimAge, PhenoAge and DNAmTL. The Hannum, Horvath and EN epigenetic age were calculated using the Methylclock R package  (Pelegí-Sisó et al. , 2021). The PhenoAge, GrimAge and DNAmTL epigenetic clocks were calculated using the PC Clocks R package  (Higgins-Chen et al. , 2022). As previously proposed, epigenetic AgeAccel were calculated, for the five epigenetic clocks (Horvath, Hannum, EN, GrimAge and PhenoAge), using the residuals from regressing epigenetic age on the chronological one (Cerveira de  Baumont et al. , 2021; Yan et al. , 2020).
Statistical analyses All the statistical analyses were performed using R version 4. 2. 1 (www. r-project. org). Categorical variables were described as number and percentages. Continuous variables were described as median and IQR or mean and SD as appropriate. We mainly used non-parametric tests. The correlation statistics and charts were done using the Per-formanceAnalytics R package  (Peterson, 2022)  and the corrr package  (Kuhn et al. , 2022). The network plots were constructed using the corrr package, based on a multidimensional clustering in order to determine the distance between the variables: this package used the absolute values of the correlations as the proximity/distance metric. Spearman correlations were used, and p-values <0. 05 were considered statistically significant. The Wilcoxon effect size r (ranging between 0 and 1) was used to calculate the effect size to create Forest plots to visualize the results of associations between AgeAccel and socio-demographic and clinical variables.
The AgeAccel values (adjusted for cellular composition), estimated using residuals, are presented as violin plots in Fig. 3. The percentages of individuals with positive accelerated aging according to the six different definitions are as follows: 49. 91% of the sample show a positive AgeAccel in the Horvath clock, 50% for the Hannum clock, 53. 80% for the EN clock, 47. 28% for the GrimAge one, 51. 09% for the PhenoAge clock and 49. 46% for the DNAmTL clock. In order to visualize the associations between the clinical variables and the different AgeAccel (adjusted for the cellular composition), forest plots are presented in Fig. 4. A higher BMI is associated with all the six AgeAccel evaluated. Male sex is associated only with the GrimAge AgeAccel. The CTQ total score is associated only with GrimAge AgeAccel, however without any specific associations with the two subdomains of CTQ: "all neglects" and "all abuses" (data not shown).
, 2018). In line with this hypothesis, Rampersaud and colleagues showed a significant association between PhenoAge AgeAccel but not with GrimAge, Horvath nor Hannum AgeAcceleration and childhood maltreatment in 81 individuals with major depressive disorder  (Rampersaud et al. , 2022). Our results show a moderate association with CTQ (r = 0. 153). This result is nevertheless statistically significant, and is in line with other studies: in the study by Joshi and colleagues, the β of the multivariable linear regression model is β=0. 06 and in the Hamlat study the b has a value of 0. 09  (Hamlat et al. , 2021; Joshi et al. , 2023). No specific association was found for the two subdomains of the CTQ: "all neglects" and "all abuses". However, some individuals had missing data for these subdomains (since only the CTQ total score has been recorded in the database), leading to a possible lack of power.
In addition, we investigate in individuals with BD the association between several clinical variables such as childhood adversity, smoking status, BMI, current medications and clinical characteristics of BD with an accelerated aging. Another limitation is that information on the length of psychotropic treatment were not available in our database, nor information about several confounders such as physical activity, sleep or diet. These information would deserve further investigations in future studies of epigenetic accelerated aging in BD. Finally, replications in larger and independent are needed to confirm the main associations observed in our study.
Acknowledgements We thank the clinicians and nursing staff of the  French Network of Centers for Expertise in BD  for the recruitment and clinical assessment of participants. The biobank is hosted at the  Plateforme de Ressources Biologique, Hôpital Henri Mondor, Créteil  ( Dr. C. Barau ). Dr. C. Marie-Claire  is supported by the  Centre National de la Recherche Scientifique. We thank the  Fondation Fondamental  for PhD fundings ( FACE-BD prize  to  Luana Spano ). This work was supported by  INSERM  ( Institut National de la Santé et de la Recherche Médicale ),  Assistance Publique des Hôpitaux de Paris PHRC Research Protocol   P07-011_AOM08214  (to  Frank Bellivier ),  Fondation de France  (to Bruno Etain), the  Agence Nationale de la Recherche  ( ANR-18-CE37-0002  to  Bruno Etain ) and  Fondation Fondamental  ( Marcel Dassault Prize 2020 to Bruno Etain ).
Thus, sequences of relevant processes and relationships among different industrial (or even agricultural) sectors must be considered  (Trevisi et al. , 2018; Blissett and Rowson, 2012; Flannery et al. , 2018). A part of the RadoNorm project in the Horizon 2020 Framework Programme (www. radonorm. eu) is focused on the identification of NORM exposure situations throughout Europe, their detailed characterisation and evaluation of possible exposure scenarios. To do so, efforts have been focused on providing a systematic and structured mapping of NORM situations across all European countries. A methodology for the qualitative identification of NORM exposure situations has been developed as the first step of these activities. Furthermore, systematised tools, in the form of specific NORM questionnaires and registers for qualitative information and quantitative data collection, have been developed for industry, legacy sites, and non-disturbed areas with high natural background radiation (HBRA)  (Mrdakovic Popic et al.
, 2023, submitted for publication). The main objective of the current paper is to present and make publicly available the developed methodology for the systematic identification of NORM exposure situations and to provide clear and applicable examples on how the methodology can be applied in practice. The main benefits that are foreseen for the developed methodology are: • Facilitation of initial and periodic review of national NORM inventories (in European and worldwide countries), as requested by the EU BSSD and IAEA BSS, and, • Identification of sites where it is necessary to gather the information and data of importance for an overall improved exposure characterisation, including the behaviour, mobilisation, and further transport of radionuclides. Such improved exposure characterisation provides the necessary insight for the evaluation of existing exposure situation doses, as well as information on the presence of any additional non-radiological hazards.
Tier I -Inventory of natural resources Information and data from geological surveys and lists of raw materials of economic importance, regularly available in national registers. For example, the Mineral Resources of Poland database contains more than 14,000 mineral raw materials deposits (Polish Geological Institute, 2022). In Portugal, an extensive database also describes the main mineralogical occurrences throughout the country (Geoportal, 2022) and can be used to identify all relevant natural resources containing elevated NOR. Additionally, associated minerals, overburden or rock that is not sufficiently mineralised to be of commercial value, but which may contribute significantly to the generated waste stream (when exploitation is underway), must also be considered  (IAEA, 2013b). Features of minerals constituting identified raw materials can be checked regarding NOR content using literature data or widely available databases, (these include www.
An example of application of Tier II and III by the combination with the European platforms of polluters Besides sources of information previously listed in the descriptions of tiers, for the identification of NORM exposure situations related to tiers II and III, information about known facilities listed in the European Pollutant Release and Transfer Register (E-PRTR The European Pollutant Release and Transfer Register, 2007) can be used. The E-PRTR contains compiled information on key environmental data of industrial facilities from different European countries, although without any information about possible radioactivity. Recently, after revisions proposed by the European Commission, a new website of the European Industrial Emissions Portal (EIEP The European Industrial Emissions Portal, 2020) was launched that includes information on the largest industrial complexes in Europe, including data on releases and transfers of regulated substances to environmental media and waste transfers.
The portal also provides detailed data on energy input and emissions for large combustion plants in EU Member States and Iceland, Liechtenstein, Norway, Serbia, Switzerland, and the United Kingdom. This portal gives public access to detailed information on the emissions and the off-site transfers of pollutants and waste from around 60,000 industrial sites from 65 economic activities across Europe. Such a source of data provides additional possibilities for identifying NORM exposure situations complementary to the options implied by the abovementioned descriptions of tiers, where it is assumed to start with a singular raw material and identify all related industries. By using E-PRTR at the outset, an almost complete set of options is available, from which NORM situations can be identified by elimination.
The approach for NORM sites identification using PRTR registers is beneficial for different end-users as the data in PRTR are widely available for different European countries. Information is structured and organized in a proper way, which made the process of NORM exposure situations identification faster. Data from the register can be retrieved in common and easily used Excel spreadsheet format. Some information on chemical pollutants (for example: heavy metals) is available in the register, which may be useful for investigating multiple hazards at NORM exposure situations and for developing an integrated hazards assessment.
Conclusions A methodology for the identification of NORM exposure situations through relevant information and data collection in a systematic and harmonised way, developed within the RadoNorm project, is presented in this paper. The proposed approach, consisting of four tiers for the identification of all cases where NOR may be a possible source of radiation exposure of concern, is based on nationally available data. Based on geological archives, mining, environmental licenses, import and export statistics and trade registers, qualitative information can be obtained on relevant natural resources, raw materials and industrial activities with potentially enhanced concentrations of NOR. To cover all possibilities and avoid gaps, it is recommended to start with the consideration of the natural resources inventory in the country (tier I), progress through the mining stage complemented with a study of the imported raw materials (tier II), and then consider the mineral processing industry (tier III) and products and waste and residues (tier IV).
For consideration of NORM in terms of waste management, it must be underlined that most NORM waste can be hazardous both from a chemical and radiological point of view. From a chemical perspective, NOR behave similarly to other non-radioactive elements. Hence, even when an industry was not characterised in terms of radiation protection to date, qualitative information can be extracted from already existing documents, such as environmental licenses, Environmental Impact Assessments (EIA), waste catalogues or the European Pollutant Release and Transfer Register (E-PRTR), as discussed in the Section 4. When situations of concern with respect to radiation protection are identified, quantitative data should be compiled, including characterisation of technological processes, information on radionuclide behaviour and final fate.
Acknowledgments This work was supported by: -The European  RadoNorm  project. This project has received funding from the  Euratom  research and training programme  2019-2020  under grant agreement No  900009. - Polish Minister of Science and Higher Education programme "PMW" (international co-found projects)  under grant agreement No  5156/ H2020-Euratom/2020/2021/2. -POPH  and national funds (OE), through  FCT-Fundação para a Ciência e a Tecnologia, I. P. , in the scope of the framework contract foreseen in the numbers 4, 5 and 6 of the article 23, of the Decree-Law  57/2016 , of August 29, changed by Law  57/2017 , of July 19. We acknowledge financial support to CESAM by  FCT/MCTES  ( UIDP/50017/2020+UIDB/ 50017/2020+LA/P/0094/2020 ), through national funds. - Joana Lourenço  was funded by national funds (OE), through  FCT-Fundação para a Ciência e a Tecnologia, I.
Additionally, evidence-based knowledge on the link between external exposure via different routes, internal levels and human health was insufficient despite the productive long-standing national HBM programmes and the large number of Research and Development projects at national and European Union (EU) level. Furthermore, there have been significant limitations to the use of existing data as a basis for policy decisions at the EU level as they were not easily available and not collected according to harmonised protocols and might therefore not be comparable. The existing data were not representative of the European population and differences in the metadata characterising the datasets impede crossdataset analyses. At the beginning of this century, the European Commission which is responsible for chemicals policy, started a series of initiatives aiming at the development of a systematic, EU-wide HBM programme with harmonised methods, standards and study materials.
, 2023). The importance of HBM as a tool for the investigation of exposure at the workplace in a multi country setting was demonstrated by HBM4EU. Even though some companies may use HBM routinely, data are scarcely accessible. The HBM4EU chromates study underlines the need and use of an extension of occupational HBM studies to improve the protection of workers in the occupational setting in Europe and for collecting harmonised and comparable data  (Santonen et al. , 2023a). In order to expand the HBM toolbox with new methods and findings concerning the relation of exposure and health, HBM4EU sought to explore different paths. One of them was the identification of relevant effect biomarkers, which is why a systematic approach to their implementation in HBM studies is explored in a dedicated article  (Rodríguez-Carrillo et al.
, 2023). This Special Issue also elaborates on options to include more extensive health information in HBM studies  (Tolonen et al. , 2022). New analytical and interpretation methods address the real-life simultaneous co-exposures to numerous chemicals which do not physiologically belong to the human body and how to deal with these very complex datasets. This special issue looks into the exposure and effects to mixtures of phthalates, PFAS, and pesticides as well as science-based recommendations for mixture risk assessment  (Luijten et al. , 2023; Ottenbros et al. , 2023 ). HBM4EU's key strengths include its interdisciplinary nature, which allows for a more comprehensive understanding of the complex interactions between exposures to hazardous chemicals and human health, and its multi-scale approach to exposure science, which provides a more complete picture of how environmental exposures impact human health.
This paper presents a measurement of electroweak production in the    final state, where the  boson decays into  ν. This choice is motivated by the fact that the  boson branching ratio into neutrinos is larger than the branching ratio into charged leptons; also, the background is under better control than in the hadronic decay channel. The analysis uses   collision data recorded between 2015 and 2018 by the ATLAS detector  [5]  during Run 2 at the LHC. Based on this measurement, a search for aQGCs is performed. Anomalous couplings produce deviations from the SM prediction that grow with increasing momentum transfer between the incoming partons. Hence, this analysis exploits a region of high momentum transfer by requiring a photon of transverse momentum larger than 150 GeV. The high energy and luminosity of the LHC allow rare VBS processes to be studied in detail.
Signal extraction procedure and results A BDT classifier created with the TMVA  [70]  package is used to separate the signal from the background processes described in Section 5. It is trained in the  inclusive region. Due to the low number of events in the  inclusive region, the +jets,  (ℓ l) and  , and multĳet (  ) backgrounds are not used to train the classifier. In order to utilise the full set of simulated events, two classifiers are created and trained on two statistically independent samples. The classifier trained on one sample is applied to the other, and the final response distribution is built by combining the responses of these two classifiers. The following variables are used to create the classifier:    , Δ(  1 ,  2 ),  miss T ,  T -balance, 12 (  2 ),  T (  1 ), (),  T -balance (reduced), 13  jets , sin (|Δ(  1 ,  2 )/2|) and Δ(  1 , ).
e. theoretical uncertainties and the  ( ν)   EWK/QCD interference) have no effect on the significance calculation. The expected significance is estimated by fitting the artificial Asimov dataset in the same way. Such a dataset is constructed by modifying the predicted values with the normalisation coefficients and NPs obtained in the fit in the CRs while assuming no signal is present  [72]. The signal strength is measured to be: 25  -0. 23 (stat. ) +0. 21 -0. 17 (syst. ). 𝜇 𝑍 𝛾EWK = 0. 78 +0. The observed (expected) significance of the result is 3. 2 (3. 7). The   QCD and    normalisation coefficients are measured to be 1. 21 +0. 37 -0. 31 and 1. 02 +0. 22 -0. 17 , respectively, signifying agreement with the predicted yields within the uncertainties. The predicted fiducial cross section is computed in the phase space defined in Table  2.
It was measured using a binned likelihood fit over the BDT classifier distribution. The measured cross section is 0. 77 +0. 34  -0. 30 fb, which is in agreement with SM predictions at NLO in perturbative QCD. The cross sections and kinematics are quoted for the sum of the three neutrino flavours. The results of this study are combined with those of the previously published ATLAS observation of this process to increase the sensitivity. This gives an observed (expected) signal significance of 6. 3 (6. 6). Having found no significant deviations from SM predictions, the data are used to set limits on anomalous quartic gauge couplings. The limits are set on EFT dimension-8 operators   0 /Λ 4 ,   5 /Λ The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF  (Canada) , NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers.
4,   8 /Λ 4 ,   9 /Λ 4 ,   0 /Λ 4 ,   1 /Λ 4 and   2 /Λ 4. These constraints are either competitive with or more stringent than those previously published by CMS. In particular, the constraints on the   5 /Λ 4 ,   8 /Λ 4 and   9 /Λ 4 operators are significantly stronger than results previously published by ATLAS and CMS, based on either the full Run 2 dataset of 139 fb -1 or a partial dataset of 36 fb -1. Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.
In addition, individual groups and members have received support from  BCKDF ,  CANARIE ,  Compute Canada  and  CRC ,  Canada ;  PRIMUS 21/SCI/017  and  UNCE SCI/013 , Czech Republic; COST,  ERC ,  ERDF ,  Horizon 2020  and  Marie Skłodowska-Curie Actions ,  European Union ;  Investissements d'Avenir Labex, Investissements d'Avenir Idex  and  ANR, France ;  DFG and AvH Foundation ,  Germany; Herakleitos ,  Thales  and  Aristeia  programmes co-financed by  EU-ESF  and the  Greek NSRF, Greece; BSF-NSF  and MINERVA, Israel; Norwegian Financial Mechanism  2014-2021 ,.
3 Advances in fields such as molecular technologies, radiology, and epidemiology have also generated useful data that are now taken into consideration for tumour classification. However, much of this information is uploaded onto different bibliometric databases and presented in various formats, making it arduous to locate, collect, and synthesise relevant evidence. 3 t is imperative that the WCT be informed by the best available evidence. While the contributing authors are experts in their subspecialties, many are not as experienced in evidence-based medicine (EBM) or systematic review methodology. Despite this, the authors are entrusted with making a scientific evaluation of various types of evidence, which will then be harmonised with the authors' subject expertise to form the eventual classification.
Data sources/measurement The Health Professional Education in Patient Safety Survey is a reliable tool with high internal consistency as suggested by a Cronbach α greater than 0. 8 for each of the 6 sections in the original description  [4]  and a McDonald ω coefficient 0. 89 in its French-language version  [10]. The French-language version was used in the present study (Supplement 1). The survey consisted of 2 sets of questions. The first set of questions was designed to characterize the sample. The second set of questions used the French-language version of the Health Professional Education in Patient Safety Survey  [10]. The demographic and professional data collected included age, gender, profession, years of experience since obtaining a degree, prior simulation experience, time elapsed since the last simulation session, and overall satisfaction with the simulation.
Outcomes and estimation Between T1 and T2, the combined score of the measurement tools remained stable (Table  2 , Dataset 3). The progression curve of the combined score categorized by profession also showed the highest score at T3 (Fig. 2 ). While a decrease is observed for physicians at T4, the curve flattened for nurses and nursing assistants. The results of linear mixed effect model showed overall statistically significant difference in "communicating effectively (C3)," managing safety risks (C4), " "understanding human and environmental factors that influence patient safety (C5), " and "recognize and respond to remove immediate risks of harm (C6)" (P = 0. 028, P = 0. 002, P = 0. 002, and P = 0. 009, respectively). The scores of C3, C4, C5, and C6 at 6 weeks after intervention (T3) are significantly higher than those at just before interventin (T1) (P = 0.
ORCID Sylvain Boloré: https://orcid. org/0000-0003-3585-5060; Thomas Fassier: https://orcid. org/0000-0001-5853-8450; Nicolas Guirimand: https://orcid. org/0000-0002-8674-1752 org/10. 7910/DVN/BJUHAG Dataset 1. Raw response data from participants. Dataset 2. Coded data for analysis. Dataset 3. Results of statistical analyses.