dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2020). Denoting these DCP sets as DCP RCM , DCP GCM and DCP Z respectively, we pro-pose the following indicator, BR W , based on the Wasserstein distance, to measure the bias reduction in dependence with respect to the raw GCM: BR W = 1 - W (DCP Z , DCP RCM ) W (DCP GCM , DCP RCM ) , (7) where W(DCP Z , DCP RCM ) is the Wasserstein distance between the DCP set from the corrections Z and that from the reference RCM data, and W(DCP GCM , DCP RCM ) is the equivalent between the GCM and RCM DCP sets. A value of BR W close to 1 indicates that the chosen dependencies (correlation, auto-correlation or cross-auto-correlation) of the correction is close to the dependence structure of the reference RCM. We call the set of this indicator a W-crossauto-correlogram. As the Wasserstein metric is sensitive to the scale of the multivariate data (here, the DCP sets) it is applied to, two normalizations of the DCP sets are proposed before the com- putation of the BR W values.
This is visible in Fig. S7 , showing the values of the Wasserstein distances (based on the second normalization of the DCP sets) used to compute BR W. In addition, some negative BR W values in Fig. 9  are related to very small differences between Wasserstein distances very close to zero. Indeed, if the model simulations to be corrected have a DCP set already close to the reference, its Wasserstein distance will be near zero. If a corrected dataset also has a distance to the reference close to zero, the resulting ratio can be quite different from 1 (and thus induce a strongly negative BR W value) while the two W values are only slightly different. For example this is the case for, among others, TSMBC-5 (S1V) at lag 1 for the tas/tas matrix under a projection context in Fig. S7 , where the W value is small but slightly higher than that of the raw IPSL simulations, implying a negative (red) BR W value in Fig.
9. Finally, when comparing TSMBC-5 and TSMBC-10, it appears that, whatever the configuration, increasing the dimension (i. e. 10 lags to be accounted for in the MBC, instead of 5) degrades the gain in correlations. The increase in the complexity (i. e. the number of dimensions) of the method is made at the expense of the quality of the results. This is not visible in Fig. 8 , which only accounts for the shape of the DCPs. Thus, it indicates that this degradation is mostly due to biases in the marginals that are not fully removed by TSMBC in a high-dimensional setting. One potential expla-nation for this is the well-known problem of the "curse of dimensionality" (e. g. Wilcox, 1961; Finney, 1977) : having ∼ 2500 values in 4576 dimensions for TSMBC10/S2V indicates that we may not have enough data to explore such a high-dimensional space and, thus, that the MBC inference and procedure performed by dOTC may not be robust.
e. differently from inter-variable or inter-site dependencies. The goal of the present study was then to investigate whether, by considering time just like other variables (i. e. by adding to the multivariate data to be corrected some lagged time series of itself), an MBC method is able to correct both the multivariate (inter-variable and inter-site) properties and the temporal properties. To test this, the dynamical optimal transport correction (dOTC) method has been applied first to a synthetic (i. e. statistically generated) dataset and, second, to a dataset of daily temperature and precipitation over the south of France, simulated from the IPSL global climate model. For evaluation, the reference dataset was extracted from higher-resolution regional climate simulations over the same region.
dOTC was then applied to correct the IPSL dataset where various lagged versions of those simulations have been added. This approach -performing an MBC on lagged time series in addition to the initial ones -has been called time-shifted multivariate bias correction (TSMBC). Furthermore, it has been tested based on four configurations: only one variable is corrected at a time, either for a given location (L1V) or for all locations at the same time (S1V); the two variables are jointly corrected, for a single location (L2V) or for all locations (S2V). From the synthetic data experiment, a comparison with a "reasonably naive" multivariate bias correction method, RBC, based on random sampling, has been proposed. The results showed the following: -TSMBC(dOTC) provides a clear improvement compared to TSMBC(RBC).
In order to evaluate the results in a fully multivariate manner (i. e. inter-variable, inter-site and temporal aspects), a new statistical criterion has been proposed. It is based on the Wasserstein distance between the set of distancecorrelation pairs (DCP) from references and that of a dataset (from corrections or simulations). This distance can be computed on lagged data, using multiple variables and at different locations, hence providing assessments of cross-autocorrelations, generalizing the traditional correlogram tool. The results obtained by applying TSMBC to climate simulations provided the following conclusions: -In terms of means and standard deviations, for both temperature and precipitation, the inclusion of lagged data does not strongly modify the results of the dOTC correction method.
e. including lagged versions of the simulated and reference datasets in a multivariate correction procedure -can indeed be relevant to adjust temporal properties, in addition to more usual marginal and multivariate components. Despite its promising results, the TSMBC approach can be further investigated and improved. For example, in the present study, only the dOTC multivariate method was used as a correction technique. Other MBC methods exist. Hence, it would be interesting to test how those alternative MBCs -such as "R 2 D 2 "  (Vrac, 2018; Vrac and Thao, 2020) , "MBCn"  (Cannon, 2018)  or "MRrec"  (Bárdossy and Pegram, 2012) , among others -would behave in this TSMBC framework. Note also that the chosen lag in TSMBC should be adapted to the type of variable and the area. For example, taking 3 d (s = 3) for precipitation in Europe seems reasonable, while pressure or temperature could require a week (s ≥ 7).
Hence, a preliminary analysis of the auto-correlation or temporal properties of the variables to be corrected should be performed to decide about the relevant lag to use. In addition, when dealing with precipitation, the rainfall occurrence is not treated differently from the non-occurrence (dry days) by the TSMBC approach proposed here (i. e. using dOTC as underlying MBC method). However, the sequences of dry days and wet days can bear a major part of the autocorrelation information. Hence, it could be interesting to account for this specific aspect of precipitation when performing the underlying MBC method. Moreover, some adjustment methods were designed to account specifically for the correction of temporal properties (e. g. Johnson and Sharma, 2012; Mehrotra and Sharma, 2015, 2016). A comparison of TSMBC to such methods would then be of interest to understand whether specific modelling is needed for adjusting temporal properties or whether considering lagged data into MBCs (i.
e. no specific modelling as in TSMBC) provides equivalent results. Finally, the Wasserstein cross-auto-correlation-based metric introduced in this study could be used more generally to compare various datasets and/or assess their diverse properties with respect to a reference. It can then be useful to make evaluations of climate simulations (adjusted or not) in a more holistic way. Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/esd-12-1253-2021-supplement. Author contributions. MV and YR had the idea of the method together. They designed the study and the experiments together. YR made the computations and plots. YR and MV jointly analysed the results. MV wrote most of the article with inputs from YR. Competing interests. The authors declare that they have no conflict of interest.
We also thank the climate modelling groups for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure, an international effort led by the US Department of Energy's Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling, and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP). Financial support. Mathieu Vrac has been supported by the Co-CliServ project. Mathieu Vrac and Yoann Robin have been supported by the EUPHEME project. Both CoCliServ and EUPHEME are part of ERA4CS, an ERA-NET initiative by JPI Climate, cofunded by the European Union (grant no. 690462). Mathieu Vrac has also been supported C3S (grant no. 428J). Yoann Robin has also been supported by project C3S 62 (Prototype Extreme Events and Attribution Service, grant no.
Methods In this systematic review and individual participant data meta-analysis, we searched PubMed, Web of Science, Embase, MEDLINE, CINAHL, Global Health, MIDIRS, and Cochrane without language restrictions for relevant articles published between database inception, and Jan 1, 2020, using search terms referencing intrahepatic cholestasis of pregnancy, ursodeoxycholic acid, and perinatal outcomes. Eligible studies had 30 or more study participants and reported on at least one individual with intrahepatic cholestasis of pregnancy and bile acid concentrations of 40 µmol/L or more. We also included two unpublished cohort studies. Individual participant data were collected from the authors of selected studies. The primary outcome was the prevalence of stillbirth, for which we anticipated there would be insufficient data to achieve statistical power.
Research in context Evidence before this study Pregnancies complicated by intrahepatic cholestasis of pregnancy are known to have an increased risk of perinatal complications, including preterm birth (both spontaneous and clinician-initiated), meconium-stained amniotic fluid, neonatal unit admission, and, for women with peak bile acid concentrations more than 100 µmol/L, stillbirth. Ursodeoxycholic acid is the most used treatment for intrahepatic cholestasis of pregnancy, yet there is no consensus as to its benefit for women or their babies. We searched PubMed, Web of Science, Embase, MEDLINE, CINAHL, Global Health, MIDIRS, and Cochrane for meta-analyses of ursodeoxycholic acid use in intrahepatic cholestasis of pregnancy published between database inception and Aug 1, 2020, using the search terms "meta$analysis", "cholestasis", "pregnancy", and "ursodeoxycholic acid".
Search strategy and selection criteria In this systematic review and individual participant data meta-analysis, we prospectively searched Ovid using the Map Term to Subject Heading feature to find Medical Subject Heading (MeSH) terms for inclusion in the subsequent literature searches. We then searched PubMed, Web of Science, Embase, MEDLINE, CINAHL, Global Health, MIDIRS, and Cochrane for articles on ursodeoxycholic acid use in women with intrahepatic cholestasis of pregnancy published between database inception, and Jan 1, 2020, using search terms referencing intrahepatic cholestasis of pregnancy, ursodeoxycholic acid, and perinatal outcomes, with MeSH additional search term permutations included in the search terms (appendix p 12). The reference lists of selected articles and relevant reviews were also searched to identify any manuscripts of potential relevance not already found in the database search.
There were no language restrictions; publications that were not in English were translated by fluent speakers of the original language or Google Translate. Studies had to have ethical approval to share data and 30 or more study participants, and publications had to report at least one of: stillbirth, preterm birth, neonatal unit admission, meconium-stained amniotic fluid, or neonatal death (appendix p 12). Studies that did not report on any individual with intrahepatic cholestasis of pregnancy and bile acid concentrations of 40 µmol/L or more at any point in pregnancy were excluded because more adverse perinatal outcomes occur at these concentrations. Duplicates were removed. Relevant articles were selected by title and abstract and adherence to the inclusion and exclusion criteria and then full-text screening was done (appendix p 12); the searches and the selection were done in duplicate by JS and KP, and any disparities were arbitrated by CO.
Data analysis The data analysis plan was pre-specified (appendix p 3). Participating authors completed pseudo-anonymised spreadsheets reporting simple maternal demographics, intrahepatic cholestasis of pregnancy diagnostic and treatment details, and perinatal outcomes (appendix p 12). Participant details were provided with numbers that could only be de-identified by the supplying author, which enabled any data inaccuracies or questions to be asked of the original author but meant that the main dataset was anonymised for our analyses. Analyses were done in Stata, version 16. 0. The primary outcome was stillbirth prevalence by ursodeoxycholic acid treatment in all studies. To compare women treated with ursodeoxycholic acid (at any dose and duration) with women who did not receive ursodeoxycholic acid, an individual participant data meta-analysis was done by use of multi-level mixed-effects logistic regression utilising the Stata function melogit, or logistic regression with a Huber-White correction when the mixed-effects regression did not converge, with participants nested within studies and (for multiple pregnancies) infants nested within mothers.
29 Adjustment was done for bile acid concentrations at baseline, number of fetuses, and maternal parity, because of the established relationships between these confounders and adverse perinatal outcomes, and anticipated data availability. 3, 5, 30, 31 ssociations between bile acid concentrations and stillbirth (by ursodeoxycholic acid treatment) were compared, for singleton pregnancies from all studies, by use of the roccomp function in Stata. The effect of ursodeoxycholic acid treatment on this association was determined on the basis of peak bile acid concentrations during treatment and for the whole pregnancy. Baseline bile acid concentration was defined as the highest bile acid concentration before treatment randomisation (for RCTs) or at diagnosis (assuming that most women treated with ursodeoxycholic acid in observational studies started treatment rapidly after baseline).
We defined high-quality studies, for this purpose, as being those that were double-blinded, placebo-controlled, and had the intervention administered until delivery. Lowerquality studies were those not fulfilling all high-quality criteria. Aggregate data on stillbirth, spontaneous preterm birth, and overall preterm birth (defined as birth before 37 gestational weeks) were extracted from the original manuscripts in duplicate by CO and JS. Study quality assessment tools from the National Heart, Lung, and Blood Institute were used to provide a quality score for each included publication. 33 These scores were independently assessed by JS and NJW, with arbitration by CO. This study is registered in PROSPERO, CRD42019131495.
Adjusted analysis of the entire dataset revealed that ursodeoxycholic acid treatment was associated with a reduced risk of spontaneous preterm birth (table  1 ), in contrast to the unadjusted comparisons, in which this reduction was not evident (appendix p 28). This reduction was seen in RCTs when restricted to singleton pregnancies (table  2 ) and when restricted to singleton pregnancies in two-arm studies (appendix pp 20, 28). Ursodeoxycholic acid treatment was also associated with a reduced risk of total preterm birth for women with singleton and multifetal pregnancies in RCTs (table  1 ) and when considering only singleton pregnancies for all studies, adjusting for the main confounders (table  2 ). Ursodeoxycholic acid did not reduce the prevalence of early preterm birth (birth before 34 gestational weeks; appendix p 19).
Previous work has shown that there is an increased risk of preterm birth in women with peak bile acid concentrations of 40 µmol/L or more (compared with women with peak bile acid concentrations <40 µmol/L); 5 ursodeoxycholic acid treatment should therefore be considered for these women with disease onset before 37 weeks' gestation. sharing agreement. The study protocol and statistical analysis plan will be available in the appendix with publication of this Article. Individual participant data from the unpublished UK cohort will be available with publication of this Article, unless consent for data sharing was withheld by the participant, upon reasonable request to Catherine Williamson (catherine. williamson@kcl. ac. uk), subject to an appropriate data sharing agreement. Unpublished data from the Italian cohort for the purpose of meta-analysis is available online.
University of Southern California, Los Angeles, CA,  USA  ( R H Lee MD );  Shanghai First Maternity  and  Infant Hospital ,  Tongji University School of Medicine, Shanghai, China  ( X Liu MD );  Department of Obstetrics and Gynecology, University of Milano-Bicocca, Monza, Italy  ( Prof A Locatelli MD );  Department of Physiology and Pharmacology, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas ,  Institute of Biomedical Research of Salamanca, University of Salamanca, Salamanca, Spain  ( Prof R I R Macias PhD );  Department of Obstetrics and Gynecology, Istanbul University, Cerrahpaşa, Istanbul, Turkey  ( Prof R Madazli MD );  Department of Cardiology, Royal Adelaide Hospital, Adelaide, SA, Australia  ( J A Marathe  MBBS);  Department of Obstetric Medicine, Mater Health Services Public Hospital, Brisbane, QLD, Australia  ( A Morton MD );  Department of Obstetrics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam ,  Netherlands  ( M A Oudijk PhD );  Department of Obstetrics and Gynecology, İzmir Bakircay University, İzmir ,  Turkey  ( D Öztekin MD );  ANU Medical School ,  College of Health and Medicine, The Australian National University, Canberra, ACT, Australia  ( Prof M J Peek PhD );  Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Buenos Aires, Argentina  ( V Tripodi PhD );  Department of Women's and Newborn, Gold Coast University Hospital, Southport, QLD, Australia  ( L F A Wong MD );  Department of Molecular and Clinical Medicine, University of Gothenburg, Gothenburg, Sweden  ( Prof H-U Marschall PhD ); Division of  Child Health, Obstetrics and Gynaecology, University of Nottingham, Nottingham, UK  ( Prof J Thornton MD ) Acknowledgments This study was funded by  Tommy 's (registered charity number  1060508 ), the  Wellcome Trust  ( 092993/Z/10/Z ),  ICP Support , and the  National Institute for Health Research (NIHR) Biomedical Research Centre at Guy 's and  St Thomas' National Health Service Foundation Trust and King's College London  ( IS-BRC-1215-20006 ).
A. Rottger et al. : Metrology for radiation protection In the first steps, the existing metrology infrastructure that underpins the radiation protection regulation has been identified and combined into a data base. The available good practice guidelines and international standards (ISO, IEC) and IAEA guidelines related to radiation protection calibrations, type testing and emergency preparedness have been collected as well and have been combined in a second data base. From these data, a gap analysis will be performed to identify the fields of radiation protection where infras tructure, guidelines and standards are missing. Further in formation is available in the newsletter of EMPIR 19NET03 supportBSS 2021 (https://www. euramet. org/index. php?eID= tx_securedownloads&p=418&u=0&g=0&t=1668514125& hash=7d4f98b29a6b19f1b51ca4f04c5fca131f18341e& file=Media/images/projects_EMRP_EMPIR_Partnership/ Networks/19NET03/supportBSS_Project_Overview_2021_ 03_15.
The mixture was ground by ball-milling into fine powders which were further pelleted and annealed again at 650°C for 96 h. The annealed pellets were then ground into fine powders. The crystal structure was verified by powder X-ray diffraction measurements and the lattice parameters, strongly sensitive to the In or Ce content, were determined from Rietveld refinements against the PXRD data using the FullProf software. [65] These analyses confirmed the successful insertion of In and Ce into the cages of the cubic crystal structure of skutterudites described in the 453 7 space group. The inferred lattice parameters are consistent with literature data and correspond to the expected values for nominal In and Ce contents of 0. 16 ≤ x ≤ 0. 20 and 0. 75 ≤ y ≤ 0. 90, respectively. A part of the prepared powders was consolidated by spark plasma sintering (SPS, Dr Syntex 505) in order to assess their thermoelectric properties between 300 and 800 K.
Preparation of the n-and p-type thermoelectric legs: The thermoelectric legs were prepared by considering two possible approaches. In the first approach, the diffusion barrier and the metallic composites were placed on either side of dense cylindrical pellets of n-or p-type skutterudites, and subsequently consolidated by SPS. As a second approach, the assembly of the n and p-type mm with a density corresponding to about 80% of the theoretical density. In order to characterize their thermal and electrical properties, some pellets were consolidated by spark plasma sintering following the same cycle as that used for the preparation of the thermoelectric leg (see below) in order to acquire experimental data that correspond as close as possible to those of the final legs. The thermal expansion coefficients of the (Ti/Ag)n, (Ti/Ag)p, (Ti/Cu)n and (Ti/Cu)p compositions were measured under the same experimental conditions used for the skutterudites.
In a stationary state, the local energy balance and charge conservation can be expressed by the two equations  [10, 29, 30]  A B⃗. = ⃗ = D B⃗ ? ⃗ A B⃗. ? ⃗ = 0 This set of partial differential equations, combined with Eq. (  1 ) and Eq. (  2 ), can be solved numerically by finite-element analyses to determine the temperature and electrical potential fields in the material. Herein, all the electrical and thermal characteristics of the modules were calculated using three-dimensional finite-element analyses implemented in the software COMSOL Multiphysics. The thermoelectric effects in steady state were expressed by the above-mentioned set of differential equations with temperature and electrical potential as unknown parameters. The three-dimensional distributions of these parameters, together with the electrical current density and heat flux, were solved using the boundary conditions of the experimental set-up (temperatures and thermal interface contact resistances) used to characterize the modules.
These simulations were conducted on model thermoelectric modules of dimensions corresponding to the fabricated modules. The measured temperature dependences of the transport properties of the skutterudites and the Ti/Ag or Ti/Cu composites were fitted using third-order polynomials, which were used as input parameters in these calculations. The output power reaches its maximum value when the impedance matching condition is achieved, that is, when the electrical load matches the internal resistance % of the module. The conversion efficiency of the TEG was calculated using the following relation (4) = (4) (4) + < 0,% (4) where the current 4 and output heat flow < 0,% were calculated using ? ⃗ and = ⃗, respectively. The derivation of the stress-strain state in the modules was performed using the software COMSOL Multiphysics by considering the boundary conditions (thermal, electrical and mechanical) imposed by the Mini-Pem.
Praomys and Mus (Nannomys) were identified to the subgenus level. Nevertheless, the determination of host species was performed only in pathogen-positive samples. A fragment of the 16S ribosomal RNA gene (16S rRNA) was amplified as previously described  [61]  and sequenced under BigDyeTM terminator cycling conditions. All sequences from this study have been deposited in GenBank under accession numbers MT256376 to MT256385 for rodent host species and MT677677 to MT677695 for shrews host species.