dataesr/scientific-paragraphs-categorization huggingface dataset:
The linear mixed model was executed using the lme function of the {nlme} package  (Pinheiro et al. , 2013). Post-hoc Tukey-Kramer tests were performed using the {mult-comp} package  (Hothorn et al. , 2008). The CSE on accuracy was estimated using a mixed logistic regression model comparing the correct responses between the four conditions and both groups. The fixed factors were the congruency of the preceding trial, the congruency of the current trial and the group. Participant was added as a random intercept. The model was executed with the glmer function of the {lme4} package  (Bates et al. , 2015). P-values from the logistic models were derived from the Wald Chi-square tests using the {car} package  (Fox and Weisberg, 2011). The CE on RT and accuracy were estimated from the effect of the congruency of the current trial from the respective models.
6 In addition, 17 of 20 specimens obtained from long-term care facilities with a positive RT-PCR for mutations at positions 417 and 484 underwent whole-genome sequencing and were all confirmed to be beta. As such, all targets identifying beta or gamma lineages were considered to be beta. We reviewed surveillance data from all 58 longterm care facilities in three departments (geographical administrative unit) in eastern France and selected five facilities in which a SARS-CoV-2 outbreak that implicated the beta variant had been documented between Jan 15 and April 16, 2021. In each selected facility, all residents (378 in total) were included in the study and the surveillance data collected by medical personnel included age, sex, history of SARS-CoV-2 infection identified by a positive RT-PCR result, and history of COVID-19 vaccination (appendix).
Participants and Procedure In this first study, the original English version of the BADS and the final French version were presented seven days apart to 147 French-English bilingual adults. Participants were recruited by Belgian and French psychology students supervised by the first and the third authors respectively in Belgium and France. All participants were informed about the study and gave their consent before starting the survey. The anonymity of data was guaranteed. The study's protocol was approved by the ethics committee of the Psychological and Education Sciences Institute of University of Liège. 2 t the first meeting, participants gave their informed consent and reported their current mood on three visual analogue scales (VAS), with a rating scale ranging from 1 to 10, focused on general mood , joy and sadness.
Then, all participants answered a few sociodemographic questions, evaluated their reading, speaking, listening and writing skills in English on a 4-point scale, and completed one version of the BADS. At the second meeting, the participants reported their current mood in the same three VAS instruments and completed the other version of the BADS in a counterbalanced order. The order of all items was counterbalanced for each version as well. Participants with less than a total score of 12 for the self-evaluation of English language skills were excluded from the data to adhere to the Gonzalez-Reigosa approach, as modified by  Vallerand and  Halliwell  (Vallerand & Halliwell, 1983). The original sample included 147 participants but 16 of them had total English scores under 12 and were excluded from the data.
A correlation of between. 10 and. 30 corresponds to a small effect, between. 30 and. 50 to a medium effect and above. 50 to a large effect  (Cohen, 1988). To measure the responses convergence and equivalence of the two translated versions, Pearson coefficients were first computed followed by equivalence paired t-tests based on the two one-sided hypothesis tests with the TOSTER package in JASP (  (Lakens, 2017; Team, 2020). T-tests on mood scores at both evaluation times were computed to control for the effect of mood on test-retest analysis. Descriptive analyses and correlational analyses were performed using STATISTICA 10 software (TIBCO Software Inc. , 2017) with a significant criterion of. 05. The de-identified data can be downloaded on the Open Science Framework on the following link : https://osf.
Participants and Procedure Participants were recruited via advertisements on social networks and the university messaging service. Candidates had to be French-speaking adults to be included. All participants were informed about the study and gave their consent online before starting the survey. Then they first completed sociodemographic questions followed by the random presentation of the BADS and other scales described below. The anonymity of data was guaranteed. The study's protocol was approved by the ethics committee of the Psychological and Education Sciences Institute of University of Liège. 3 our hundred and eighty-five non-clinical adults completed the online survey, and 76 participants were excluded from the study because of missing data. Thus, the data analysis was run on 409 subjects.
Statistical and Power Analysis To determine the accurate factor structure for the French translation of the BADS, a confirmatory factor analysis (CFA) was computed with the Lavaan package in R Studio  (Rosseel, 2012). CFAs were computed on the 25 items of the French BADS. A four-factor model was tested based on the original version of the BADS and the translations. As goodness-of-fit indices to test the factor structure, the χ2 with the associated degrees of freedom, its p-value and the χ2/df were first computed. A non-significant value of χ2 and a χ2/df = 3 correspond to an acceptable fit  (Cangur & Ercan, 2015). However, χ2 is sensitive to sample size  (Gerbing & Anderson, 1992). Then, we computed indices more contingent on a set of cut-off scores as the Root Mean Square Error of Approximation (RMSEA), the Tucker-Lewis Index (TLI), the Comparative Fit Index (CFI) and the Standardized Root Mean square Residual (SRMR)  (Bentler, 1990; Cangur & Ercan, 2015; Hu & Bentler, 1999 ).
An RMSEA between. 05 and. 08, a TLI >. 95, a CFI >. 95 , a SRMR <. 10 are generally interpreted as an acceptable fit  (Bentler, 1990; Schermelleh-Engel, Moosbrugger, & Müller, 2003). Then, scale properties were computed, with internal consistency relying on the calculation of Omega () with 95% confidence intervals (CIs)  (Dunn et al. , 2014; Kelley & Pornprasertmanit, 2016). Finally, construct validity was assessed with Pearson's correlations and multiple linear regressions. The de-identified data can be downloaded on the Open Science Framework The deidentified data can be downloaded on the Open Science Framework on the following link : https://osf. io/8ct7f/. The required sample size for scale properties and Pearson's correlations was a priori determined based on the recommendations of at least 10 subjects per item of the instrument  (Nunnally & Bernstein, 1999)  and based on Jackson recommendations of at least 20 subjects per estimated parameter for the CFA  (Jackson, 2003).
documenting of the monsoon here is the first in a series of short pieces reporting the progression of the seasons on Mt Everest The arrival of the summer monsoon is known to signal a progressive and remarkable transformation across the Nepalese Himalaya, characterised by increases in air temperature, cloud cover, and precipitation  (Shea et al. , 2015). Surface melt accelerates  (Litt et al. , 2019)  and avalanches become more likely, meaning mountaineering becomes increasingly difficult and dangerous  (Moore & Semple, 2006). To date, very few people have reached the summit of Mt Everest during the monsoon  (Huey & Salisbury, 2003; The Himalayan Database, 2019). The new AWSs on the mountain therefore offer a glimpse into the weather conditions during this period of the year when the mountain has been largely hidden from the outside world.
Acknowledgements This research was conducted in partnership with  National Geographic Society ,  Rolex  and  Tribhuvan University , with approval from all relevant agencies of the  Government of Nepal. ICIMOD gratefully acknowledges the support of its core donors: the  Governments of Afghanistan, Australia, Austria, Bangladesh, Bhutan, China, India, Myanmar, Nepal, Norway, Pakistan, Sweden and Switzerland. We also wish to thank the communities of the Khumbu Region, our climbing support team and  Shangri-La Nepal Trek.
FUNDING This work was supported by  MICINN  (Grant number  PGC2018-094630-B-I00  to FM),  Comunidad de Madrid  (CB was a recipient of " Ayuda de Garantıá Juvenil para la contratación de investigadores predoctorales " fellowship, grant number  PEJD-2019-PRE/BMD-15940 ),  CSIC  (BG-M was a recipient of a  JAE intro fellowship , grant number  JAEINT_19_00602 ),  Inserm (ATIP-Avenir program  to NR) and the  French National Research Agency -ANR-("Investments for the Future" programs LABEX SIGNALIFE   ANR-11-LABX-0028  and  IDEX  UCAJedi  ANR-15-IDEX-01  to NR). FM is a recipient of a RyC-2014-14961 contract. MEFP (CGB is a recipient of a  FPU predoctoral fellowship , grant number  FPU19/04449 ),  UAM  (BG-M is a recipient of a predoctoral fellowship, grant number  SFPI/2020/00878 ).
Characteristic of participants Between March 2016 and August 2017, we recruited participants among pregnant women or young mothers referred for parenting support. We followed pregnant women at least 3 months and up to 12 months postpartum, and recorded their perinatal data prospectively. For participants included in the post-partum period, we recorded perinatal data retrospectively. Potentially eligible women received verbal and written information regarding the study. Additional information was provided to those who expressed interest, together with their partner if applicable. They gave written consent to participate. A specific consent form was signed for authorizing video of mother-child interactions. When applicable, the participant's partner or the co-parent signed a consent form for the collection of information on their child and the recording of videos.
Statistical analysis and data management We used an electronic research form from Ad Scientiam, Paris, France (https:// www. adsci entiam. fr/). Data were stored anonymously, according to a procedure authorized by the Comité Consultatif sur le traitement de l'information en matière de recherche or CCTIRS, an independent agency of the French government. Most statistics were descriptive and exploratory. To compare the distribution of CIB dimensions to that of controls, we used videos from dyads enrolled as controls in a previous study  [30]. We compared the median score for each dimension in the 15 cases who consented to video recordings to 13 controls using a bilateral Mann and Whitney non-parametric test. Statistics were run using StatView, Abacus Concept California USA.
Acknowledgements We thank the patients that enrolled in the study, the team of the  "Service d' Aide à la Parentalité des Personnes en situation de Handicap", Paris, France , which made this study possible, the obstetrical, neonatal, and anesthetic teams of  Pitié Salpêtrière Hospital , and specifically  Dr Vauthier Brouzes ,  Prof Nizard , and  Pr Foix L'Helias  whose dedication to pregnant women with disabilities and their neonates was crucial to ensure a safe motherhood. We also thank the  Institut Mutualiste Monsouris, Hôpital Louis Mourrier, Hôpital Bichat ,  Maternité des Bluets ,  Hopital Franco Britannique ,  Hopital Jean Verdier ,  Hôpital Mignot ,  Hôpital Robert Debré , and  Clinique Sainte Félicité , who provided obstetrical care to some of the participants. We thank  Mrs April Hail  for kindly checking the syntax of our manuscript.
| Quantitative analysis The cohort reports were not amenable to meta-analysis because of their variable study designs and outcome measures. We performed quantitative analyses (using SPSS 23. 0) comparing 17 reported cases with psychotic-like symptoms attributed to narcolepsy, and 41 diagnosed by the authors as narcolepsy plus a psychotic disorder. Each case was reviewed (by C. H. ) with a checklist of clinical features (Table  S3 ), rating features "present" (mentioned/strongly suggested) or "absent" (denied/not described   1 ; Table  S2  lists citations for each article type).
Literature Search Procedure We conducted a computerized search of the PsycINFO and PubMed databases in February 2021, using the following combination of search terms in titles and keywords: (self-esteem OR self-concept) AND (enhanc* OR incre* OR chang* OR improve* OR intervention OR therap* OR manipulat* OR conditioning). This initial search identified 2,768 papers and dissertations published in English between 1989 and 2021. We included unpublished studies and dissertations in our search to minimize publication bias  (Ferguson & Brannick, 2012). A subsequent manual search of the bibliographies of published meta-analyses, systematic reviews, and papers on the impact of interventions or therapies on well-being and psychosocial outcomes allowed us to add 67 more references to our corpus. After reading titles and abstracts, we excluded a large number of our initial 2,835 papers and dissertations because they did not report a non-medical intervention on adults (i.
e. , developmental studies, fundamental studies, medication treatment, cosmetic or medical surgery). After excluding a further 29 references whose full texts we were unable to obtain, despite contacting the authors and searching open-access databases, we were left with a sample of 322 papers and dissertations. As a final step, we used mailing lists and listservs (APA DIV29 and Psy16) to request published and unpublished studies. In the end, the only paper we retrieved in this way lacked empirical findings and was, therefore, excluded. The first author read all 322 references (342 studies) in our corpus to determine whether they were eligible for inclusion in the meta-analysis. Any doubt as to whether a study met our inclusion criteria was resolved through discussion with the last author.
We excluded 10 studies that did not use a measure of self-esteem at all or used only specific self-esteem assessments (e. g. , social self-esteem subscale of the State Self-Esteem Scale;  Heatherton & Polivy, 1991). However, we included many global self-esteem measures, notably state and trait self-esteem assessments, explicit self-report questionnaires, and implicit measures. Finally, we excluded 4 qualitative studies. (5) The study had to provide enough statistical information to compute or reconstruct an effect size. The studies we included had to report descriptive data (sample size, mean self-esteem scores, and standard deviations) for each measurement time (pre-and post-assessment depending on the study design) and for each condition (experimental and control groups if applicable). Despite contacting authors to obtain this information when it was not included in the paper, we excluded 47 studies that did not meet this criterion.
However, to minimize the number of studies excluded, we included papers that provided incomplete but usable data. 1  Applying these criteria led us to exclude 223 studies. The main reasons for excluding studies were lack of focus on self-esteem in the intervention description and/or design (37. 22%), incomplete or unreliable data (21. 07%), and absence of randomization in controlled studies (17. 78%). Our final sample contained 119 studies.
Coding of Studies The first and last authors independently coded all 119 studies included in the meta-analysis. Disagreements were solved through discussion. Inter-rater agreement was high, as is shown by the Kappa coefficient (greater than0. 81) for the coding of categorical moderators  (Landis & Koch, 1977) , and the small percentage (4. 05%) of disagreements in coding the quantitative data (descriptive data, sample sizes, estimated attrition rate). Studies that included several subsamples and several measurement times, and/or used a variety of self-esteem measurement tools to assess an intervention's efficacy, provided more than one effect size. We coded each effect size, along with several parameters describing the study design, the study sample, the intervention, and the self-esteem measures used (see Appendix A).
Intervention We began by categorizing self-esteem interventions by type of therapeutic approach, differentiating between CBTs, reminiscence-based interventions, evaluative conditioning, psychoeducation/counseling, self-statements, support groups, mindfulness/relaxation, positive psychology interventions, physical activities, art therapies (including crafts, 1 When sample sizes for each group were not reported, we estimated the number of participants in the experimental and control groups by dividing the total number of participants by two. For studies that directly reported preintervention/post-intervention differences, we adapted our effect size calculations to the data provided (in such cases, we included only studies that provided the standard deviation of the pre-intervention score). 2 An independent double rating of the quality of the studies was carried out on 68% of the studies included in the meta-analysis by the first and the last author.
Effect Size Calculations We calculated separate effect sizes for each sample as standardized mean differences using a raw score metric  (Morris & DeShon, 2002). We used Hedges' coefficient to adjust the effect sizes to reduce the likelihood of bias due to overestimating the population effect size in samples with few participants  (Hedges, 1981). d denotes the adjusted effect size and can be interpreted using  Cohen's criteria (1992)  of small (0. 2), medium (0. 5), and large (0. 8) effects sizes. Individual effect size computations were performed using the "metafor" R-package  (Viechtbauer, 2010). As recommended by  Rosenthal (1991) , we set a conservative estimate of 0. 7 as the pre-post correlation (ρ) for the distribution of effect sizes of studies using a pre-post measurement design. This is the lower bound of expected test-retest reliability in psychometric measurements  (Dunlap et al.
Data Analyses All analyses were carried out with the "metafor" R-package  (Viechtbauer, 2010 ) and Wilson's SPSS for Windows meta-analysis macros  (Wilson, 2005). We assumed there would be some variability between individual effect sizes due to sampling error within studies and to differences between studies as a result both of identifiable factors (i. e. , moderators) and unmeasured random factors  (Valentine et al. , 2010). Therefore, we used a random-effects model to perform the mean effect size analysis and a mixed-effects model to perform moderation analyses. Because sample sizes differed greatly between studies, we weighted each effect size by multiplying its value by the inverse of its variance, which is strongly correlated with sample size. This ensured that effect-size estimates from larger samples had greater weight than effect-size estimates from smaller samples.
The Efficacy of Self-esteem Interventions Overall, the 119 studies included in our meta-analysis suggest that self-esteem interventions are effective regardless of their format (individual or group), the target population (clinical or healthy), the type of contact with the experimenter/therapist (face-to-face or online), the comparison with a control group (inactive, active or placebo control group) and the length of the intervention. The positive effects last up to one year. However, these results should be interpreted with caution as our conclusions are highly dependent on the reliability of the database and as strong associations between some moderators have been identified (Table  2 ). First, with strong analytical power, we found a significant effect of interventions on adults' global self-esteem (overall d = 0.
According to the design type, the exact interpretation of the sign of the mean effect size is not strictly the same, given the way effect sizes were computed. However, talking efficacy in the broad sense (increase in self-esteem in the experimental group or smaller decrease compared to a control group), it is possible to conclude that the three types of design included in our meta-analysis demonstrate the efficacy of interventions on self-esteem, with no significant difference in effect sizes between studies that use a control group or not, and those that control for baseline's self-esteem or not. Interestingly, in our database, studies considered to be of low quality did not significantly contribute to overestimating the positive effect of interventions on self-esteem. Because good quality studies also show an increase in self-esteem while controlling for more risk of bias, it seems that the overall efficacy of the interventions is not entirely due to major methodological biases.
CSE for person ability The European EMPIR NeuroMET 15HLT04  [13]  and NeuroMET2 18HLT09 projects  [14]  combine expertise from clinical, academic, and National Metrology Institutes to provide a better understanding of how to analyze and improve measurements in Alzheimer's disease (AD) diagnosis and treatment. As part of the project, PCOMs of neuropsychological assessments (e. g. , recall, language and praxis) are examined. The NeuroMET cohort includes 88 subjects, including patients with suspected dementia due to Alzheimer's disease (n = 26), mild cognitive impairment (MCI) (n = 23), subjective cognitive decline (n = 14) and healthy controls (HC) (n = 25). In this analysis we include 77 subjects with complete memory ability and biomarker measures. Missing data could for instance include subjects not being able to take MRI.
• The UzR are estimated based on the standard errors of each β-coefficient furnished by the Mathcad module polyfitc used at step [iv], thus capturing the multivariate model uncertainties. As shown in Fig. 3 , the corridor of the zR ± UzR for each person's predicted memory ability is mostly considerably wider than the observed U(θ) for that person. This may be due to additional components of vari- ation not yet included in the CSE model. Examples of such additional components could be biomarkers related brain entropy and connectivity as well as the person's ability to pay attention to the task to be performed and his or her executive functions. • Measurement uncertainties arising both from the psychometric observations as well as from the PCR analysis contribute to setting a limit on the smallest detectable change, SDC.
Conflict of interest CG received research grants from the Volkswa-genStiftung (Freigeist Fellowship) and the German Parkinson Society and was also supported by the Deutsche Forschungsgemeinschaft (GA2031/1-1 and GA2031/1-2) and Actelion Pharmaceuticals. He also received financial support/honoraria to speak at meetings by Actelion pharmaceuticals and as ad hoc advisory board for Lundbeck. DM has received personal compensation for consultancies for Sunovion and serves in Advisory Boards of Sunovion and Paladin Labs. He was also granted honoraria from Dystonia Medical Research Foundation Canada and royalties from Springer-Verlag. Open Access This article is licensed under a Creative Commons Attribution 4. 0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
Participants The body odours were collected during a larger study testing the relationship between male acoustic traits and cooperative behaviours (see  Tognetti et al. , 2019). During this previous study, we recruited 81 male participants (average age was 21. 3 ± 3. 2 SD) from the student population at the University of Montpellier, France. Students were invited via the ORSEE software, from a pool of more than 4,000 volunteers, to participate in an experiment at the Laboratory of Experimental Economics in Montpellier (LEEM, University of Montpellier, France).