dataesr/scientific-paragraphs-categorization huggingface dataset:
The aim is to identify the homogeneity or, on the contrary, the diversity of points of view. The target's perception of each organizing dimension was measured. The variables whose factor loadings were concentrated on the same factor were grouped. This also served to uncover variables, which allowed streamlining specific segments. Since data analysis and interpretation can be influenced by the personality and culture of the evaluator, having unbiased data collected in a neutral and fair manner ensures validity and reliability. In both phases, neutrality and impartiality were considered while constituting an evaluation team that would overcome biases in data collection, and also in the analysis of the results obtained for better objectivity in scaling up or replication in another context. While in the first phase an impartial facilitator was recruited, in the second phase the student was assigned by the ORIVE service due to their reliability.
This, therefore, guaranteed administrative and political independence. In parallel, and due to the mixed-methods situation, exclusively relying on a neutral and impartial team would lead to a situation of non-in-depth or superficial analysis of cases or phenomena during the process. Both independent entities were supervised by institutional components in the shape of the International Affairs Department and the ORIVE. The ORIVE furthermore declared the survey to the data protection officer, as it was not implemented through internal services but through the OpenU project and its platform. Most importantly, the information collection stage required use of prior knowledge and expertise in the field to better understand the responses and collect information. The interpretation therefore relied on regular and open peer-discussions with analysts and was finalized by the authors.
Acknowledgments: The authors thank the participants of the focus group and the student Steering Committee for their participation. While participants of the focus group wished to remain anonymous, special thanks go to the students who have been involved in those experimentations. This work would also have not been possible without the intervention, advice and support of the following:  Bruno Selun  ( Kumquat ) who has facilitated and coordinated Phase 1,  Johannes Posel  ( Freie Universität Berlin ) for his technical assistance, and both  DPEIP  and ORIVE ( Université Paris 1 Panthéon-Sorbonne ) for their availability, their work and advice, especially  Elodie Hutin ,  Elodie Mette ,  Pamela Torres  and  Agnes Garcia.
Data Collection and Analysis The data consists mainly of working documents collected from field actors' archives  [2]. We collected emails, meeting minutes, proof documents, interview records, analysis texts, and slideshows, and complemented these with interviews. For the first case, we collected 47 documents (30 related to operational outsourcing and seven to risk governance outsourcing) and conducted eight interviews (lasting 12 h 45 min in total). For the second case, we collected 357 documents (240 related to operational outsourcing, 12 to risk governance outsourcing) and conducted three interviews (lasting 5 h 5 min in total). Our study is based upon the technique of narrative analysis  [8]  using the framework proposed by Burke  [6]. Instead of analysing the narratives through their common thread or structure, Burke proposes to analyse their ingredients: who (agent), what (act), how (agency), where and when (scene), and why (purpose).
Eine Einführung aus historischer Perspektive, Springer-Gabler, Wiesbaden (2017), V-VI (our translation). 14. Claude Diebolt, Louis Fontvieille, "Dynamic Forces in Educational Development: A Long-Run Comparative View  of France and Germany in the 19th and 20th Centuries", Compare, 31, no. 3 (2001), 295-309. 15. Nadir Altinok, Claude Diebolt, Jean-Luc Demeulemeester, "A New International Database on Education Quality:  1965-2010", Applied Economics, 46, no. 11 (2014) school and primary education in the nineteenth century. A second objective of this article is to analyse how far the beginning of an economic take-off, which occurred in parallel with an increase in educational investment, may have contributed to fostering and feeding this process. To do this, the article uses retrospective national accounts of the primary education funding allocated by the state, departments, municipalities and households over the period 1820-1913, in order to capture   what is commonly referred to as the long nineteenth century.
ARIC The AGES-Reykjavik study was launched in 1967 and included 19,390 randomly selected subjects born between 1907 and 1935 living in Reykjavik, Iceland. Participants were re-invited between 1967 and 1996 for follow-up examinations. 17 The AGES-Reykjavik study (AGES-I) was done between 2002 and 2006 and included 5764 subjects aged were alive (response rate approximately 70%). A follow-up examination (AGES-II) was done from 2007 to 2011. 18 For this analysis, we included 3907 participants with information on dementia status and CVH at midlife (Figure  2 ). To evaluate CVH at midlife in the Reykjavik study, we used data from the closest measurement to 50 years. 18 th studies were approved by institutional review boards and written informed consent was signed by all participants. For the secondary analysis investigating CVH at late-life and change in CVH from midlife to late-life, we included 5011 participants from ARIC who had available information on dementia status and CVH at both visits 1 and 5 (Figure  1 ).
Of the individual CVH metrics at midlife, physical activity was associated with incident dementia in ARIC, but not in AGES-Reykjavik. Physical activity at midlife in AGES-Reykjavik was based on recalled data at the late-life visit, which may have led to measurement error bias. Dietary habits and total cholesterol were also not associated with incident dementia. Previous studies on dietary habits and total cholesterol and risk of dementia also report inconsistent results,  34, 35  and this requires further study. The present study has limitations. First, the observational design precludes reaching causal conclusions. As with any observation study, our results might be susceptible to residual confounding. For example, some risk factors are more prevalent among persons of lower socioeconomic status, and adjustment for education may not capture that potential confounding completely.
Fourth, data on dietary habits were not available at the ARIC late-life visit and the AGES-Reykjavik midlife and late-life visits. Fifth, the generalizability of this study may be limited given that the study sample consisted of Black and White individuals from four selected US communities and White individuals from Iceland. In conclusion, higher CVH and improvement in CVH within midlife were associated with a lower risk of dementia. These findings may have important public health implications highlighting the need for promotion and maintaining ideal CVH at midlife to reduce risk of dementia.
ACKNOWLEDGMENTS The authors thank the staff and participants of the ARIC and AGES-Reykjavik studies for their important contributions. The Atherosclerosis Risk in Communities study is carried out as a collaborative study supported by  National Heart, Lung, and Blood Institute contracts  ( HHSN268201700001I ,  HHSN268201700002I ,  HHSN268201700003I ,  HHSN268201700004I ,  HHSN2682017000-05I ). Neurocognitive data are collected by  U01 2U01HL096812 ,  2U01HL096814 ,  2U01HL096899 ,  2U01HL096902 ,  2U01HL096917  from the  NIH (NHLBI ,  NINDS ,  NIA , and  NIDCD) , and with previous brain magnetic resonance imaging examinations funded by  R01-HL70825  from the  NHLBI. The AGES-Reykjavik was funded by contracts  N01-AG-12100  and  HHSN27120120022C  from the  National Institutes of Health ; the  Intramural Research Program  of the  National Institute on Aging ; and by the  Icelandic Heart Association  and the  Icelandic Parliament.
Sanaz Sedaghat  is supported by a  McKnight Clinical Translational Research Scholarship in Cognitive Aging and Age-Related Memory Loss. Thomas van Sloten is supported by a  VENI research grant  ( 916. 19. 074 ) from the  Netherlands Organization for Scientific Research and a Dutch Heart Foundation  research grant ( 2018T025 ). Pamela Lutsey is supported by  K24 HL159246. Rebecca Gottesman  is supported by the  Intramural Research Program  of the  National Institute of Neurological Disorders and Stroke. Keenan Walker  is supported by the  Intramural Research Program  of the  National Institute on Aging.
An ultrasonic microphone, UltraSoundGate Condenser Microphone CM 16 (Avisoft Bioacoustics, Berlin, Germany), was mounted 2 cm above the cover of the testing cage; it was connected via an UltraSoundGate 116 USB audio device (Avisoft Bioacoustics) to a personal computer, with which acoustic data were recorded with a sampling rate of 250 kHz in 16-bit format with Avisoft Recorder (version 2. 97; Avisoft Bioacoustics). The recordings were then transferred to Avisoft SASLab Pro (Version 5. 20; Avisoft, Berlin, Germany) and Fast Fourier transformation was applied (512 FFT length, 100% frame, Hamming window, and 75% time window overlap). Spectrograms were generated with Avisoft at a frequency resolution of 488 Hz and a time resolution of 0. 512 ms. Signals below 30 kHz were cut to reduce background noise to 0 dB  (Premoli et al.
, 2019). For USV detection, an interactive function with section labels was used. This tool permits to define manually USV borders by inserting section labels, and it is useful when automatic threshold-based USV separation may not work satisfactorily because of ambient noise or because of poorly structured vocalizations (manual guide of Avisoft Bioacoustics). Number, mean duration, peak frequency, and peak amplitude were calculated for each vocalization together with the calling time of the mice based on previous studies  (Wohr et al. , 2011). Call subtypes were also determined for a more detailed qualitative analysis. For this purpose, USVs were automatically classified with the Sonotrack Call Classification (version 1. 4. 7, Metris B. V. , The Netherlands) software, using the categories described in detail in Figure  1 , based on previous literature on mouse USVs  (Caruso et al.
, 2020). To deal with background noise and artifacts in the ultrasound recordings, the Sonotrack Call Classification software applies various filters to remove unwanted signals such as white noise and artificial sound sources. In addition, a logic filter is used that further processes the recorded signal by removing sounds that are too short or appear at many frequencies at the same time. The logic filter also reduces echo that is found in the recording and merges spectral elements that are interrupted by a very short time and a frequency gap. On each testing day, the vaginal estrous phases of both testing and stimulus female mice were assessed from the analysis of their vaginal smears  (Caligioni, 2009). In both experiments, all stimulus females used for male-female interactions were in non-receptive diestrous phase in order to minimize mounting attempts and other sexual behaviors that could confound the evaluation of sex differences in USVs and social behaviors.
Statistical Analyses Normality of data distribution was confirmed by Shapiro-Wilks test for each sex and testing session and for each variable of interest. Behavioral data from each experiment were separately analyzed by ANOVA with sex as the between-subject factor and testing session as the within-subject factor. Furthermore, behavioral data from the female mice in each testing session were subjected to an additional ANOVA with the estrous phase (estrous or diestrous) of the experimental B6 female and the estrous phase (e. g. , Supplementary Figures  2, 3 ) of the stimulus CD1 female as the between subject-factors. The analysis of the data from male mice did not include the estrous phase of the stimulus, since all CD1 females selected for testing males were in diestrous phase. A further ANOVA with experiment as the additional between-subject factor was performed on the data from female mice only in order to quantify the replicability of the female phenotype (under the same testing conditions) across the two experiments.
Post-hoc comparisons (Fisher's LSD test) and separate ANOVAs were performed when appropriate. All the analyses were conducted using the software Statview and SPSS, and α was set at 0. 05. The data were inspected for exclusion of outliers (by Grubbs' ESD test adapted for small sample size). Outlier values were excluded only from a specific dataset (e. g. , body sniffing time on session 1), except for the analysis of repeated measures, when values for all the 3 sessions had to be excluded for the affected variable. The results are expressed as mean ± SEM throughout the text. Individual data of social behaviors and USV parameters are also provided for all the animals in Supplementary Figures  4, 5 ; in addition, the individual composition of call types is illustrated in Supplementary Figures  6, 7  for half (i.
e. , 5 over 10) of individuals for each sex emitting the higher rates of USVs in each experiment. The call types were automatically classified using the software Sonotrack and based on the parameters described above. Definitions of the call types were mutually exclusive. Overlap of components was removed when more than 70 % to prevent wrong call durations. Short gaps between components in both frequency (≤6 kHz) and time (≤5 ms) were interpolated (gaps can be caused by changes in microphone sensitivity or direction of vocalization). Complex "3 component" and "+3 component" calls were summed up into a "complex tot" category. While the female CD1 intruders used for assessing males' USVs and social behaviors in male-female interactions were all in diestrous phases, the intruders used for female-female interactions were either in diestrous or estrous phase.
3 and 5. 96, p < 0. 001 and <0. 05; Figure  5C ], and the FIGURE 2 | Sex differences in social behaviors and USVs in experiment 1 (same pre-testing isolation). All behaviors were scored in the male and female experimental B6 subjects (A-E) toward a female CD1 stimulus during 3 testing sessions of 3 min each (inter-session interval: 7-10 days). Time spent performing social behaviors and cage exploration was scored from video files by an observer who was unaware of the sex of the subjects and their experimental assignment. Affiliative behaviors refer to all sniffing + crawl under/over + allogrooming (refer also to definitions in the text). Cage exploration refers to locomotion in the testing cage and wall rearing. USVs were quantified by spectrographic analysis using the software Avisoft SASLab Pro (F-J).
Comparison Between Experiments 1 and 2 in Female Mice: Social Interaction and USVs The female mice in both experiments were tested under the same experimental conditions, i. e. , following a 72-h isolation period before social encounters. Since the female subjects belonged to FIGURE 5 | Effects of the estrous phase of the resident female mice on social behaviors and USVs in experiment 1 (same pre-testing isolation). The impact of the estrous phase of the experimental female B6 subjects was investigated on each testing day on social behaviors (A-E) and USVs' characteristics (F-J). All the B6 mice were isolated for 3 days in the testing cage before each social encounter. For the exact number of mice in each estrous phase, refer to Table  1. Data are mean ± SEM. Total N = 10 before exclusion of statistical outliers by Grubb's test for small samples.
*p < 0. 05. two independent cohorts, in order to evaluate the replicability of female phenotypes, we analyzed the female dataset by an additional ANOVA with experiment as the between-subject factor and testing session as the within-subject variable. Concerning social behaviors, the results on session-dependent changes were similar between the experiments, as shown by lack of the interaction experiment × session (all effects, n. s. ). Independently of the experiment, the levels of affiliative behaviors tended to decrease with the testing sessions while those of cage exploration increased [session effect, respectively: F (2,32) = 10. 31 and F (2,34) = 10. 47, p < 0. 001; Figures  2, 6 ]. Independently of the experiments, all the USV parameters did not significantly change across the testing sessions (Figures  2, 6 ), and the expression of the different call types (Figures  3, 4, 7, 8 ; session effect and its interaction with experiment: all ns).
Since the female mice were tested under exactly the same experimental conditions in experiment 2, it is natural to infer that the differences emerging between our two experiments are due to corresponding differences in the behaviors of the male mice that were exposed to pre-testing isolation only for experiment 1. The behavior of the female mice was indeed highly comparable in our two experiments, as confirmed by the statistical comparison of the two female datasets, supporting the replicability of female social and ultrasonic behavioral profiles across the repeated testing sessions. Male behaviors appeared instead slightly different between the two experiments, although we could not conduct a statistical quantification of these differences because of the confounding effects of independent testing on social isolation.
Social behaviors and USVs were analyzed following otherwise the same procedures used for experiment 1 (3 testing sessions of 3 min each and at an interval of 7-10 days). A detailed distribution of the estrous phase in the female residents and intruders is provided in Table  1. Data are mean ± SEM. N = 10 before exclusion of statistical outliers by Grubb's test for small samples. duration of the testing session and the estrous cycle of the intruders may critically influence the social effects of isolation, an issue that deserves to be specifically investigated in future studies. Independently of the experiments, our findings suggest that the major sex differences affecting mouse ultrasonic communication are of qualitative nature (duration and call composition) rather than quantitative. While the presence of longer USVS in the female mice was in line with previous studies (e.
The proposed model may also help studying the long-term impacts of booster injection frequencies, according to the characteristics of a given population. Using the Israeli Ministry of Health database, a study conducted between 10 January and 2 March 2022 (when Omicron was most prevalent) has confirmed that both the incidence and the severity of SARS-Cov-2 infection were lower after a fourth dose of BNT162b2 vaccine than after only three doses  [27]. In the simulations carried out here, strategies were compared without constraint relative to the access to the vaccine. Thus, vaccinating either all still-refractory adults or children <12 years was not supposed to slow down the administration of booster shots. This choice is justified, at least in France, because of the currently high vaccination coverage (53.
Data Availability Statement: All data generated during this study are available from the corresponding author on reasonable and motivated request. The prevalence values in France are publicly available from Santé Publique France https://www. santepubliquefrance. fr/ (accessed on 3 October 2022) for Alpha, Delta, and Omicron variants. The data used for estimation are also publicly available from Santé Publique France https://www. data. gouv. fr/fr/datasets/donneeshospitalieres-relatives-a-lepidemie-de-covid-19/ (accessed on 3 October 2022). The prevalence of Removed individuals in France on 1 January 2021, are publicly available from Institut Pasteur https://modelisation-covid19. pasteur. fr/realtime-analysis/infected-population/ (accessed on 3 October 2022).
Study design and population We conducted a multicentre, retrospective, observational cohort study. Patients with three doses of COVID-19 vaccines approved in France were included between 1 January 2021 and 31 August 2021. Participants were recruited at nine lung transplant centres belonging to the Groupe de Travail de Transplantation de la Société Française de Pneumologie, a network composed of all lung transplant centres involved in biomedical research projects in France. Exclusion criteria were age <12 years, vaccination before transplantation, less or more than three vaccine doses, absence of data on post-vaccination SARS-CoV-2 antibody levels, COVID-19 infection before vaccination or before serological testing and treatment with monoclonal antibodies to SARS-CoV-2 before serological testing.
Data collection Data were entered into a secure and anonymised database. We recorded demographic features, characteristics of the transplantation procedure, medications, nature and timing of the vaccine doses, occurrence of COVID-19 infection after vaccination, and administration of monoclonal antibodies to treat or prevent COVID-19. The maintenance immunosuppressive regimen at the time of vaccination was collected, as well as whether intensified immunosuppression was given within 6 months before vaccination. Follow-up for the study was ended on 31 December 2021.
Discussion We report data on the spike protein IgG antibody response to three doses of COVID-19 vaccine in the largest cohort to date of lung transplant recipients with no history of COVID-19. The humoral response to vaccination was poor, with only 16% of patients producing protective levels of anti-spike IgG antibody. Clinically, severe COVID-19 did not occur in any of the responders. Of the non-responders, 1. 7% had severe COVID-19 and 0. 7% died of COVID-19 during study follow-up. The recruitment at multiple transplant centres involved in and the sample size of over 1000 patients are major strengths of our study. No patients with a history of COVID-19 or anti-SARS-CoV-2 antibody treatment before vaccination, or of antibody treatment before serological testing, were included. All study centres used the same vaccination protocol.
Although titres of anti-spike IgG antibodies correlate with those of neutralising antibodies, no threshold or correlate of protection has been established for variants of concern. Lower levels of neutralising antibodies have been reported with variants compared with the ancestral strain  [23]. Data on correlations between antibody titres and disease severity are lacking  [24]. No change in the 264 BAU•mL -1 anti-spike IgG antibody threshold has been recommended since the emergence of variants of concern. The use of monoclonal antibodies in a quarter of the non-responders may have decreased the number of COVID-19 cases. Several different immunoassay brands were used to determine the antibody titres. Nonetheless, manufacturers have established standardised results  [25]. Due to the start of the omicron wave, follow-up was ended on 31 December 2021, limiting our ability to diagnose subsequent COVID-19 episodes.
Finally, safety of the vaccination protocol was not specifically assessed, although no serious adverse effects of the vaccine were recorded and neither was the frequency of transplant rejection unusually high. Our findings are consistent with published data on the humoral response to three vaccine doses in solid-organ transplant recipients  [7] [8] [9] [10] [11] [12] [13]  and add to the scant information available on lung transplant recipients  [6, [14] [15] [16] , for whom the effect of three vaccine doses had not yet been reported in substantial cohorts. The marker for vaccine efficacy was usually anti-spike antibody production  [6-8, 11-13, 15-17] , with only a few studies assaying anti-receptor binding domain  [10, 17]  and neutralising antibodies  [10]. With two doses of mRNA vaccine, the proportion of lung transplant recipients who achieved a serological response was only 10-39% in earlier work  [11, 15, 17].