dataesr/scientific-paragraphs-categorization huggingface dataset:
NV work was supported by a grant of the  Ministry of Research, Innovation and Digitization, CNCS-UEFISCDI , project number  PN-III-P4-PCE-2021-1450 , within PNCDI III. PFML thanks  CNPq  for a productivity grant ( 301515/2019-0 ). SM is funded by the  Fisheries and Oceans Canada Multi-Partner Research Initiative.
5 years  [22]. Mouse lemurs are strict long-day photoperiodic breeders  [23]. At the beginning of the breeding season, females enter oestrus and males compete to priority access to females  [24]. Females give birth to 1 to 3 offspring after a 2-month gestation period and nurse infants for approximately 40 days without male parental care. Records of ages at conception for both mothers and fathers and the relative long longevity of captive mouse lemurs give the opportunity to test the "Lansing effect". Using a large database on captive mouse lemur's life history traits, the aim of this study was to examine whether parental age at conception affects the longevity of offspring. We expected a reduced longevity of offspring born from old parents. Finally we tested the potential relationship between parents' and offspring's longevity.
Animals To investigate the effects of parental age at conception on offspring lifespan, we analysed the longevity data of mouse lemurs for which the age of both parents at the time of reproduction was known. Data were recorded in the mouse lemur history traits database from a laboratory breeding colony established in Brunoy (UMR 7179 MNHN-CNRS, IBISA Platform, agreement F91. 114. 1, DDPP Essonne, France) from a stock originally caught near the southern western coast of Madagascar sixty years ago. Captive conditions were maintained constant with respect to ambient temperature (24-26˚C) and hygrometry (55-60%). Animals were fed ad libitum on a standardized diet, including fresh fruits, a homemade milky mixture (19. 3% proteins, 17. 2% lipids and 63. 5% carbohydrates) and mealworms. To ensure seasonal reproductive rhythms, animals were routinely exposed to an artificial photoperiodic cycle consisting of 6 months of summer-like photoperiod (LD = 14 h of light/day) followed by 6 months of winter-like photoperiod (SD = 10 h of light/day)  [23].
Data analysis Our analysis was focused on parents (132 dams and 122 known sires) and their offspring (140 males and 138 females) that died naturally. Paternity determinations have been previously determined by behavioural observations and genetic analyses and were registered in the database. Briefly, DNA samples were collected from ear or skin tissue samples, extracted (with a QIAmp DNA Mini Kit no. 51306-Qiagen) and amplified. Genetic analyses were then conducted using random amplified polymorphic DNA method or microsatellite loci  [25] [26] [27]. To assess which parameters may influence the longevity of offspring, several parameters for both parents and offspring were selected. Data are presented as mean± SEM. First, age at conception for both parents was considered. dams' age at conception averaged 2.
Thus, the accessibility of a tangible tactile map with clear shapes and the power of an internet database with massive geo-referenced information were combined. The SMAug system was made to be used at a chart table aboard a sailboat to prepare navigation, but it can also be used at home or in the office (cf. Figure  1 ). system. More precisely, users digitally explored 3D maps, a cam the tactile map, and a colorimetric-based detection script allow to be triggered to give the names of the seamarks. Thus, the a tactile map with clear shapes and the power of an internet dat referenced information were combined. The SMAug system w chart table aboard a sailboat to prepare navigation, but it can al the office (cf. Figure  1 ). Figure  1. SMAug system at a chart table on a sailboat before navigatio the tactile map with a sticker on a finger to track it.
Equipment Participants explored the same 60 × 60 cm 3D-printed tactile map. It was a real maritime chart for blind sailors. It represented the bay of Brest (France) at a scale of 1:20,000, i. e. , 1 cm on the map represented 200 m in the real environment. Land elevation followed the altitude of the digital terrain model, but all the values were doubled to make the coastline easier to feel by touch. The sea area was flat and contained 38 seamarks among 10 kinds of marks. The experiment used only 12 seamarks from 4 kinds of shape. In other words, only 12 seamarks were made audible. The map model was made with the open-source software Navisu (https://github. com/terre-virtuelle/navisu accessed on 6 June 2022) Nine tiles of 20 × 20 cm were printed with an Ultimaker 3 3D-printer with blue PLA material.
To run the colorimetric-based detection SMAug software, we used a dual core computer with 4 GB RAM, the Ubuntu exploitation system, and a 1080 HD Logitech camera mounted on a 50 cm-high desk lamp. The software application was coded with Python 3, and the libraries OpenCV (https://opencv. org/ accessed on 6 June 2022) and pyttsx3 (https://pypi. org/project/pyttsx3/ accessed on 6 June 2022) for computer vision and text-to-speech. Vocal announcements were made via loudspeaker. The finger condition used a 15-mm-diameter sticker on the right index finger, and the marker condition used a 17-mm-diameter 3D-printed hand piece (cf. Figures  3  and 4 ). years old (mean = 22. 5). All participants were familiar with the tech were right-handed. In response to the question, "Are you familiar with paper ch "medium", four, "no", and two, "yes".
Estimation Task The next task was to estimate the distance and the direction f another. Three in the finger condition, three in the marker condition ample, the question could be, "What is the distance and direction bet Portzic?" Distance estimations were given in meters, corresponding rection estimations in cardinal degrees (i. e. , 0° north, 90°east, 180° sou could use the SMAug system during the question. Thus, they did no the names of the seamarks. We collected the precision errors of the es and direction. Finally, we also collected data on how long it took t and then to compute the calculation and give the answer. At the end, we ask the users to complete a short questionnaire they preferred for each task: localization and estimation. In each condition, as soon as the finger or the marker was less than 1 cm from the seamark, the vocal announcement of the seamark's name was triggered once.
Localization Task Thereupon each participant performed the localization task. They had to find the seamark indicated by name. Three seamarks in the finger condition, three in the marker condition; then three in the finger condition again, and three more in the marker condition. For example, the question was: "Could you find Penoupele?" Here we collected data on how long it took to find each seamark. Naturally, conditions were counterbalanced to avoid the order effect.
Estimation Task The next task was to estimate the distance and the direction from one seamark to another. Three in the finger condition, three in the marker condition, and so on. For example, the question could be, "What is the distance and direction between Penoupele and Portzic?" Distance estimations were given in meters, corresponding to the scale, and direction estimations in cardinal degrees (i. e. , 0 • north, 90 • east, 180 • south, 270 • west). Users could use the SMAug system during the question. Thus, they did not have to remember the names of the seamarks. We collected the precision errors of the estimations of distance and direction. Finally, we also collected data on how long it took to find the seamarks, and then to compute the calculation and give the answer. At the end, we ask the users to complete a short questionnaire on which conditions they preferred for each task: localization and estimation.
Participants explored the same 60 × 60 cm 3D-printed tactile ma time chart for blind sailors. It represented the bay of Brest (France) a i. e. , 1 cm on the map represented 200 m in the real environment. Lan the altitude of the digital terrain model, but all the values were double line easier to feel by touch. The sea area was flat and contained 38 kinds of marks. The experiment used only 12 seamarks from 4 kind words, only 12 seamarks were made audible. The map model was m source software Navisu (https://github. com/terre-virtuelle/navisu) N were printed with an Ultimaker 3 3D-printer with blue PLA material To run the colorimetric-based detection SMAug software, we us puter with 4 GB RAM, the Ubuntu exploitation system, and a 1080 H mounted on a 50 cm-high desk lamp. The software application was c and the libraries OpenCV (https://opencv.
Epidemiological Analysis of the Treatment of Otosclerosis This analysis was based on the literature and retrospective data on hospital stays from the French Diagnosis-Related Group system (Programme de Médicalisation des Systèmes d'Information). Information was also gathered from public health databases in France and other European countries, namely Sweden,  17  Switzerland,  18  Germany,  19  and Norway. 20 Full details regarding the epidemiological analysis are provided in eAppendix 1 in the Supplement. The economic models were implemented using data from the literature to ensure the cost and budget impact analysis were realistic. Otosclerosis symptoms appear between age 30 and 50 years. 1, 2, 6, 21 Between 13% and 58% of cases are hereditary. 1, 21 Otosclerosis surgery has a reported success rate of more than 90%.
02. reimburses its share of hearing aids every 4 years, allowing patients to update their hearing aids. The hospitalization costs associated with initial and revision surgery were obtained from the 2018 French survey of health care costs (Étude Nationale des Coûts; the last available data set). The distribution in terms of Diagnosis-Related Groups was obtained from the ScanSanté website for 2019 (Table  1 ). 26 e costs of consultations and of medical examinations were set to the current regulated fees in France (eTable 1 and eTable 2 in the Supplement). The costs of hearing aids and hearing aid batteries were estimated from a survey of audiologists and the literature. Costs were discounted at 2. 5% per year as recommended. 37 Deterministic (tornado diagram) and probabilistic sensitivity analyses were performed to test the robustness of the results.
Procedure Upon accessing the first page of the questionnaire, participants were presented with a short paragraph explaining its purpose and were asked to read a consent form and accept it electronically. No question was asked prior to this acceptance, and participants could disconnect from the survey at any point. Then demographic data were gathered and a reminder that all answers were strictly anonymous was presented. Finally, questions regarding degraded states of engagement were asked. From this point on, all questions were optional, and no default answer was proposed. The questionnaire also comprised a few questions pertaining to engagement for internal use at DSNA (not presented here). A total of 11 pages were presented, three of which only displayed information to the participants, two requested short written answers, and six included boxes to be ticked.
Data Collection and Analysis The questionnaire was implemented on a Limesurvey server hosted by ISAE-SUPAERO. Data were collected between November 2019 and March 2020. The raw results were reformatted with Python 3. 7. 3 using pandas 0. 24. 2. Descriptive statistics were computed with numpy 0. 16. 4 and statsmodel 0. 10. 0. Inferential statistics were computed with R version 3. 6. 3, using MASS 7. 3-51. 6 for the ordinal logistic regression. As one exploratory hypothesis was tested in this study for the distribution of occurrences of degraded engagement, seven more in the ordinal regression of degraded engagement against age, and three for the Cochran's Q test on the impacts of degraded states, a Bonferroni correction to the significance threshold was applied to mitigate the type I error. A value of α = 0.
94) and older people (ICC =. 95) between the Quebec and Belgian judges, so that the words were evaluated similarly regardless of the country of the judges. Moreover, the values of the ICC remained high (≥. 87) when considering the Belgian and Quebec judges separately, which led us to include all judges in the analyses. For each participant, we finally calculated a total score by creating a mean for the valences of words produced, with a higher score indicating a more positive vision of older adults. Percentage estimations were analyzed by comparing the two groups of participants using a bilateral student's t-test on overestimation indexes for questions concerning people older than 65 and older than 80. For both targeted age groups, the overestimation index was computed in two steps: 1) For each question, we subtracted the data available in the scientific literature from the raw estimation given by each student 1 , except for the use of the Internet, which was inverted.
Acknowledgements: This work was supported by the  Fund for Scientific Research Belgium (F. R. S. -FNRS ) to  Manon Marquet  (Research Fellow), by a postdoctoral grant from the  Fonds de Recherche du Québec -Santé (FRQS)  to  Guillaume T. Vallet , and by the  Fund for First Spin-off  ( DGO6 ,  Walloon Region, Belgium)  to  Pierre Missotten.
However, a follow-up Fisher's z test estimated by cocor package  39  showed that the magnitude of correlations of log-attenuation rate and error between HC and TD was not significantly different [z = -1. 240, p (two-tailed) = 0. 215]. Proactive delay was also significantly correlated with error in both HC [r (25) = -0. 775, p (one-tailed) < 0. 001, R 2 = 0. 601, BF -0 > 100] and TD [r (44) = -0. 735, p (one-tailed) < 0. 001, R 2 = 0. 540, BF -0 > 100]. Bayesian statistics suggests this relationship was 'decisive' (BF ≥ 100) for both groups. Influence of ADHD and medication on CRTT metrics. Since we found a link between deceleration rate and attention in Indrajeet and Ray (2019) and effect of medication on SSRT in Atkinson-Clement et al. (2020), we subsequently verified whether presence of ADHD or medication influenced CRTT metrics (see Table  3 ).
The ENTER key of the keyboard was assigned for response input. The pre-processing and basic analysis (e. g. , descriptive statistics, estimation of SSRTs) of the data was carried out by using Matlab® (The Mathworks Inc. , USA). Matlab® Statistical Toolbox (The Mathworks Inc. , USA) (correlations, t-tests), JASP software (JASP team, 2019, version 0. 11. 1) (Bayesian statistics) and SigmaStat (SYSTAT Inc. , USA, version 4. 0) (ANOVAs and post-hoc tests) was used for statistical analysis. Curve Fitting Toolbox™ of Matlab® was used for fitting curves. Estimation of CRTT metrics. The CRTT model advocated that the preparatory build-up activity is decelerated after the stop-signal is detected if and only if the stop-signal is detected in a stipulated time and the magnitude of deceleration is sufficient to prevent the preparatory activity building up over time from reaching a threshold  36.
Table1shows the details of demographics and incidence of comorbidities. The data collected from 14 participants (10 TD and 4 HC) were removed from analyses due to incomplete behavioural data or misunderstood instructions. A total of 53 TD (Sex: 11 females, 42 males, mean ± SD age: 30. 21 ± 10. 5 years, education: 14. 25 ± 2. 56 years) and 30 HC (Sex: 09 females, 21 males, mean ± SD age: 31. 63 ± 10. 44 years, education: 14. 57 ± 2. 93 years) was available for this study. In this sample, there was no significant difference in age [t (81) = 0. 596, p (two-tailed) = 0. 553, d = 0. 136, BF 01 = 3. 624]; education level [t (81) = 0. 522,.
Acknowledgements The study was supported by the  National Research Agency  ( ANR-18-CE37-0008-01 ),  French Tourette Syndrome Association (AFSGT)  and  Fondation pour la Recherche Medicale (FRM). Author II was supported by fellowships by the  University Grants Commission (UGC) ,  India , and  Edmond & Lily Safra Center for Brain Sciences , the  Hebrew University of Jerusalem , Israel. The author SR was supported by a fellowship from the  Wellcome Trust DBT India Alliance  [ IA/I/13/2/501015 ].
Table1shows the details of demographics and incidence of comorbidities. The data collected from 14 participants (10 TD and 4 HC) were removed from analyses due to incomplete behavioural data or misunderstood instructions. A total of 53 TD (Sex: 11 females, 42 males, mean ± SD age: 30. 21 ± 10. 5 years, education: 14. 25 ± 2. 56 years) and 30 HC (Sex: 09 females, 21 males, mean ± SD age: 31. 63 ± 10. 44 years, education: 14. 57 ± 2. 93 years) was available for this study. In this sample, there was no significant difference in age [t (81) = 0. 596, p (two-tailed) = 0. 553, d = 0. 136, BF 01 = 3. 624]; education level [t (81) = 0. 522, p (two-tailed) = 0. 603, d = 0. 119, BF 01 = 3. 756]; or gender [ X 2 (1, N = 83) = 0. 895, p = 0. 344, Cramer's V = 0. 012] between the TD and HC groups. Out of 53 TD patients, 19 were taking antipsychotic medication, 23 had ADHD, and 11 had OCD.
0004 384 ± 15 44. 07 ± 1. 42 TD without ADHD 0. 0089 ± 0. 0002 384 ± 12 44. 65 ± 0. 99 p 0. 717 0. 997 0. 733 BF 01 3. 279 3. 461 3. 299 Medicated TD 0. 0086 ± 0. 0003 366 ± 16 45. 89 ± 1. 51 Un-medicated TD 0. 0089 ± 0. 0003 395 ± 11 43. 48 ± 0. 91 p 0. 412 0. 117 0. 153 BF 01 Ethics. The study was approved by the Comité de protection des personnes (CCP) of Sorbonne Université 2. 601 1. 235 1. 471 (CCP16163/C16-07) and preregistered prior to the research being conducted on ClinicalTrial (https:// clini caltr ials. gov/ show/ NCT02 960698). All participants gave their informed consent. All procedures comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. total.
Methods Data were collected in three European universities: the University of Pisa (Italy), Loughborough University (UK) and the École Polytechnique Fédérale de Lausanne, (EPFL, Switzerland). As often is the case of qualitative studies, this is a purposeful sample  (Patton, 1990)  in that the universities are chosen to represent three very different higher education traditions (see Table  8  in Appendix 1). This is a key feature of the sample, and it allows an investigation of the impact of institutional differences on students' experiences of STT. The questionnaire used in Di  Martino and Gregorio (2019)  was translated into English and French (the English version is in Appendix 2) and administered to first-year students enrolled on a mathematics degree at the three universities. Complete data were collected from 26 students from Italy, 45 from the UK, and 58 from Switzerland.
Data Analysis Data analysis consisted in three stages and followed the method of data reduction  (Namey et al. , 2008). Following this technique, the data were analysed first qualitatively with coding techniques that allowed the development of a unified set of codes and then quantitatively investigating frequencies distributions, when possible. Stage 1: creation of a simultaneous and descriptive coding  (Saldaña, 2015). The qualitative answers to the questionnaires were coded independently by two researchers, and then a common list of agreed upon codes across the complete dataset was reached via an inductive process as follows: 1. Two researchers coded the data independently, developing a definition for each code introduced. When a new code was created, the researcher reviewed the previously coded data to ascertain whether the new code could be used in previous sections.
2. The researchers shared their list of codes and definitions, and each one re-coded the data using the other researcher's list of codes. 3. After step 2, a discussion about the codes and their explanatory power was held until a final list of codes-a mixed selection of the two independent lists-was shared. The final list of codes was simultaneous, meaning that the application of two or more codes to a single utterance was possible, and descriptive since the labels used for the coding were strictly related to the summarised content. 4. The two researchers compared and discussed the outcome of point two of the above process until agreement was reached. At the end of this stage, the three datasets shared the same code schemes (triangulation analysis,  Mok & Clarke, 2015). An example of the process described in points 1-4 is reported in Table  1.
Stage 2: mapping of codes in the TMA model. The codes obtained by the qualitative analysis of the three samples were mapped on the dimensions of the TMA model (Di  Martino & Zan, 2010). Codes not included in this model and related to other aspects of the passage (e. g. teaching methods) were considered separately. In this way, a qualitative analysis of the open-ended questions of the questionnaire was obtained. Stage 3: quantitative analysis. Starting from the coding described in the previous stages, qualitative data were 'quantitised' for statistical analysis, using the frequency of each code in each sample  (Namey et al. , 2008). With the aim of evaluating the comparative significance of the responses of the three different populations, the frequencies of each of the codes were analysed, when possible, first with X 2 test across the three datasets and then with paired X 2 tests with Bonferroni adjustment between pairs of datasets.
013) and the Italian sample with respect to the Swiss sample (p ≅ 0. 014). As frequencies in Table  3  suggest, indeed passion as a motivation for choosing university mathematics characterises the Italian sample. The same investigation for the code 'work opportunities' returned borderline significance (p ≅ 0. 0507) when performed across the three sites. The paired X 2 tests again with Bonferroni adjustment failed to return significance, but only just, between the UK and Italian samples (p ≅ 0. 02) indicating likely significant difference in the distribution of this code between the two datasets. In summary, UK and Italian students appear to report different motivations for joining a mathematics degree: the UK students are significantly more driven by extrinsic motivation (employability opportunities) than the Italian students are to join mathematics degrees, while Italian students report mostly intrinsic motivation (passion for the subject).
Teaching and the environment Codes relative to the changes in teaching and educational environment were less frequent than expected, although more frequent in the UK sample (24. 44%) compared to the Italian sample (7. 7%) and the Swiss sample (15. 52%). However, some of the themes across the three samples are similar. For example, reference to the fast pace of the lectures can be found in the three datasets: The largest difference is the times -at school (obviously) the pace is slower, both because the teacher writes more slowly so that students have the time to write too and because the students do not understand and ask for clarification repeatedly (and even this does not guarantee that all is clear). (IT20) Yes, huge change, I have a lot of trouble understanding the concepts and knowing how to apply them.
Data processing Spectral data acquisitions were processed using Analyst (v1. 6. 3) software and quantifications were performed with Multiquant (v3. 0. 2) software (SCIEX, Ontario, Canada). GraphPad Prism (v6. 01) (San Diego, CA, USA) and SIMCA (v16. 0. 2. 10561) (Göttingen, Germany) softwares were used for statistical analysis.
Population characteristics are plotted in Figure  2. The study was approved by the local ethical committee. Participants gave written informed consent, according to the Declaration of Helsinki, and they were paid for their participation. Please note that this dataset has been included in the analysis presented in a previous study of the impact of ageing upon oscillatory activities  (ElShafei et al. , 2019). Data from younger participants have also been used in other studies  (ElShafei et al. , 2019; Masson et al. , 2020).