dataesr/scientific-paragraphs-categorization huggingface dataset:
We note that in this case the fraction of tracked observed interactions is about 50%, a value very close to the one recently obtained in  [47]  in a comparison between the contacts between human individuals as observed in an annotated video and as registered by wearable sensors. We finally note that we can consider the reverse procedure, considering the contacts registered by the sensors as ground truth. To this aim, we restrict the sensors' contact data to the time windows corresponding to the behavioral observation periods: only 6. 63% of these contacts were recorded by the observer as interactions. Note that this small number is not surprising, as the observer focuses on one individual at a time, while the sensors' infrastructure registers contacts between all collared individuals during the same time window.
Other aggregation timescales As described in Methods, we also considered other timescales on which to aggregate the data coming from the observations and from the sensors infrastructure. Indeed, the time constraint of observational measures implies that the amount of information concerning each individual per day is relatively small. Building a reliable picture of the social bonds between individuals requires thus many days of observation and an aggregation window of one month is usually advocated  [22, 48]. In the case of data collected through wearable sensors on the other hand, a large amount of contacts is already recorded after a few hours. However, it is a priori unclear whether the structures present on short timescales such as e. g. one day of data fluctuate from day to day or are stable and already representative of the group social structure and of its strong links.
We show in the Supplementary Material that the interaction networks aggregated at daily scale are even more fluctuating, and that important differences are measured even between weekly aggregated successive networks. On the other hand, daily networks obtained from sensor data are already quite stable. We then build interaction and contact networks on time windows of increasing lengths, starting from the beginning of the observations (using only the first day of data, then the first two days and so on), and compare them with the aggregated network based on the whole observation time window. Figure  7  shows the resulting GCS and average LCS as a function of the length of the time window considered. The obtained similarities are already close to 1 when only one day of the sensors data is used (GCS = 0.
Discussion In this paper we analyzed and compared data sets describing social relationships in a group of non-human primates, collected through two different methods: behavioral observations and wearable proximity sensors. Sensors and behavioral observations methods have different advantages and limitations that influence their ability to detect contacts and interactions between individuals. On the one hand, observational methods provide high-quality data, through which we can distinguish different behaviors and describe in depth social relationships between individuals. However, the data suffers from several sampling issues: only a limited amount of time can be spent observing each individual, and data may be completely absent on certain days for logistical reasons (the week-ends in our case).
Another difficulty could also come from data losses whenever a part of the infrastructure fails. We show however in the Supplementary Material by simulating the failure of a reader that the structure of the social network deduced from the sensor data remains very stable even when the amount of data lost is important. We have performed a comparison of the two data sets at various levels of detail. At the most detailed level, we have checked for each observed interaction whether a contact was registered by the sensors at the same time. This matching turns out to be very limited: about one third of the observed interactions was also recorded by the sensors, but this amount fluctuates and depends strongly on the type of interaction. In particular, for interactions that tend to last, such as grooming, the percentage of tracked events rises to ∼ 50% and is above ∼ 80% in some days of observations.
Material Eight PLDs depicting an emotional facial expression (happiness, anger, disgust, or surprise) of a man or woman were used in the experiment. These PLDs were taken from the PLAViMoP database  (Decatoire et al. , 2018 ; https://plavimop. prd. fr/en/ motions 1 ). They were each made up of 41 points representing the position of the actors' eyes, eyebrows, mouth, nose, outline of their face, shoulders and sternum. 4 mm hemispherical facial markers were used for face and 6. 4 mm spherical markers for sternum and shoulders (see Appendix 1 and Image 1 in Supplementary Material for a complete description). Importantly, the eyes' position has not been recorded directly but has been calculated a posteriori from the position of dots placed at the edge of each eye. This choice was made to render our PLDs more "face like" because a pre-test including 15 adult participants showed that without eyes, our face PLDs seemed strange and ghostly.
We extracted 60 neutral nouns composed of one (30 nouns) or two (30 nouns) syllables from the validated French Affective Norms database  (Monnier and Syssau, 2014). These French words were selected for their neutral valence (M = 4. 88, SD = 1. 53) and level of arousal (M = 3. 30, SD = 2. 22), as rated on the nine-point scale of the database.
Data Analysis In the priming task, our first dependent variable (DV) was participants' binary responses to categorizing neutral words (i. e. , negative vs positive) as a function of PLD prime (i. e. , negative or positive expression). Each response was coded one when it was congruent with the valence of the PLD prime (i. e. , positive response when the PLD represented a positive expression; negative response when the PLD represented a negative expression), and 0 when it was incongruent. The second DV was the corresponding response times. For these two DVs, we calculated mixed models, using the GLIMMIX procedure with SAS Version 9. 4 statistical software. For the first DV (i. e. , categorisation), we ran a logistic mixed model, with participants and items as random-effects factors. Three fixedeffects factors were considered: PLD category (positive/happiness vs negative/anger), sex of participants (male or female), and their interactions (see  Baayen et al.
FUNDING Support for this research was provided by a grant from  La Région Nouvelle Aquitaine  ( CPER-FEDER P-2017-BAFE-68 ), in partnership with the  European Union (FEDER/ERDF ,  European Regional Development Fund) , and by the  French Government research program Investissements d'Avenir through the Robotex Equipment of Excellence  ( ANR-10-EQPX-44 ).
It was recognized long ago by Seneca through his famous "errare humanum est. " that the human information processing system is intrinsically fallible. What is newer is the fact that, at least in sensorimotor information processing realized under time pressure, errors are largely dealt with by several (psycho)physiological-specific mechanisms: prevention, detection, inhibition, correction, and, if these mechanisms finally fail, strategic behavioral adjustments following errors. In this article, we review several datasets from laboratory experiments, showing that the human information processing system is well equipped not only to detect and correct errors when they occur but also to detect, inhibit, and correct them even before they fully develop. We argue that these (psycho)physiological mechanisms are important to consider when the brain works in everyday settings in order to render work systems more resilient to human errors and, thus, safer.
, 2002b). If this opinion is correct, there may exist two (independent) factors contributing to variations of accuracy: those resulting from variations in the reliability of the information processing chain and those resulting from variations in the efficiency of the action monitoring system. Two datasets can exemplify the contribution of each of these factors. van  de Laar et al. (2012)  showed that, in a choice RT task, 8 or 12-year-old children committed about three times more errors (9. 7%) than 20-year-old adults (3. 5%). The same effect showed up on partial errors (29. 05% vs. 10. 1%; calculated based on table 2 in van de  Laar et al. , 2012, p. 327). On this basis it is possible to estimate the correction ratio of the children (0. 76) and young adults (0. 74). It is clear that the increase in the error rate of children cannot be attributed to a failure of the action monitoring system as they could correct their errors at least as well as young adults.
This means that before EMG onset, M1 involved in the response was activated, while M1 involved in the not to be produced response was inhibited. In the same type of task,  Tandonnet et al. (2011)  demonstrated that the Motor Evoked Potentials (MEP) generated in the muscles involved in the response by the magnetic transcranial stimulation of contralateral M1 increased just before EMG onset, while the MEP of ipsilateral M1 decreased just before EMG onset. This dataset perfectly bridges the gap between the observations of  Hasbroucq et al. (2000)  and those of  Burle et al. (2002a). Still, in a between-hand choice RT task, response-locked ERPs showed that, shortly before EMG onset, a transient negativity developed over contralateral M1, while a positive wave developed over ipsilateral M1  (Vidal et al.
BMI (in kg/m 2 ) was calculated by dividing weight (in kg) by squared height (in m). Hip, waist, upper arm (flexed and tensed) and calf circumferences were measured to the nearest mm in a standing position using a tape measure  [45]. Waist-to-hip ratio (WHR) was calculated. A Harpenden skinfold caliper (Holtain Ltd. , Crymych, UK) was used to measure triceps, supraspinal, subscapular and medial calf skinfold thicknesses to the nearest mm  [46]. A Mitutoyo Dial Caliper (Mitutoyo America, Aurora, Illinois, USA) was used to measure the biepicondylar humerus and femur bone breadths. Using the Somatotype 1. 0 software package (MER Goulding Software Development, Geeveston, Australia), the somatotype of each participant was assessed from the calculation of its ternary component (musculature, slimness and fatness indexes) based on ten of the anthropometric measures described above  [37] , and stated in the BSS development protocol  [27].
The BOSHAS is the first body image scale to rigorously and accurately capture a large variation in African body shape. First, real African models of both genders standing in two positional views were captured by the BOSHAS, so this tool represents a significant improvement in the development of body image scales for Africans  [41]. Indeed, the BOSHAS avoids misestimating that results from using silhouettes or drawings  [20, 23] , or inappropriate Eurocentric photographic body image scales, illadapted to African populations  [29, 30]. In addition, the BOSHAS adds to a body of evidence, which has limited anthropometric data on body shapes scales for both males and females  [22, 23, 49, 64] , and seldom incorporates frontal and side views  [22, 23, 65]. The side view represents the belly, buttocks and breast shapes best  [41] , which are criteria contributing to body attractiveness  [31, 66, 67].
Whilst computerized methodologies are available to capture body shape in three-dimensions, they do not present real human models, are expensive, and remain unfeasible for large scale epidemiological studies in low and middle income countries  [29, [68] [69] [70]. Additionally, the BOSHAS captured varying African body shape phenotypes by presenting 10 models on each sex-specific subscale including somatotype (i. e. different degrees of mesomorphy, ectomorphy and endomorphy Fig. 3  Somatotype profiles of male candidates as models for the BOSHAS. In somatocharts (generated with the Somatotype 1. 0 software package), mesomorphy is represented by the vertical axis pointing upward; endomorphy by the horizontal axis pointing to the left; and ectomorphy by the horizontal axis pointing to the right.
A possible explanation could be that the BOSHAS expresses a body shape variation whereas BMI expresses a body size variation. Future studies could correlate CBS with the somatotype of participants, but for this present study it was unfeasible to assess the somatotype of 597 subjects in the field. Despite these relatively low kappa coefficients, agreements between CBS and BMI were demonstrated and significant in both subscales. Globally, the validation of Fig. 4  Somatotype profiles of female candidates as models for the BOSHAS. In somatocharts (generated with the Somatotype 1. 0 software package), mesomorphy is represented by the vertical axis pointing upward; endomorphy by the horizontal axis pointing to the left; and ectomorphy by the horizontal axis pointing to the right. The coordinates 951 on the left side present, for instance, the highest degree of endomorphy  [9] , a medium degree of mesomorphy  [5]  and the lowest degree of ectomorphy  [1].
Aims: Hypoglycemia is one of the most important complications associated with Ramadan fasting in people with type 2 diabetes. LixiRam (NCT02941367) was the first randomized trial comparing safety and efficacy of lixisenatide + basal insulin (BI) vs. sulphonylurea + BI in people with type 2 diabetes who fast during Ramadan. This post hoc analysis focuses on the LixiRam study population from India. Methods: Adults with type 2 diabetes insufficiently controlled with sulphonylurea + BI ± an other oral anti-hyperglycemic drug were randomized 1:1 to receive lixisenatide + BI or to continue sulphonylurea + BI treatment. Results: In total, 150 participants were randomized in India. One participant (1. 3%) with lixisenatide + BI vs. 5 participants (6. 8%) with sulphonylurea + BI experienced 1 documented symptomatic hypoglycemic event during the Ramadan fast (odds ratio [OR]: 0.
The use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) has been suggested for type 2 diabetes management during Ramadan in recent guidelines due to their favorable efficacy and safety profiles  [1, [9] [10] [11]. Lixisenatide is a oncedaily prandial GLP-1 RA that effectively improves glycemic control through its immediate and sustained effects of lowering both post-prandial and fasting glucose concentrations in people with type 2 diabetes, with a relatively low risk for hypoglycemia  [12]. In the recently published LixiRam study (NCT02941367)  [13] , lixisenatide as an add-on therapy to BI was shown to be beneficial for the treatment of type 2 diabetes both before and during Ramadan fasting. Rates of any hypoglycemic event were lower with lixisenatide + BI vs. the comparator group, SU + BI.
Acknowledgements The authors would like to thank the participants, their families and all investigators involved in this study. The authors would also like to thank  Virginia Rafael , Biostatistician, of  Linical (CRO company ). Medical writing support was provided by  Amber Lynch, PhD , and  Rob Campbell, PhD , of  Prime, Knutsford, Cheshire, UK , and funded by  Sanofi  according to Good Publication Practice guidelines (https://annals. org/aim/fullarticle/2424869/good-publication-practice-communicating-company-sponsored-medical-research-gpp3). Coordination of the development of this manuscript and assistance with the revision was provided by  Helena Andersson, PhD , at  Sanofi. Sanofi was involved in the study design and collection, analysis and interpretation of data, as well as data checking of information provided in the manuscript.
Data statement Qualified researchers may request access to participant level data and related study documents including the clinical study report, study protocol with any amendments, blank case report form, statistical analysis plan and dataset specifications. Participant level data will be anonymized and study documents will be redacted to protect the privacy of trial participants. Further details on Sanofi's data sharing criteria, eligible studies and process for requesting access can be found at: https://www. clinicalstudydatarequest. com.
-Coffee, tobacco and alcohol consumption Data on coffee, tobacco and alcohol intake was self-reported by participants on a daily basis on the sleep diary. Participants were asked to record the daily amount of each substance consumed: the number of cigarettes, the number of cups of coffee and the number of standard glasses of alcohol per day. We classified coffee, tobacco and alcohol use into 2 ascending ranks for each substance: regular consumption (at least one consumption per day) and no daily use. We also calculate the average daily use of cigarettes, coffee and alcohol for the 3 weeks period of recording. Individuals also filled in the Fagerström Test for Nicotine Dependence  (Heatherton et al. , 1991)  and we calculated the lifetime pack-years of cigarettes, by multiplying number of packs of cigarettes smocked per day by the total duration of smoking.
-DISCUSSION This study investigated for possible associations between the daily use of coffee, tobacco and alcohol and the sleep and activity parameters in a sample of euthymic individuals with BD who have been objectively recorded by actigraphy over 21 consecutive days. To our knowledge, this is the first study in the literature to investigate such an issue. First, individuals drinking daily coffee had shorter sleep duration and there was an association between the average amount of coffee drank and a shorter sleep duration. Even if the first result was not confirmed by the multivariable analyses, our results remained consistent with data in the literature showing that caffeine reduces total sleep time, the effect is suggested to be mediated by a blocking effect on adenosine receptors  (Shilo et   (Angarita et al.
Remerciements A Monsieur le  Professeur Jean-Pierre KAHN ,  Professeur des Universités -Praticien Hospitalier de Psychiatrie ,  Merci de me  faire l'honneur de présider ce jury de thèse. Je vous remercie pour vos précieux conseils, pour m'avoir accueilli et encadré au sein de votre service ainsi que pour votre bienveillance et votre enseignement à travers le partage de votre savoir et votre expérience clinique. Vous m'avez ainsi transmis votre passion pour les troubles de l'humeur. Je vous remercie de la confiance que vous m'avez accordée et votre soutien constant tout au long de mon internat. Vous m'avez donné l'opportunité de réaliser un Master 2 au sein de l'équipe de recherche du  Professeur Frank BELLIVIER  qui fut une année passionnante et enrichissante tant professionnellement qu'humainement.
Funding/support This work was supported by  Institut National de la Santé et de la Recherche Médicale  ( INSERM -Research Protocol C0829 ),  Assistance Publique des Hôpitaux de Paris  ( APHP -Research Protocol GAN12 ). This research was also supported by the  Investissements d'Avenir, program  managed by the  Agence Nationale de la Recherche (ANR)  under reference  ANR-11-IDEX-0004  and  Fondation FondaMental (RTRS Santé Mentale).
psychiatric department in Paris, France. This research project was approved by the French ethics committee (Comité de Protection des Personnes -Ile de France (IDRCB2008_AO1465_50 VI -Pitié Salpêtrière 118-08) and by Commission Nationale de (Young et al. , 1978)1994)ertés (CNIL, that is the national committee in charge of the protection of data recorded from persons who participate to biomedical research). The study is registered under the number NCT02627404 (ClinicalTrials. org). Inclusion criteria for patients were as follows: 1) age 18 or more; 2) been diagnosed with BD according to DSM-IV criteria using the Diagnostic Interview for Genetic Studies (DIGS)(Nurnberger et al. , 1994); 3) been currently euthymic, for at least three months prior to the study, as defined by both scores below 8 on the Montgomery-Asberg Depression Rating Scale (MADRS) (Montgomery and Asberg, 1979) and Young Mania Rating Scale (YMRS)(Young et al.
Statistical analyses The standard polysomnographic variables were analysed using 2-way ANOVA with one independent factor (group) and one repeated measure (recording). To assess group effect on spindles and SWO densities, we performed mixed-models with one independent factor (group) and three repeated measures (stage, derivation, recording). Fixed effects for the group, the stage, the derivation and the recording and full factorial interactions were studied. The global significance of the different effects and interactions was tested for a 0. 025 alpha cut-off, according to Bonferroni correction, because data were analysed twice: for all cycles, and for the first cycle alone. Statistical analyses were performed with IBM SPSS Statistics version 20 © software.
, beng in English) and they must repeat out loud each as similarly to the model as possible. These studies often employ 12-30 items varying in length from 1 to 5 syllables (most commonly 2-4 syllables). NWR scores are typically estimated as the percentage of items repeated correctly (as judged by the researchers). NWR scores have been found to correlate with other measures of phonological processing concurrently  [16, 17]  and to be a robust predictor of later literacy  [18, 19]. Additionally, and in line with theories proposing that phonological processes depend on lexical development, NWR correlates with vocabulary size (e. g. ,  [20] ). In the present study, we report on NWR data collected from both adults and children. If directed input is crucial for the development of short-hand-like phonological representations, then Tsimane' children's NWR scores will be lower than that among children growing up in populations where infant-directed input is more common.
To simplify discussion, we collapse across illiterates, non-readers, zero years of schooling, and "before literacy training", but interested readers can inspect Table  1  for raw data on these separate categories. As in the childhood literature reviewed above (see  Fig 1) , studies on adults report widely variable levels of NWR scores. Among these studies,  [52]  is particularly relevant in terms of decorrelating literacy and schooling. [52]  reports on a longitudinal study in which 8 previously illiterate adults received 14 weeks of reading training, and six of them learned how to read in this process. NWR data was collected several times through this period, each time having participants repeat nonwords with increasing syllable complexity (CVs, then CCVs) and length (1-6 syllables). NWR data was available for 7 participants, whose average score on a subset of 8 items increased from 21% to 38%-however, this was for a subset that the authors thought had no ceiling effects.
The current study In a nutshell, we tested children and adults in a society where infants are rarely spoken to, and where literacy is variable. As a result, it is possible that phonological processing is different due to the low levels of directed input in infancy, as well as because literacy (and any skill associated with it) has not served to reinforce and/or maintain short-hand-like phonological representations among our illiterate participants. As discussed in subsequent sections, the sample size of the present study is fairly small and analyses were not pre-registered, and should be considered exploratory. We inspect our data in three main ways. First, by comparing the NWR scores of Tsimane' participants against those of participants in previous literature, we aim to shed light on the potential long-term effect of low levels of infant-directed input on phonological processing.