dataesr/scientific-paragraphs-categorization huggingface dataset:
The MPC/MIPD method merits further discussion. Correlated residual errors in tacrolimus models were previously identified by Størset et al. ,  17  who reported that bioavailability varied less between subsequent occasions. Correlated IOV, which could otherwise be classified as "parameter drift," has not been studied in detail. Pragmatic solutions include down-weighing older concentration samples or arbitrarily increasing ω during estimation. The novel idea of adapting the estimation method rather than the model resulted in a significant improvement to predictive performance in this dataset. The predicted outcome, in the form of predicted tacrolimus trough concentrations for the MIPD arm, differs from the estimated model predictive performance for three reasons. First, an accurate prediction does not necessarily imply a future concentration in target.
ACKNOWLEDGEMENTS The authors wish to acknowledge the contributions of  Dr. Thomas Van Hove  in collecting the dataset,  Ir. Quentin Leirens  in supporting the development of the software, and  Dr. Daniel Röshammar  for reviewing the manuscript. We recognize the support of  Annouschka Laenen  at the  KU Leuven University Biostats department  in providing feedback to the study statistical analysis plan.
Objectives This study aimed to estimate the prevalence of psychoactive substance (PAS) use in night-shift healthcare workers (NSHW) during France's first COVID-19 wave (March-May 2020). Design Observational cross-sectional online survey. Setting 39 public hospitals in the Assitance Publique des Hôpitaux de Paris (AP-HP) network in the Parisian area. Participants A total of 1238 nurses, assistant nurses, X-ray technicians, managers, lab technicians, midwives and childcare assistants working at night or alternating between days and nights answered the questionnaire. Intervention Online survey. Outcome measures PAS use prevalence after weighting data for sex, age and profession using calibration on margins, in order to be representative of all AP-HP NSHW. We used the Fagerström scale and the Alcohol Use Disorders Identification Test Concise to assess PAS use.
It has a maximum score of 16, and a score higher than 10 indicates dependence. We also used many items from France's national population-based 2018 Health Barometer  23  to assess PAS use and associated consumption habits. Finally, to assess frequency of use for tobacco, alcohol, and other substances, we asked the following question three times, adapting it according to the PAS in question: 'In the past 3 months, how often have you used tobacco/alcohol/cannabis, cocaine, amphetamine, inhalants, sedatives or sleeping pills, Open access hallucinogens, opioids, other?' Response modalities were never, once or twice, monthly, weekly and daily. In addition to the two validated scales, we asked questions, which collected data on NSHW self-reported changes in PAS use since the beginning of the COVID-19 pandemic.
STATISTICAL ANALYSES Data were weighted to be representative all NSHW in the AP-HP network according to sex, age and profession. This weighting was performed using calibration on margins with the raking ratio technique,  26  which is a poststratification procedure for adjusting the sample weights in order to match the study sample's characteristics in terms of sex, age and profession as closely as possible with the known distribution of the NSHW characteristics. We estimated the weighted prevalence of PAS use and the associated 95% CIs. The following age classes were used: 20-34, 35-49 and 50 years old or over. Differences between age classes, between professional groups and between both sexes were assessed using a χ 2 test, with a 5% p value threshold for statistical significance. Stata/SE V.
Comparisons with the French general population We compared our data with those of several editions of Santé Publique France's (SPF) (French Public Health Agency) Health Barometer. These surveys are conducted on a representative sample of the French general population almost every year. For tobacco use, we focused on the 2019 and 2020 editions. 23 37 For alcohol use, even though the tools used to assess PAS use were different, we compared our findings with those from the 2017 French Barometer. 38 We also compared our data with the 2004 editions  25  which explored healthcare professionals' PAS use, to assess differences in prevalence of substance use depending on profession. NSHW in our study had lower self-reported tobacco and alcohol use than he French general population, yet the difference was small, 39 and mostly concerned daily smokers and the proportion of male smokers.
Strengths and limitations This study is the first to focus solely on NSHW in France and their use of PAS during the COVID-19 pandemic. Moreover, it is innovative in that we quantified the use of a number of PAS in several healthcare professions (nurses, midwives, managers, etc. ) as opposed to just one. Specifically, it provides novel results on the prevalences of cannabis, opioid, amphetamine and cocaine use in NSHW in France. Similar data on this population are scarce. The large sample is also representative of the whole population of NSHW in the 39 hospitals of the AP-HP network in and around Paris, in terms of profession, sex and age. Our study has limitations. First, some professions were underrepresented which prevented in-depth statistical analysis. This lack of statistical power may have resulted in some results not appearing significant when the reality may be different.
Acknowledgements We would like to thank all the study participants. We also thank the medicine students who helped us actively recruit participants, and the  AP-HP communication department  for their help in promoting the survey. Finally, our thanks to  Jude Sweeney  ( Milan, Italy ) for the English revision and copyediting of the manuscript. Contributors Conceptualisation: LC, FM, IC, ORT, SC and MD. Data curation: LC, VDB, ORT and MD. Formal analysis: LC, VDB, FM, VM, SC, OC, MD and  MPC. Funding acquisition: LC, IC, ORT, SC, OC, MD and  MPC. Investigation: LC, VDB, FM, VM, IC, SC, OC, MD, MPC. Methodology: LC, VDB, FM, ORT, SC, OC, MD, MPC. Project administration: LC, IC, ORT and MD. Resources: LC, IC, ORT and MD. Software: LC and ORT. Supervision: VDB, SC, OC, MD and  MPC. Validation: VDB, VM, SC, OC, MD and  MPC.
At the local level, the network evolves under Hebbian learning with STDP  (36). However, all the global connections are controlled by reinforcement learning  (12). To do so, we introduce the dopamine reward system  (37) , which is modulated by interactions with the external environment (Fig. 1 ). Description of the Tasks. The three selected tasks challenge differentially the sensorimotor, cognitive, and conscious levels. The sensorimotor level is common to all tasks. At this level, we use the MNIST (Mixed National Institute of Standards and Technology) dataset of handwritten digits as visual input to the visual cortex  (38). The network performs a number recognition task  (39). Following image presentation, the network processes spikes arriving within the first 250 ms, followed by a relaxation period of the same length.
Then, in the second layer, only the strongest orientation reaches the V1 area. And, in the last layer (V4 area), the patterns of digits are learned by means of STDP. In the text, we use the notation of "complex" and "simple: cells; thus the overall architecture can be written as S1-C1-S2 (see ref. 37). A detailed description of each layer can be found in Materials and Methods. To train the model and observe the local epigenesis of STDP regulated synapses, we used the MNIST dataset of handwritten digits (Fig. 2B ). These inputs consist of images of handwritten digits from "0" to "9. " MNIST is one of the fundamental datasets in machine learning, which makes it reliable and easy to use, as well as an informative benchmark for nontraditional learning methods. The images are introduced to the network continuously, with equal relaxation periods in between.
Materials and Methods This section presents a technical description of the network with all the learning mechanisms used. All the code is available on the GitHub repository: https:// github. com/ppsp-team/EpigeneSys/tree/master/GNW (91). Local Network. S1 layer. The convolution of the images is done with six 7 × 7 Gabor filters. The frequency is 0. 1 and the SD is 1 for all of them. The angles of the filters start at π/8 and go with a step of π/6. The offset of π/8 was introduced in order not to focus on vertical and horizontal lines which are not as informative in classification. Every time the Gabor kernel overlaps a border of a picture, this picture is extended by replicating the edge pixels. The resulting convolution is again resized to 128 × 128 pixels, thus creating an S1 layer with the size of 128 × 128 × 6.
MATERIALS AND METHODS This internet-based study was conducted in France in April and May 2018. A total of 234 participants completed the questionnaire. Our final sample was n = 225, since 9 participants did not meet inclusion criteria (3 did not provide consent for their data to be used; 2 obtained a Ritvo Autism and Asperger Diagnostic Scale (RAADS) score less than 14; 4 were aged less than 18). In order to facilitate results replication and refutation, an extended and detailed version of the statistics section is provided as Supplementary Material, as well as an English translation of the questionnaire. Repository URL for R code is: https://nakala. fr/10. 34847/nkl. 4021h29a. Repository URL for dataset is: https://nakala. fr/10. 34847/nkl. d3d35i2o.
Procedure After a short description of the study, women were asked to participate in this survey if they were identifying as autistic women. Participants provided consent for their data to be used in the study after completing anonymously the online questionnaire. A trigger warning was included before questions regarding victimization, as well as an invitation for victims to contact a health practitioner. After pre-submission, the president of the ethics committee of Paris V decided that it was not necessary to review the study insofar as the participants were strictly anonymous (no identifying data were collected, nor IP addresses of respondents). As per French laws regarding data privacy, the questionnaire was declared to CNIL authorities (National Commission on Informatics and Liberty) under identifier # 2172655.
ACKNOWLEDGMENTS Quality research on autism cannot be conducted without the input of concerned individuals. We are deeply grateful to  Marie Rabatel  who drew our attention to the importance of Post-Traumatic Stress Disorder consecutive to sexual violence in autistic women. She was also of invaluable help for broadcasting this study toward potential participants. We extend our thanks to French non-profit organizations such as  Association Francophone des Femmes Autistes ,  Asperger Amitié ,  Asperger Aide ,  France Asperger.
In contrast, physically identical jumps across both deeper and shallower trenches (Figure  1B ) follow the same path, require equal effort, and carry an equal probability of failure. But, the negative consequences of falling into a deep trench are worse than following into a shallow one--the deeper the trench, the farther the fall, and the greater the injury. Such intuitions are verified empirically. We collected a pilot dataset on adult participants (N=19 from Amazon Mechanical Turk) gauging these intuitions, and found that varying the width of the trench strongly modulated people's intuitions about the probability of success, the force required to jump, and the perceived effort of the jump, more so than manipulations of depth. See Supplemental Materials for full results, and  Gjata et al.
Participants. Our final sample of participants included 32 thirteen-month-old infants (M=12. 9 months, range=12. 6-13. 5, 17 female). Seven infants were excluded and replaced due to fussiness (3 infants) or inattentiveness during test trials (4 infants). Participants were recruited through a database of families who expressed interest in cognitive development research in the Greater Boston Area. Of the families in this database who chose to provide demographic information, 79. 5% identified their children as White, 10. 2% as Asian, 6. 9% as Other, 2. 5% as Black or African American, 0. 4% as American Indian/Alaska Native, and 0. 4% as Native Hawaiian/Pacific Islander; 90. 3% as not Hispanic or Latino, 9. 5% as Hispanic or Latino, and 0. 2% as both. Most families in the database (90. 4%) had at least one parent or legal guardian with a college diploma or higher.
All data were collected at the Harvard Lab for Developmental Studies with procedures approved by the Harvard University Committee on the Use of Human Subjects. We studied 13-month-old infants, rather than 10-month-old infants that participated in previous studies of similar design  (Liu et al. , 2017)  because the younger infants lack experiences with walking and falling that may foster the development of these abilities. The sample size was chosen based on a simulation power analysis over the confirmatory analyses from 2 previous experiments with similar structure, conducted with 10-month-old infants (Experiments 1-2 from  Liu et al. , 2017) , and we collected data until we attained our pre-specified N. The full pre-registration document, including details about methods, sample size, hypotheses, and analysis plan, along with original data, scripts, and stimuli, are available at https://osf.
Data Coding and Analysis Strategy. Infant looking times were coded online using XHAB  (Pinto, 1995) , and offline using Datavyu  (Datavyu Team, 2014). All experimenters and coders were naive to the order of the test events and unable to see the video events (they relied on sound cues to start each trial). To check for exclusions and coding errors, all test trial data were re-coded in Datavyu and excluded if an infant looked away from a test event without ever having seen the agent jump, or if the trial ended too early or late (15 out of 320 total familiarization trials). We used these offline coded looking times for our final analyses. To assess the reliability of the data, (160 out of 320 trials) were re-coded in Datavyu by an additional researcher who was naive to test event order. Reliability was high, intraclass correlation coefficient (ICC)=0.
97, 95% confidence interval = [0. 95, 0. 98]. All decisions to include or exclude trials or participants from our analysis were made by researchers who did not know the order of events shown to infants. Infant looking times often are log-normally distributed  (Csibra et al. , 2016) , including in this dataset (log-likelihood of average looking times during test and control trials for Experiments 1-4 under normal distribution -2624. 45, under lognormal distribution = -2456. 77). Our pre-registered dependent measure therefore was the average looking time towards the higher-or lower-danger choice at test in log seconds. All analyses were conducted on this measure, but our summary statistics and plots feature untransformed looking times for interpretability. We analyzed all looking times using mixed effects models  (Bates et al.
, 2019 ). Cohen's D derived from lme models were calculated using the EMAtools package  (Kleiman, 2017). To enhance reproducibility, all results were written in R Markdown  (Xie et al. , 2018). Prior to conducting Experiment 1, we did not have a clear prediction for the direction of infants' looking preferences during test events and therefore pre-registered a two-tailed alpha of. 05 for that experiment. In light of the findings of Experiment 1, we predicted longer looking to unexpected events across Experiments 2-3 and therefore pre-registered a one-tailed alpha threshold of. 05 for infants' looking preferences during the test events. We therefore report onetailed significance values for analyses of all the effects that replicate or extend those of Experiment 1, and two-tailed p-values for all other analyses.
Participants. Our final sample of participants included 30 thirteen-month-old infants (M=12. 89 months, range=12. 53-13. 50, 12 female). We chose this sample size using a simulation power analysis over the confirmatory analysis of data from a pilot study, as well as estimates of effect sizes of studies with similar displays and design  (Liu et al. , 2017). We collected data until we attained our pre-specified N. Infants were excluded and replaced in the final sample due to fussiness that prevented study completion (3 infants), inattentiveness during test trials (2 infants), or interference from caregivers (2 infants). To assess infants' interest in the deep and shallow trenches outside of the context of goaldirected action, two control trials (Figure  3A ) presented a shallow and a deep trench with no animated characters.
Methods. 4. 1. 1 Participants. Our final sample included 42 twelve-to fifteen-month-old infants (M=13. 95 months, range=12. 29-15. 67, 24 female): a slightly wider age range that enabled more rapid testing of participants, who were recruited both from our lab database, and also through a cross-institution platform for recruitment for developmental cognitive science (https://childrenhelpingscience. com/). Our preregistered target sample size of 40 was determined based on a simulation power analysis over infants' looking preferences towards the test events from Experiment 2; our stopping rule was to stop recruiting as soon as we reached our target N, but to finish collecting data if we over-recruited. Thus, our final sample was N=42. A further 6 infants were excluded from the study (3 due to technical issues, 2 due to inattentiveness and 1 due to interference from the caregiver).
Our pre-registration, original data and scripts, and stimuli are available at https://osf. io/kz7br/. Relative to Experiment 2, three changes were made to the methods of Experiment 3. The most important change is that infants in Experiment 3 were familiarized to events with no breaking or shattering, or indeed any enduring damage (Figure  5A ): a soft ball was dropped from the top of the screen into shallow, medium and deep trenches, deforming to varying degrees as it landed on the trench floor at varying speeds, and then returning to its original shape (3. 4s, 5. 2s, and 6. 6s, with a 0. 5 black screen following each event). Corresponding sounds of warping and wobbling accompanied each event. These events, like those of Experiment 2, paired differing outcomes with trenches of different depths, but all of the final outcomes (the ball returning to its original shape) were identical and involved no breakage or observable damage.
Before the experiment, infants saw a calibration video where their attention was drawn to the four corners of the screen, as well as the center of the screen. To maximize the quality of the videos seen by infants, we shared our stimuli with caregivers through YouTube playlists, controlled the caregiver's screen using Zoom's proprietary remote control feature, and coded infants' looking times during the study using jHab  (Casstevens, 2007). Caregivers rated the quality of the audio and video on a 5-point Likert scale (1 = very poor; 5 = very good), giving high ratings for both (video: M=4. 88, SD=0. 33; audio: M=4. 85, SD=0. 36). After the session, we double checked for trial exclusions and generated the final data from the recording of the session video using Datavyu  (Datavyu Team, 2014).
These scores are plotted in Figure  S3 , are related to each other, and to infants' looking preferences at test, in Figure  S4. The model summary is shown in Table  S1 , and data and analysis scripts are available at https://osf. io/kz7br/. Supplemental Materials  (Liu et al. , "Dangerous Ground")  9 Overall, infants were equally likely to glance away from the screen (vs attend for the entire duration) during the 4 events. See Table  S1  for results of the linear mixed effects model (lmer formula: prop. glancedoff ~ videoclip + (1|subj)). Thus, infants did not attend selectively to the events where they had the opportunity to compare the agent's acceptance and refusal of the medium trench towards the two goals (alternative explanation for Experiment 1). They also did not more vigilantly monitor events that occurred near the deep trench (alternative explanation for Experiments 2-3).
Acknowledgements We thank the families who volunteered to participate, members of the  Harvard Lab for Developmental Studies  for helpful discussion, the Cambridge Writing Group for writing feedback,  Linette Kunin  for help with creating stimuli,  Jane Hu  for help with data collection, and  Melyssa Almeida ,  Cameron Calderwood ,  Caitlin Connolly ,  Linette Kunin ,  Laura Lee ,  Yuman Li , and  Vanessa Kudrnova  for help with data coding. Funding:  NSF   CCF-1231216 ,  Siegel Foundation  Award  S4881 ,  DARPA CW3013552 ,  NSF   GRFP DGE-1144152  (to SL),  NIH   F32HD103363  (to SL).
It has been shown that varying levels of asymmetry in odontocetes are directly correlated with production of sound and its frequency  [13, 15] , as well as in directionality of hearing  [9]. While evolutionary changes in skull asymmetry and its possible drivers have been studied extensively in Odontoceti [e. g. 2, 12, 13] , the developmental origin of this trait remains largely unexplored, despite the established importance of ontogenetic shifts in the rise of other unique cetacean traits, such as hind limb reduction or tooth loss  [16, 17]. Here, we address this gap with a quantitative analysis to answer the question: how does skull asymmetry develop in toothed whales? We approach this question by applying landmark-based 3D geometric morphometrics (GM) methods in a dataset that represents all prenatal and postnatal growth stages of an ecologically and taxonomically diverse selection of modern odontocetes: Delphinidae (oceanic dolphins -Stenella and Lagenorhynchus, pilot whales -Globicephala), Monodontidae (beluga -Delphinapterus), and Phocoenidae (porpoises -Phocoena).
(b) The ontogeny of skull shape Phenotypic trajectory analysis [PTA, 19] of skull shape ontogeny reinforces the morphological convergence between Delphinapterus and Globicephala and also highlights the peculiarity of skull development in Phocoena (figure  2 , electronic supplementary material, figure  S3 , table  S2 ). The phenotypic trajectories of all taxa are similar in shape but have unique directions. Delphinapterus and Globicephala, the two most asymmetric genera, are characterized by a longer trajectory compared to the rest of the dataset. However, the distribution of shape change in these two taxa is very different, owing to their phylogenetic history. Delphinapterus has a very prominent shape change early in the ontogeny followed by shorter shifts among postnatal stages, while Globicephala has similar amounts of shape change across all growth stages.
Phocoena is the only taxon in the dataset to maintain low levels of asymmetry throughout its ontogeny, with early fetuses and adults sharing mostly symmetric skulls (figure  1 ), a characteristic also reflected in their soft tissue morphology  [37]. The closely related Delphinapterus starts from similarly low levels of asymmetry but goes on to develop a highly asymmetric skull in adults. Despite drastically different levels of asymmetry and phylogenetic distance, Phocoena displays a similar cranial morphology to oceanic dolphins like Stenella and Lagenorhynchus throughout development (electronic supplementary material, supplemental results, figure  S7a-b , table  S6 ). Phocoena and Delphinapterus also share a similar shortened postnatal development of skull shape (figure  2 ), as well as a generally paedomorphic trend in allometry inherited from their ancestor (figure  3 ).