dataesr/scientific-paragraphs-categorization huggingface dataset:
fMRI Data Brain imaging data were acquired using a 3. 0 Tesla MRI scanner (Philips Medical Systems, Best, Netherlands) equipped with an 32-channel SENSE head coil. Functional images were acquired using a T2 * -weighted echo-planar sequence with 37 axial slices recorded in descending manner (voxel size = 3. 5 × 3. 5 × 3. 5 mm (42. 875 mm 3 ), TR = 2,000 ms, TE = 20 ms, FOV = 224 × 129. 5 × 224 mm). To reduce artifacts from the nasal cavities, images were tilted 30 • from the transverse plane of the anterior and posterior commissures. In addition, a shim box was placed onto orbitofrontal regions. High-resolution T1-weighted structural images were acquired containing 170 slices (voxel size = 1 × 1 × 1 mm, TR = 9 ms, TE = 8 ms, FOV = 232 × 170 × 256 mm).
Preprocessing Preprocessing of the structural MRI data including registration to Talairach space, intensity normalization, removal of non-brain tissue was performed with Freesurfer 2  (Fischl, 2012; Fischl et al. , 2004). Functional Image preprocessing and analysis were performed using AFNI 3  (Cox, 2012)  within a framework of R software 4  (Boubela et al. , 2012). Standard preprocessing procedures included slice timing correction, co-registration and normalization into Talairach space. Images were smoothed using a 6-mm full-width half-maximum Gaussian kernel, and the signal time course was scaled to percentage signal change relative to the mean signal across time in each voxel. To correct for motion artifacts, volumes with excessive motion were censored (Euclidean norm > 0. 3). Four subjects had more censored volumes than the pre-defined cut-off point of more than 40% of the acquired volumes and were excluded from the analysis.
In order to find significant activation-clusters the resulting parametric maps were thresholded at a voxel-level p-value of 0. 005. Subsequently, in order to determine the significance of the resulting clusters, Monte-Carlo simulations were used to calculate the likelihood of observing a cluster with a certain size in white noise using the newest version of 3dClustSim  (Cox et al. , 2017) , resulting into a lower limit of 16 Voxels (686 mm 3 ) for a corrected significance level of p < 0. 05. For subsequent post hoc tests individual median parameters of the contrasts between positive and neutral as well as negative 2 http://surfer. nmr. mgh. harvard. edu 3 http://afni. nimh. nih. gov/afni 4 https://cran. r-project. org/ and neutral feedback were extracted from all significant clusters. Further evaluating the effects found in the main analysis, cluster-wise random-intercept multilevel models (using the nlme-package in R;  Pinheiro et al.
, 2018)  were fitted on the parameters, including both responses to positive and negative social feedback. Estimating valence-general effects, the models included NA-RMSSD, NA-Inertia as well as mean NA. For the estimation of valence specific effects, the interaction effect between valence of the feedback and NA-RMSSD as well as NA-Inertia was additionally included into the model. In order to further investigate, whether the association between those parameters and the ESM-measures were unique for one of the ESM-measures (see also  Nieuwenhuis et al. , 2011) , the effects of NA-Inertia and NA-RMSSD were compared directly using the linearHypothese() function of the car-package  (Fox and Weisberg, 2011)  in R.
Experiment design and procedure Participants sat at a computer in a sound-attenuated booth. Stimuli were presented over Sennheiser HD 280 pro, 64Ω headphones. EEG was recorded from 32 electrodes as participants were exposed to the training stimuli. Eye movements were recorded with an Eyelink 1000 eye tracker in order to record and later remove ocular artefacts in the EEG data. Stimulus presentation and participant responses were conducted with SR Research Experiment Builder software. The exposure phase lasted approximately 25-30 minutes. The presentation frequency of the 13 continuum steps followed a bimodal distribution (Table  1 ). Each trial consisted of a series of five stimuli. An oddball design was used, in which a series of four standards (tokens selected from the same tone category) was presented (randomly sampled from one of the two distributions, e.
Acknowledgements We would like to thank the organizers of the " Modeling meets Infant Studies in Language Acquisition " Workshop (2013),  Lorentz-Center, Leiden ,  The Netherlands  and  Harald Baayen  for use of the  Quantitative Linguistics Group EEG lab. This research was supported by a  Research Networking grant (ESF)  NetwordS No. 6609  to NB and a  Leiden University   AMT Individual Researcher Grant  to JSN.
TMSeEEG Single pulse TMSeEEG was performed and recorded similarly to our previous studies  [21, 31, 33]. We used a figure-of-eight coil driven by a mobile stimulator (Nexstim Ltd. , Finland) to stimulate the left or right superior parietal lobule and superior frontal lobule, avoiding obvious structural lesion as detected on the subjects' MRI  [47]. These two targets were identified with a neuronavigation system (Nexstim Ltd. , Finland) using infrared camera and a software aiming device preventing any stimulation more than 2 mm away from the target. We recorded around 200 to 300 trials on each site for healthy subjects, and around 400 trials for most of the patients (to preserve sufficient data quality despite the expected artefacts in this population). The exact number of trials varied, and is reported for the session with the best PCI in Table  1.
The intensity was adjusted for optimal response amplitude while avoiding TMS or muscle artefacts (evoked electric field of 100e150 V/m). By using a 60 channel sample and hold amplifier (Eximia, Nexstim Ltd. , Finland), we recorded EEG while avoiding the large artefact evoked by the TMS pulse. Auditory evoked potentials were also prevented using a white noise masking throughout the stimulation sessions. Data were pre-processed on MATLAB 2007 (Matworks, Natick, MA). All the artefacted trials (e. g. , electrode movement, eye movement, overwhelming muscle activity) were visually identified and discarded. At least 150 good trials per session were kept for further analysis. Isoelectric channels, or channels with constant or major artefacted activity were also visually selected and discarded. Independent component analysis was sometimes used to remove further artefacts, such as 50 Hz line noise, muscle activity, or blinks.
MRI MRI was acquired with a 3T MRI scanner (Allegra, Siemens, DWI: 64 non-collinear directions using a b-value ¼ 1000 s/mm 2 , two b ¼ 0, TR ¼ 5700 ms, TE ¼ 87 ms, matrix size ¼ 128x128, 45 slices, slice thickness ¼ 3 mm, gap ¼ 0. 3 mm; and T1 3D MPRAGE). Light sedation was required to obtain movement artefact free data in 15 patients with DOC. We used typical pre-processing steps  [48, 49]  to analyse DWI data, employing eddy current distortion correction  [50]  utilizing FSL diffusion toolbox 2. 0 (FSL 5. 0, FMRIBs Software Library, http://www. fmrib. ox. ac. uk/fsl, Oxford, UK). We applied the same rotations to diffusion-weighted volumes and their corresponding gradient directions. We then stripped the skull and used a mask to isolate the white matter with the brain extraction tool  [51].
We used weighted linear least squares fitted to the logtransformed data to estimate the FA image for each subject. If needed, after visual inspection, we removed any vibration artefact by excluding the volumes with the highest FA values (diffusion gradient in the x direction greater than 0. 8)  [52]. Finally, we computed the tensor eigenvalue maps for each subject. The global FA value for each subject was obtained by averaging the FA values of the voxels in the white matter mask, using FSL maths  [53] , as in Ref. [25].
In this model, we introduced in a hierarchical entry the CRS-R total score, the time since injury, age, and gender as potential co-predictors. We assessed the assumption of errors independence using the Durbin-Watson statistics, and checked the assumption of no multicollinearity. All analyses were performed using SPSS 20 (IBM Corp. , Armonk, N. Y. , USA). Results were considered significant at p < 0. 05.
Acknowledgement OB is a research fellow, AT and OG are post-doctoral fellows and SL is a research director at the national fund for scientific research (FNRS). This research was supported by the  Belgian National Funds for Scientific Research (FNRS) , the  Human Brain Project  ( EU-H2020-FETFLAGSHIP-HBP-SGA1-GA720270 ), the  Belgian American Educational Foundation , the  Wallonie-Bruxelles International ,  São Paulo Research Foundation (FAPESP)  grant  2016/08263-9 , the  European Commission ,  EU project 'Luminous'  ( EU-H2020-FETOPEN-GA686764 ), the  Fonds L eon Fredericq , the  James McDonnel Foundation , the  Mind Science Foundation , the  French Speaking Community Concerted Research Action  ( ARC-06/11-340 ), and the  University and University Hospital of Li ege. The authors would like to thank their colleagues  C.
Sections were counterstained with Hoechst and mounted on slides with fluoromount (Southern Biotechnologies). Images were acquired with LSM 700 confocal microscope (Zeiss) under x20 magnification and x0. 7 digital zoom. Quantifications of the proportion of GFP cells coexpressing either AR or ERα (Table  2 ) were performed in one anteroposterior level of the RP3V corresponding to the AVPV (plate 29) and one level corresponding to the PeN (plate 31-32 of Paxinos and Franklin atlas) and from 12 equidistant (120 μm) hemi-sections encompassing the whole rostro-caudal extent of the arcuate nucleus (plates 41 and 53). Data are displayed as average numbers of GFP-positive nuclear counts per section or hemi-section and per group. AR-and ERα-immunolabeling was processed as previously shown  37. Images were acquired with Nikon Eclipse 80i light microscope under x10 magnification.
The time spent in chemo-investigation of each stimulus and the number of entries into each arm of the Y-maze were scored during a 5 min test. Ultrasonic vocalization recording. Each male was tested in its home cage, in the presence of a sexually receptive female. After the introduction of the female, vocalizations were recorded for 4 min with a microphone (UltraSoundGate), which was connected to an ultrasound recording interface plugged into a computer equipped with the recording software Avisoft-SASLab Pro 5. 2. 09, then analyzed using SASLab Pro (Avisoft Bioacoustic). Spectrograms were generated for each call detected (frequency resolution: FFT-length: 512; frame size: 100%; overlap: 50%). The parameters used for the automatic quantification of the ultrasonic vocalizations were: cut-off frequency of 30 kHz, element separation based on an automatic single threshold with a hold time of 15 ms.
As the specificity of antibodies used was verified in previous studies  36, 55, 59  , the membrane was cut in order to perform the three quantifications on the same loaded samples (Figure  S1 ). Blots were probed overnight with polyclonal anti-AR (1:400, Santa-Cruz Biotechnology), anti-ERα (1:400, Santa-Cruz Biotechnology) or anti-glyceraldehyde 3-phosphate dehydrogenase gene GAPDH (1:10000, Santa-Cruz Biotechnology) and then with peroxidase-conjugated second antibodies diluted at 1:5000 (Amersham Bioscience). Signals were visualized with the Super Signal detection kit (Thermo Scientific), quantified with ImageJ software (NIH) and normalized with respect to GAPDH. Statistics. Data were expressed as the mean ± S. E. M. Student's t-tests were used to determine the effects of NP exposure on kisspeptin immunoreactivity, and on the number of AR-and ERα-expressing cells.
Acknowledgements We thank the  INRA  for the use of the hormonal assay platform for testosterone assays and the  UPMC  and  INRA (UEPAO)  platforms for taking care of the animals. We are grateful to  Vincent Robert  ( INRA UMR85 ) for his expert assistance in PCR genotyping of the Kiss1-creGFP mouse line. This work was supported by the  "Agence Nationale de Sécurité Sanitaire de l' Alimentation, de l'Environnement et du Travail" (Anses ; Project no  2012-2-077 ).
Behavioral data The number of daily log items identified by the participants as being incorporated into their dream reports, with scores of 4 or higher, was counted for each daily log and dream report combination. The threshold of 4 was used so as to ensure that participants had confidence in identifying each memory source item used for the analysis. All dream reports were included in the analysis, with no minimum length requirement, as several of the shortest reports were found to exhibit correspondences; furthermore, dream length was controlled for in partial correlation analyses. Recent waking-life experiences were defined as items from the day of going to the laboratory and the day before that (i. e. from daily logs 1-2, respectively). Older waking-life experiences were defined as items from daily logs 3 to 10 and were analyzed in pairs as respectively daily logs 3-4, 5-6, 7-8 and 9-10.
EEG recordings and spectral analysis In the laboratory, electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG) were continuously recorded using a Trackit 18/8 system (Lifelines Ltd, UK, sampling rate: 200 Hz). EEG electrodes were placed according to the standard 10-20 system at F3, F4, C3, C4, M1 and M2. EOG electrodes were applied above the right outer canthus and below the left outer canthus, and EMG electrodes on the chin muscles. The common reference electrode was placed on top of the head at CPz position, and the ground electrode on the forehead. EEG analysis was performed using Fieldtrip  (Oostenveld et al. , 2011)  and MATLAB (The MathWorks, Inc. ). Frontal EEG channels (F3 and F4) were filtered between 1 and 25 Hz (high-There was a Ferris wheel, and my anatomy teacher and family were getting on it, and I was sat with my, I think mum and dad and we were talking about getting a new phone.
Statistical analysis MATLAB (The MathWorks, Inc. ) and SPSS (IBM, USA) were used to perform the statistical analyses. Correlation analyses. The correlations between frontal theta activity and wakefulness-related dream content were tested using Spearman rank-order correlation coefficient and the significance was set at P < 0. 05 (two-tailed). For the all REM (and SWS) dreams analyses, where the number of repetitions per participant could vary (from 1 to 4 for REM, and 1 to 2 for SWS), the weighted correlation coefficient as described in  Bland and Altman (1995)  was computed (using the participant-specific averages for each variable and the number of observations per participant as weights). The significance of this weighted correlation coefficient was determined using a Spearman statistical table  (Ramsey, 1989)  with n ¼ number of participants and df ¼ nÀ2.
Socio-Demographic Information A brief ad hoc self-report questionnaire was administered in order to ensure that control participants had never consulted for a psychiatric disorder, and to obtain socio-demographic data (i. e. , parental employment status and education). Parental SES was determined according to each parent's employment status. A dimensional index was developed as follows: (1) low-grade salary workers, (2) intermediate professions, and (3) white collar workers. Parental education was coded according to three levels of education: (1) technical training, (2) secondary education, and (3) higher education. Mean scores of mother and father SES as well as education were used.
Latitude was estimated in degrees from the equator. Population density was derived as number of inhabitants per square kilometer, based on official total population estimates. We derived 3 measures of the social environment (unemployment, owner-occupied housing, and single-person households) from the 2011 European Household and Population Census,  20  a decennial census that provides comparable data at a provincial level (NUTS-2 [Nomenclature of Territorial Units for Statistics-2] regions). Equivalent data for Ribeirão Preto were derived from the 2010 National Census of Brazil. 21 Duration of untreated psychosis (in weeks) was estimated for descriptive purposes, assessed via the Nottingham Onset Schedule,  22  and based on time from onset of symptoms to first contact with secondary mental health services for suspected psychosis.
Statistical Analysis For each outcome, we estimated crude incidence rates per 100 000 person-years and 95% CIs by catchment area and sociodemographic characteristics. Next, we used direct standardization for age-band and sex and for age-band, sex, and racial/ethnic minority status to investigate variation in rates between catchment areas. We used the total population of England and Wales (2011 Census 23 ) as our standard population, and estimated standardized incidence ratios using the overall sample incidence rate as the reference category. Finally, we used random-effects (intercepts) Poisson regression to investigate variance in incidence by sociodemographic and environmental factors, accounting for the hierarchical structure of the data set. Age, sex, their interaction, and racial/ethnic minority status were treated as a priori confounders.
Acknowledging the potential for reverse causality, owner-occupancy may also be a proxy for a variety of social exposures, most obviously socioeconomic position,  5  but extending to social stability and cohesiveness, which have previously been associated with psychosis. 26 The incidence of FEP appeared to be lower in southern Europe, but we found no evidence of variation by latitude in our multivariable models. Nevertheless, settings were located within a narrow band (38°-53°north of the equator), except for Brazil (21°south of the equator). This location may have contributed to our null findings, and the absence of high rates of psychosis in our southern Europe settings, particularly in major urban centers, requires further investigation; incidence patterns with respect to population density in southern European settings appeared to diverge from those observed in northern Europe (eTable 4 in the Supplement).
This misclassification would have conservatively biased IRRs with respect to racial/ethnic minority status, as would have our decision to code participants with missing data on race/ethnicity (0. 2%) to the racial/ethnic majority group. 4 Our binary race/ethnicity variable may also have permitted residual confounding; risk of psychosis by race/ ethnicity will be studied in greater detail in future EU-GEI publications. We used a consistent method in European catchment areas to estimate measures of the social environment, with comparable data taken from the Brazilian census. European data could only be obtained at the NUTS-2 regional level, which is larger than our catchment areas. Data from this level may have led to exposure misclassification, although the effect of this ecological bias is difficult to determine.
Data Recording and Metrics Participants' bodily postures and movements in the frontal plane were automatically and continuously recorded for offline analysis and labeling. We used a RGB sensor (KINECT), located in front of them, on the wall above the TW, at a height of 1. 85 m. The KINECT captured the figure of the participant at a mean rate of about 25 frames per second. The information contained by each frame was accessible through a comma-separated values (csv) file. For each frame, the participant's posture and the TW's posture were recorded as well as the timing of the frame, the participant's and the TW's bar and head inclinations were measured in degrees (Figure  2 ). The interpersonal synchronization defined as the synchrony between the participant's and the tightrope walker's bars was assessed using the correlation between the bar angles of the TW and that of the participants.
Statistical Analysis Statistical analyses were performed using R Software, Version 2. 12. 2. For every test, the level of significance, alpha, was fixed at 5%. To assess the variables of interests, we assessed the following dependent variables using Generalized Linear Mixed Model (GLMM; lme4 package): correlation coefficient between the participant's bar and the tightrope walker's bar angles, correlation coefficient between the participant's bar and its head axis angles, standard deviation of the participant's bar movements, standard deviation of the participant's head. The following explicative variables were entered in each model: developmental age, type of group (TD vs. DCD vs. ASD), and the trial number (1 to 7). For each dependent variable, the normal distribution was checked. Variable transformations were conducted to reach normalization when needed.
Data collection and statistical analysis Data related to the study objectives were extracted from a standardized and individualized electronic register (Excel) used to monitor hospital activities; this database is used in all major maternities in MSF-Operational Centre Brussels. Data were single-entered into this register from patient files and were routinely validated by supervision staff. District level population data of Khost were obtained from the Khost Governors office and used to estimate utilisation of maternity services. The number of expected deliveries by district population was derived by multiplying the crude birth rate (39 births/1000 population)  [18]  by the total population of the district (n = 1,002,563). The expected proportion of women with DOC was set at 15% of all expected deliveries/year (approximately 5865 per year or 1466 per quarter in Khost), in line with WHO guidelines  [16].
The DOC case fatality rate was calculated by dividing the maternal deaths due to DOC by the overall number of patients managed with DOCs in the MSF maternity hospital and is expressed as a percentage. A level < 1% is considered acceptable. It is estimated that a minimum of 5% of all expected deliveries will require a caesarean section for both maternal and foetal reasons  [16]. This was the basis for calculating the relative contribution of the MSF maternity hospital to caesarean coverage in Khost province. Outcomes of women and newborns were assessed at hospital exit and were standardized. The chi-square test for trend was used to assess linear trend. The level of significance was set at P < 0. 05. The data were analysed using EpiData Analysis software (version 2. 2. 2. 183, EpiData Association, Odense, Denmark).
The study has some limitations. There was a discrepancy between the population size data obtained from the Khost governorate office and from the national census. We used the former, as this provided more recently updated population figures. Another limitation was that the age of the study population was not recorded in the database. This limited the possibility of assessing outcomes of the adolescent subgroup, which is considered to be more at risk of obstetrical complications and the associated averse outcomes. Age will be included as a variable in the database henceforth. In addition, data on maternal deaths only included hospital-based maternal mortality. Thus, there may have  • The 24-h availability of specialized maternity staff on all days of the week (including nurses/midwives, doctors, and gynaecologists).
Acknowledgements The authors wish to thank the teams of Médecins Sans Frontières both at the coordination in Kabul as all the teams in Khost, and in particular the data encoder for the rigorous work done. This research was conducted through the  Structured Operational Research and Training Initiative (SORT IT ), a global partnership led by the  Special Programme for Research and Training in Tropical Diseases at the World Health Organization (WHO/TDR ). The model is based on a course developed jointly by the  International Union Against Tuberculosis and Lung Disease  ( The Union ) and  Médecins Sans Frontières (MSF). The specific SORT IT programme which resulted in this publication was jointly developed and implemented by: The  Centre for Operational Research, The Union, Paris, France ;  The Operational Research Unit (LUXOR) ,  Médecins Sans Frontières, Brussels Operational Center, Luxembourg ;  The Union, South-East Asia Regional Office, New Delhi, India; and The Centre for International Health, University of Bergen, Norway.