dataesr/scientific-paragraphs-categorization huggingface dataset:
The comparison is summarized in Tables  8  and 9  which show that the proposed framework performs the best among different approaches. Table  8  shows the performance of our method, with LOSO-CV and under MEGC conditions, comparing with baselines and recent methods, that obtain high accuracy on the four datasets. The results indicate that our method outperforms handcrafted, deep learning, and hybrid approaches for almost all datasets (ICE-GAN  [48]  has the highest performance on SAMM). As expected, results in Table  9  with LOSO-CV and under 5 classes based AU conditions are less accurate. We moderately improve the accuracy for three datasets (CASME II & SAMM, CASME II, SAMM) compared to other stateof-the-art methods.
Conclusion In this paper, we have presented a novel spatiotemporal deep learning solution for MiE recognition from local facial regions. We have reported details and tests that support the used techniques and parameters. The main contributions of the proposed solution are the use of some particular regions of the face instead of the whole face and the extraction of spatiotemporal features from these regions with a deep learning architecture that combines CNN and LSTM. The solution is tested on different datasets and different distributions of classes and with different evaluation methods and metrics. The experiments showed that the proposed solution has a good performance that exceeds state-of-the-art solutions. In this paper, we focused only on the recognition task without spotting and a static method for region cropping is used.
, 2020). To this intent, in Italy and France, the countries in which the study was conducted, PE teachers paid special attention to the promotion of PA. Indeed,  Gobbi et al. , (2020)  revealed, from before to during lockdown, an increase of behaviors supporting students' self-regulated PA. For instance, a higher frequency of behaviors encouraging students to be active, to set goals or to monitor their PA levels was observed. Yet, despite the massive effort needed from teachers to adapt their behaviors, this study did not examine the motivational determinants involved in such evolution of teachers' behaviors. To fill this gap, the present work provides a complementary analysis of this dataset. It aims at explaining changes in PE teachers' behaviors by testing an integrated model that encompasses several motivational determinants  (Hagger, 2009).
Results Descriptive statistics including means, standard-deviations, ranges, Cronbach's alphas are provided in Table  1  and correlations between residualized scores are reported in Table  2. Regarding measurement invariance across the Italian and French samples, the baseline model showed acceptable fit to the data (CFI = 0. 901; RMSEA =. 064 [90 % Confidence Interval (90CI) = 0. 061; 0. 067]) supporting configural invariance (factors loadings are presented in Table  S1 ). When constraining factors loadings and intercept of items across samples, we obtained DCFI =. 004, D RMSEA =. 003 for metric invariance, and DCFI =. 006, DRMSEA =. 003 for scalar invariance. These findings suggested that measurement invariance should not be rejected among the two samples  (Cheung & Rensvold, 2002). The hypothetical model gathering residualized scores from the two samples showed poor fit to the data (CFI = 0.
25 mg/kg of propofol could be infused to allow achievement of the procedure in optimal conditions. Clinical data were collected every 2 min during the procedure (respiratory rate, oxygen saturation, heart rate and blood pressure) and patient's comfort was evaluated with three hetero-assessment scales: the Puchner scale  [24] , cough scale, and OAA/S scale (Table  1 ). Total dose of remifentanil, maximal Cet and infusion duration were collected at the end of the procedure. Respiratory parameters were reassessed 1 h and 24 h after the end of the procedure. We defined intensification of ventilatory support as an increase in the need of oxygen, or a rise in the level of respiratory care from oxygen therapy to noninvasive (NIV) or invasive ventilation in previously spontaneous breathing patients.
Statistics Continuous variables are reported as means ± SD or median (first, third quartiles), and categorical variables as count and proportion. Normality of the data distribution was visually assessed by means of histograms. Comparisons of proportions were made using Chi-square and Fisher exact tests. Continuous variables were compared using Student's t tests or Wilcoxon rank sum test statistics. Numeric variables at two different time points were compared with paired t-test or Wilcoxon test. No assumptions were made for missing data, and we followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations  [26]. Statistical analyses were done with R (version 3. 5. 1, http:// cran. r-proje ct. org). All P values were two-sided, and value less than 0.
Nonetheless, each of the reviews emphasize that there is room for improvement in the development and psychometric evaluation of tools. In typically developing children aged 8-9 years, Mazza et al. showed that self-report of sleep-wake patterns through use of a diary might be a means to obtain complementary subjective information. A more objective measure is local forehead and abdomen skin temperature, as Bach et al. reported from data collected in 6-12 year olds. This study offers a noninvasive measure of the sleep-wake cycle discussing the best and fewest number of sites for temperature measures. This proxy assessment of sleep via body temperature regulation in particular is potentially neglected in children with developmental disabilities. Smith et al. went one-step further in the discussion concerning accelerometery compared to the gold standard.
Jacobson Fund to TTY; by the National Institute of Mental Health (NIMH) R01MH085734 and the Brain and Behavior Research Foundation (formerly NARSAD) to TTY. YC acknowledges the Medical Leader Foundation of Yunnan Province (L2019011) and Famous Doctors Project of Yunnan Province Plan (YNWR-MY-2018-041). DTG, BCF and RAA wish to thank all PAFIP patients and family members who participated in the study as well as PAFIP´s research team and Instituto de Investigación Marqués de Valdecilla. Work by the PAFIP group has been funded by Instituto de Salud Carlos III through the projects PI14/00639, PI14/00918 and PI17/01056 (Co-funded by European Regional Development Fund/European Social Fund "Investing in your future") and Fundación Instituto de Investigación Marqués de Valdecilla (NCT0235832 and NCT02534363).
Finally, these previous studies did not examine structural brain alterations in children and adolescents. Therefore, we established the transdiagnostic ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium, which allows investigation of neural correlates of STBs across a range of psychiatric conditions, leveraging many samples worldwide. This large dataset enables assessment of structural brain alterations that are common across groups (e. g. , groups with a variety of psychiatric conditions including mood disorders, anxiety disorders, posttraumatic stress disorder [PTSD], addiction, and obsessive-compulsive disorder [OCD]), but also alterations that are specific to subgroups, such as males or females. For this ENIGMA-STB study, we focused specifically on young persons, as there is limited information concerning the mechanisms underlying STBs in youth, even though suicide is a leading cause of death in this population.
We first pooled data from six studies that were more homogeneous, as all used the Columbia Suicide Severity Rating Scale (C-SSRS) (providing data on the intensity of suicidal ideation and suicide attempts defined specifically as "actual attempts," i. e. , with at least some intent to die) to assess STBs. This sample aimed to investigate differences in structural MRI measures between young persons with a lifetime history of an actual suicide attempt compared to those without and associations with the intensity of current suicidal ideation. To examine how well the observed associations generalize to different STB measures and across psychiatric conditions, we conducted an additional large-scale mega-analysis combining the C-SSRS data with data from additional studies that included young people with different psychiatric conditions and that employed different STB instruments (total of 21 studies).
Image processing and harmonization Structural T1-weighted brain MRI scans were acquired at each site. Information regarding the acquisition parameters, software versions, and scanner characteristics for the different sites is presented in Table  S2. The T1-weighted images were analyzed locally using harmonized analysis and quality control protocols for FreeSurfer (18) (http://surfer. nmr. mgh. harvard. edu/), developed by the ENIGMA consortium and freely available (http://enigma. ini. usc. edu/protocols/imaging-protocols/). The ENIGMA FreeSurfer protocol provides tools for quality control of the segmented cortical and subcortical phenotypes. Each site visually inspected the segmentation and excluded regions that were not appropriately segmented. To reduce the number of statistical tests and avoid issues related to left-right flipping that may have occurred at the various sites, we combined regional measures across both hemispheres by taking the mean of the left and right hemisphere regions.
Secondary analyses In addition to evaluating the main effect of current suicidal ideation or a history of suicide attempts, we conducted the above-mentioned analyses in the larger ENIGMA-STB sample separately for males and females, including age and ICV as covariates. Data on lifetime psychiatric diagnosis were available in a subsample of participants (N=655 in the ideation analysis and N=842 in the attempt analysis), as some sites only assessed current disorders. Because there were numerous combinations of lifetime diagnoses and comorbidities with low frequencies per combination, we categorized them into six main lifetime diagnosis types: MDD, BD, anxiety disorders, PTSD, OCD, and psychotic disorders. The primary type of diagnosis per group is shown in Figure  3. In secondary analyses, this variable was included as an additional covariate.
Moreover, when multiple instruments were used to assess suicidal ideation (thoughts) or attempts within one cohort, we defined STBs in that sample using instruments that showed strong correlations with the instruments used by other cohorts to assess STBs  (39). Future multi-site collaborations would be improved by prospective harmonization in data collection and/or measurement. A second limitation was the cross-sectional study design. Although the findings are consistent with a prior report on future suicide attempts (9), we cannot determine whether brain structure increases the risk for STBs or whether prior attempts affect brain structure. It is important to note that segmentation of the surface area of the frontal pole showed moderate test-retest reliability  (40). Finally, while including participants from many international studies, the samples mainly included Caucasian participants from high-income countries.
In conclusion, by harmonizing neuroimaging data from research groups worldwide, we found that a deficit in the surface area of the frontal pole was related to suicide attempts in young people, which we suggest represents a pre-existing vulnerability to suicide attempts. Future studies focusing on the frontal pole may elucidate the functional and structural neurobiological mechanisms through which this region contributes to the development of STBs in young people and is a promising candidate to be a target for the early prevention of suicide. Table  1. Descriptive statistics for studies included in the ideation analysis Presented here are age (median, minimum, maximum) and sex for the three groups (HC: healthy controls, CC: clinical controls, Ideation: group with current suicidal ideation) for the different sites included in the analysis on suicidal ideation.
Acknowledgments This work was supported by the  MQ Brighter Futures  Award  MQBFC/2  ( LS, LC, LV, MRD, LvV, ALvH, HB ) and the  U. S. National Institute of Mental Health  under Award Number  R01MH117601  ( LS, LvV, NJ ). LvV received funding through the  National Suicide Prevention Research Fund , managed by  Suicide Prevention Australia. LS is supported by an  NHMRC   Career Development Fellowship  ( 1140764 ). ALvH is funded through the  Social Safety and Resilience programme of Leiden University. SA, NB, FP, and GS acknowledge that data collected in IRCCS Santa Lucia Foundation,  Rome , Italy was funded by a study funded by the  Italian Ministry of Health  grant  RC17-18-19-20-21 /A. ZB, KC, B K-D acknowledge data collected at the  University of Minnesota  was funded by the  National Institute of Mental Health  ( K23MH090421 ), the  National Alliance for Research on Schizophrenia and Depression , the  University of Minnesota Graduate School , the  Minnesota Medical Foundation , and the  Biotechnology Research Center  ( P41 RR008079  to the  Center for Magnetic Resonance Research) ,  University of Minnesota , and the  Deborah E.
Powell Center for Women's Health Seed Grant, University of Minnesota. HB acknowledges data collected at the  Yale School of Medicine, New Haven, CT, USA , was funded by:  MQ Brighter Futures ,  R61MH111929RC1MH088366 ,  R01MH070902 ,  R01MH069747 ,  American Foundation for Suicide Prevention ,  International Bipolar Foundation ,  Brain and Behavior Research Foundation ,  For the Love of Travis Foundation and Women's Health Research at Yale. LC is supported by  Interdisziplinäres Zentrum für Klinische Forschung, UKJ. BCD was funded by a  CJ Martin Fellowship (NHMRC app   1161356 ). BCD research leading to these results has received funding from the program " Investissements d'avenir "  ANR-10-IAIHU-06. CGD and BJH acknowledge that data collected in Melbourne, Australia, was supported by  Australian National Health and Medical Research Council of Australia (NHMRC)  Project Grants  1064643  (principal investigator, BJH) and 1024570 (principal investigator, CGD).
BJH and CGD were supported by  NHMRC Career Development Fellowships  ( 1124472  and  1061757 , respectively). UD and TH acknowledge data collected at the FOR2107-Münster was funded by the  German Research Foundation  (DFG, grant  FOR2107-DA1151/5-1  and  DA1151/5-2  to UD, and  DFG  grants  HA7070/2-2 ,  HA7070/3 ,  HA7070/4  to TH). AJ and TK acknowledges data collected at the FOR2107-Marburg was funded by the  German Research Foundation  (DFG, grant  FOR2107-JA 1890/7-1  and  JA 1890/7-2  to AJ, and  DFG , grant  FOR2107-KI588/14-1  and  FOR2107-KI588/14-2  to TK). KD acknowledges data collected for the Münster Neuroimaging Cohort was funded by the  Medical Faculty Münster, Innovative Medizinische Forschung  (Grant  IMF KO 1218 06  to KD). JMF, PBM, BJO, and GR acknowledge that the " Kids and Sibs" Study  was supported by the  Australian National Medical and Health Research Council  (Program Grant  1037196  and Investigator Grant  1177991  to PBM, Project Grant  1066177  to JMF), the  Lansdowne Foundation ,  Good Talk  and the  Keith Pettigrew Family Bequest (PM).
JMF gratefully acknowledges the  Janette Mary O'Neil Research Fellowship. IHG is supported in part by  R37MH101495. Support for TAD comes from the  National Institute of Mental Health  ( K01MH106805 ). TH acknowledges support for TIGER includes the  Klingenstein Third Generation Foundation , the  National Institute of Mental Health  ( K01MH117442 ), the  Stanford Maternal Child Health Research Institute , and the  Stanford Center for Cognitive and Neurobiological Imaging. TCH receives partial support from the  Ray and Dagmar Dolby Family Fund. KAM, ABM, MAS acknowledge data collected at  Harvard University  was funded by the  National Institute of Mental Health  ( R01-MH103291 ). IN is supported by grants of the  Deutsche Forschungsgemeinschaft  ( DFG grants   NE2254/1-2 ,  NE2254/3-1 ,  NE2254/4-1 ).
391, χ 2 1 = 12. 041, P = 0. 001): post hoc Sidak tests showed that uni-component acts in wild orang-utans were more likely to be multisensory (than unisensory) compared to those of their captive counterparts regardless of species (Borneans: -3. 13 ± 0. 338, Z = -9. 314, P < 0. 001, Sumatrans: -1. 82 ± 0. 216, Z = -8. 461, P < 0. 001), and that captive Sumatrans produced more multisensory, uni-component acts than captive Borneans (-1. 342 ± 0. 334, Z = -4. 021, P < 0. 001; see Fig. 3 ). For effects of other, non-significant key predictors and those of control variables see Supplementary Table  S2. Use of multicomponent multisensory acts. F i n a l l y ,w et e s t e d sources of variation in the use of multicomponent multisensory acts, considering subsets of the dataset that consisted either only of multicomponent acts or only of multisensory acts (allowing to test the effect of the second type of integration).
First, considering only the dataset of multisensory acts (i. e. contrasting MC-MS with UC-MS), we again found that the full model including the key test predictors fitted the data better than the null model (LRT: χ 2 5 = 45. 235, P < 0. 001, N = 2348). Specifically, we found a significant interaction between species and setting (-2. 071 ± 0. 866, χ 2 1 = 6. 049, P = 0. 014; see Fig. 4 ): post hoc Sidak tests showed that the multisensory acts of captive Sumatran orang-utans consisted more often of multiple components than those of wild Sumatrans (1. 406 ± 0. 343, Z = 4. 097, P = 0. 001) and captive Borneans (-2. 458 ± 0. 815, Z = -3. 016, P = 0. 003). With regard to kinship effects, we found that multisensory acts among mother-offspring dyads were less likely to be multicomponent than those among other interaction dyads (-0.
627 ± 0. 314, χ 2 1 = 3. 987, P = 0. 046; see Fig. 4 ). For effects of control variables see Supplementary Table  S2. Second, considering only the dataset of multicomponent acts (i. e. contrasting MC-MS with MC-US), the full model including the key test predictors fitted the data better than the null model (LRT: χ 2 5 = 33. 793, P < 0. 001, N = 2633). Specifically, we found a significant interaction between species and setting (-1. 916 ± 0. 726, χ 2 1 = 7. 664, P = 0. 006; see Fig. 5 ): post hoc Sidak tests showed that the multicomponent acts of wild Bornean orangutans were more likely to be multisensory than those used by wild Sumatrans (0. 691 ± 0. 299, Z = 2. 312, P = 0. 021) and captive Borneans (-1. 461 ± 0. 68, Z = -2. 15, P = 0. 032). For the individual main effects, we found that multicomponent acts were more likely to be multisensory in interactions among mother and offspring (0.
Methods Study sites and subjects. Data were collected at two field sites and five captive facilities (zoos). We observed wild orang-utans at the long-term research sites of Suaq Balimbing (03°02′N; 97°25′E, Gunung Leuser National Park, South Aceh, Indonesia) and Tuanan (02°15′S; 114°44′E, Mawas Reserve, Central Kalimantan, Indonesia), inhabited by a population of wild Sumatran (Pongo abelii) and Bornean orang-utans (Pongo pygmaeus wurmbii), respectively. Both field sites consist mainly of peat swamp forest and show high orang-utan densities, with 7 individuals per km 2 at Suaq and 4 at Tuanan  68, 69. Captive Bornean orang-utans were observed at the zoos of Cologne and Munster, and at Apenheul (Apeldoorn), while Sumatran orang-utans were observed at the zoo of Zurich and at Hellabrunn (Munich; see EEP studbook for details on captive groups  70  ).
In captive settings with glass barriers, we also used a Zoom H1 Audio recorder that was placed in background areas of the enclosure whenever possible, to enable the recording of audible communicative acts. Second, using instantaneous scan sampling at ten-minute intervals, we recorded complementary data on the activity of the focal individual, the distance and identity of all association partners, in case of social interactions the interaction partner as well as several other parameters. During ca. 1760 h of focal observations, we videorecorded more than 6300 social interactions which were subsequently screened for good enough quality to ensure video coding. Ethical Video coding procedure. A total of 2655 high-quality video recordings of orangutan interactions (wild: 1643, captive: 1012), which could each include multiple communicative acts, were coded using the programme BORIS version 7.
0. 4. 72. We designed a coding scheme to enable the analysis of articulators and sensory modalities involved in presumably communicative acts directed at conspecifics (i. e. close-range social behaviours that apparently served to elicit a behavioural change in the recipient and were mechanically ineffective, thus excluding practical acts such as picking up an object or acts produced with physical force  63, 73  ; see also Table  1 ) and thus included potential gestures sensu  63. Actions that were directed at observers or achieved their presumed goal sensu  63  (apparent aim based on the individuals involved and the immediate social context) directly (e. g. nursing solicitations, infant collections) were thus excluded from the dataset. For each communicative act, we coded the following modifiers: body parts involved in production (e.
We used the R package Venn Diagram  74  to visualise the proportional composition of the dataset (Fig. 1 ). Adopting the terminology of Hobaiter and Byrne  11  , we considered an outcome as apparently satisfactory if the signaller ceased communication and if it represented the signaller's plausible social goal. The specific types of communicative acts comprising individual and group repertoires, as well as their interaction outcomes, are reported elsewhere  75  , but we used data on the dominant outcomes of communicative acts for a given research setting and orang-utan species for our test of the refinement hypothesis (Supplementary Table  S7  and Supplementary Data S1). After an initial training period of 2-4 weeks, and afterwards, in regular intervals (once a month), reliability of coding performance (using the established coding template) between at least two observers was evaluated with different sets of video recordings (10-20 clips each) using the Cohen's Kappa coefficient to ensure intercoder reliability  76.
Trained coders (M. F. , N. B. , C. F. , C. W. , L. M. , M. J. ) proceeded with video coding only if at least a good level (κ = 0. 75) of the agreement was found for communicative act type, articulator, sensory modality, presumed goal, and interaction outcome. For further details on the distribution of coded interactions across species, settings and interaction dyads, see Supplementary Table  S8. Statistics and reproducibility. For the dataset of 7587 communicative acts resulting from the coding procedure, we used Generalised Linear Mixed Models 77 with a binomial error structure and logit link function. We investigated sources of variation in four sets of response variables, referring to (a) the use of communicative acts produced with different articulators (manual, bodily, facial, vocal, recipient-directed gaze), (b) the use of communicative acts perceived via different sensory modalities (visual, tactile, auditory, seismic), (c) multicomponent and multisensory use of communicative acts, (d) effectiveness (i.
e. whether or not the signaller received an apparently satisfactory response; sensu  11, 63  ), and (e) dominant outcome matching (i. e. whether or not the presumed goal sensu  63  of a communicative act matched the major interaction outcome [i. e. share food/object, play/ affiliate, co-locomote, stop action, sexual contact, or move away] associated with it; see Table  1 , and Supplementary Data S1 for the dominant outcome of communicative acts for every setting and species  75  ). In models (a), (b), and (c), we included orang-utan species (2 levels: Bornean, Sumatran), research setting (2 levels: captive, wild), and kin relationship (3 levels: mother-infant [i. e. only including unweaned immatures], maternal kin, unrelated) Fig. 8  Conceptual summary of findings. Our results suggest that refinement is the primary function of multicomponent communicative acts, whereas redundancy refers more to multisensory communicative acts.