dataesr/scientific-paragraphs-categorization huggingface dataset:
661, SD =. 122, min = 6. 5, max = 6. 9) and the other one scored low on the imageability dimension (M = 2. 908, SD =. 379, min = 1. 9, max = 3. 4)  (Content, Mousty, & Radeau, 1990). The entire experiment was comprised of 60 trials, with 15 trials in each experimental conditions. Six different list versions were created using an algorithm programmed under MATLAB®. The algorithm ensured that a word could not be repeated within the same list, or within the same serial position throughout the experiment. Furthermore, two stimulus conditions (high, low imageability words) or interference conditions (no interference, interference) could not be repeated on more than three consecutive trials. Six further list versions were created by inverting the pairings of the stimulus lists and interference conditions, resulting in 12 different versions.
033, SD =. 388 for high and low imageability words, respectively, BF01 = 2. 472). The neighborhood density values were obtained by computing the Levenshtein distance (Levenshtein, 1966)  between the phonological form of each word relative to all other entries of the Lexique 3 database. The neighborhood frequency values were obtained by computing the ratio of the log10-transformed frequency of each word against the summed frequency of all neighbors including the target word. All the stimuli were recorded by a French native female speaker in a neutral voice. Background noise was removed via the noise reduction tool implemented in Audacity®. The original stimuli were normalized to a duration of 375 ms.
Acknowledgements This study was supported by grant  EOS 30446199  from the  Belgian National Fund for Scientific Research FRS-FNRS  and grant  FSR-S-SH-17/04  from  Fédération Wallonie-Bruxelles (Belgium). We thank Delchambre, R. , Mossay, K. and Pauls, M. for their help in data collection and all the participants for their time devoted to this study. Wagenmakers, E. -J. , Wetzels,  R. , Borsboom , D. , & van der Maas, H. L. J. (2011). Why psychologists must change the way they analyze their data: the case of psi: comment on Bem (2011). https://doi. org/10. 1037/a0022790Walker, I. ,  & Hulme , C. (1999). Concrete Words Are Easier to Recall Than Abstract Words : Evidence for a Semantic Contribution to  Short-Term Serial Recall. Journal of Experimental Psychology: Learning, Memory , and Cognition, 25(5),  1256-1271.
4  Education, as a result, has largely moved online. The World Economic Forum reports a surge in the use of language apps, virtual tutoring, video conferencing tools, This work is licensed under Creative Commons Attribution 4. 0 International License. and online learning software in the last three months. India, too, is witnessing an e-learning boom. Classes on Zoom, WhatsApp and Skype are becoming the norm for students, parents and teachers. 5  Though these new age online interactive classes are being the modern form of education, amidst these new forms there is an high rise of fear among the parents and students on the privacy concerns of using online virtual interactive applications. O e such familiar case was Zoom App, Zoom has been criticised for a range of privacy issues, including sending user data to Facebook, wrongly claiming the app had endto-end encryption, and allowing meeting hosts to track attendees.
INITIATIVES BY INDIAN GOVERNMENT Looking at this challenge of colleges and schools being shut, government of India, as well as state governments and private players have regularly been publishing information on various initiatives undertaken by ministries like MHRD, Department of Technical Education, NCERT and others to support and benefit youth/students. These initiatives were in place years ago and few new initiatives has also emerged. These initiatives came in handy during the current pandemic situation. A few of the initiatives are SWAYAM online courses for teachers, DIKSHA PORTAL-will serve as National Digital Infrastructure for Teachers. All teachers across nation will be equipped with advanced digital technology. UG/PG MOOCs for non-technology courses, e-PG Pathshala or e-content containing modules on social science, arts, fine arts, natural and mathematical science, CEC-UGC YouTube channel, Vidwana database of experts who provide information to peers and prospective collaborators, NEATan initiative by AICTE based on the PPP model to enhance the employability skill among students, in collaboration with Education Technology This work is licensed under Creative Commons Attribution 4.
While a definitive objective is mass customization, different applications and projects will help this grow in reach and impact. Tutoring applications will be modified, with their lesson structures relying upon the execution of a one of a kind user profile. Increased data crunching will make testing an increasingly interactive marvel. AI and machine learning will be used to outline a student's qualities and shortcomings. Individual learning rates and records will be contemplated and computed. These tests, intended to support students' confidence in zones they exceed expectations in and challenge them in regions they don't will become holistic methodologies to enables students to stay encouraged and motivated. Examination & grading will undergo a change: AI will help teachers deal with assessment, evaluating, paper setting, making mark-sheets and tracking the performance of each student with less tedium.
Understanding activity patterns is thus fundamental to establishing effective strategies for the conservation and sustainable management of animal communities  [29]. Most of the studies concerning the activity patterns of mammals have been conducted on animals held in captivity using direct observations  [30, 31]. Indeed, studying the activity patterns of animal populations in their natural environment is often difficult, and even more so in rainforests  [32]. Activity patterns in the natural environment can be assessed using activity loggers, GPS or VHF collars, but this invasive method requires capturing and equipping animals  [32, 33]. Less invasive and more affordable, camera traps are now massively used in tropical forests and provide large datasets on the activity of a wide range of species  [29, 34].
Camera Traps Data Collection Overall, 428 camera traps were installed at the 12 sites over a five-year period (2014, 2016-2019, see Table  S2  for details). Different models of camera traps (Bushnell Trophy Cam HD and Moultrie Game Spy) with passive infrared sensors were used. Camera trap locations were predetermined using systematic sampling. They were deployed at a density of one camera per 0. 12 km 2 to 2 km 2 according to the size of the sites (see Figure  1 ). Specific sites for camera placement were selected using predefined GPS coordinates. Cameras were installed at the base of a tree at an average height of 30 cm above the ground, and were oriented towards animal tracks or open spaces, without using bait  [45, 46]. In order to reduce false triggers, and allow a good identification of species, the cover of grasses and lianas were slightly reduced in the camera's field of vision within a radius of 3 m.
Thus, the equation is giving the proportion of N 2 camera stations that also have species 1 under the condition that the two species co-occur at j camera stations  [63]. The standardised effect sizes were also calculated. They were obtained by the difference between the observed and expected co-occurrence frequencies divided by the number of sampling points (315 camera stations)  [26]. Varying from -1 to 1, it has the advantage of facilitating the comparison of results between different studies or methods  [26, 46]. Finally, we performed the Mantel test to evaluate the correlation between spatial co-occurrence and temporal overlap patterns. All statistical analyses were performed using R software  [64]  with the packages "ade4"  [65] , "CircMLE  [66] ", "cooccur"  [63] , "circular"  [67] , "overlap"  [61] , and "activity"  [68].
Inventory Data A total of 4358 independent detection events (32% of duiker photos analyzed) were recorded and corresponded to six species of duiker. The most detected species was P. congica (n = 2562), while the least was C. nigrifrons (n = 42) (Table  1 ). Because of their close phylogenetic relationship, C. crusalbum and C. callipygus are considered to be the same species (under C. callipygus, n = 945). We did not take C. nigrifrons into account in the analyses of temporal overlap and spatial co-occurrence, since it is known that its habitat is completely different from other species (swampy area)  [9, 69]. All six species are sympatric in the Makalaya, Bambidie, Djoutou, and Ovan sites.
Conclusions Data from 315 camera traps allowed the quantification of activity patterns of a community of duiker species. We studied the extent of overlapping activity patterns and co-occurrence for duikers for the first time in Central Africa. More specifically, we gathered important information on two poorly-known species, namely C. leucogaster and C. nigrifrons. A clarification was also made on the activity patterns of C. silvicultor which was previously subject to controversy. In view of these results, we consider camera traps to be suitable tools for studying the behaviour, in particular the activity patterns of duikers, which are elusive mammals difficult to observe in their natural environment. Camera traps do not, however, make it possible to determine the influence of weight, age and sex for these species, as such observations are difficult to detect on the images.
Acknowledgments: We would like to thank  Nathalie van Vliet ,  Kasso Daïnou ,  Brent Huffman ,  Remy Fagot ,  Etienne Granier , the  companies Pallisco, Compagnie Equatoriale des Bois (CEB)-Precious Woods , the  Center for International Forestry Research (CIFOR) , the  French Agricultural Research Center for International Development (CIRAD) , the  Food and Agriculture Organization (FAO) , the  Global Environment Facility (GEF) , all the staff of CARE "Forest is life" in the  TERRA Teaching and Research Centre of the University of Liège-Gembloux Agro-Bio Tech , the  King Léopold III  fund for nature exploration and conservation, and the Fund for research training in industry and agriculture/ Fund for scientific Research  ( FRIA/FRS-FNRS ) for their assistance. We sincerely thank three anonymous reviewers for their constructive suggestions that helped to improve the manuscript.
Assuming that in 2030 cell's capacity will follow the same trend as the specific energy density, a value of 400 Ah was considered. The electrical system nominal voltage is set to 540V. Based on the performance of lithium-manganesecobalt-oxide batteries, the cells nominal voltage selected was 3. 7 V  [41]. The sizing details of battery packs for the configurations assessed are detailed in Table  4. Figure  13  shows the C rate curves obtained with the Simcenter Amesim dedicated module that represents the performance need from the batteries to obtain the targets set above. In the missions simulated, the C rate is included between 0. 5 and 1, and it is therefore deemed as acceptable. In addition, the state of charge is limited at 20%, as required. The dependence of voltage and resistance (losses) with respect to the temperature was neglected in this study.
Procedures The data reported in this article stem from the International Situations Project, a large cross-cultural study assessing situational experience, daily behavior, and individual differences. Participants were directed by a local study coordinator to the study's custom-made website (ispstudy. net). After providing informed consent, participants completed a series of individual difference measures. Participants then had the opportunity to receive feedback on their personality trait levels (for an English-language wireframe of the data-gathering website see https://osf. io/r4q8p/).
e. , the pattern of LOT-R inter-item correlations) between two countries. These correlations can also be interpreted as indicators of factorial invariance, because the factor structure of an instrument derives directly from the intercorrelations of its items. The average correlation was r =. 91, ranging from r =. 997 (Serbia and Greece) to r =. 54 (Malaysia and Indonesia). To evaluate these correlations, we used as a reference point the average similarities of inter-item correlation patterns among subgroups within single countries. Specifically, we generated inter-item matrices for the data gathered within six U. S. states and within two cities in the 11 countries for which multi-site data are available. The average interitem matrix correlation across states in the U. S. and multiple cities within various countries was r =.
Country-Level Associations Given the wide range of countries included in our dataset, we were able to investigate whether the limited but detectable variability in optimism across countries was predictable based on societal characteristics, quality of life, or cultural values. Perhaps surprisingly, people in countries that appear to experience more challenging circumstances reported higher levels of dispositional optimism. Concerning cultural values, people in more traditional societies and countries that de-emphasize individual autonomy were higher in dispositional optimism on average. No result contradicted this general pattern, although some country-level indicators were unrelated to optimism. We can only speculate, but three possible explanations for this trend can be offered. First, people might use their compatriots as a reference point when evaluating their future outlook  (Heine, Lehman, Peng & Greenholtz, 2002).
author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. The Center for Open Science built and hosted the multi-lingual data-gathering website. The research was supported by the US National Science Foundation under Grant BCS-1528131. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the individual researchers and do not necessarily reflect the views of the National Science Foundation. Data gathering in the Czech.
author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. The Center for Open Science built and hosted the multi-lingual data-gathering website. The research was supported by the US National Science Foundation under Grant BCS-1528131. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the individual researchers and do not necessarily reflect the views of the National Science Foundation. Data gathering in the Czech F o r F o r F o r F o r F o r F o r P e P e P e P e P e P e e r e r e r e r e r e r Republic was supported by grant 17-14387S by the Czech Science Foundation and by R e R e R e R e R e R e v v v v v v institutional research funding RVO: 68081740 from the Institute of Psychology, Czech Academy i e i e i e i e i e i e of Sciences.
The Experimenter placed objects on the stage in front of the occluder, visible for infants at all times but for the Observer only when the occluder was lowered. Infants were video-recorded using a camera that was placed beneath the stage to allow for later visual analysis and confirmation of eye-blinks and other movement artifacts. Audio playback, object order, and EEG triggering was controlled using Psychotoolbox-3 running on MATLAB 2017 (MathWorks Inc, Natick, Massachusetts, USA). Procedure. As a family arrived in the lab, the experimenters played briefly with the infant, they then explained the procedure to the parents and obtained their informed consent. We attained the ethics approval from the Ethics Committee of E€ otv€ os Lor� and University. During the experiment, parents wore headphones playing music, and they were requested to look downwards to the floor, not to follow events on the stage and not to talk to or interact with their children, unless they wished to take a break to calm and help them engage again.
Two seconds after sound playback, the Experimenter removed the object, and the Observer closed the curtains for two seconds before the next trial began. Trials were presented in a pseudo random order: a particular object appeared only once in every five trials, the same condition did not repeat for more than two consecutive trials, and in Incongruent-for-Observer trials the first object was replaced with an object from a different category. Individual pseudo-random stimulus lists were generated using Python 3. 6 (Python Software Foundation, Beaverton, Oregon, USA). EEG recording and analysis. A continuous EEG signal was recorded using a 128-channel Geodesic Sensor Net (EGI Inc. , Eugene, Oregon, USA) at a 500 Hz sampling rate. The data was filtered with a 0. 3 Hz highpass and 30 Hz low-pass filter, and then segmented into epochs starting 200 ms before and 1200 ms after audio onset.
Acknowledgements This work was supported by the postdoctoral fellowship of the  Hungarian Academy of Sciences  ( 462003 ) and an  NKFIH   Young Researcher Grant  ( 125417 ) to B� alint Forg� acs, a  HFSP Young Investigator Grant  ( 0073/2014 ) and an  ERC Consolidator Grant ("BabyRhythm" 773202)  to  Judit Gervain , and an  ERC   Synergy Grant  ( 609819 ) to Gy€ orgy  Gergely. Eugenio Parise  is a researcher of the LuCiD team at  Lancaster University ; the support of the  Economic and Social Research Council  ( ES/L008955/1 ) is gratefully acknowledged.
Backbone extraction processes dedicated to bipartite networks have been also developed  [38] [39] [40] [41]. W. S. Jo et al. 41  proposed a new heuristic able to estimate the direction and strength of the hierarchical relationships between a pair of nodes in order to select the essential part of the networks. Experiments performed on two empirical datasets (the Gene Ontology network and a bipartite network of skills and individuals collected from LinkedIn) show that it manages to identify the most meaningful hierarchical relations from the bipartite networks. A R package  42  has been developed for bipartite networks in order to extract the backbone. It contains three methods: Hypergeometric Model (HM)  38  , Stochastic Degree Sequence Model (SDSM)  39  and Fixed Degree Sequence Model (FDSM)  40.
Dataset description A set of real-world networks is collected from different fields (social, co-appearance, biological, technological and collaboration networks) to conduct a series of experiments. Their size ranges from hundreds to thousands of nodes and edges. Zachary's karate club. It is a well known social network describing the relationship between members of a karate club at a US university. Nodes are the members of the karate club while the links represent the friendship between two members. A number between 0 and 8 is associated with each pair of club members. It indicates the strength of the relationship between a pair of members. Intra-organisational. This network is extracted from a consulting company. The nodes represent the 46 employees. A link exists between two employees if they have exchanged information or advice requests.
Treatment history The adequacy of past treatment trials, whether psychological, pharmacological or neurostimulatory in nature, should be assessed. Treatment failures throughout the disease course (not just the current episode) are relevant. The types of medication previously used may inform subsequent treatment choices and inform the degree of difficulty that might be expected. For example, has the patient just had multiple trials of selective serotonin reuptake inhibitors (SSRIs) as opposed to a variety of drugs with at least slightly different mechanisms of action? The latter would suggest a greater degree of difficulty of treatment. Failure to respond to particular treatments may be especially relevant when considering degree of difficulty of treatment. For example, fiveyear longitudinal data suggests that the outcome of patients who have failed to respond to electroconvulsive therapy (ECT) is worse than those that have  (Aaronson et al.
No share holdings in pharmaceutical companies. Lead Investigator for Embolden Study (AZ) ,  BCI  Acknowledgments An initial draft of the consensus statement prepared by  Samantha Stanbury, PhD , a professional medical writer contracted to  Vivari Ltd. , funded by  LivaNova , based on the minutes of the concensus group meeitng held on 1st April 2019. RHMW developed subsequent drafts. Lumbini Azim  and  Paul Hindmarch , from  Newcastle University and Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust , and  Samantha Stanbury  assisted with the production of the tables and figures. All authors reviewed the consensus statement, provided input to its development, and approved the final consensus statement. The authors thank  Kate Clare  and  Rachel Kelly  of  Vivari Ltd. for organizing the consensus meeting and co-ordinating pre-meeting preparations and post-meeting development of the consensus statement.
The third one was the 2005-2007 MONA LISA cross-sectional survey of cardiovascular risk factors and nutrition carried out by the French Lille MONICA (monitoring of trends and determinants in cardiovascular disease) centre  (13). This sample included 1,584 men and women aged 35-75 living in the Lille urban area, randomly selected from the electoral rolls. Detailed information on anthropometric, demographic and health data including treatments coded according to the ATC class were available. As for the two previous reference samples the numbers of individuals that had an ACEI, an ARB or any antihypertensive drug were calculated for each 5 year-age classes and each gender. In addition, a third stratification level was considered based on the Body Mass Index (BMI) coded in three classes as normal (18.
Statistical analysis As a continuous variable, age was expressed as mean and standard deviation. Categorical data were summarised as counts and percentages. For the 95% confidence interval of proportion where the numbers were less than 5, fluctuation interval was calculated according to binomial law. For each of the four groups of severity a standardised prevalence ratio of consumption of each type of drug and a 95% confidence interval were calculated  (14). Firstly, an observed number of prescription was calculated; secondly, the number of consumption estimated was calculated by applying the stratumspecific prevalence rates by 5 year age classes and gender obtained from two reference populations : the exhaustive population of the North of France (R1) and the representative sample of the French population (R2).
A third type of standardised prevalence ratio of consumption were calculated for the ICU sample stratified on age classes, gender and BMI classes obtained from the MONA LISA cross-sectional survey. We calculated the necessary number of individuals to include in our study based on comparison of two binomial proportions. Statistical analyses were performed using R software (version 3. 3. 1) (RCore Team, 2016) and Epitools package (version 0. 5-7).
Methods Studies for this narrative review were included based on a literature search in two electronic databases (MEDLINE and Cairn) for articles published through January 2020. The literature search was performed by using the following keywords: forensic psychiatry, France, criminal law, responsibility, insanity defense, competency to stand trial, prison, jail. The article titles and abstracts of studies identified by the searches were screened. Only articles written in English or French were considered. Legislative acts were extracted from L egifrance which is the official website of the French government for the publication of legislation, regulations, and legal information.
Acknowledgements This work was supported by the  F ed eration R egionale de Recherche en Psychiatrie et Sant e Mentale des Hauts-de-France  ( F2RSM   Psy ) and the  Direction g en erale de la sant e (DGS)  [Sant e mentale en population carc erale sortante]. The authors would like to thank  Anne-H el ene Moncany  for providing a picture of the USHA in Toulouse.