dataesr/scientific-paragraphs-categorization huggingface dataset:
Target pseudowords The phoneme list was the same as in Experiment 1. However, with a view to improving the material, we took a further criterion into account when constructing the pseudowords, namely syllable occurrence. For these new pseudowords, no syllable resembled a real word in French, but all the syllables existed in the French language, according to the Lexique database  (New, Pallier, Ferrand, & Matos, 2001). For instance, the first syllable of handeau can be found in the word hanche, and the second in cadeau. By contrast, the second syllable in the pseudoword hancheau (Experiment 1) does not exist in French. The 28 pseudowords were divided into two sets and two subsets (Table  4 ), as in Experiment 1. Thus, the phoneme /ε/ appeared in the pseudowords /bεkar / and /lεfõ /. It was spelled ei in the pseudoword beicart in Set A and leiphon in Set B, and also ai in laiffon in Set A and baicare in Set B.
Participants This study is based on the QLSCD, a population-based birth cohort which tracks the development of 2120 children born in the Canadian province of Quebec in 1997-1998 and followed up until 2015. The sample was drawn through a stratified sampling procedure based on living area and birth rate from the Quebec Master Birth Registry. All mothers giving birth after 24 weeks and not later than 42 weeks of gestation who spoke English or French were eligible. Detailed information on the QLSCD can be found elsewhere. 35 The QLSCD protocol was approved by the Quebec Statistics Institute and the Sainte-Justine Hospital Research Center ethics committees. Written informed consent was obtained from all participating families at each assessment. The person most knowledgeable about the child (the mother in 98% of the cases) provided data about the child, the family, and the broader social context at 5 months, 1½, 2½, 3½, 4½ and 5 years after birth through home interviews.
The wording of the items was adapted to reflect changes in the experience of victimization that could occur with age (e. g. , the item "did not let me play with his or her group" used when participants were aged 6-12 years was changed to "did not let me be part of his group" when children were aged 13 years or older). At each wave, if participants answered at least 4 out of the 6 questions of the peer victimization scale, we calculated the mean of the items (range 0-2) and considered the data missing otherwise. The mean score at each wave, was rescaled (multiplied by 5) to range from 0 to 10 (with a higher score indicating a higher level of peer victimization). Cronbach α ranged from. 74 to. 81 across ages. Table  2  provides the description of the measures used to assess family socio-demographic characteristics, parental mental health, parent-child relationship and children's behavior.
Missing data and attrition The excluded participants were more likely to be male, of non-Canadian origins, come from socioeconomic disadvantaged families, to have a mother with higher depressive symptoms and overprotective parents compared to participants retained in the study (Table  S3 , available online). Therefore, these variables were used to derive weights that were applied in all regression models using the inverse probability weighting procedure. Missing data rate was below 3. 5 % for the majority of the variables with the exception of father psychopathology (13. 4%) and fatherchild relationship (20%). To avoid loss of participants due to listwise deletion, the multivariate models were estimated using multiple imputation by chained equation (n=50 dataset).
This research was supported by the  Quebec Government Ministry of Health , the  Canadian Institute of Health Research ; the  Quebec's Health Research Fund ; the  Canadian Social Science and Humanities Research Council ;  Ste-Justine Hospital's Research Center , the  University of Montreal ; the  University of Bordeaux  via the grant  IDEX 'Origin' (Investissements d'avenir). Massimiliano Orri  receives a grant from the  European Union 's  Horizon 2020 research and innovation program  (# 793396 ). Michel Boivin  is supported by the  Canada Research Chair Program. Louise Arseneault  is the  Mental Health Leadership Fellow  for the  UK Economic and Social Research Council (ESRC).
1 mm copper filter, and isometric voxels of 7. 49 microns3. Volume data were reconstructed using isometric voxels of 30 µm. The image stacks were segmented in Avizo 9. 1 (Thermo Fisher Scientific), to separate the enamel from the dentine and to reconstruct 3D digital models of the tooth, which were refined (i. e. cleaning processes and corrections of defects to create fully closed surfaces) in Geomagic Design X software (3D Systems Software). S5000 mtDNA extraction and library preparation. Seven samples of between 8. 8 and 41 mg of tooth powder (Table  S3 ) were removed from the S5000 specimen using a sterile dentistry drill. DNA was extracted using the DNA extraction method of  63  with modifications described in  64  , either manually or on an automated liquid handling platform  65. In an attempt to remove present-day human and microbial DNA contamination from the specimen, one of the tooth powder aliquots was treated with 0.
Lithic analysis. The lithic assemblage is under study and, in this examination, we report data on the items bigger than 2 cm. The analysis is carried out following the chaîne opératoire approach  77, 78. The Levallois and discoid technology is identified following the criteria defined by Boëda  78. The intermediate core morphologies, characterised by a hierarchisation of the flaking surfaces and core configuration with secant fracture planes, are considered hierarchised, and discriminated on the base of the direction of detachments (e. g. unidirectional, bidirectional or centripetal) as described in Picin  79  , Picin et al. 80. The study of the flake assemblage is performed by analysing the presence (cortex > 50% = cortical flake; cortex < 50% = semi-cortical flake) or absence of cortex, the number and direction of detachments on the dorsal face, the angle and the type of striking platform, the flaking axis, the presence of knapping accidents (e.
Acknowledgements This study was funded by the  Max Planck Society. S. T. is supported by the  European Research Council  under the European Union's  Horizon 2020 Research and Innovation Programme  (Grant Agreement No. 803147-951  RESOLUTION, https ://site. unibo. it/resolution -erc/en). S. B. is supported by  ERC  No. 724046 -SUCCESS, https ://www. erc-success. eu/. The authors thank  M. Meyer  and  S. Pääbo  for valuable discussions. A. P. and A. W. thank  Dr. W. Brzeziński  of the  State Archaeological Museum of Warsaw  for the permission to study the lithic material of Stajnia Cave. The authors are grateful to the  Lasecki  family, owner of land, for granting the access to  Stajnia Cave  and the fieldwork. The authors would like to thank the Editor and the five anonymous reviewers whose commentaries helped to improve the final version of this paper.
Gossip Girl (The CW, 2007-2012), a television series focused on the Upper East Side golden youth, makes it clear from its first opening scene that no protagonist can escape the grasp of the eponymous blogger and their 1 network of informers looking for the latest gossip. It also illustrates a gradual shift in storytelling, as devices such as smartphones and computers are becoming a common property, and as the digital world is taking up increasing space in our daily lives through internet, and especially social media. Contemporary works of fiction must deal with the same, dramatic evolution we face in the real world, mainly the fact that we are now all equipped with high resolution cameras and microphones and have access to unlimited knowledge  2  and entertainment, while at the same time our private lives are more threatened than ever before through state-sponsored mass surveillance and obscure use of our data by private companies every time we visit a website or use an app.
The 'Long Lines Building' has indeed become, in season three of Mr. Robot, the site where E. Corp gathers its analog archives to try to rebuild the database fsociety deleted. The dense surveillance network of the city is another matter of concern for police procedural as well as science-fiction television series, as this year, another major American city, San Francisco, issued a ban on facial recognition technology  19. In this section, we will mainly focus on Elementary and Person of Interest, as they are more directly concerned with matters of privacy and mass surveillance, and offer two different points of view, opposing consultants for the NYPD for the former, and a team of vigilantes for the latter.
Data processing Answers to the multitasking part of the questionnaire were processed to yield four pieces of information for each multitasking activity: (1) Did the student engage in this particular activity during the tutorial? (2) How many times did he or she engage in this activity? (3) What was the total duration of this activity? (4) When exactly (during the slideshow, while watching the video, or while the teacher was reading the book) did this activity take place? Total duration was scored by assigning numerical values to answers on a 5-point Likert scale ranging from 1 (Less than 1 minute) to 5 (15-20 minutes). For multimedia multitasking, scores for social media (checking and posting), messaging (sending or receiving) and Internet searches (related to the course content or not) were summed to yield a single series of scores per activity.
Results The sample size was N = 187. Because the three multitasking indices were positively skewed, all inferential tests were performed using bootstrapping (20. 000 resamples; inference based on bias-corrected and accelerated confidence intervals; analyses performed using SPSS v20). These three indices were highly correlated (all Spearman's rank correlation coefficients ρs >. 80, all ps <. 001), confirming that the three ways of indexing the amount of multitasking provided converging information. For simplicity, the three scores were thus summarized with a single multitasking index for analysis (average of the three scores after standardization; analyzing the three scores separately yielded similar results).
Therefore, we focus on developing a GOS (what to measure) for the purpose of the LEAD registry. The GOS is intended to be applied for the assessment of various, unrelated skin diseases that are treated with different types of lasers. In summary, there is an urgency of using the same generic outcomes in laser therapy. Hence, establishing consensus on the relevant outcomes for the LEAD registry will promote clinical researchers to use outcomes chosen by consensus that are relevant to patients and clinicians. The use of generic outcomes support data synthesis for many diseases in dermatology. The protocol outlines the context, scope and methods for the development of a GOS to be implemented in the LEAD registry.
11 16 Results of the consensus study will be reported according to the Core Outcome Set-STAndards for Reporting. 17 Phase 1: identification of potential outcomes and domains Phase 1. 1: systematic literature review The first phase of the study is to identify which outcomes should be measured and reported in a registry on laser treatments for skin disorders (what to measure: the GOS, see definitions in online supplementary file 2). An SR will be performed to explore existing outcomes that are used in laser studies. According to the COMET guidelines,  18  searches will be performed in the following database: Medline and Embase. Articles between January 2013 and December 2017 will be retrieved. The electronic search strategy is detailed in online supplementary file 3. A recent 5-year time period has been selected for the search so that outcomes extracted represent the practice of present-day laser research.
The inclusion and exclusion criteria are presented in table 1. Two reviewers will select articles and extract the data independently. Disagreement will be resolved by discussion and by consulting a third review author if necessary. The following data will be extracted from the selected articles in data extraction tables : authors, years of publication, country, cutaneous indications for treatment and type of laser treatments. We will assess what outcomes and outcome measurement instrument are used, consistency in outcomes, number of times an outcome was used, consistency in classification used.
Phase 1. 2: classification of outcomes into domains Subsequently, data will be classified according to the standardised taxonomy for outcomes proposed by the COMET initiative. 19 This taxonomy encompasses 38 domains within 5 core areas: mortality/survival; physiological/clinical; life impact; resource use; adverse events. Outcomes and their classification in domains will be discussed with three members (FF, PS, AW) of the steering committee. The preliminary list of outcomes classified to domains will be included in the consensus process. Phase 2: consensus process Phase 2. 1: Delphi procedure For investigating crucial outcomes in context of the LEAD registry, a Delphi study will be conducted. The Delphi is based on a structured process for gathering and condensing knowledge from key stakeholder groups by means of three rounds with a series of questionnaires  20  The procedure will consist of three online rounds (figure  1 ).
Patient and public involvement Patient and public were not involved in the development of this study protocol. However, patients will be involved and included within the Delphi procedure as expert group. Consensus methodology will ensure that the opinions and preferences of patients will be given the same weighting as those of the laser experts and health professionals. Furthermore, patients will participate in the final consensus meeting. We disseminate the main results to study participants and patients by email which will include a copy of the final outcomes of the GOS. In addition, where approval has been given, participants (including members of the public) will be named as contributors in the acknowledgements section. dIsCussIon By the end of this study, we hope to reach consensus on a GOS that could be implemented in an international registry with a research focus, that collects data of rare skin diseases treated by lasers.
Agradecimentos O autor agradece à Comunidade de Remanescentes Quilombolas do Mandira, pela abertura a essa parceria desde 2015. À Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), pelo financiamento da pesquisa no mestrado e, também, à Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), pelo financiamento da pesquisa no doutorado, processos nº 2017/23227-1 e 2019/01101-1.
Such information may also help target social protection interventions;  Johnson et al. (2013)  states that 'targeting on the basis of projected regional patterns of climatic vulnerability requires extensive information about labour, poverty and long-range meteorology'. A crucial component of ASP is the use of climate information to trigger a scale-up in social protection as a response to, or in anticipation of, a climate shock according to its expected severity  (Kuriakose et al. , 2013). In the case of drought, for example, by observational monitoring or prediction of meteorological indicators, such as seasonal rainfall and soil moistureas used in the Africa RiskView software for the African Union's Africa Risk Capacity (ARC) initiative. 4 Two other examples of ASP come from East Africa: the Kenya Hunger Safety Net Programme (HSNP, 2015) 5 and Ethiopia's Productive Safety Net Project (PSNP, World Bank, 2013), both using climate observations to trigger scale-up of actions  (Drechsler & Soer, 2016).
Each day between 1st November and 31st March, observed and forecast temperature data are taken from weather stations across the UK. If the average daily station temperature is observed as, or forecast to be, 0°C or below on average for seven consecutive days, eligible households (e. g. people receiving pension credit) assigned to that station receive an automatic payment from the UK's Social Fund, coordinated by the Department of Work and Pensions. Accurate forecasts are required to minimize the risk of payments made in vain. For ASP to be effective, climate and livelihoods information needs to be integrated to determine the sensitivity to climate shocks among different communities at different times of the year. This information is critical to enable impact-based forecastingi. e. forecasting the impact of weather or climate on people and infrastructure (WMO, 2015)to help target ASP interventions and support post disaster response and rehabilitation.
ASPIRE The ASPIRE project aimed to demonstrate how weather and climate information can inform ASP decisions and related resilience initiatives in the Sahel, engaging closely with DFID, the World Bank, and national social protection and climate stakeholders. A key objective of ASPIRE was to find suitable entry points for the development and use of climate forecasts in the SASSP. The focus on forecasts, particularly seasonal forecasts, was driven by the desire to increase lead times for early action, acknowledging that improved use of observational data to trigger the scale-up of social protection also has a vital role  (Boyd et al. , 2013). An inception workshop in March 2017 preceded a project implementation phase from late 2017 to early 2020 (see Figure  1 ). During the implementation phase ASPIRE focused on: 5.
g. the size of a country). Consistent with WMO guidance (WMO, 2020) promoting objective methods, enhanced use of dynamical models is critical to improve the objectivity of forecasts issued through the PRESASS process. NMHSs have an important role to use local knowledge to tailor and communicate seasonal forecast information to target audiences. Yet not all NMHSs are able to utilize dynamical model output and many do not have access to relevant non-climate datasets to further understand climate impacts (e. g. agriculture or economic datasets). Moreover, there is a significant knowledge gap in understanding the impacts of seasonal climate variations on livelihoods, food security and poverty in the region. Sparse climate observation data across the region to evaluate forecasts and help understand climate impacts presents a significant barrier  (Dinku, 2019).
Recommendation 2: improve understanding of climate impacts on livelihoods and response options to help tailor seasonal forecasts for ASP Training activities conducted in ASPIRE highlight the need to improve livelihoods data collection, integration and analysis to enhance understanding of how seasonal climate variations impact on livelihoods. A range of tools and approaches are available to explore these relationships (e. g. Ziervogel & Calder, 2003; Reed et al. , 2013 ; Integrated Database for Africa Policymakers (IDAPS) initiative 12 ). Cross-disciplinary collaboration is key to a richer and more robust understanding of impacts to support impact-based forecasting and better integrate seasonal climate forecasts into ASP programmes. Further targeted research is also needed to build on assessments of past seasonal climate and impacts on livelihood and economic indicators in the Sahel (e.
In this paper, we approach the multilingual text classification task in the context of the epidemiological field. Multilingual text classification models tend to perform differently across different languages (low-or high-resource), more particularly when the dataset is highly imbalanced, which is the case for epidemiological datasets. We conduct a comparative study of different machine and deep learning text classification models using a dataset comprising news articles related to epidemic outbreaks from six languages, four low-resourced and two high-resourced, in order to analyze the influence of the nature of the language, the structure of the document, and the size of the data. Our findings indicate that the performance of the models based on fine-tuned language models exceeds by more than 50% the chosen baseline models that include a specialized epidemiological news surveillance system and several machine learning models.
, 2019) , which can help to predict the epidemic disease dynamics and where the next outbreak of epidemic would most likely happen. The classification task entails the identification of texts relevant to disease outbreaks from a large collection of data. Considering, for instance, a dataset of online news articles, the articles that report an outbreak of disease are separated from those which do not. Next, the event extraction task takes the identified relevant documents as input and predicts health-related events with arguments such as the disease name and the location where the outbreak was reported. Like any other task that involves text analysis using NLP approaches, ambiguity is a key challenge when dealing with epidemic-related text data. Ambiguity manifests itself where a sentence in a document may have mentioned a disease, but may not necessarily be reporting on an outbreak of a disease.
Therefore, we seek to provide a comprehensive quantitative study of lowshot text classification models applied on a dataset comprising news articles about disease outbreaks from several diverse language families namely, English, Greek, French, Russian, Polish, and Chinese. We seek to compare state-of-the-art approaches for epidemiological text classification from both deep learning and classical machine learning techniques by training a variety of models and evaluating them in several circumstances, in order to analyze their application in a real-world scenario. To the best of our knowledge, this is the first extensive study to specifically evaluate the performance of multilingual epidemiological text classification methods. The remainder of this paper is organized as follows. Section 2 reviews works related to NLP-based epidemic surveillance systems, Section 3 describes the dataset used in the study, while the experiment setup and results are presented in Section 4.
Related Work There are a number of empirical works targeted at the application of NLP for the detection of disease outbreaks. Among them is Data Analysis for Information Extraction in any Language (DANIEL), a multilingual news surveillance system that leverages repetition and saliency (the beginning and the end of a news text often comprises the salient zones), properties that are common in news writing  (Lejeune et al. , 2015). By avoiding grammar analysis and the usage of language-specific NLP toolkits (e. g. , Part-ofspeech tagger, dependency parser) and by focusing on the general structure of journalistic writing style  (Hamborg et al. , 2018; Lucas, 2009) , the system is able to detect crucial information from news articles. Furthermore, the multilingual nature of the system enables global and timely detection of epidemic events since it eliminates the requirement for translating local news to other languages for subsequent transmission.
The system can easily be adapted and scaled to extract events across languages, therefore, being able to have a wider geographical coverage. Reactivity and geographic coverage are of paramount importance in epidemic surveillance  (Lejeune et al. , 2015). Similar to DANIEL is BIOCASTER  (Collier, 2011; Collier et al. , 2008)  which has produced good results in analyzing disease-related news reports and in providing a summary of the epidemics. The BIOCASTER, an ontology-based text mining system, processes, and analyzes web text for the occurrence of disease outbreak in four phases namely, topic classification, Named Entity Recognition (NER), disease/location detection, and event recognition. The Naïve Bayes algorithm is used for the classification of the reports for topical relevance. The news stories identified to be relevant to disease outbreaks are propagated to the subsequent levels of processing.