dataesr/scientific-paragraphs-categorization huggingface dataset:
Contrary to the natural history of a consensus to go forward, political struggles with other digitized systems (like Interpol) existed, and the reluctance of national and local forces were also strong, especially with the UK outside trying to propose other solutions. Nevertheless, digital Information Systems on Foreigners were considered more and more significant for border controls, and the securing of documents (especially passports and visa) as well as the systematization of biometrics in these documents became a way to extract, collect, share, transmit quickly information between national databases, at a speed superior to the speed of a plane travel. The UK went on to build the same kind of system. The entry of the intergovernmental agreement of Schengen into EU law with the Amsterdam Treaty as well as the enlargement process with the accession of new member states into the Schengen area have been complex steps.
Schengen and its SIS were not any more at the margins, or in advance, they became the core of the functioning of the area of freedom, security and justice. It became almost impossible to enter the EU without accepting the "Schengen acquis" integrally. This created a lot of resentment in many Eastern countries during the first enlargement and even more for Romania and Bulgaria in the second eastern enlargement when they were left outside despite their efforts to reorganize their police and border forces 3. Once again, the argument of the necessity of interoperability of the data bases was used against their will to re-discuss the basis of the Schengen logic. They had to comply first at tests that they were up to date, even if at the same moment, the number of countries part of the SIS obliged to revisit almost completely the architecture of SIS (1) by developing a, by far, more sophisticated software, first by accelerating the speed of the system as well as the number of participants, and secondly on allowing searches on the Schengen database even if the searches were nevertheless restricted to specific national authorities whose conditions of access were depending on the motives described in the specific articles of the Schengen agreement.
The first success of these tenants of a strong interoperability was to succeed to obtain that police officers and other law enforcement agencies (including prefectures administrative services dealing with foreigners) has access to the specific database on asylum seekers applying in Europe: Eurodac in 2011, despite the strong resistance of the European Data Protection Supervisor and its national counterparts, as well as the UNHCR. It was also simultaneously to have the creation of a "technical" EU-agency called EU-LISA set up in 2011, explicitly to run all the different existing data bases and their future projects, in order to be sure that no more other option can really emerge blocking the different smart borders projects They also insisted of the necessity of a creation of a Visa Information System (VIS) and to develop PNRs and entry exit systems that can be compatible both inside the EU and within the Global North area of civil aviation.
The fight between the two visions of the role of Information System and especially between the differentiation of access between police and border controls continued during at least three years. The Portuguese vision to maintain limitation purposes and cheap development was eliminated and the SIS 2 arrived in force after almost six years of delays in 2013. The new system changed the way police was working. The prevention discourse of the politicians of the time was sustained by a technique of multiple alerts creating what was called reasonable suspicion on some individuals and groups of population. Even if some police organizations were not keen to have so much data to look at, the drive to connect the dots, if necessary, in case of emergency, succeeded and the European Parliament accepted this "neutral" technology while insisting on the privacy question.
This ETIAS proposal foresees that all travelers to the Schengen area not subject to visa requirements shall be obliged to obtain authorization prior to their departure through an online application. The travel authorization requirement does not concern EU citizens, holders of a valid residence permit or a local border traffic permit, among others, but applies to third-country nationals enjoying the right of free movement who do not hold a residence card, including third-country nationals who are family members of a Union citizen and to whom Directive 2004/38/EC applies. The delivery of an authorisation to travel under the ETIAS scheme is conditional upon the automated processing (comparison) of applicant personal data held in existing information systems, such as the Schengen Information System (SIS), the Visa Information System (VIS), Europol data, the Interpol Stolen and Lost Travel Document database (SLTD), the EES, Eurodac, the European Criminal Records Information System (ECRIS), and the Interpol Travel Documents Associated with Notices database (TDAWN); in the ETIAS-specific watchlist established by the ETIAS proposal; and specific risk indicators that are kept secrets.
This is one of the rare piece available on the importance of digitization of data regarding security in Europe and the key role of engineers, IT specialists and data analysts in framing what is security, not so much through discussion about security limits, but through the technical "design" on the exchange of communication between the different agencies and the permanent argument of the necessity of the continuity of the maintenance of the digital network, and the extension of functions perform by the system as well as the number of agencies to be connected. The PHD is not yet available but elements are on Glouftsios G (2018) Governing Circulation Through Technology Within EU Border Security Practice-Networks. Mobilities. 13(2): 185-199. display particular category traits. While not directly a data mining and profiling measure, the ETIAS watchlist is nevertheless future-oriented by aiming to deny travel authorisation to individuals whose authorities believe they are likely to commit criminal offences in the future  (Vavoula 2017).
This created a strong mobilization of the privacy and fundamental rights authorities as well as Ngo's activists working for the Courts to condemn these projects. The climate created by the Snowden disclosures on the NSA was also important to put a stop to this "collect it all" logic. But as a variety of attacks occurred around Europe and with particular force in France, the push towards coordination and in the end interoperability of (some) databases, those containing personal data on third country nationals, became once again seen as "the" solution to solve all problems (see the specific article on interoperability after 2015 in this issue). For the people willing to cross borders it has created a ban-opticon normalising most of the travelers but abnormalizing a small minority on dubious criteria obtained by correlations of data and no real causalities (Author 2007).
Technology is therefore seen as a solution to avoid major political disagreement by desecuritizing , depoliticizing the issue itself; issue reduced to the problem of "efficient border controls". This way of "mediating" security and freedom via technologies of interoperability and to present them as "inocuous" and non political, ("neutral") is therefore a powerful tools in the hands of the EU bureaucrats to be in charged as much as the national politicians  (Papilloud, Christian 2005). It tends to present alternatives to the conflictual relations between different political and ethical orientations towards foreigners and national identity, under the label of expertise, neutrality and science. The so-called move from Integrated Border Management (IBM) to Integrated Data Management (IDM) is ultimately the marker of the rise of these computer and databases specialists who are the producers of these numerical technologies and who are populating the EU-LISA agency of the EU as well as the recipients of the EU-funds given to some very specific private companies.
Brief reflective field notes were made by interviewers after each interview. Electronic data files were stored in password-protected folders in the University filestore. Interview recordings were transcribed and names were anonymised. We then completed initial inductive coding  [37]  of the data to explore a) opportunities to improve connections at a local level, i. e. , factors that had the potential to impact negatively on people's geographically proximate social relationships in terms of quality, quantity or satisfaction; and b) participants' engagement with technology in relation to their social lives generally. Codes were organised under themes, following the process outlined by Braun and Clarke  [37]. For example, codes such as 'places people used to socialise no longer exist', 'many buildings are not accessible', and 'there are few facilities' were grouped together under the theme 'few local places to socialise'.
Exploring Ideas to Increase Opportunities for Local Social Interactions As described earlier, the workshop was designed to build on the findings from our interviews. An extensive list of ideas was generated through our ideation activities, which we combined and organised under themes and sub-themes. Table  4  summarises the themes and sub-themes identified in our analysis of the written workshop data. Participants commented that the workshop had been enjoyable and thought-provoking-an outcome that supports us in challenging ageist stereotypes of older people as unable or unwilling to engage in creative, disruptive or wild thinking. The three main themes we use to understand the workshop data are: social spaces and places; processes to promote social interactions; mechanisms to drive change.
Data Data from Public Health England (PHE) (https://coronavirus. data. gov. uk/) were used to inform model parameters and thereby infer the latent causes of these data. Time series of reported cases of COVID-19 for the nation of England were recorded from Jan 30 th , 2020, (1 st confirmed case). We analysed data up to May 18 th , 2020. Reports of COVID-19 confirmed deaths 'Deaths of people who have had a positive test result confirmed by a Public Health or NHS laboratory' accompanied the case report data for England with the first death recorded on the 9 th of March, 2020. The total cases reported in England by PHE up to this date at the time of analysis was 146,273. The total deaths reported at the time of analysis was 31,008. Population sizes for the nation, regions and upper tier local authorities were obtained from the 2018 census reports (https://www.
ons. gov/peoplepopulationandcommunity). Regional time series comprised confirmed cases only, from the nine regions of England: the North West, the North East, Yorkshire and the Humber, the West Midlands, the East Midlands, the East of England, London, the South West and the South East. Death records were not divided by regions or local authority. Confirmed case data from Upper Tier Local Authorities (UTLA) for all regions were also analysed for these dates. These comprised: Result'. Thus, the combinatorics allow for an individual to occupy 320 distinct states e. g. at home, infected, with symptoms, while waiting for a test. Probabilistic state transitions occur within factors determining, for example, the probability of developing ARDS once symptomatic. These sorts of probabilities and other rate parameters-for example the time to recover from infection given mild symptoms-are set to a priori levels consistent with the literature  (Chen et al 2020 , Wang et al 2020a , Wang et al 2020c , Weiss & Murdoch 2020).
Prior values of parameters were set as previously reported  (Friston et al 2020a)  and are provided in Appendix A. We find that the models accurately recapitulate the dynamics of these time series,. capturing outbreaks (from Jan 30 th to May 18 th ) in the regions and upper tier local authority data in a similar way to the national data (Figure  3 ). It is important to note that the models account for a proportion of the population that are not susceptible to infection in the current outbreak but could partake in future outbreaks. These 'resistant' proportions (discussed below) were set a priori to 0. 25 and were found to be 0. 64 for the national model and on average 0. 42 ± 0. 06 ( ± ) once optimised to the nine regional datasets. To account for social distancing, the model features an infection level-dependent probability of leaving home.
METHODS Study Sample Publicly available data from the 2003-2008 Global School-Based Student Health Survey (GSHS) were analyzed. Details on this survey can be found at www. who. int/chp/gshs and www. cdc. gov/ gshs. Briefly, the GSHS was jointly developed by WHO and the U. S. Centers for Disease Control and Prevention (CDC) and other UN allies. The survey draws content from the CDC Youth Risk Behavior Survey, for which test-retest reliability has been established. 23 The survey used a standardized 2-stage probability sampling design for the selection process within each participating country. For the first stage, schools were selected with probability proportional to size sampling. The second stage involved the random selection of classrooms that included students aged 13 -15 years within each selected school.
All students in the selected classrooms were eligible to participate in the survey regardless of age. Data collection was performed during one regular class period. The questionnaire was translated into the local language in each country and consisted of multiple choice response options; students recorded their response on computer scannable sheets. All GSHS surveys were approved, in each country, by both a national government administration (most often the Ministry of Health or Education) and an IRB or ethics committee. Student privacy was protected through anonymous and voluntary participation, and informed consent was obtained as appropriate from the students, parents, or school officials. Data were weighted for nonresponse and probability selection. From all publicly available data, all data sets from LMICs that included the variables pertaining to this analysis were selected.
If there were more than 2 data sets from the same country, the most recent data set was chosen. Surveys conducted after 2008 were not included, as depressive symptoms were not assessed. Thus, a total of 22 countries were included in this study. The characteristics of each country or survey are provided in Table  1. Data were nationally representative for all countries except Tanzania (Dar es Salaam), China (Beijng), Ecuador (Quito), and Chile (Metropolitan).
Limitations The findings should be interpreted in the light of several limitations. There was a lack of detailed data on SHS (e. g. , type of smoke, place, circumstances, and intensity), May 2020 and these data could have provided more insight into the association between SHS and depressive symptoms. In particular, future studies should take place of SHS exposure into account, as a study including Korean adolescents showed that the SHS-depressive symptom relationship was significant when SHS exposure occurred at home but not at school. 30 Relatedly, the question on SHS was based on the number of days people smoked in the presence of the student. Given that the level of exposure within a day can vary widely between students, it may not accurately reflect the level of SHS exposure. Moreover, SHS and depression were assessed with a single question based on self-report for which validity and reliability have not been established.
Also, food insecurity may not completely capture differences in SES playing a significant role in the SHS-depression relationship, and thus residual confounding by SES and depressive symptoms estimated by multivariable logistic regression. Analysis is restricted to those who had never smoked. Models are adjusted for sex, age, and SES (food insecurity). Overall estimate was obtained by meta-analysis with fixed effects. www. ajpmonline. org remains possible. For example, as family structure has been reported to be associated with both SHS exposure  52  and depression in adolescents,  53  residual confounding because of this factor may exist. Data on chronic physical conditions (e. g. , asthma) were also not available in the data set. Thus, their mediating role in the association between SHS exposure and depression could not be assessed.
ACKNOWLEDGMENTS This research was based on data from the  Global School-Based Student Health Survey , which was made available for use by the  Chronic Diseases and Health Promotion Department of the WHO  and the  U. S. Centers for Disease Control and Prevention. Ai Koyanagi 's work is supported by the  PI15/00862  project, integrated into the National R + D + I and funded by the  ISCIII -General Branch Evaluation and Promotion of Health Research  -and the  European Regional Development Fund (ERDF-FEDER). LJ contributed to the design of the study, undertook the statistical analysis, managed the literature searches, wrote the first draft of the manuscript, and contributed to the correction of the manuscript. LS, SEJ, JMH, and JIS contributed to the design of the study and the correction of the manuscript.
approval. An independent data safety monitoring board reviewed study progress and safety events, and all participants provided written informed consent. We used the weighted Kaplan-Meier method and Cox proportional hazard models to assess the effect of routine amoxicillin vs placebo on sustained nutritional recovery, transfer to inpatient care, and death from admission to 12 weeks. Inverse probability weights 5 were used to account for censoring at the time of death or transfer to inpatient care. The intervention outcomes on total anthropometric gains among children who had recovered from admission to 12 weeks were assessed using t tests (of weight) and linear regression adjusted for baseline measurements (of midupper arm circumference and height). Anthropometric gains over time were estimated by intervention group using hierarchical generalized linear models with a cubic spline.
f  [Standard Diagnostics Inc] ). The presence of malaria antigens in breast milk samples was investigated by P falciparum-specific pHRP-2 and pLDH enzyme-linked immunosorbent assays (Quantimal CELISA [Cellabs]), with protocol adaptation (detection levels were 1. 2 pg/mL and 4. 8 units/mL, respectively). Data analyses were performed with Prism version 6 (Graph-Pad Software). We used 2-sided Fisher exact tests to address differences between groups, and P values less than. 05 were considered significant. Data collection and analysis occurred from March 2018 to December 2018. Results | A total of 123 mothers who were lactating visited the malaria clinic during the low malaria-transmission season; an additional 201 visited during the high transmission season. The overall mean [SD] age, body mass index (calculated as weight in kilograms divided by height in meters squared), and lactation duration of the mothers analyzed in this study were  26.
Parliamentary, executive and media agenda Tracking policy attention over time in the three institutions (parliament, executive and media) entailed the topic coding of relevant comparable documents in the three countries using the methodology and codebook developed by the Comparative Agendas Project (CAP, www. comparativeagendas. net). The present analysis relies on datasets collected and coded by the Belgian, French 3  and Portuguese 4  CAP teams. Due to differences in data availability, the datasets cover different time periods: respectively from 1999 to 2008 for Belgium, from 1993 to 2013 for France and from 2007 to 2015 for Portugal. We rely on three distinct datasets, coded into 21 major topics 5  (see Figure  1  for the list of topics) 6  : We chose oral and not written questions to track issue attention in parliament because we are interested in party issue competition strategies.
Executive = Media(lag) + Majority PQ(lag) + Opposition PQ(lag) + Executive(lag) + major topics Executive = Media(lag) + Media(lag) * Majority PQ(lag) + Majority PQ(lag) + Opposition PQ(lag) + Executive(lag) + major topics Executive = Media(lag) + Media(lag)* Opposition PQ(lag) + Opposition PQ(lag) + Majority PQ(lag) + Executive(lag) + major topics 9 As often seen in agenda-setting research (see e. g. Vliegenthart & Walgrave, 2011)  to avoid excessive zeros, weeks without executive decisions (e. g. during ministerial recess) are left out of the dataset, resulting in a 'shortened year'. If no question time debate occurred in t-1, we decided to use data from the most recent debate up to a month away from the executive meeting. 10 Hausman tests recommend the use of fixed over random issue effects.
Data collection Quantitative and qualitative data were collected through a participatory rural appraisal (PRA), a semi-structured household survey, key informant interviews and personal observations. Following a livelihoods approach, data were collected on households' characteristics, their livelihood strategies, their access to different assets (i. e. natural, social, financial, human and physical capital, as described in the Sustainable Livelihoods Framework (DFID, 1999)), their vulnerability context (including their experience of various unanticipated shocks), and the coping strategies employed in response to unanticipated shocks. The PRA, conducted during voluntary community workshops, consisted of exercises such as the construction of seasonal calendars; historical profiles; time trends; and impact chains, which all allowed for discussions on the community's overall vulnerability context  (DFID, 1999; Dazé et al.
Acknowledgement We extend our thanks to the communities of  Bennde Mutale  and  Vondo  for welcoming the research team and for participating in the research. Thanks also to the translators and enumerators for their invaluable contribution. The research was made possible with funding provided by  South Africa's National Research Foundation (NRF) , the  Global Change Institute  (with funding from the  Carnegie Foundation of New York) , the  NRF Centre of Excellence in Tree Health Biotechnology , the  University of the Witwatersrand and the Centre for International Forestry Research.
ACKNOWLEDGMENTS The workshop reported here was sponsored primarily by the  European Research Council (ERC)  project  CLIOARCH , under the European Union's  Horizon 2020 research and innovation program  (grant agreement No. 817564 ). In addition, the support of the  Aarhus University Research Foundation  (# AUFF-E-2019-FLS-1-25 ) and the warm welcome by the  Sandbjerg Manor  staff are gratefully acknowledged.
Methods of Data Collection and Analysis Data has been analyzed by using SPSS20 (Statistical Package for Social Science) and PROCESS by, Andrew F. Hayes. The analysis and results were centered on  31  Johnny Hellgren, Anders Sjoberg, and Magnus Sverke, "Intention to Quit: Effects of Job Satisfaction and Job Perceptions," in Feelings Work in Europe, 1997, 415-23, https://www. academia. edu/download/40604544/C6_Hellgren__Sjoberg___Sverke_1997. pdf. Vol. 6, No. 1 || January -June 2020 || P. 1-23 https://doi. org/10. 29370/siarj/issue10ar1 reliability analysis (internal consistency), mean, standard deviation, correlation analysis and regression analysis.