dataesr/scientific-paragraphs-categorization huggingface dataset:
WNA appears in the standards for mathematics of every country (see http://www. mathunion. org/icmi/other-activities/database-project/introduction/) in specific international studies (e. g. the Learner's Perspective Study, with 16 country teams). In some countries also independent research communities have developed projects on teaching and assessing WNA, which, in some cases, are internationally acknowledged (e. g. Realistic Mathematics Education in the Netherlands, NCTM Curriculum and Evaluation Standards in the USA, Davydov's math curriculum in Russia, the theory of didactical situations in France). In the ethnomathematics trend, projects sensitive to the local cultures and traditions have been developed (e. g. in • How does the use of representations in WNA teaching and learning contribute to build connections with other mathematical areas? For example, to what extent is the number line used to exhibit the connections between WNA and arithmetic of fractions?.
Acknowledgements These language and cultural issues were debated in different working groups, mainly working groups 1 (Chap. 5) and 3 (Chap. 9). We considered it important to collect contributions in a more systematic way in this chapter. We wish to thank all of the participants in the two working groups for providing interesting discussions and examples. Acknowledgements I wish to thank  Caroline Lajoie  and  Frédéric Gourdeau  for their most inspiring discussions about the topic of this paper. I also wish to express my gratitude to  Linda Lessard , sessional lecturer at  Université Laval , with whom I have closely collaborated over a period of more than 35 years in the teaching of arithmetic and geometry to prospective primary school teachers. This paper is dedicated to the memory of  William S.
Introduction Computational approaches to grounded language learning have typically involved mapping from perceptual to linguistic modalities through the application of complex information processing operations. Yu and Siskind (2013) , for instance, use hidden Markov models to translate from object tracks to natural language descriptions of event observed in video clips. Likewise the ImageNet database has provided a platform for the productive application of deep neural network architectures for mapping between images and natural language labels  (Krizhevsky et al. , 2012). Significantly with regard to the ideas outlined here,  Oh et al. (2017)  describe a methodology for training an agent to construct novel sequences of actions based on analogies with previously learned strategies; the mechanism for learning a vocabulary of basic actions consists of a combination of convolutional and LSTM layers within a neural network.
We take these grammatical features to correspond, at least in a rough sense, to the kind of thing that can be done with the corresponding target object, the things that do these things, and the things that can be affected by actions involving this object. With these probability spaces established, we can compute the top words in terms of probabil-1 Implemented using the Gensim library for Python. ity of observation in a particular grammatical role across all vocabulary words up to some arbitrary count. So, for instance, an affordance matrix for the word taxi built with three-element probability distributions would look like this (where PRO and YEAR are generic representations for personal pronouns and years respectively): predicate subject ind. object take = 0. 587 PRO = 0. 809 YEAR = 0. 385 drive = 0.
They interpreted these data as ruling out a push-down stack model of sentence processing (a push-down stack is the simplest computational mechanism that can generate and parse centerembedding). This prompted the introduction of embedded pushdown automata (EPDA,  Joshi, 1990) , which allow the processing of crossed dependencies using multiple embedded stacks. EPDAs can process both crossed and nested dependencies, but the latter are computationally more costly (in terms of numbers of items that have to be stored during computation). This would theoretically justify the intuition that crossed dependencies, despite being formally more complex, might nonetheless be processed more easily by humans, since load on working memory may be less than for nested dependencies. However, since these seminal experiments were based on natural language sentences, they had to leave other key variables (such as semantic content and lexical access) uncontrolled.
Analyses Statistical analyses were conducted in the R statistical environment (v 3. 3. 3). For the Bayesian analysis, the consistency between participants' responses and those expected for the hypothesized suite of possible grammars was assessed using Generalized Linear Mixed Models (GLMMs) fit with the 'MCMCglmm' package  (Hadfield, 2010). Participants' responses per trial were coded as being either consistent or inconsistent with the hypothesized grammars for each experimental session, and we subsequently fit univariate GLMMs for each set of trial-level responses (Bernoulli distribution, logit link function, average participant intercept term, and a participant-level random intercept effect). Model parameters were estimated using Markov Chain Monte Carlo (MCMC) sampling to facilitate unbiased estimation of marginal parameter densities, as well as to effectively quantify parameter uncertainty for hypothesis testing  (Zhao et al.
The pollen data confirm this trend of increasing aridity furthermore revealing a cooling stage at the Oligocene/ Miocene transition. These cool conditions were first highlighted by  Gorin (1975) , based on the presence of Pinaceae-rich pollen assemblages. The increasing aridity associated with a cooler climate may have led to the well-documented mammal impoverishment  (Hugueney, 1984; Legendre, 1987 Legendre, , 1989;; Comte, 2000; Becker et al. , 2002)  A wetter climate prevailed during the lower part of the Aquitanian (MN1) followed by a gradual increase in temperature toward the upper part of the Aquitanian (MN2). (Gorin, 1975)  and by the high fish tooth d 18 O values measured throughout the Chattian/Aquitanian boundary. Our study confirms that the global climate evolution around the Oligocene/Miocene boundary involved several successive temperature changes as already suggested by  Hugueney (1984) ,  Comte (2000)  and  Becker et al.
Acknowledgements. We would like to thank  J. Gaudant ,  A. Genter ,  P. Rossi ,  P. Jezequel ,  P. Lozouet ,  P. Maestrati ,  P. Freytet ,  B. Vincent  and  P. Skipwith , plus the  Lasalle Beauvais Institute  and  MNHN Geology Laboratory  for their help and support; and a special thanks to  Marguerite Hugueney  for her help. This study received financial support from the  Conseil Général of the Allier Department , the  COPGEN  project, and the  "Carte géologique de la France " programme. We would also like to thank  Vicat, SATMA and Chaux d'Auvergne  for permission to access their quarries.
Overview of studies undertaken We collected three distinct datasets on an online consumer panel, using brand logos as stimuli in all studies. In order to test for explicit emphasis on brand heritage as well as embedded brand heritage, the pilot study tests a logo for an existing brand, Study 1 tests a case of embedded brand heritage for existing brands, and Study 2 tests an explicit emphasis for a new brand. The pilot study and Study 2 use different symbols (font, founding date, and font, headquarters and signature), which improve the ecological validity of our results. We utilize brands from low-and high-involvement product categories to increase the robustness of our model: cars (Study 1) are arguably higher-involvement product categories than chocolates (pilot study and Study 2). Three distinct samples were recruited through Foule Factory (sample details, Table  1 ).
Procedure In contrast with the pilot study, we test the full model on automobile brands. This category is considered here to be of higher involvement. A two-step pre-test was conducted to select high, medium, and low perceived heritage brands with which to conduct the main study. First, secondary sources from the French automotive market established that the average price for a new car was €24,012 in 2014 and that among the 30 most popular brands, the following ten are the closest to this average price (Table  3 ) (Argus de l'Automobile, 2015, [the official pricing reference for automobiles in France]). This first selection makes sure that all brands are from the same price category and if not equally successful, among the most successful brands in the country where the data is collected.
authors would like to thank  M. Castañer ,  J. Feliu  and  J. Martin ,  University of Girona. We have completed this database with the analysis of other cross-border projects and initiatives (Interreg I, II, II and IV, Leader, programmes emanating from  CET Pyrénées Méditerranée). We also used data and documents provided by the  University of Girona  and the  University of Perpignan. The authors would like to thank  Professor Ben Khelil  ( UPVD ) and  Professor Agüera  ( UDG ) for their help. 3. Interviews were conducted both in Perpignan and  Girona  with key actors involved in cross-border issues, especially directors of cross-border academic programmes and vice-presidents in charge of international affairs.
This paper used a database compiled of cross-border programmes (POCTEFA and Interreg) implemented along the Pyrenean border(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) and developed by the Territorial and Environmental Analysis and Planning research group at the University of Girona. The.
3, b = 10%, φ = 20% up to t = 0 then s = 1 to draw a random φ). It notably defines remaining life expectancy at age x and time t, e x,t , that is used for the calibration. Overall, the model and its parameters are chosen to fit mortality rates and life expectancy in Japan, as indicated in Figure  1 , as a representation of the life expectancy of pensioners weighted by amount (that are higher than the general population as higher amounts are correlated with lower mortality due to social inequalities). The longevity level at time t = 0, a, can of course be adjusted to model specific populations of pensioners, but what mostly matters for what follows is the range of possible longevity trends for t > 0. 1 )), in gray lines using different values of ϕ as written, and from 1990 to 2015 for specific countries based on historical data (more precisely based on the mortality rates estimates provided by the Human Mortality Database): Japan in (red) short dashes, France in (blue) continuous lines, and the USA in black long dashes.
We use the following formula for the 10-year profitability ρ: ρ = ln(exp(ρ L ) + A) + ε (14) where the coefficients, ρ L , A, and ε are defined as follows. ρ L is a function of longevity that increases the profitability ρ with longevity. Under strong longevity scenarios, the parameter A is small compared to exp(ρ L ) and then ρ ≈ ρ L + ε: ρ L represents the evolution of ρ with longevity. Historically, this evolution can be estimated via the annual 35 new molecular entities and biologicals described above, that are taken by approximately 10 M patients in the years under patent: ρ L = p × Y 10 C 0 = Bϕ (15) with B = p×(Y 10 /ϕ) C 0 = 10%×(20,000 k$/ϕ)×10M 35 × 50M$ = 11. 4. The 10 M patient is an estimate provided by experts but it corresponds for example to 21% of 48. 5 M of Americans over age 65 (see Human Mortality Database) which is half of those taking polypharmacy (see  Kantor et al.
We investigated the main types of clinical trials: Phase I, II, and III. Phase I trials are conducted with a small number of patients (20-80) mainly to test safety and first side effects, phase II trials involve a larger group of patients (100-300) to determine efficacy against a placebo, and to further evaluate side effects, and phase III trials are conducted with a large group of patients (1000-3000) to confirm efficacy and safety, and to compare the drug or treatment with existing ones. The results are shown in in Figure  A4 : various indicators of drug development are particularly stable which suggests that the pharmaceutical research and development field is relatively stable. In particular, in the first 3 graphs on the left of Figure  A4  the number of declared new clinical trials in the USA, according to clinicaltrials.
gov, is stable since 2008 and roughly equal to the number of clinical trials ended: there are as many clinical trials starting as ending. Both the stability and the equality at a plateau suggest that, contrary to what one may read, the number of clinical trials of each type has remained very stable. Since declaring clinical trials in clinicaltrials. gov is needed to publish in the USA, it is a relatively reliable source. pharmaceutical developments based on open data. More precisely, we followed the evolution of clinical trials and FDA approvals in the USA, Europe, and the UK. We investigated the main types of clinical trials: Phase I, II, and III. Phase I trials are conducted with a small number of patients (20-80) mainly to test safety and first side effects, phase II trials involve a larger group of patients (100-300) to determine efficacy against a placebo, and to further evaluate side effects, and phase III trials are conducted with a large group of patients (1000-3000) to confirm efficacy and safety, and to compare the drug or treatment with existing ones.
The results are shown in in Figure  A4 : various indicators of drug development are particularly stable which suggests that the pharmaceutical research and development field is relatively stable. In particular, in the first 3 graphs on the left of Figure  A4  the number of declared new clinical trials in the USA, according to clinicaltrials. gov, is stable since 2008 and roughly equal to the number of clinical trials ended: there are as many clinical trials starting as ending. Both the stability and the equality at a plateau suggest that, contrary to what one may read, the number of clinical trials of each type has remained very stable. Since declaring clinical trials in clinicaltrials. gov is needed to publish in the USA, it is a relatively reliable source. The plateaus observed with the first two lines and the latter two lines, underlined (in red), differ due to the non-100% completion rate, as measured in the arrows pointing down (with a "<" sign with respect to success rate).
Other observations in Figure  A4  are less striking but they all similarly suggest a good stability of pharmaceutical developments, which contributed to our estimates of financial returns. It is expected that the two curves are at a lower level before 2008 as clinicaltrials. gov is recent. The decay of the curves gives an estimate of the duration of the clinical trials including enrollment time: 2-3 years for Phase I, 3-4 for Phase II, and 3 for Phase III. The rate of normal completion of clinical trials (defined in clinicaltrials. gov as having the "last subject, last visit" occurred) is estimated by the ratio between the number of completed trials and the number of trials. Even though the lines of completed clinical trials have bias both on the left (since clinicaltrials. gov is recent) and on the right (since not all trials have had the time to end), a plateau can again be seen.
Looking at the difference of the plateaus (number of clinical trials and number of completed clinical trials), the data suggests that the rate of normal completion is stable for the different phases. These rates are approximately 15% greater than the success rate estimated by  Wong et al. (2018) , which is not incoherent. The European and UK data suggests similar patterns although the more recent and not mandatory declaration in clinicaltrialsregister. eu make it less reliable: it is difficult to judge in what degree the results are different from the USA. The last graph of Figure  A4  indicates that the success rate from starting a Phase III-the most costly phase-to approval is greater than 50%: out of 400 annually completed phase III trials, 200 new drugs are accepted per year. This is more than is often perceived by communications in the field.
: various indicators of drug development are particularly stable which suggests that the pharmaceutical research and development field is relatively stable. In particular, in the first 3 graphs on the left of Figure A4 the number of declared new clinical trials in the USA, according to clinicaltrials. gov, is stable since 2008 and roughly equal to the number of clinical trials ended: there are as many clinical trials starting as ending. Both the stability and the equality at a plateau suggest that, contrary to what one may read, the number of clinical trials of each type has remained very stable. Since declaring clinical trials in clinicaltrials. gov is needed to.
The three graphs on the right side are equivalent slides but for Europe and the UK, based on clinicaltrialsregister. eu; clinicaltrialsregister. eu is more recent than clinicaltrials. gov and does not provide the same filters, so we only rely on clinical trials started each year, completed since or not. The last graph shows the accepted drugs of different types in the USA, by the FDA, every year. The top (blue) line represents any type of new drug accepted (United States Government Accountability Office, 2017). The middle yellow curve represents approvals for some specific types of treatments: New Molecular Entities (NME), New Drug Applications, Biologic License Applications (types 1-8 in (Drugs@FDA 2018)). The bottom green curve represents NMEs only. The number of NME submissions (accessdata.
Kantor et al. 2015) an estimate provided by experts but it corresponds for example to 21% of 48. 5 M of Americans over age 65 (see Human Mortality Database) which is half of those taking polypharmacy (seeKantor et al. 2015), a proxy for using one of the 35 drugs. Risks 2018, 6, x FOR PEER REVIEW 10 of 27 annual 35 new molecular entities and biologicals described above, that are taken by approximately 10 M patients in the years under patent: 𝜌 𝐿 = 𝑝 × 𝑌 10 𝐶 0 = 𝐵φ (15) with 𝐵 = 𝑝×(𝑌 10 /φ) 𝐶 0 = 10%×(20,000 k$/φ)×10M 35 × 50M$ = 11. 4.
Acknowledgements This project has been funded through the  Tara consortium, France Genomique  grant number  ANR-10-INBS-09 , and  KAUST baseline and KAUST BESE division  funds to CRV. Tara Pacific  consortium acknowledgement: We are keen to thank the commitment of the people and the following institutions and sponsors who made this singular expedition possible:  CNRS ,  CSM ,  PSL ,  KAUST ,  Genoscope/CEA ,  ANR-CORALGENE ,  France Genomique  (specifically grant number  ANR-10-INBS-09 ), agnès b. , the  Veolia Environment Foundation ,  Region Bretagne ,  Serge Ferrari ,  Billerudkorsnas, AmerisourceBergen Company, Lorient Agglomération, Oceans by Disney , the  Prince Albert II de Monaco Foundation, L′Oreal, Biotherm ,  France Collectivites ,  Kankyo Station ,  Fonds Francais pour l′Environnement Mondial (FFEM) ,  Etienne Bourgois ,  UNESCO-IOC , the  Tara Foundation  teams and crew.
Methods This rapid anthropological assessment was designed to investigate predefined topics (Table  1 ), using semi-structured interviews or focus groups and to allow the emergence of open (unexpected) answers based on the interviewees' experiences. In addition, all study participants were asked to fill in short close-ended questionnaires to obtain quantitative data on circumscribed topics such as cholera experience and vaccine acceptability. In-depth interviews and focus groups were tape-recorded when possible, and then transcribed. We excluded interviews if: (1) we were not allowed to record the interview and our notes were insufficient to produce comprehensive information, (2) the recorded sound quality was poor or (3) interviews were too short (less than 15 min) with no clear answers from the interviewees (Fig.
1 , Flowchart of Study participants included in the quantitative and qualitative analyses). Qualitative data were analyzed using NVivo Software (Version 11) to perform thematic coding. Questionnaires were anonymized and entered using the ''Open Data Kit" platform. Data analyses were performed using the R software (R Project for Statistical Computing -Version 3. 3. 1). Quantitative results were derived from questionnaires to provide complementary information to support the interpretation of qualitative data. The sampling techniques used in this assessment were not designed to be representative of the study population and the results cannot be generalized to a broader population.
Authorship contribution EG developed the study protocol and questionnaires with inputs from RD, CB, LH and PC. CB and RD supervised the data collection. RD, CB and CS performed the data collection. LH supervised the NVivo data analysis. Analysis and interpretation of the data was conducted by RD, LH, CS and AM. RD coordinated the draft report. RD and LH drafted the study report with inputs from CB, CS, PC and AM. PC, MM and JBLG provided guidance and oversight throughout the study: PC as project director, JBLG as Health Economics and Medical Anthropology Program Leader and MM as primary investigator of the ''VaxiChol" project for OCV monitoring and evaluation within which the present study was nested. RD was the main author of the article with significant contribution from EG. BDG provided input into study design and extensively revised the first manuscript draft.
Acknowledgements We would like to thank the  Nampula District Direcção Provincial de Saúde , the  Municipality of Nampula City  and the residents of Mutauanhana, Murrapaniwa, and  Muatala  who participated in this assessment. We also would like to acknowledge the interviewers who participated in this assessment:  Idilza Franco ,  Maria Matsimbe ,  Migdalia Uamba ,  Catija Maivasse ,  Elidio Muamine. We would like to thank  José-Paolo Langa  who contributed to the facilitation and the implementation of this assessment. Florentina Rafael ,  Sergio Chicumbe  and  Maité Irurzun Lopez  provided feedback on the manuscript. We also thank  Richard Wood ,  Claire MacDonald  and  Federica Joele.
This international network was meant to allow researchers to coordinate and understand research in relevant fields based on past and on-going observations in the real environment and allow them to be linked with laboratory and theoretical developments. While observatories do currently exist at sites of known contamination, collection of much more data would be required to produce a picture of the impact of exposure on the ecosystem. In the area of human health there have recently been proposals for the establishment of a formal "exposome" i. e. a detailed, preferably life-time exposure assessment database  (Wild, 2005). Unlike the genome the exposome is highly variable and dynamic, and its establishment would presumably require significant infrastructure, standards, and commitment to legal and financial sustainability.
Importance of historic dose? This insight came from radiobiology and may have profound implications for radioecology. A concern in the radioecology field is that there appears to be a big discrepancy between field data and that predicted using the FREDERICA and other databases  (Copplestone et al. , 2008; Garnier-Laplace et al. , 2015). The issue has resulted in heated, and sometimes acrimonious debate but an established phenomenon in radiobiology may hold the key. It has been known for over 30 years that persistent expression of genomic instability or lethal mutations can occur in progeny of irradiated cells which survive and reproduce apparently normally for many generations but carry a higher tolerance for mutation than the normal (unirradiated) population  (Holmberg et al. , 1993; Kadhim et al.