dataesr/scientific-paragraphs-categorization huggingface dataset:
Campagne de communication auprès des professionnels de santé En 2016, la Bourgogne-Franche-Comté, compte environ 30 000 infirmiers et médecins  1. Pour les informer de l'étude, la première étape a consisté à créer une base de données, à partir des données disponibles via l'ARS et des bases de données libres, répertoriant les différents établissements sanitaires (hôpitaux, cliniques) et médico-sociaux (EHPAD, foyer-logement) ainsi que les différentes structures de soins ; réseaux de santé, maisons de santé et cabinets médicaux et infirmiers. Des plaquettes de communication reprenant une information complète sur l'étude accompagnées d'une lettre et des documents relatifs à l'information et au recueil de l'accord des participants (recueil de non-opposition) 2  ont fait l'objet d'un premier envoi en décembre 2016 sur le lieu d'exercice des professionnels de santé.
Remerciements Les auteurs remercient chaque membre du groupe de travail constitué autour de l'étude epiDESA2 pour leur précieuse participation et implication dans la construction, la mise en place et le recueil des données ;  Dr Yvan Beaussant ,  Dr Nicolas Becoulet ,  Dr Jean-Francois Roch ,  Dr Véronique Alavoine ,  Dr Christophe Devaux ,  Nathalie Denefle ,  Virginie Conuau ,  Dr Marc Degois ,  Dr Delphine Brissac ,  Dr Christophe Petitjean ,  Dr Domina Mugabo ,  Dr Clémence Delavaud ,  Magali Robadey ,  Dr Marie-Claude Schneider ,  Filipe Ricardo ,  Dr Carole Finck ,  Dr Philippe Biedermann ,  Dr Céline-Marie Ferry ,  Dr Anne-Claude Pillot ,  Dr Patricia Mercier ,  Dr Arnaud Chevre ,  Bernadette Tribault ,  Dr Claude Plassard ,  Dr Pascale Michel ,  Brigitte Ragot ,  Dr Jean Petit ,  Ghislaine Chiabri ,  Dr Chantal Virot ,  Dr Zahia Haddad-Guichard ,  Dr Pascale Seynaeve ,  Pascale Monnier ,  Dr Sébastien Lahousse ,  Dr Marion Lyoen ,  Dr Laurence Andre ,  Dr Christian Gaillard ,  Dr Elisabeth Valle-Dauvissat ,  Dr Pascale Arne ,  Dr Mohamed Mahni ,  Gilles Gas ,  Dr Anne Guedon ,  Dr Jean-Marie Faroudja.
Funding This work was supported by a grant from the  German Research Foundation  (DFG, grant number:  PE 3125/1-1 ) to SP, two  FWF  grants (grant numbers:  P 33853  and  I 4332)  awarded to SH, the  French National Research Agency  (grant number:  ANR-19-CE28-0009 ) awarded to  ALe , and the  Luxembourg National Research Fund  (FNR grant number:  C21/SC/16241557 ) to ALo.
In this respect, Céüze 2000 embodied the "prototype of school ski resorts 4 " whose development was acknowledged and encouraged by the local authorities 5. Intercommunal Syndicate (SIVU) was created in 1951, associating the town of Manteyer and the city of Gap, with the town of La Roche-des-Arnaud joining in 1986. 11 The resort now counts eight ski lifts, ranging from 1550 meters to 2060 meters in altitude. No artificial snow network has been developed and the site has never gone beyond the capacity of 500 tourist beds. Today, apart from one or two places offering accommodation, the only other building that still accepts visitors is located in the summer camp in the town of Noisy-le-Sec (93). 12 Our data comprises documentary sources  from departmental archives and reports from local authorities and media sources (fig.
2 ), as well as qualitative and quantitative data. These data made possible the construction of a chrono-systemic timeline  (Spiegelberger et al. , 2018). 13 We used direct observations (since 2018), interviews with users, and institutional, economic, and local actors (N=26), and we distributed online questionnaires in 2019 and 2020 (N=832) 6. Despite distributing the questionnaire at the national level, the sample was primarily composed of local visitors and residents (three quarters resided in the Hautes-Alpes region and 70% in one of the two communautés de communes in which the Céüse Mountain is located). There were slightly more men than women (52. 6% of the sample compared with 48% for the entire French population). All age groups were represented, with the majority aged between 30 and 59 (63.
Organization and Availability of Data 9 The data that is currently available on hut attendance consists of the number of overnight stays per season (spring-summer) and/or per year. Depending on who manages the huts, the length of time and precision of the available data vary greatly. 10 The data from the Swiss Alpine Club (SAC) is among the most complete and accurate. For each hut, the number of overnight stays per season (spring and summer), details of the rates applied (SAC members, non-members, SAC youth, children under 7, young people aged 7-18 and free overnight stays) and the average occupancy rate per berth (number of overnight stays recorded in a season divided by the number of berths) are given. Such data, which comes from the local sections that own the huts, have been archived by the SAC central committee since 1969 but remain incomplete until 1985.
The database has been computerised since 1997. Unfortunately, this database only covers SAC huts. For the huts managed by another actor (public or private), generally located in the mid-range mountains, it was necessary to contact each manager individually and ask for access to the data, which may be formatted differently, and in some cases unavailable. Managers are often reluctant to provide this data, which is indirectly telling about the income associated with the management of the hut. It is therefore much more difficult to create a database for huts which are not managed by the SAC. In the canton of Valais, out of a total of 71 huts, 40 are owned by the SAC, which is 56%  (Obin, 2020).
Sample of Huts Studied To build a suitably robust database that is also best suited to the study of the transformation of mountain sports practices (cf. "Value of the Data" section), we selected the high mountain huts of the Hérens and Anniviers valleys. These two valleys are located in Switzerland, in the Valais Alps, on the left bank of the Rhône River and include numerous peaks that are over 3500 m, 5 peaks over 4000 m and 17 glaciers (Fig. 1 ). Each selected hut meets the following selection criteria: it is (i) isolated and inaccessible by car/lift; (ii) managed by the SAC; and (iii) a high mountain hut, defined in this work as any hut supporting mountaineering. The sample consists of 8 huts (ranked from west to east; Fig. The main characteristics of the huts studied are presented in Table  1.
47 Putting this into perspective, the inter-and transdisciplinary programmes Refuges Sentinelles ( https://refuges-sentinelles. org, since 2016) and HutObsTour ( https:// wp. unil. ch/hutobstour, since 2020), aim to fill in some of the biases and limitations of the visitor data presented in this article. Through a collaborative process involving hut keepers, guides, mountain leaders and alpine clubs, more extensive and accurate visitor data than the number of nights per season will be acquired, including the number of daily nights and the destination (practice, summit, route) of each person sleeping in the hut. These records of destinations, collected and interpreted with those involved in the field, are intended to provide a much more detailed analysis of the ways in which sporting activities are practised in less-developed mountains and how they are changing.
except for Arpittetaz where no data prior to 1985 has been found. The number of overnight stays per season (spring and summer) is known for the period 1995-2019 for the Dix and Vignettes huts, 1986-2019 for the Bertol, Dent Blanche, Moiry, Mountet and Tracuit huts and 1988-2019 for Arpitettaz. Some seasonal data prior to 1986 was also found. The database is therefore continuous for the 8 huts studied, from 1985 to 2019 (35 years) for the number of overnight stays per year and from 1995 to 2019 (25 years) for the number of overnight stays per season (spring and summer). The analysis presented in the following section will therefore only cover those periods where the database is complete and continuous for all huts.
Hyaenidae (Crocuta, Parahyaena, Hyaena) Few studies concern teeth eruption in hyenids. From observations on non-adult mandibles belonging to three extant species (spotted hyena, Crocuta crocuta; striped hyena, Hyaena hyaena; brown hyena, Parahyaena brunnea), tooth eruption sequences are recorded for young, juvenile and subadult individuals (i. e. from specimens younger than 15 months old). Tooth eruption sequences, crown wear and mandibular growth are presented and sometimes measured. These data fill published studies and are used on particularly well-preserved cave hyena (Crocuta intermedia) mandibles from the Lunel-Viel cave, dated to the Middle Pleistocene (~MIS 7). No major differences were found in the chronology of teeth eruption among hyenid species. Six age classes are presented for non-adult hyenids, based on tooth eruption, tooth wear and mandibular measurements.
Methodology The aim of this study was to identify, from an onomasiological approach, some markers of pride in drag queens' language, in order to analyse them. We will thus focus on a qualitative analysis in order to pave the way for further studies on this matter in the future. To do so, we first carried out a preliminary exploration of the corpus, using SketchEngine. The frequency lists did not reveal any markers but highlighted several elements: the strong intersubjective dimension of our corpus, with "I", "you" and several proper names being the most frequent words; and the feminine dimension of drag language, with feminine terms of address such as "girl", "ladies", "bitch" and some typically feminine hedges mentioned in  Lakoff's (1973)  study ("like", "know", "think", "feel", "well", "right").
REMERCIEMENTS Nous exprimons notre gratitude à France Maloumian pour son aide dans la réalisation des figures de cet article, ainsi qu'à l'ensemble des auteurs de l'article original  [3]. Le glutamate libéré peut activer ses récepteurs postsynaptiques de type AMPA et NMDA, et ainsi induire une réponse neuronale participant à la mise en mémoire (encodage) du nouvel objet. Ce processus de mémorisation requiert une libération soutenue du glutamate présynaptique. Pour ce faire, les astrocytes peuvent capturer le glutamate synaptique grâce à leurs transporteurs GLT-1/GLAST, puis le transformer en glutamine grâce à la glutamine synthétase (GS). Le transfert de la glutamine astrocytaire au compartiment présynaptique du neurone nécessite l'ouverture des hémicanaux (HC) astrocytaires contenant la connexine 43 (Cx43).
Analyses statistiques Les analyses statistiques ont été réalisées à l'aide des logiciels STATISTICA v13. 4 (TIBCO software, Inc. ) et XLSTAT 5. 1. L'étude de la validité de structure de l'échelle ECA2, et tout d'abord sa structure interne, a été réalisée à l'aide d'une analyse factorielle (méthode d'extraction : Composantes Principales) appliquée sur les 30 items. Le nombre de facteurs a été défini en ne retenant que les valeurs propres supérieures à 1, situées au-dessus de la rupture de pente observée sur le diagramme des valeurs propres (critère de Cattell) et au-dessus des courbes obtenues avec des jeux de données aléatoires simulés. Après rotation oblique Promax (permettant d'interpréter des dimensions possiblement corrélées), les variables pour lesquelles les poids factoriels sont faibles (<|0,40|) ou quasi-identiques pour plusieurs facteurs (différence < |0,10|) n'ont été rattachées à aucun facteur.
REMERCIEMENTS « Moi, si je devais résumer ma vie aujourd'hui avec vous, je dirais que c'est d'abord des rencontres. » Otis, Astérix et Obélix mission Cléopâtre Aux membres du jury, le Pr Menjot de Champfleur, le Pr Thouvenot et le Dr Carra Dallière, d'avoir accepté de porter un regard critique sur ce travail, très perfectible, mais qui m'a beaucoup fait grandir. Merci également à toutes les personnes qui ont offert quelques heures de leur temps pour participer à ce projet : Giovanni, Dimitri, Lila, Ioana, Morgane, Perrine, Teodora, Marie, Cassiana, Laura, Ibrahim, Kate, Emilia, Alina, Valentine, Morgane et Eric bien sûr. Merci Sabine pour ton travail hyper efficace sur les statistiques et tes précieux conseils. Merci à Thibault Mura pour son expertise méthodologique. Merci Eric de m'avoir permis et aidé à faire évoluer ce projet selon mon idée.
En l'absence d'attention particulière, l'IA risque de maintenir et même de renforcer les inégalités sociétales, notamment par la faible inclusion de dataset provenant des minorités, aboutissant à une diminution de la qualité des soins qui leur sont proposés. Par exemple, le diagnostic de mélanome sur une peau de phototype 6 impliquera des paramètres différents pour les algorithmes par rapport à un phototype 1, et donc un apprentissage à part (104). La sécurité des données personnelles des patients est un point important, déjà questionnée dans le cadre des systèmes informatiques des établissements de santé ou des dossiers médicaux dématérialisés. Le dossier médical est strictement confidentiel et ne doit pas être divulgué, sous peine de se transformer en arme utilisable contre les patients dans leur vie quotidienne (employeurs, assurances…).
Ainsi, de nombreuses traces mnésiques pourraient être créées, qui s'associeraient à la première trace, permettant non seulement à la mémoire d'être plus pérenne, mais également d'être facilement rappelée. Sur la base des observations expérimentales et des modèles proposés, l'hippocampe apparaît comme ayant une double fonction. Il élabore une carte spatiale et établit parallèlement des liens multiples entre cet environnement spatial et les personnes, les objets, les événements associés à cette carte pour « raconter » une histoire, créer un souvenir en relation avec des composants élémentaires répartis dans des aires corticales. En Ce travail a été soutenu par le Centre National de la Recherche Scientifique. HT a reçu un financement de l'université Paris Cité. IC et DF ont reçu un financement de l'Agence nationale de la recherche (ANR- 20-NEUR-0005 VELOSO) et du programme ERANET NEURON JTC 2020 sur les troubles sensoriels.
Remerciements Je tiens tout d'abord à exprimer mes remerciements à la Société d' Anthropologie de Paris  qui m'a fait l'honneur de me décerner le prix de la SAP 2022. Je remercie aussi  Emmanuel Mellet  pour avoir dirigé cette thèse et  Francesco d 'Errico pour sa contribution à cette collaboration. Ce travail a été financé par l' IdEx Bordeaux/CNRS  ( PEPS 2015 ),  le CNRS  (project  80 Prime Neurobeads ) et a  bénéficié du soutien financier du gouvernement français dans le cadre du programme IdEx "Investissements d'avenir" de l'Université de Bordeaux / GPR "Human Past ".
Acknowledgements I thank  G. Carron  for his many advices and remark that helped shape this article into its present form, and  L Guillopé  for his comments on the manuscript. I also thank the  Centre Henri Lebesgue   ANR-11-LABX-0020-01  for creating an attractive mathematical environment. I was partially supported by the  ANR  grant:  ANR-18-CE40-0012 : RAGE.
3 Acknowledgments. We like to thank Kevin Coulembier, Pavel Etingof and Victor Ostrik for very helpful email exchanges. DT thanks randomness for giving them/us the key idea underlying this note. This project was in part sponsored by Université Clermont Auvergne and Université Catholique de Louvain, which is gratefully acknowledged. DT was supported by the Australian research council, and PV was supported by the Fonds de la Recherche Scientifique-FNRS under Grant no. J. 0189. 23.
Remerciements Nous tenons à remercier les rapporteurs ayant examiné la présente contribution, ainsi que  Nicolas Brisset ,  Raphaël Fèvre ,  Céline Fellag et Baptiste Mélès  pour leur relecture attentive d'une version intermédiaire de notre article. Nous souhaitons également exprimer toute notre reconnaissance à  Éric Brian ,  Martha-Cecilia Bustamante ,  Olivier Dard ,  Gerhard Heinzmann ,  Mathieu Marion , et  Peter Schöttler  pour leurs remarques constructives au cours de nos recherches. Enfin, nous voudrions remercier  Yann Potin , qui nous a permis de localiser le dossier d'épuration de Jean Mariani aux Archives nationales.
Acknowledgements This work began at the workshop Finiteness results for special subvarieties: Hodge theory, ominimality, dynamics organised by  S. Filip ,  D. Fisher  and  B. Klingler  held in Como (Italy) from October 16 to 22, 2022. We are indebted to several participants of this workshop (including  S. Cantat ,  S. Filip ,  B. Klingler ,  L. Lerer  and  M. Möller ) for many interesting discussions.
Au cours du processus d'itération, une chaîne de Markov est construite en utilisant les valeurs actuelles de paramètres π t (π t représente le jeu de paramètres à l'itération t ) sur lesquelles une fonction aléatoire gaussienne définie par les écart-types s appliqués à chacun des paramètres, π t +1 = N (π t , s). Cette étape correspond au processus de Monte-Carlo. La valeur des écarts types s sont un compromis entre deux contraintes : si les valeurs sont trop élevées, les nouvelles valeurs π t +1 peuvent donner des résultats très loin de la solution optimale, tandis que si elles sont trop faibles, le modèle peut être piégé dans des minimums locaux. Un modèle de distribution adaptative permettant de changer les valeurs s au cours des itérations  [23] , tel qu'implémentée dans le package R HelpersMG  [9] , garantira que le taux d'acceptation soit proche de 0, 234, qui est le taux d'acceptation optimal  [22].
Remerciements L'auteur tient à remercier  Mr Adlane Ait Djaoud du Service Accueil Famille et Citoyenneté à la mairie de la ville de Chaville, l'adjoint au directeur du Bureau de la Réglementation Générale et des Élections (Direction de la Citoyenneté et de la Légalité) de la Préfecture des Hauts-de-Seine et le service « Populations » de la Mairie de Choisy-le-Roi  pour leur aide à l'obtention d'informations utilisées dans cette publication.
To the best of our knowledge, we are the first to combine information on emissions, imports, imported emissions and environmental policy stringency, all at the firm level. The unique features of our data allow making substantial steps forward in understanding how companies' environmental performance responds to both trade liberalizations and changes in environmental policy stringency in the manufacturing sector. The starting point of our analysis is a novel firm-level measure of imported emissions. We obtain our measure of imported emissions by weighting firm-level imports using data on the carbon intensity (direct and indirect) of each sector-country pair obtained from the combination of International Energy Agency (IEA) and the World Input-Output Database (WIOD) data. An advantage of our firm-level measure of imported emissions is that it can be extended to other firm-level datasets because it relies on publicly available data.
Weighting imports by foreign emission intensity allows us to capture the environmentally-related motive of industrial relocation towards emerging economies and to go beyond  Li and Zhou (2017)  and  Cherniwchan (2017) , who focus on import volume from less-developed countries, assuming that they have less stringent regulations than the US  (Ederington et al. 2005). By contrast, we measure actual differences in carbon intensity between sourcing countries. The idea is that companies already importing polluting goods from abroad find it easier to increase the extent of imported carbon emissions. The subsequent step consists in correlating imported emissions with firm's domestic emissions and emission intensity, which are obtained from confidential data on the energy use and expenditures of French manufacturing establishments.
Data and measures Domestic emissions and energy prices. Domestic emissions and energy prices are obtained from the Enquête annuelle sur la consommation d'énergie dans l'industrie (EACEI) conducted by the French statistical office  (INSEE). EACEI collects data on consumption of electricity, natural gas, coal, oil and other fuels (12 energy sources in total) for manufacturing establishments. As in similar plant-level surveys, sampling probabilities depend on size. All plants having at least 250 employees are included in EACEI, while plants with more than 20 employees are sampled through a two-level stratification procedure based on employment class and location. The response rate is very high: for example, 90% of the plants surveyed responded to the 2014 wave. To compute plant-level CO 2 emissions from fuel combustion, we follow the common practice of multiplying CO 2 emission factors from the French Environment and Energy Management Agency (Ademe) for each different fuel source available in EACEI  (Marin and Vona 2017, Dussaux 2020).
To do this, we compute the proportion of each firm's employees working at all of the firm's establishments observed in the EACEI survey, using the Déclaration annuelle des données sociales (DADS), a database containing information on employment-related variables for the universe of French establishments. As a threshold for inclusion in our baseline estimation sample, we keep firms with a share of employment covered in EACEI of 90% or more and impute carbon emission and all other relevant variables proportionally. 6 To calculate imported carbon emissions, we combine confidential customs office data with data on foreign emission intensity at the country-sector level computed using emissions data from the International Energy Agency (IEA) and real output data from the World Input-Output Database (WIOD) socio-economic accounts released in 2013 and 2016 (see table  1 ).
We use the 2018 edition of the IEA CO2 Emissions From Fuel Combustion database to compute emission intensities by country, sector and year. The IEA database covers annual data for 143 countries, 12 industrial sectors for more than 40 years. 7  Emissions are calculated using the IEA energy database and emission factors similar to those used for domestic emissions. The IEA energy database provides emissions for each fuel separately as well as for all fuels altogether. The IEA emission data have two key advantages compared with the emission data of the WIOD environmental accounts: (i) a greater coverage in terms of countries and years because WIOD emissions are available from 1995 to 2009 and only for a limited number of countries and (ii) a criterion of measuring CO 2 emissions that is consistent with that used in the EACEI data set.
Estimation sample Before turning to the empirical analysis of the relationship between imported and domestic emissions, it is important to briefly discuss the way the estimation sample is selected. As in previous research using firm-level emission data (e. g. , Marin and Vona 2021) combined with trade data (e. g. ,  Barrows and Ollivier 2018a) , our estimation sample is not representative of the entire population for four reasons. First, the information on emissions is obtained from the EACEI survey on approximately 10,000 establishments per year. 12  Second, only a subset of firms imports for at least three years, which, as will be explained in the next section, is the minimum required to compute the firm fixed effect and the instrument. Third, imports are available at the firm level; thus, we need to aggregate emissions at this level, retaining only firms for which we can observe at least 90% of establishments.
17  Using the same data and empirical strategy as this paper,  Marin and Vona (2021)  show that long-term effect of energy prices on various outcomes is not significantly different from (although larger than) the short-term effect. Our measure of energy prices is the average cost of energy from the EACEI data set. We first use energy prices to explain differences in imported emissions. If the pollution haven motive is the primary driver of emission reduction within a company, we expect to observe that firm responds to higher prices in France by relocating polluting tasks abroad. Next, we include energy prices in equation (  2 ) so we can compare the role of policy with that of carbon imports: ln (e it ) = α • ln (ImpE it ) + β • ln (p it ) + τ kt + θ rt + d i,t=0 × ϕ t + μ i + ε it. (4) Conditional on imported emissions, we interpret the coefficient of energy prices on emission intensity β as an induced innovation effect.