dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments. The research leading to these results received funding from the  European Research Council  for the project Nexus 1492 ( ERC  grant no. 319209 ), the  Netherlands Organization for Scientific Research  ( NWO Open Competition  grant no. 360-62-060 ) as part of the research program  Island Networks ; and  NWO-CaribTrails. A first version of this article was presented at the 83rd Annual Meeting of the  Society for American Archaeology  in 2018, in Washington, DC, in the symposium "Material Culture and Multivocal Cultural Dialogue in the Construction of the  Criollo Universe in the Caribbean ," organized by  Antonio Curet  and  Jorge Ulloa Hung. We thank  Loe Jacobs ,  Becki Scott ,  Anneleen Stienaers , and  Patrick Degryse  for sharing their insights and knowledge on the fabric and mineral composition of the studied clays and ceramics.
AGRADECIMIENTOS El equipo de sociólogos e historiadores fue coordinado por Vania Markarian y Gabriela González Vaillant e integrado por Cecilia Lacruz, Paolo Venosa y Camille Gapenne, con la asistencia de Cecilia Muniz. Estamos muy agradecidos a los demás integrantes del equipo por los valiosos insumos que aportaron a este trabajo, así como a los estudiantes del curso de maestría de Historia Política por sus comentarios.
Se trata del carácter exponencial que ha ido cobrando la migración de centroamericanos que atraviesan la república mexicana para llegar a los EE. UU. Obviamente este flujo migratorio no es un fenómeno que data de hoy. La migración procedente de El Salvador, Guatemala y Honduras se ha consolidado como flujo sostenido desde la década de los años sesenta y setenta debido a las políticas de injerencia de los EE. UU. que desestabilizaron la región con la recrudescencia de guerrillas y acciones paramilitares  (Cortés, 2018: 42; Willers, 2016: 167-168). Las catástrofes naturales (como el huracán Mitch en 1998, el terremoto en El Salvador en 2001, el huracán Stan en 2005) tendrán también un impacto en el aumento del flujo migratorio, al igual que las consecuencias desastrosas de proyectos ecoturísticos que obligan a comunidades indígenas a desplazarse  (Cortés, 2018: 42).
Agradecimientos Este trabajo fue realizado en el marco del Proyecto ANID ECOS 170005: "CAMHUDES". C. Castillo agradece a Beca CONICYT de Doctorado Nacional Folio 21160199; M. Sepúlveda agradece a proyectos Mayor de Investigación Científica y Tecnológica Universidad de Tarapacá 8766 -17 y FONDECYT-ANID 1130808 que contribuyeron a financiar excavaciones de donde se obtuvo el material aquí analizado, entre los años 2013 y 2016. Finalmente, E. M. Gayo agradece a PROYECTO ANID FB210006 y ANID-Programa Iniciativa Científica Milenio-NCN19_153.
AGRADECIMIENTOS Agradezco la generosidad de las personas entrevistadas, asi como los comentarios de Eduard Sala Barceló, Luis Sanmartín Cava y Gabriele D'Adda, que leyeron atentamente versiones previas de este artículo. También agradezco el respetuoso y constructivo trabajo de las personas evaluadoras anónimas, que fue de gran ayuda para precisar mis argumentos, así como el minucioso trabajo de edición del revisor.
Agradecimientos Los autores agradecen los comentarios críticos de los dos evaluadores anónimos, lo que ayudó a mejorar el manuscrito sustancialmente. Agradecemos también el importante apoyo interdisciplinario del Prof. Dr. Martin Grosjean, director del Centro de Investigaciones para el Cambio Climático de la Universidad de Berna, durante su participación en diversos proyectos conjuntos en la circumpuna. De igual manera el aporte del actual proyecto FON-DECYT 1181627.
AGRADECIMIENTOS Este estudio ha sido posible gracias a los proyectos "Recursos minerometálicos, intercambio y comercio en la Prehistoria y la Protohistoria peninsular (Cataluña y el norte del País Valenciano)" (MINECO, HAR2014-54012-P, 2015-2017) dirigido por Núria Rafel, y "Activités minières et métallurgiques: anthropisation des milieux et productions matérielles" (CNRS, Chaire d'Excellence 2011-2016) dirigido por Florence Cattin. A las dos personas que han evaluado el artículo por su revisión y comentarios.
Bibliografía Alazard, Florence: Art vocal, art de gouverner. La musique, le prince et la cité en Italie à la fin du XVI e siècle, París, Minerve, 2002. Amilien, Estelle: Les instruments de musique et leur fonction en espagnol à partir de la base de données du LMR. Analyse et contextualisation, tesina de máster, École Normale Supérieure de Lyon, 2010. Barthes, Roland: "La mort de l'auteur", Le bruissement de la langue. Essais critiques IV, París,  Seuil, 1984 (1. ª ed. 1967).
He dirigido varios trabajos sobre esta temática, por ejemplo el de Estelle Amilien: Les instruments de musique et leur fonction en espagnol à partir de la base de données du LMR. Analyse et contextualisation, tesina de máster, École Normale Supérieure de Lyon, 2010; o el de Jesús Noguera Guillén: La musique pour clavier dans l'Espagne du Siècle d'Or. De la lexicologie à la pratique, travail d'étude personnel (TEP), París, Conservatoire National Supérieur de Musique de Paris, 2018.
Agradecimientos Esta investigación se desarrolló gracias a la investigación Análisis comparativo de las políticas de lucha contra las desigualdades educativas en Francia y España financiado por la Université Vincennes-Saint-Denis (Paris 8). y participa en proyecto sobre la democracia en las escuelas. Email: carmen. marquez@uam. es ORCID ID: https://orcid. org/0000-0003-0708-6698.
C'est là le coeur du programme de recherche Filiation, Identité, Altérité Médiévales (Fil_IAM), financé par l'Agence Nationale de la Recherche depuis 2020 et dirigé par Carole Avignon. URL : https://anr. fr/Projet-ANR-19-CE41-0004 et https://filiam. hypotheses. org/.
Agradecimientos Este trabajo forma parte del proyecto MONOBESAT (PID2019-111435RB-I00) financiado por el Ministerio de Ciencia, Innovación y Universidades, y del contrato Margarita Salas dentro del programa de recualificación del sistema universitario español -Ministerio de Universidades-financiado por la Unión Europea -NextGenerationEU-. Los autores agradecen a la ESA (Agencia Espacial Europea) y al USGS (Servicio Geológico de los Estados Unidos) el acceso a las imágenes de satélite, a Puertos del Estado por los datos oceanográficos y a la DGSCM por la información relativa a los movimientos de arena. Queremos agradecer las observaciones realizadas por los revisores del manuscrito que, sin duda, han hecho que mejore el resultado final.
Agradecimientos La investigación para este libro fue posible gracias a un financiamiento de la Università degli Studi di Torino. Esta fue precedida por una estancia en la Universidad de Cuenca para investigar acerca del contexto ecuatoriano, de la historia del movimiento indígena y de su proyecto educativo. Posteriormente, efectué las visitas y las permanencias en seis unidades educativas gracias a la colaboración con la Unidad Nacional de Educación (UNAE), con cuyos docentes dialogué constantemente. Por medio de la institución, también participé en el Primer Festival de Interculturalidad y Plurinacionalidad y en el VI Foro Regional de Responsabilidad Social Territorial; en ambas ocasiones profundicé el conocimiento del proyecto intercultural bilingüe. En particular, mi permanencia en la Unidad del Milenio de Sagrado Corazón coincidió con la práctica docente de los estudiantes de la Carrera de Educación Intercultural Bilingüe.
Cuadro 1. Esperanza de vida al nacer y a los 60 años para los años intercensales 1955-2005, según sexo Fuente: Palloni, A. , Pinto, G. y Beltrán-Sánchez, H. (2014). Latin American Mortality Database (Lambda). [Machine-readable database], Madison: University of Wisconsin. Cuadro 2. Venezuela y grupo de entidades. Índices de evaluación de calidad de la información. Registro de Defunciones del MPPS, años 2000-2010.
Cuadro 1. Esperanza de vida al nacer y a los 60 años para los años intercensales 1955-2005, según sexo Fuente: Palloni, A. , Pinto, G. y Beltrán-Sánchez, H. (2014). Latin American Mortality Database (Lambda). [Machine-readable database], Madison: University of Wisconsin. Cuadro 2. Venezuela y grupo de entidades. Índices de evaluación de calidad de la información. Registro de Defunciones del MPPS, años 2000-2010. Años Esperanza de vida al nacer Hombres Mujeres Esperanza de vida a los 60 años Hombres Mujeres 1955 55. 6 58. 6 14. 1 15. 7 1966 60. 8 64. 6 14. 7 16. 4 1976 62. 1 67. 8 14. 5 17. 0 1985 65. 0 70. 6 15. 4 17. 8 1995 66. 8 72. 7 16. 6 19. 0 2005 67. 6 74. 9 17. 5 20. 2 Grupo de entidades Myers Whipple % de edad desconocida % causas de muerte no declarada % de completitud* Mín. Máx.
Agradecimientos Agradecemos a los miembros del equipo de investigación ArScAn-AnTET y a los colegas de la Universidad de París Nanterre y el Museo Nacional de Historia Natural por el debate y la discusión en curso sobre este tema. Los datos y ejemplos arqueológicos presentados en este trabajo han sido recopilados con el permiso de los Museos Nacionales de Kenia, el Museo Nacional de Etiopía, Costech en Tanzania, la Junta de Andalucía (España), la Universidad degli studi di Ferrara (Italia), Instituto de Paleontología y Paleoantropología de Vertebrados (Beijing, China), Instituto de Arqueología y Protección de Vestigios Culturales de Guangxi (Nanning, China), Instituto de Arqueología (Universidad de Buenos Aires, Facultad de Filosofía y Letras, Argentina). Nuestro agradecimiento también va para Francesca Manclossi, quien amablemente nos permitió reproducir una de sus ilustraciones.
El grupo 1 reúne ZAT con la más alta vulnerabilidad para enfrentar la situación impuesta por la crisis sanitaria: los habitantes de estos sectores tienen largos viajes (número alto de etapas y duración muy larga), la tasa de motorización es baja y la población es altamente dependiente del transporte público, cuya oferta es escasa. Pocos viajes tienen como destino sectores con alta afluencia. Son zonas muy poco  [10]  Se utilizó FactoQGIS, una extensión desarrollada por F. Demoraes (https://github. com/ESO-Rennes/FactoQGIS). La clasificación se calculó con base en los cinco primeros ejes factoriales para conseguir una tipología más estable. densas con hogares pobres (tenencia de celulares y de computadora baja, y escasa conexión a Internet) y una tasa de inactividad mucho mayor a la del promedio metropolitano.
INTRODUCTION A key defining feature of a species' niche and ecological roles is its diet  (Pocheville 2015). What an animal species eats influences its trophic position, how it moves around, and which other species it interacts with, among many other behaviours. While diets are flexible, predators have evolved to forage optimally on certain prey types or species  (Hayward et al. 2011 (Hayward et al. , 2016)). The mechanisms that determine optimal foraging behaviour include adaptative responses to prey availability, food quality, energy required to handle prey  (Pyke et al. 1977 , Sundell et al. 2003) , and predation risk from larger co-occurring predators  (Haswell et al. 2018). Ecological and climatic conditions determine animal distributions and, in turn, diet composition, so the study of intraspecific diet variation using large biogeographical datasets provides a powerful means to understand the ecology of Carnivora.
2017). In Australia, where the fox has been introduced, its diet mainly comprises small and medium-sized mammals, livestock, reptiles, birds, invertebrates, and vegetation  (Fleming et al. 2021). Notwithstanding these regional-and continental-scale studies of fox diet, quantitative studies describing worldwide biogeographical patterns in fox diet composition have not been undertaken. Understanding of geographic variation in red fox diet at a global scale can be used to predict how this widespread species will respond and adapt to future land use and climate change. We compiled the most complete dataset to date to assess variation in fox diet composition throughout its global geographic range. First, we assessed geographic patterns in the dietary ecology of foxes, particularly among continents.
Literature search and dataset construction We carried out a quantitative literature review to select studies focused on fox diet, published before or during 2018. We used ("Vulpes vulpes" OR fox) AND (diet OR predation OR ecology) as keywords in ISI Web of Science, JSTOR, and Google Scholar. For each study, we downloaded the title, abstract, authors, year, and journal name. Additionally, we examined the reference lists of all articles that were identified in our initial dataset to ensure key literature was not missed. We selected studies reporting frequency of occurrence (FO, i. e. the number of individual samples where a food item was present as a percentage of the total number of samples) of food items consumed by foxes, from scats, stomachs, or both scats and stomachs (Appendices S1 and S2).
Diet data We used a consistent set of 13 food categories to report on fox diet: 1) small mammals (adult weight <500 g), 2) medium-sized mammals (500-6999 g), 3) large mammals (≥7000 g), 4) unidentified mammals, 5) birds, 6) invertebrates, 7) reptiles, 8) amphibians, 9) fish, 10) fruit, 11) vegetation, 12) garbage (i. e. human-related materials and discarded food), and 13) unidentified food. These food categories were chosen because they have been widely reported as foods consumed by foxes in many parts of the world  (Abe 1975 , Catling 1988 , Jankowiak et al. 2008 , Drygala et al. 2014). If the authors of a study pooled data for multiple mammal sizes in only one food category, we classed this category as 'unidentified mammals'. In those instances, we recorded 'not applicable' against the individual mammal size categories.
Also, if a primary source reported on food types that encompassed more than one of our categories (e. g. 'fruit and vegetation' or 'amphibians and reptiles'), we considered them as 'unidentified food'. Values reported as <1% and <0. 01% were included in our dataset as 0. 5% and 0. 005%, respectively. If a value or comment was not provided for a food category in the study, we coded it as 'not applicable' in our dataset. When the food category was mentioned in the text or accounted for but not recorded in the diet, we included a zero value in our dataset. Where food categories used in primary sources differed from the set of categories we adopted, we used combinatorial probabilities (for more details, see  Murphy et al 2019)  to pool FO of food categories (i. e. number of individuals of each food or food occurrences over sample size).
Spatial variables We created a 20 km circular buffer around each study location to estimate mean annual temperature and precipitation, elevation, and HFI. Mean annual temperature, precipitation, and elevation at 5 m resolution were sourced from the WorldClim dataset (www. wordc lim. org). We quantified anthropogenic influence using the HFI layer version 2,  1995 -2004 (Wildlife Conservation Society -WCS 2005) ; this database represents a global spatial dataset of the HFI normalised by biome and realm. Global HFI is estimated using population density, human land use, infrastructure (e. g. built-up areas, night-time lights), and human access (e. g. coastlines, roads, railroads). Given the range in publication dates among papers included in our study , we fitted for each food category one model using the full dataset (n = 217 fox diet studies) and another only including papers carried out between 1995 and 2004 (n = 59 fox diet studies) to match the temporal resolution of the HFI layer (Appendix S3).
We found similar patterns between those models; thus, we used the full dataset for subsequent analyses (Appendix S4). Predictor variables were not highly correlated with each other (r ≤ 0. 62). To confirm that our choice of a 20 km buffer was appropriate, we tested the degree of correlation between three different buffer radius values (i. e. 5, 10, and 20 km) and found that correlation coefficients were very high (temperature: r > 0. 99; precipitation: r > 0. 99; elevation: r > 0. 96; and HFI: r > 0. 90). This indicates that our inferences are unlikely to be influenced greatly by our choice of buffer distance.
Analysis of global and continental fox diet We assessed patterns of fox diet composition (excluding unidentified birds, unidentified mammals, and unidentified food) among and within continents using the analysis of similarity (ANOSIM) in the 'vegan' package (version 2. 5-7;  Oksanen et al. 2020)  in R (version 4. 1. 2; R Core Team 2021). We excluded Africa from these analyses because only two studies from Africa met our criteria. ANOSIM provided a measure of dissimilarity (R) among and within continents. Dissimilarity (R) values range between -1 (i. e. low dissimilarity) and +1 (i. e. high dissimilarity between groups). Because ANOSIM requires a complete dataset, we considered food category absences as genuine absences. We used Euclidean distances to ordinate fox diet composition in two dimensions using 300 random starts.
That is, we fitted two models for each response variable. We used the 'lme4' package (version 1. 1. 27. 1;  Bates et al. 2015)  in R to fit generalised linear models. All predictor variables were mean-standardised before they were added to the model. We assessed model fit using the quartile-quartile plot function provided in the 'DHARMa' package  (Hartig 2021 ). This analysis indicated overdispersion of residuals in all food categories; thus, a Tweedie generalised linear model was fitted. The alpha value was set in each model to maximise the normality of the residuals as indicated using the 'Tweedie' package in R  (Dunn & Smyth 2005 , 2008 , Dunn 2017). For each food category, models of all combinations of variables were assessed using dredge in the 'MuMIn' package in R (Barton 2020), which were then weighted according to the Akaike Information Criterion corrected for small sample size (AICc;  Burnham & Anderson 2002)  or Tweedie-AIC value (t-AIC; Dunn 2017).
DISCUSSION Based on the collation of a large dataset of comparable dietary studies from most of the global range of the fox, we assessed geographic variation in fox diet and tested predictions in relation to environmental and anthropogenic drivers. We found that fox diet composition varied among continents and that geographic, climatic, and anthropogenic variables influenced fox diet richness. These results are likely to reflect differences in both prey availability and anthropogenic influences. Moreover, the sample type used in studies (stomach-to-scat ratio) influenced the occurrence of mammals and fruit in fox diet samples.
g. bones and hairs, which are indigestible) than those consuming large mammals. We also found greater FO of fruit in studies that analysed scat contents rather than stomachs. This could also reflect the fact that some authors failed to consider fruit as possible dietary item for foxes  (Brunner et al. 1975 , Kirkwood et al. 2000 , Rosalino & Santos-Reis 2009 , Dawson et al. 2016). For instance, in our dataset 17% of studies based on stomachs and 10% of studies based on scats did not report data for fruits. Indeed, contrary to our result,  Fleming et al. (2021)  found that plant material (including fruits and other vegetation parts) in Australian fox diets was more often recorded in studies using stomach contents than in studies based on scat analysis, probably due to the presence of highly digestible plant material (i.
Using standardized protocols, the expedition took samples in different water layers, and for a wide range of plankton organism sizes, in combination with a detailed contextual description  (Pierella Karlusich et al. 2020; Sunagawa et al. 2020). Here, we analysed the eukaryotic phytoplankton community of the SWAO using Tara Oceans data mainly derived from 18S rRNA gene metabarcoding. In particular, we explored phytoplankton community composition and diversity within three different size fractions and two distinct water layers in the context of biotic and abiotic factors. We complemented the molecular observations with images from confocal microscopy. We then compared the community composition with that of samples from the global ocean. Overall, this study intends to shed light on the process of marine phytoplankton community assembly in the SWAO.
M�������� ��� M������ In the late spring of 2010 (29 th November-16 th December), the Tara Oceans expedition sailed from Buenos Aires to Ushuaia (Argentina) onboard the oceanographic schooner TARA and sampled at four different stations of the SW A������� ������������� ₈₃₇ SWAO. During this leg, the expedition aimed at stations in the center of relatively stable oceanic features (e. g. , an eddy or a major current). For this, preliminary locations were selected on a sea surface height map about a week prior to the sampling. The four definitive stations were located between 40° S and 55° S (Figure  1A ). A complete physical data report by station can be found in store. pangaea. de/ Projects/TARA-OCEANS/Station_Reports/. Station TARA_080 (29 th November ) was located in an area dominated by mesoscale features.
The environmental conditions were recorded at each station. Detailed protocols from the Tara Oceans expedition can be found in  Pesant et al. (2015) , and full contextual data are available at doi. org/10. 1594/PANGAEA. 875582. Water temperature was measured with a vertical profile sampling system (CTD-rosette). Chlorophyll a (chl a) concentrations were obtained through HPLC  (Van Heukelem and Thomas 2001; Ras et al. 2008). Nitrate (NO 3 -) ions were analysed according to the protocol of  Bendschneider and Robinson (1952). Total water column depth was obtained from the American Oceanic and Atmospheric Administration (NOAA) via R-package marmap (version 1. 0. 5) (Pante and Simon-Bouhet 2013)  specifically for this work. We included abundances of other broad planktonic groups to further characterize each sample habitat.
2014) , and classified taxonomically against a customized ribosomal reference database (for complete details see  de Vargas et al. (2015)  and its companion website taraoceans. sb-roscoff. fr/ EukDiv/; the global OTU table is available at zenodo. org/record/3768510). Photosynthetic unicellular eukaryotes were identified based on their taxonomic affiliation, and only those with >80% identity with the database reference sequences were kept. We included photosynthetic dinoflagellates when their taxonomic resolution was sufficient to match known photosynthetic lineages from the literature. We did not include mixotrophs that obtain their chloroplast or photosynthetic capacity by different mechanisms from other unicellular organisms  (Pierella Karlusich et al. 2020). Throughout this work we refer to deep-branch lineages that consist of a set of informative names of phyla (e.
e. , presence/ absence). The principal coordinates analysis was carried out via the function wcmdscale on the global dissimilarity matrix derived from the Hellinger-transformed compositional data and only the two first axes were displayed. We set focus on the two major basins (Atlantic and Pacific, north-south) and the Southern Ocean to follow the main analysis in Ibarbalz et al. (  2019 ) and without the Arctic samples due to differences in size fractions. By compositional data we refer to abundances relativized by the total number of phytoplankton reads per sample. The R-function hclust served for performing the hierarchical clustering analysis, using the unweighted average linkage criterion. Finally, to further support the observations derived from 18S rRNA gene metabarcoding, we inspected the Tara Oceans dataset of environmental High Content Fluorescence Microscopy (eHCFM)  (Colin et al.