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  • Open Access English
    Authors: 
    Niels Meijer; Guillaume Dupont‐Nivet; Alexis Licht; Pierrick Roperch; Alexander Rohrmann; Aijun Sun; Shengcheng Lu; Amber Woutersen; Norbert Nowaczyk;
    Publisher: HAL CCSD
    Countries: France, France, Germany, France, France
    Project: EC | MAGIC (649081)

    International audience; The Cenozoic strata of the Xining Basin, NE Tibet, have provided crucial records for understanding the tectonic and paleo-environmental evolution of the region. Yet, the age for the lower part of the sedimentary stratigraphy and consequently the early tectonic evolution of the basin remain debated. Here, we present the litho- and magnetostratigraphy of various early Eocene sections throughout the Xining Basin and provide two possible age models independently constrained by the radiometric age of a carbonate bed. Our study extends the dated Eocene stratigraphy down to an unconformity at 53.0 Ma, which is coeval with increased uplift of the nearby Western Qinling Shan and the formation of flexural basins in northern Tibet related to the far-field effects of the India-Asia collision. However, the Paleogene Xining Basin lacks the characteristic features of these foreland basins such as high sedimentation rates and coarsening due to foredeep propagation, which appear only later during the Neogene. Instead, the strata show NW-SE extensional features during the Cretaceous. Here, we propose that this regime persisted until the Paleogene, coeval with Eocene grabens developing further east and related to the subduction of the Pacific Plate. Yet, the rotations and unconformities observed in the Xining Basin strata show that the basin was increasingly affected by the growing Tibetan Plateau throughout the Paleogene and Neogene while experiencing a transition from extension to transpression and/or transtension.

  • Open Access
    Authors: 
    Linda Juel Ahrenfeldt; Lasse Lybecker Scheel-Hincke; Karen Andersen-Ranberg; Sören Möller; Tine Bovil; Christian Tolstrup Wester;
    Publisher: Elsevier BV
    Project: EC | SSHOC (823782), EC | SHARE-COHESION (870628), EC | SERISS (654221), EC | SHARE-DEV3 (676536)
  • Open Access
    Authors: 
    Joan Costa-Font; Cristina Vilaplana-Prieto;
    Publisher: Elsevier BV
    Project: EC | SERISS (654221), EC | SHARE-COHESION (870628), EC | SSHOC (823782), EC | SHARE-DEV3 (676536)
  • Open Access
    Authors: 
    Rubén López-Bueno; Lars Louis Andersen; Joaquín Calatayud; José Casaña; Lee Smith; Louis Jacob; Ai Koyanagi; José Francisco López-Gil; Borja del Pozo Cruz;
    Publisher: Elsevier BV
    Project: EC | SERISS (654221), EC | SSHOC (823782), EC | SHARE-COHESION (870628), EC | SHARE-DEV3 (676536)
  • Publication . Article . Conference object . Preprint . 2022
    Open Access
    Authors: 
    Valentin Hofmann; Janet B. Pierrehumbert; Hinrich Schütze;
    Publisher: Association for Computational Linguistics
    Country: United Kingdom
    Project: EC | NonSequeToR (740516), EC | NonSequeToR (740516)

    Static word embeddings that represent words by a single vector cannot capture the variability of word meaning in different linguistic and extralinguistic contexts. Building on prior work on contextualized and dynamic word embeddings, we introduce dynamic contextualized word embeddings that represent words as a function of both linguistic and extralinguistic context. Based on a pretrained language model (PLM), dynamic contextualized word embeddings model time and social space jointly, which makes them attractive for a range of NLP tasks involving semantic variability. We highlight potential application scenarios by means of qualitative and quantitative analyses on four English datasets. Comment: ACL 2021

  • Open Access
    Authors: 
    Orsholits, Dan; Cullati, Stéphane; Cheval, Boris; Ghisletta, Paolo; Oris, Michel; Maurer, Jürgen; Studer, Matthias; Marques, Adilson; Marconcin, Priscila; Gouveia, Élvio; +2 more
    Publisher: Open Science Framework
    Country: Portugal
    Project: EC | SERISS (654221), EC | SHARE-COHESION (870628), EC | SHARE-PREP (211909), EC | SHARE_LEAP (227822), EC | DASISH (283646), EC | SHARE_M4 (261982), SNSF | Individual pathways of co... (189407), EC | SSHOC (823782), SNSF | Behaviors minimizing ener... (180040), EC | SHARE-DEV3 (676536)

    A.I. acknowledges support from the Swiss National Science Foundation (Grant Number: 10001C_189407). This work was further supported by the Swiss National Centre of Competence in Research LIVES—Overcoming vulnerability: life course perspectives, granted by the Swiss National Science Foundation (Grant Number: 51NF40-185901). B.C. is supported by an Ambizione Grant (PZ00P1_180040) from the Swiss National Science Foundation. This study uses data from SHARE Waves 1, 2, 3, 4, 5, 6, 7 and 8 (DOIs: https://doi.org/10.6103/SHARE.w1.710, https://doi.org/10.6103/SHARE.w2.710, https://doi.org/10.6103/SHARE.w3.710, https://doi.org/10.6103/SHARE.w4.710, https://doi.org/10.6103/SHARE.w5.710, https://doi.org/10.6103/SHARE.w6.710, https://doi.org/10.6103/SHARE.w7.711, https://doi.org/10.6103/SHARE.w8.100). The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA N°211909, SHARE-LEAP: GA N°227822, SHARE M4: GA N°261982, DASISH: GA N°283646) and Horizon 2020 (SHARE-DEV3: GA N°676536, SHARE-COHESION: GA N°870628, SERISS: GA N°654221, SSHOC: GA N°823782) and by DG Employment, Social Affairs & Inclusion through VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, and VS 2020/0313. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C, RAG052527A) and from various national funding sources is gratefully acknowledged (see www.share-project.org). Previous work has found that later life urban-rural differences in cognitive health can be largely explained by indicators of cognitive reserve such as education or occupation. However, previous research concentrated on residence in limited, specific, periods. This study offers a detailed investigation on the association between urban (vs. rural) residence from birth, and cognitive functioning in older age. Using data from the Survey of Health Ageing and Retirement in Europe we created residential trajectories from birth to survey enrolment with a combination of sequence and cluster analysis. Using mixed-effects models, we investigated the association between residential trajectories in early, mid, and later life and three cognitive functioning outcomes: immediate recall, delayed recall, and verbal fluency. In a sample of 38,165 participants, we found that, even after accounting for differences related to education and occupation, rural (vs. urban) residence in early life remained associated with poorer cognitive performance later in life. This suggests that growing up in rural regions leads to a long-term disadvantage in cognitive functioning. Thus, public health policies should consider that urban-rural inequalities in early life may have long-lasting associations with inequalities in cognitive health in old and very old age. © The Author(s) 2022 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommons. org/ licenses/ by/4.0/.

  • Open Access English
    Authors: 
    Paulo Jorge Nogueira; Carla Farinha; Maria Adriana Henriques; Andreia Costa; Ana Catarina da Costa Maia;
    Publisher: MDPI
    Country: Portugal
    Project: EC | SSHOC (823782), EC | SERISS (654221), EC | SHARE_M4 (261982), EC | SHARE-COHESION (870628), EC | SHARE-PREP (211909), EC | SHARE_LEAP (227822), EC | DASISH (283646), EC | SHARE-DEV3 (676536)

    The knowledge of long-term informal care is particularly interesting for social and health measures related to ageing. This study aims to analyze how Portugal differs from Denmark regarding long-term informal care, specifically referring to personal care received by older people. A cross-sectional study was developed in Portugal and Denmark through the Survey of Health, Ageing and Retirement in Europe (SHARE) in 2015, with a total of 2891 participants. Descriptive statistics and logistic regressions were performed. The findings suggest a significant association for older people from Portugal who receive long-term informal care from non-household caregivers and household caregivers. Moreover, as they age and are from Portugal, their availability to receive long-term informal care from non-household caregivers increases. Furthermore, older people in Portugal are more likely to receive long-term informal care from a household caregiver. It is important to take a closer look at long-term informal care in both countries and think about healthy ageing policies in the current context of the ageing population. This study provides knowledge about disaggregated health data on ageing in the European region, helping to fill research gaps related to older people. The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA N°211909, SHARE-LEAP: GA N°227822, SHARE M4: GA N°261982, DASISH: GA N°283646), Horizon 2020 (SHARE-DEV3: GA N°676536, SHARE-COHESION: GA N°870628, SERIES: GA N°654221, SSHOC: GA N°823782), and DG Employment, Social Affairs & Inclusion through vs. 2015/0195, vs. 2016/0135, vs. 2018/0285, vs. 2019/0332, and vs. 2020/0313. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Ageing (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C, RAG052527A), and from various national funding sources is gratefully acknowledged (see www.share-project.org, accessed on 18 November 2020). © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

  • Open Access
    Authors: 
    Rebecca Groh; Luzia M. Weiss; Martina Börsch‐Supan; Axel Börsch‐Supan;
    Publisher: Wiley
    Project: EC | SSHOC (823782), EC | SHARE-COHESION (870628), EC | SERISS (654221), EC | SHARE-DEV3 (676536)
  • Open Access
    Authors: 
    Francesco Iacono; Elisabetta Borgna; Maurizio Cattani; Claudio Cavazzuti; Helen Dawson; Yannis Galanakis; Maja Gori; Cristiano Iaia; Nicola Ialongo; Thibault Lachenal; +7 more
    Publisher: Springer Nature
    Countries: Italy, Spain, United Kingdom, Spain, France, France, Germany, Germany, United Kingdom
    Project: EC | WEIGHTANDVALUE (648055), EC | WEIGHTANDVALUE (648055)

    AbstractThe Late Bronze Age (1700–900 BC) represents an extremely dynamic period for Mediterranean Europe. Here, we provide a comparative survey of the archaeological record of over half a millennium within the entire northern littoral of the Mediterranean, from Greece to Iberia, incorporating archaeological, archaeometric, and bioarchaeological evidence. The picture that emerges, while certainly fragmented and not displaying a unique trajectory, reveals a number of broad trends in aspects as different as social organization, trade, transcultural phenomena, and human mobility. The contribution of such trends to the processes that caused the end of the Bronze Age is also examined. Taken together, they illustrate how networks of interaction, ranging from the short to the long range, became a defining aspect of the “Middle Sea” during this time, influencing the lives of the communities that inhabited its northern shore. They also highlight the importance of research that crosses modern boundaries for gaining a better understanding of broad comparable dynamics. Funder: Alma Mater Studiorum - Università di Bologna

  • Publication . Article . Preprint . 2022 . Embargo End Date: 01 Jan 2021
    Open Access
    Authors: 
    Christian M. Dahl; Torben S.D. Johansen; Emil N. Sørensen; Simon Wittrock;
    Publisher: arXiv
    Project: EC | DONNI (851725)

    Methods for linking individuals across historical data sets, typically in combination with AI based transcription models, are developing rapidly. Probably the single most important identifier for linking is personal names. However, personal names are prone to enumeration and transcription errors and although modern linking methods are designed to handle such challenges, these sources of errors are critical and should be minimized. For this purpose, improved transcription methods and large-scale databases are crucial components. This paper describes and provides documentation for HANA, a newly constructed large-scale database which consists of more than 3.3 million names. The database contain more than 105 thousand unique names with a total of more than 1.1 million images of personal names, which proves useful for transfer learning to other settings. We provide three examples hereof, obtaining significantly improved transcription accuracy on both Danish and US census data. In addition, we present benchmark results for deep learning models automatically transcribing the personal names from the scanned documents. Through making more challenging large-scale databases publicly available we hope to foster more sophisticated, accurate, and robust models for handwritten text recognition.