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108 Research products, page 1 of 11

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  • English
    Authors: 
    Gonzalez-Leonardo, M.; Potančoková, M.; Yildiz, D.; Rowe, F.;
    Publisher: OSF Preprints
    Country: Austria
    Project: EC | FUME (870649)

    Previous studies have examined the impact of COVID-19 on mortality and fertility. However, little is known about the effect of the pandemic on constraining international migration. We quantify the impact of COVID-19 on immigration flows in 15 high-income countries by forecasting their counterfactual levels in 2020 assuming no pandemic and comparing these estimates with observed immigration counts. We then explore potential driving forces, such as stringency measures and changes in unemployment moderating the extent of immigration decline. Our results show that immigration declined in all countries, except in Finland. Yet, significant cross-national variations exist. Australia (60%), Spain (45%) and Sweden (36%) display the largest declines, while immigration decreased by between 15% and 30% in seven states, and by less than 15% in four where results were not statistically significant. International travel, mobility restrictions and stay-at-home requirements exhibit a relationship with declines in immigration, although countries with similar levels of stringency witnessed different intensities of decline. Work and school closings and unemployment show no relationship

  • Open Access
    Authors: 
    Sotiris Pelekis; Karakolis, Evangelos; Silva, Francisco; Schoinas, Vasileios; Mouzakitis, Spiros; Kormpakis, Georgios; Amaro, Nuno; Psarras, John;
    Publisher: Zenodo
    Project: EC | I-NERGY (101016508)

    In power grids, short-term load forecasting (STLF) is crucial as it contributes to the optimization of their reliability, emissions, and costs, while it enables the participation of energy companies in the energy market. STLF is a challenging task, due to the complex demand of active and reactive power from multiple types of electrical loads and their dependence on numerous exogenous variables. Amongst them, special circumstances—such as the COVID-19 pandemic—can often be the reason behind distribution shifts of load series. This work conducts a comparative study of Deep Learning (DL) architectures—namely Neural Basis Expansion Analysis Time Series Forecasting (N-BEATS), Long Short-Term Memory (LSTM), and Temporal Convolutional Networks (TCN)—with respect to forecasting accuracy and training sustainability, meanwhile examining their out-of-distribution generalization capabilities during the COVID-19 pandemic era. A Pattern Sequence Forecasting (PSF) model is used as baseline. The case study focuses on day-ahead forecasts for the Portuguese national 15-minute resolution net load time series. The results can be leveraged by energy companies and network operators (i) to reinforce their forecasting toolkit with state-of-the-art DL models; (ii) to become aware of the serious consequences of crisis events on model performance; (iii) as a high-level model evaluation, deployment, and sustainability guide within a smart grid context.

  • Open Access English
    Authors: 
    Cino, Davide; Brandsen, Silke; Bressa, Nathalie; Eriksson, Eva; Mascheroni, Giovanna; Zaman, Bieke;
    Publisher: Zenodo
    Project: EC | ySKILLS (870612)

    This report is based on findings from a cross-national qualitative study investigating young people’s digital skills practices in non-formal learning contexts in Belgium, Denmark, and Italy. The goal of this study was to gain better knowledge about how to foster digital skills acquisition and practices in non-formal learning contexts. This study combined 16 observations of digital skills workshops (i.c. programming and robotics workshops), 11 interviews with organisers and moderators of such activities, and 4 subsequent co-design activities with the collaboration of children, organisers, moderators, and researchers. The research activities took place in non-formal learning contexts, such as public libraries, youth clubs, and school spaces used for extra-curricular activities (i.e., outside the formal curriculum). Due to different COVID-19 restrictions across Belgium, Denmark and Italy, flexibility with the research protocol was needed. The main aim of the observations and interviews was to first map existing situated experiences of digital skills workshops across countries, investigate their structure and teaching philosophies, and inform co-design activities. Then, with the co-design activities, we aimed to gain knowledge about potential future trajectories, drawing insights from best practices and formulating recommendations, with Italy focusing on teaching style, Denmark on technology and tools, and Belgium on policy. Our work allowed us to address several research questions, investigating three main areas to be understood as broader thematic units. As a first thematic unit concerned with teaching, we questioned how the philosophies that drive the digital skills workshops ran by moderators and organisers have an impact on the workshop organisation in terms of their formality, activities chosen, teaching styles, imaginaries and values. Indeed, we argue that these matters should not go unnoticed, as part of a hidden curriculum (Gordon, 1982), as these are likely to impact children’s and young people's digital skills acquisition and practices. Secondly, as for the theme of learning, we investigated whether and how the formality and structure of the non-formal digital skills workshops may have influenced children’s digital skills practices and learning, what types of learning strategies were promoted by moderators, and what practices were enacted by the children themselves. As a third theme sensitive to including, we aimed to understand who participates in digital skills workshops and who is excluded, and why, questioning for instance potential sociocultural or material barriers (or absence thereof) shaping the democratisation and distribution of the learning opportunities.

  • Open Access English
    Authors: 
    Seker, Mert; Mannisto, Ansi; Iosifidis, Alexandros; Raitoharju, Jenni;
    Publisher: Zenodo
    Project: EC | MARVEL (957337)

    The COVID-19 pandemic has been ongoing since March 2020. While social distancing regulations can slow the spread of the virus, they also directly affect a basic form of non-verbal communication, and there may be longer term impacts on human behavior and culture that remain to be analyzed in proxemics studies. To obtain quantitative results for such studies, large numbers of personal and/or media photos must be analyzed. Several social distance monitoring methods have been proposed for safety purposes, but they are not directly applicable to general photo collections with large variations in the imaging setup. In such studies, the interest shifts from safety to analyzing subtle differences in social distances. Currently, there is no suitable benchmark for developing such algorithms. Collecting images with measured ground-truth pair-wise distances using different camera settings is cumbersome. Moreover, performance evaluation for these algorithms is not straightforward, and there is no widely accepted evaluation protocol. In this paper, we provide an image dataset with measured pair-wise social distances under different camera positions and settings. We suggest a performance evaluation protocol and provide a benchmark to easily evaluate such algorithms. We also propose an automatic social distance estimation method that can be applied on general photo collections. Our method builds on object detection and human pose estimation. It can be applied on uncalibrated single images with known focal length and sensor size. The results on our benchmark are encouraging with 91% human detection rate and only 38.24% average relative distance estimation error among the detected people.

  • Open Access English
    Authors: 
    Bernal-Delgado, Enrique; Estupiñán-Romero, Francisco; González-Galindo, Javier; Martínez-Lizaga, Natalia; Derycke, Pascal; Schutte, Nienke; Van Eycken, Liesbet; Van Damme, Nancy; Henau, Kris; Lyons, Ronan; +8 more
    Publisher: Zenodo
    Project: EC | PHIRI (101018317)

    The PHIRI Federated Research Infrastructure (FRI) is supported by a containerized reproducible solution for data analysis (i.e. use cases) to be deployed on-premises by each participant partner (a.k.a PHIRI-app) to generate a set of local results (outputs) to be further analysed and interpreted generating relevant insight for health policy. This use case will seek to elicit whether there has been an increase in time to treatment in women diagnosed with breast cancer in the month previous to the lockdown measures, as compared with the woman diagnosed with breast cancer before that period and whether the distribution of this delay could be influenced by the healthcare reorganisation measures due to the COVID pandemic. Health Systems across Europe had to reorganise healthcare services reallocating resources towards providing complex assistance to COVID-19 patients. COVID-19 surge of cases during the different epidemic waves requiring intensive care has led countries to cancel or postpone non-urgent care (i.e. elective surgery). The present outputs correspond to the analyses of four nodes that completed the deployment of the analytical pipeline in their premises (Belgium (BE), Wales (UK), Marche (IT), and Aragon (ES)). Others are still ongoing; so, Latvia is reviewing some errors in their dataset; in turn, Croatia, Estonia and Slovenia showed availability for the deployment of the use case. The outputs from the local analyses in those countries include: - Interactive joint report of the trends in diagnosis and delayed treatment for breast cancer (HTLM) - Compilation of the local reports for each country (ZIP file containing HTML documents) - Compilation of the Data Quality Analysis reports for the original data in each country (ZIP file containing HTML documents)

  • Open Access
    Authors: 
    Wallace Claire; Shaddock John;
    Publisher: Zenodo
    Project: EC | SPOT (870644), EC | SPOT (870644)

    One of the SPOT project tasks was to collect comparative information on several themes. These themes are not directly part of the quantitative data collection but are a requirement for project reporting. We collected comparative data across the different case studies to put together into a summary report. Given the nature of these data, we decided to collect them as “expert” assessments from teams. The topics included: economic development and growth; impact on jobs; the impact of cultural tourism for de-industrialised areas, for peripheral areas, for cross-borders issues; how cultural tourism could promote tourist flows and how over-tourism could be managed. Finally, we included a section on the impact of COVID-19 on tourism. Each country is referred to by the international notation, but we should note that data was collected about case studies within countries, rather than the country as a whole. For this reason we have included a table below indicating how country notation is used and to which case study it refers.

  • Open Access
    Authors: 
    Lola Casal-Sanchez;
    Publisher: Zenodo
    Project: EC | EuroAgeism (764632), EC | EuroAgeism (764632)

    This presentation was part of the webinar What is Ageism? Ageism in the Social Media at University of Third Age, Scotland, 26 April 2021. In this webinar, members of the European Network EuroAgeism provided insights into current research on ageism in the media. The media (e.g. newspapers or social media sites) can be seen as one of the many institutions that contribute to the construction of stereotypical images of ageing and old age. At the same time, the media can play a crucial role in breaking stereotypes and helping to solidify the socially and culturally constructions about older people and late-life. Among other research, an example of ageist portrayal of nursing homes in newspapers during COVID-19 were discussed. During the first part of the webinar activities of the whole EUROAGEISM H2020 project in all 15 FIPs/ESRs projects were introduced

  • Open Access
    Authors: 
    Stavrevska, Elena B.;
    Publisher: Zenodo
    Project: EC | GenderedPeace (786494)

    This report highlights the importance of states complying with their obligations under international human rights law in their responses to the COVID-19 pandemic and its aftermath, in particular those with respect to the rights of women and girls as set out in the 1979 Convention on the Elimination of All Forms of Discrimination against Women (CEDAW). Failure to undertake a gender analysis in policy and decision-making with respect to temporary emergency measures to contain the spread of the virus has resulted in variable impacts across different communities and on women within those communities who have experienced disproportionate disadvantage and harm. A gender analysis, therefore, must be carried out, taking into account other intersecting factors that impact women’s lives such as their race, ethnicity, class, sexuality, and able-bodiedness. As the only specific category of women explicitly protected by a separate provision in CEDAW, the situation of rural women provides a useful illustrative case study to show how rurality can operate to create additional disadvantage and contribute to intersectional discrimination. The report examines the position of women in rural areas and the impact of pandemic-related policy responses on their (1) right to adequate living conditions and related right to livelihood; (2) right to security of person; (3) right to healthcare, including reproductive health services; and (4) right to participation in political and public life. Ultimately, the report shows how state failure to comply with the CEDAW obligations has resulted in foreseeable and preventable violations of women’s rights and draws recommendations from the lessons learned.

  • Other research product . Other ORP type . 2022
    Open Access English
    Authors: 
    Enrique Bernal-Delgado; Marc Van den Bulcke;
    Publisher: Zenodo
    Project: EC | PHIRI (101018317), EC | PHIRI (101018317)

    Technical notes and documentation on the common data model of PHIRI Use Case B (WP6) measuring delayed treatments in breast cancer patients as an indirect effect of the COVID-19 pandemic The ZIP file includes: - A spreadsheet in EXCEL format with the data model specification for the use case - An HTML document with a description of Use Case B including the metadata of the data model - A JSON file in schema.org format including the metadata on the data model in a machine-readable format - A CSV file with a synthetic data set produced following the specifications of the use case data model for testing purposes

  • Other research product . Other ORP type . 2022
    Open Access English
    Authors: 
    Carmen Rodriguez-Blazquez; Hanna Tolonen;
    Publisher: Zenodo
    Project: EC | PHIRI (101018317), EC | PHIRI (101018317)

    Technical notes and documentation on the common data model of PHIRI Use Case D (WP6) measuring changes in mental health and health care utilization by mental health patients as an indirect effect of the COVID-19 pandemic The ZIP file includes: - A spreadsheet in EXCEL format with the data model specification for the use case - An HTML document with a description of Use Case D including the metadata of the data model - A JSON file in schema.org format including the metadata on the data model in a machine-readable format - A CSV file with a synthetic data set produced following the specifications of the use case data model for testing purposes !!!Attention: There is a typo in the naming of the files of the common data model within the ZIP file. This version corresponds to use case D common data model specification v.2.0.0.