Recent Submissions

  • Automated image analysis for single-atom detection in catalytic materials by transmission electron microscopy 

    Mitchell, Sharon; Parés Pont, Ferran; Faust Akl, Dario; Collins, Sean; Kepaptsoglou, Demie; Ramasse, Quentin; Garcia Gasulla, Dario; Pérez Ramírez, Javier; López Alonso, Nuria (2022-03-25)
    Article
    Restricted access - publisher's policy
    Single-atom catalytic sites may have existed in all supported transition metal catalysts since their first application. Yet, interest in the design of single-atom heterogeneous catalysts (SACs) only really grew when advances ...
  • Pulmonary function and radiologic features in survivors of critical COVID-19: a 3-month prospective cohort 

    González Gutiérrez, Jessica; Benítez Iglesias, Iván D.; Carmona Arias, Paola; Santisteve, Sallya; Monge Esqué, Aida; Moncusí Moix, Anna; Gort Paniello, Clara; Pinilla Latorre, Lucía; Carratalá García, Amara; Zuil Moreno, María; Ferrer Roca, Ricard; Ceccato, Adrián; Fernández Barat, Laia; Motos Galera, Ana; Riera del Brío, Jordi; Menéndez Villanueva, Rosario; Garcia Gasulla, Dario (2021-07)
    Article
    Open Access
    BACKGROUND: More than 20% of hospitalized patients with COVID-19 demonstrate ARDS requiring ICU admission. The long-term respiratory sequelae in such patients remain unclear. RESEARCH QUESTION: What are the major long-term ...
  • Building a territorial working group to reduce gender gap in the field of artificial intelligence 

    Gibert, Karina; Valls Mateu, Aïda (2022-03-18)
    Article
    Open Access
    The gender gap (both at vocational and professional sides) in Artificial Intelligence (AI), and scientific and technological fields in general, is one of the most critical challenges that the current digital society must ...
  • Impact of time to intubation on mortality and pulmonary sequelae in critically ill patients with COVID-19: a prospective cohort study 

    González Gutiérrez, Jessica; Benítez Iglesias, Iván D.; de Gonzalo Calvo, David; Torres Cortada, Gerard; Batlle, Jordi de; Gómez Falguera, Silvia; Moncusí Moix, Anna; Carmona, Paola; Santisteve, Sallya; Gort Paniello, Clara; Ferrer Roca, Ricard; Garcia Gasulla, Dario; Torres, Antoni; Barbé, Ferran; Monge Esqué, Aida; Zuil Moreno, María (Springer Nature, 2022-12)
    Article
    Open Access
    We evaluated whether the time between first respiratory support and intubation of patients receiving invasive mechanical ventilation (IMV) due to COVID-19 was associated with mortality or pulmonary sequelae. Materials and ...
  • Large scale prediction of sick leave duration with nonlinear survival analysis algorithms 

    Béjar Alonso, Javier; Pérez Arnal, Raquel Leandra; Vilalta, Armand; Álvarez Napagao, Sergio; García Gasulla, Dario (2022-07-15)
    Article
    Restricted access - publisher's policy
    The management of sick leaves is a critical task that public and private health systems carry out. This enables the good care of sick workers and guarantees a safe return to their jobs. Most health systems enforce regulations ...
  • The digital revolution in the urban water cycle and its ethical–political implications: a critical perspective 

    Popartan, Lucia Alexandra; Cortés Martínez, Atia; Garrido Baserba, Manel; Verdaguer Planas, Marta; Poch Espallargas, Manel; Gibert, Karina (Multidisciplinary Digital Publishing Institute, 2022-02-28)
    Article
    Open Access
    The development and application of new forms of automation and monitoring, data mining, and the use of AI data sources and knowledge management tools in the water sector has been compared to a ‘digital revolution’. The ...
  • Bootstrap–CURE: A novel clustering approach for sensor data: an application to 3D printing industry 

    Suman, Shikha; Karna, Ashutosh; Gibert, Karina (2022-02-19)
    Article
    Open Access
    The agenda of Industry 4.0 highlights smart manufacturing by making machines smart enough to make data-driven decisions. Large-scale 3D printers, being one of the important pillars in Industry 4.0, are equipped with smart ...
  • Operational modes detection in industrial gas turbines using an ensemble of clustering methods 

    Bagherzade Ghazvini, Mina; Sànchez-Marrè, Miquel; Bahilo, Edgar; Angulo Bahón, Cecilio (2021-12-01)
    Article
    Open Access
    Operational modes of a process are described by a number of relevant features that are indicative of the state of the process. Hundreds of sensors continuously collect data in industrial systems, which shows how the ...
  • Adaptive optics control with multi-agent model-free reinforcement learning 

    Pou Mulet, Bartomeu; Ferreira, Florian; Quiñones Moreno, Eduardo; Gratadour, Damien; Martín Muñoz, Mario (2022-01-14)
    Article
    Open Access
    We present a novel formulation of closed-loop adaptive optics (AO) control as a multi-agent reinforcement learning (MARL) problem in which the controller is able to learn a non-linear policy and does not need a priori ...
  • The INSESS-COVID19 Project: evaluating the Impact of the COVID19 in social vulnerability while preserving privacy of participants from minority subpopulations 

    Gibert, Karina; Angerri Torredeflot, Xavier (Multidisciplinary Digital Publishing Institute, 2021-03-31)
    Article
    Open Access
    In this paper, the results of the project INSESS-COVID19 are presented, as part of a special call owing to help in the COVID19 crisis in Catalonia. The technological infrastructure and methodology developed in this project ...
  • Distribution-based entropy weighting clustering of skewed and heavy tailed time series 

    Mattera, Raffaele; Giacalone, Massimiliano; Gibert, Karina (2021-05-28)
    Article
    Open Access
    The goal of clustering is to identify common structures in a data set by forming groups of homogeneous objects. The observed characteristics of many economic time series motivated the development of classes of distributions ...
  • A trainable monogenic ConvNet layer robust in front of large contrast changes in image classification 

    Moya Sánchez, Eduardo Ulises; Xambó Descamps, Sebastián; Sánchez-Pérez, Abraham; Salazar Colores, Sebastián; Cortés García, Claudio Ulises (Institute of Electrical and Electronics Engineers (IEEE), 2021-12-20)
    Article
    Open Access
    Convolutional Neural Networks (ConvNets) at present achieve remarkable performance in image classification tasks. However, current ConvNets cannot guarantee the capabilities of the mammalian visual systems such as invariance ...

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