Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Digital Time Use, Adolescent Well-Being and Social Inequalities (DIGINEQ)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Soci al World and Its Interactions
Panel description: Sociology, social psychology, education  sciences , communication  studies
Countries involved: Spain
Call: ERC CONSOLIDATOR GRANTS (ERC-2022-COG, 2022)
Start date: 2024-10-01
End date: 2029-09-30
Duration (months): 60.0
Total project cost (EUR): 1999589.0
EU funding (EUR): 1999589.0
Participants: 3
Project status: SIGNED

In our highly unequal and digitalised world, understanding how adolescents’ digital lives intersect with social inequalities is critical. Research has consistently shown that adolescents from privileged socioeconomic backgrounds are advantaged in their academic, health and socioemotional outcomes. However, how adolescents’ digital engagement relates to social inequalities in well-being is poorly understood. DIGINEQ significantly contributes to close this major scientific gap. The project applies an innovative 24-hour time-use approach that brings a complex understanding of how exactly adolescents’ digital time use shapes social inequalities in well-being in daily life. DIGINEQ has three main objectives: 1. To understand how changes in digital engagement from childhood to late adolescence explain socioeconomic disparities in well-being outcomes. 2. To disentangle how exactly adolescents’ digital time use forms social inequalities in their well-being in everyday life. 3. To establish if digital interventions can promote adolescents’ healthy digital engagement and improve well-being outcomes, while reducing socioeconomic gaps in these areas. By adopting a novel approach that combines multiple disciplines and methodologies, this project brings three major scientific innovations: (1) it creates an innovative method based on mobile-app data to accurately track adolescents’ exact digital time use and measure socioeconomic gaps in well-being in real time; (2) it implements a novel mixed-method digital intervention to show if digital self-efficacy programmes can promote adolescents’ healthy digital engagement and improve well-being outcomes, while reducing related socioeconomic gaps; (3) it merges existing high-quality longitudinal time-diary data from three largescale surveys in Australia, Ireland, and the United States to illustrate how adolescents’ digital time use explains socioeconomic gaps in well-being from childhood to late adolescence.

Keywords: time use social inequalities adolescent well being screen time quantitative sociology
Advanced Design of Heat Exchangers using multiscale models and machine learning (ADeHEx)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Denmark,United States
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2023-10-01
End date: 2025-09-30
Duration (months): 24.0
Total project cost (EUR): 230774.4
EU funding (EUR): 230774.4
Participants: 2
Project status: SIGNED

Heat exchangers (HXs) are at the heart of many energy systems, one example being engine cooling in the aviation industry. Advanced design of HXs is urgent since aircraft systems are becoming smaller and need to become more efficient. Through topology optimisation (TO) and additive manufacturing (AM), custom compact HXs will be designed to cool the engines of tomorrow. Although TO of thermofluidic problems has recently undergone tremendous development, the technology is mostly limited to academic problems, since existing approaches are restricted to macroscopic design with extreme computational cost being prohibitive for industrial applications. The objective of ADeHEx is therefore to propose an integrated design methodology for multi-scale 3D fluid-to-fluid HXs using machine learning-based de-homogenization. Specifically, I will a) construct a homogenized thermohydraulic computational model; b) use convolutional neural networks to recover detailed micro-channel design from homogenization-based TO, reducing computational time by at least two orders of magnitude. Implemented at University of Southern Denmark and at the secondment, Brown University, a two-way transfer of knowledge is guaranteed through my expertise in level-set-based TO and the expertise of the supervisors in complex multiphysics modelling and physics-based machine learning. ADeHEx will a) consolidate my academic excellence and professional maturity through new skills and competences in machine learning, homogenized thermohydraulic models, teaching, supervision, project management, dissemination, industrial engagement, networking; b) harness the complementary expertise of two strong multidisciplinary teams, pushing research to the forefront of design engineering and computer science and informatics; c) revolutionize the design process of HXs and multiphysics system optimisation, while benefiting EU companies in manufacturing, aviation, etc., and raising European economic competitiveness.

Keywords: simulation based design optimisation,computational engineering and scientific computing,computational fluid dynamics,energy systems and heat exchangers,machine learning
Transition from Transport Reindeer Herding to Reindeer Pastoralism: A study of Indigenous Governance during Change (TransRein)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Study of the Human Past
Panel description: Archaeology and history
Countries involved: Sweden
Call: ERC CONSOLIDATOR GRANTS (ERC-2023-COG, 2023)
Start date: 2025-01-01
End date: 2029-12-31
Duration (months): 60.0
Total project cost (EUR): 1989816.0
EU funding (EUR): 1989816.0
Participants: 1
Project status: SIGNED

Aboriginal societies around the world have independently transitioned their production mode. In northern Eurasia, the transition manifested itself in a movement away from transport reindeer herding towards reindeer pastoralism from the sixteenth to nineteenth centuries. Although this was one of the most significant changes affecting circumpolar people across the region, much remains unknown about the drivers of this transition, and even less about its consequences for indigenous governance and social relations. Northern Fennoscandia was one of the first regions to witness the transition, and the indigenous Sami of northern Sweden are an especially suitable case for addressing these gaps. The historical sources are exceptionally rich and Sami are a very interesting case because reindeer pastoralism developed in a foraging culture, with many households continuing as hunters and fishers even after the transition dominated society. A central assumption is that the transition to reindeer pastoralism was induced by market opportunities. TransRein builds on the hypothesis that the transition of these societies was driven by concomitant, self-governed responses as the transition progressed and will advance research about indigenous reindeer-herding societies beyond the state of the art by pursuing the following three objectives. 1. Create a detailed depiction of the transition from transport reindeer herding to reindeer pastoralism among indigenous Sami, focusing on governance of natural resources and—for the first time—its effect on social relations, and significantly deepen our understanding of indigenous governance, 1550–1800. 2. Identify common forces behind the transition through comparisons with other reindeer-herding societies in Eurasia that underwent the same transition. 3. Place the transition in two wider contexts; the transitions from foraging economies to pastoralism in other societies, and the transition in a European context of early modern agrarian change.

Keywords: sami,pastoralism,reindeer,aboriginal,indigenous,common pool resources,social ecological systems,agricultural history,eurasia,foraging,early modern,fennoscandia
Tailored immune receptor engineering for resistance against rice blast disease (Tailored Immunity)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: France
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-06-02
End date: 2027-06-01
Duration (months): 24.0
Total project cost (EUR): 242260.56
EU funding (EUR): 242260.56
Participants: 1
Project status: SIGNED

Fungal pathogens are a major constraint to crop production worldwide. As part of their virulence strategy, pathogens secrete effector proteins to manipulate host machinery and promote colonization. Effectors can be recognized by host immune receptors that launch a robust immune response that restricts pathogen spread. Pathogens quickly overcome immune receptor-mediated resistance by modifying or losing effectors to evade detection. In the Tailored Immunity project, our aim is to massively expand the effector recognition specificity of immune receptors to provide durable disease resistance against the fungus Magnaportha oryzae, the causal agent of blast disease, and one of the most destructive diseases of rice. In order to do this, we will use a host-target guided engineering approach to replace the heavy-metal associated (HMA) effector binding domain of nucleotide-binding and leucine-rich repeat domain (NLR) immune receptors from rice with the HMA domain of host proteins that are targeted by multiple M. oryzae effectors. We hypothesize that introducing the HMA domain of the newly identified effector hubs to NLRs will allow the simultaneous recognition of numerous effectors. As the pathogen would need to undergo complex mutation pathways to escape this detection, and since changing multiple effectors is presumably associated with high fitness costs, we expect that this new strategy will generate resistance that the pathogen has difficulties to overcome and that is therefore highly durable. By these means, this ambitious project promises to provide a proof-of-concept for a new knowledge-guided and powerful approach for the creation of durable immune receptors that will be highly valuable for the improvement of a large range of crop species. In addition to boosting host immunity, the Tailored Immunity project will provide invaluable information about how immune receptors can be engineered for tailored disease resistance in crops.

Keywords: plant immune receptors,plant resistance,effector target,hub,molecular engineering,plant disease,crop biotechnology
Extremal Combinatorics and Circuit Complexity (EXCICO)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Czechia,United States
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2024-01-02
End date: 2026-01-01
Duration (months): 24.0
Total project cost (EUR): 180421.44
EU funding (EUR): 180421.44
Participants: 2
Project status: CLOSED

Computational complexity theory is the systematic study of computational problems in order to classify them in terms of their inherent logical hardness. Several decades of research have not only given rise to important understanding of limits of computation, but have also developed algorithms which constitute a crucial part of modern life. A formidable challenge in complexity theory is to show non-linear lower bounds for an explicit Boolean function. Our project is motivated by this fundamental problem and in fact we will approach several such questions motivated by understanding the complexity of explicit Boolean functions. Our main objective look at circuit complexity through the lens of extremal combinatorics, a rich and vibrant of branch of combinatorics which studies objects satisfying various constraints. Therefore we aim to develop a systematic methodology which adopts tools of extremal combinatorics to tackle complexity problems. More concretely we attack the problem of lower bounds for depth-3 circuits and specifically attempt to prove sharp lower bounds for the Majority function thus breaking a barrier in this area. We will further extend the techniques used in recent breakthrough on the Sunflower Conjecture and apply it to CNF formula and the structure of their satisfying assignments. We will our new insights on the structure of satisfying assignments to develop new improved algorithms for the satisfiability problem (SAT).

Keywords: circuit complexity,lower bounds,extremal combinatorics,satisfiability
GEODE: GEographical Object Detection, Explained (GEODE)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Spain
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2026-09-01
End date: 2028-08-31
Duration (months): 24.0
Total project cost (EUR): 209914.56
EU funding (EUR): 209914.56
Participants: 1
Project status: SIGNED

The GEODE project brings explainability to deep learning for Earth observation. GEODE aims at improving the transparency of computer vision models used for analyzing satellite imagery in large-scale mapping projects. As AI models are increasingly used in applications such as environmental monitoring and land-use classification, their opaque decision-making processes limit trust and usability. Using novel XAI (eXplainable AI) techniques, GEODE will offer pixel-level explanations to understand why a given model fails or succeeds on certain objects. Performance maps will indicate where the model is expected to have standard performance. Finally, an active learning strategy will be developed, to define how to conduct labeling work for global mapping. Answering the why, where and how deep mapping models work, GEODE is a bold step towards unlocking the full potential of AI paired with large volumes of satellite imagery. The project will take place at the Image & Signal Processing Laboratory at Universitat de València in Professor Gustau Camps-Valls' group, a world-renowned leader in machine learning for Earth observation.

Keywords: computer vision,explainable ai,earth observation,large scale mapping,
Optimizing Passenger Experience in Public Transport (OptiPEx)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Mobility
Destination: Safe, Resilient Transport and Smart Mobility services for passengers and goods
Action type: Research and Innovation actions
Partnership: CCAM (co-programmed)
Countries involved: Finland,Germany,Poland,Austria,Spain,Ireland,Czechia
Call: User-centric development of vehicle technologies and solutions to optimise the on-board experience and ensure inclusiveness (CCAM Partnership) (HORIZON-CL5-2023-D6-01, 2023)
Start date: 2024-05-01
End date: 2027-10-31
Duration (months): 42.0
Total project cost (EUR): 4083230.25
EU funding (EUR): 4083230.25
Participants: 14
Project status: SIGNED

The current global climate crisis and ongoing shift towards autonomous transport necessitate sustainable and passenger-centric public transport solutions. The goal of OptiPEx is to enhance of sense of comfort and safety of the passengers as well as the security and ease of travelling by co-creating ethical and passenger-aware public transport services together with specific target user groups, such as wheelchair users, passengers with large objects, fragile passengers with limited mobility, tourists and students. To achieve this, OptiPex is built on three fundamental development pillars: measurement, analytics and interaction. OptiPEx partners will develop perception technologies to measure passenger behaviour and situations. Trustworthy analytics is essential in recognising real-time passenger experiences and situations, enabling interaction with services and vehicles. Moreover, OptiPEx partners will develop adaptive and interactive vehicle technologies and digital services in collaboration with target groups and suitable for various public transport modes. These services will optimise the onboard experience, promoting safety, inclusiveness and trust. Ultimately improved passenger satisfaction will drive the adoption of automated public transport technologies and improve the sustainability of mobility services via contribution to the modal shift. A consortium consisting of 3 research organisations, 6 industry members and 2 SMEs will validate the developed solutions together with target groups and other stakeholders in three living labs. The consortium has leading expertise in human behaviour, user-centric design, vehicle technologies, modelling and data analysis, and adaptive and interactive services. The successful adoption of OptiPEx results will be facilitated by efficient dissemination, communication, and exploitation activities in collaboration with the Connected, Cooperative and Automated Mobility (CCAM) partnership.

Keywords: public transport,co creation,perception technologies,data analytics,service development,validation
City based interventions to stimulate active movement for health (CITY-MOVE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Tackling diseases and reducing disease burden
Action type: Research and Innovation actions
Countries involved: Belgium,Netherlands,Slovenia,Peru,Colombia,Uganda,United Kingdom
Call: Interventions in city environments to reduce risk of non-communicable disease (Global Alliance for Chronic Diseases - GACD) (HORIZON-HLTH-2023-DISEASE-03, 2023)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 3667023.75
EU funding (EUR): 3667023.75
Participants: 10
Project status: SIGNED

CITY-MOVE adapts and implements the WHO Global Action Plan on Physical Activity (GAPPA) in six cities across three continents and develops a cross-contextual evaluation framework for transferability and scalability. Physical activity is a key behavior to reduce the NCD burden, including protecting against cancers and type 2 diabetes. There are many evidence-based interventions for cities to promote physical activity, yet they remain under-implemented, with a whole-of-system approach particularly lacking, and often fail to target the least active or vulnerable groups. Knowledge gaps are: a) how to adapt, b) successfully implement, and c) evaluate interventions, and d) how to transfer lessons to other interventions, target groups and contexts. In partnership with the cities, we identified interventions targeting individuals across the life course, particularly vulnerable and least active groups, aligned with the GAPPA domains of active people, societies, environments and systems. CITY-MOVE will: 1) Develop a city-GAPPA Theory of Change and operationalise assessment measures; 2) Adapt city-GAPPA to six cities, engaging stakeholders in each context; 3) Support cities in successful implementation through action research in living labs; 4) Assess reach, adoption, feasibility, fidelity, and sustainability of selected interventions in each city; 5) Improve the development and utilisation of routinely collected data to support successful implementation; 6) Generate cross-contextual evidence on implementation, evaluation and scalability through multi-criteria decision assessment for 12 interventions in six cities; and 7) Generate global capacity through regional Communities of Practice. CITY-MOVE results lead to increased physical activity by target populations, contributing to reduced premature NCD mortality, and to adaptable solutions ready for take-up by implementers.

Keywords: non communicable diseases latin america sub saharan africa europe living labs multi criteria decision assessment implementation evaluation
The role of an Epstein-Barr virus infection in the pathogenesis of multiple sclerosis (BEHIND-MS)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Tackling diseases and reducing disease burden
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Netherlands,Belgium,Switzerland,Spain,Cyprus
Call: Relationship between infections and non-communicable diseases (HORIZON-HLTH-2023-DISEASE-03, 2023)
Start date: 2023-12-01
End date: 2028-11-30
Duration (months): 60.0
Total project cost (EUR): 7550708.75
EU funding (EUR): 7550708.75
Participants: 13
Project status: SIGNED

Multiple Sclerosis (MS) is the most frequent neuroinflammatory disease. Despite new treatments that slow the progression of the disease, patients with MS (PwMS) frequently evolve towards major disability. The pathogenesis of MS is controversially debated, but the recent discovery that infection with the Epstein-Barr virus (EBV) is a major risk factor will radically change research avenues. The BEHIND-MS consortium ambitions to understand how EBV promotes MS development. To this end, we have established a multidisciplinary team that will for the first time draw a comprehensive map of the interactions between the virus and all arms of the immune system in the blood and brain of PwMS and how they ultimately lead to neural damage, in the context of genetic risk factors. We will also develop an in vitro model of MS that integrates the virus, the immune system and brain cells reprogrammed from the blood of the same PwMS. Thus, for the first time, we will study in the laboratory the complex molecular mechanisms that give rise to MS. Finally, we will develop an animal model of prodromal MS that would be a ‘game changer’ for our understanding of MS pathogenesis and allow testing of promising new treatments. The pivotal knowledge developed in this project will empower the entire healthcare value chain to work towards better clinical management of MS. A detailed understanding of EBV-MS interactions, combined with newly identified biomarkers, and study models will open the doors for researchers, clinicians and industry to capitalize on the mechanisms underlying EBV-MS interactions, and develop new diagnostic, preventive and therapeutic tools and guidelines. Throughout the project, an open dialogue with the main stakeholder representatives will ensure a mutual understanding of patient needs and project results. Ultimately, by contributing to improved risk analysis, stratification and treatment strategies, BEHIND-MS has the potential to reduce the burden of MS on society.

Keywords: epstein barr virus,multiple sclerosis,immune response