Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : Democracy Challenged (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University College Dublin — Pays : Irlande — Rôle : PI
Acronyme de l'entité : UCD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

This project develops a new theoretical framework and causal mechanism to explain how corporate tax avoidance fuels the wealth inequalities that undermine democracy. It implements new methodological innovations that explain how global capital evades the fiscal constraints of democracy, using a combination of forensic accounting, in-person interviews, computational text analysis and original survey experiments. The objectives of the project are guided by two overarching research questions: Why is concentrated capital and wealth inequality a problem for democracy? What is the role of corporate tax avoidance and law in enabling this process? The empirical and comparative case study analysis are designed to answer these questions. First, we explain the global wealth chains and tax avoidance structures of big tech and big pharma multinational groups. Second, we explain how legal-technical actors create these structures and strategies. Third, we explain how their wealth protection strategies destabilise the functioning of democracy. Fourth, we explain the role of the media in politicising corporate tax avoidance as a problem for democracy.  The project has four work packages. First, we construct a new theoretical framework, typology and causal mechanism to explain how corporate tax avoidance leads to the wealth inequalities that undermines democracy. Second, we explain the tax avoiding wealth chains of big tech and big pharma using a combination of forensic accounting and statistical mapping techniques. Third, we explain how legal-technical actors create these structures using a combination of in-person interviews, list survey experiments and computational text analysis. Fourth, we implement a cross-national survey experiment to explain the role of the media in disrupting the political consensus of legal-technical experts. Finally, we develop a set of new normative principles to guide how governments can respond in a democracy-enhancing way.

Mots-clés : comparative political economy international political economy capitalism and democracy
Projet ERC : BMoral (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : University College Dublin — Pays : Irlande — Rôle : PI
Acronyme de l'entité : UCD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Women continue to be excluded and marginalized in histories of eighteenth-century British moral philosophy. BMoral addresses this by advancing a novel transdisciplinary methodology that brings together philosophical methods of close reading and interpretation with recent computational methods used by digital humanities researchers. Research on women philosophers has often focused on individual figures. BMoral’s new approach moves beyond the study of individual women philosophers and analyses intellectual networks with the goal of gaining a deeper understanding of how male and female philosophers interacted and influenced each other’s writings. Further, it offers unprecedented opportunities to analyse and assess the extent of women’s distinct contributions to moral philosophy and to recover neglected themes in the corpus of 18th-century moral writings.  The overall research question is: How can women and their philosophical contributions as well as unduly neglected male philosophers be better integrated into histories of 18th-century British moral philosophy? To address this question, BMoral pursues three objectives, which aim to analyse and assess (1) how male and female philosophers approach not only theoretical moral issues, which have been the main focus of recent scholarship, but also practical moral issues; (2) women’s unique contributions and their role in 18th-century intellectual networks; (3) what themes have been neglected or understudied. BMoral will deliver ground-breaking results by (i) conceptually shifting the focus of 18th-century British moral philosophy towards practical lived experience; (ii) recovering and reassessing 18th-century intellectual networks; (iii) analysing a large corpus. These results have the potential to achieve lasting breakthroughs, first, by changing the focus of the study of 18th-century British moral philosophy and, second, by advancing a novel transdisciplinary methodology that can help diversify philosophy.

Mots-clés : eighteenth century british moral philosophy,early modern women philosophers,recovering neglected philosophers
Projet ERC : BILQIS (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Université nationale d'Irlande à Galway — Pays : Irlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1994249.0 €

BILQIS emerges from a critical concern around Muslim women’s access to justice in Europe. BILQIS will be driven by methodological advances in Islamic feminism that the PI has been to the fore in delivering and will be primarily distinguished by its systematic and rigorous inquiries into questions of gender in relation to Islamic family laws (IFL) and IFL-related socio-religious and socio-legal power structures. The project will engage in a comparative study how Muslim women in Europe have navigated agency and authority over time from the long 19th century to the present day across diverse European peripheries, specifically the Ottoman Balkans, the post-Ottoman Balkans, and the territorial spaces that are currently governed by Bosnia and Herzegovina, Bulgaria, Greece, Ireland, Norway, and Sweden. BILQIS will interrogate how the gendered development of IFL in each of these peripheral contexts can be better understood in terms agency and authority through studies of legal texts and authorities (e.g., qadis, sijills, muftis, fatwas, istintâk, national court judgements) and will produce new critical, contextual, conceptual, and constructive knowledge in this regard. As a result BILQIS will break significant epistemic, conceptual and methodological impasses around shari’a, conflict of laws, and cultural pluralism in Europe. Finally, BILQIS will aim to use the sum of this new knowledge to construct a new methodological framework to transform the study of gender gaps and power imbalances related to agency and authority. This new methodology will direct the future of critical work on gender gaps across multiple disciplines (e.g., Islamic studies, Socio-legal Studies, Women’s and Gender Studies, European Studies, Near and Middle Eastern Studies, Cultural Studies, Political Philosophy, Government and Policy Studies).

Mots-clés : women s access to justice,islamic family laws,agency,authority,muftis,qadis,fatwas,ottoman archives
Projet ERC : DULCE (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : École normale supérieure PSL — Pays : France — Rôle : PI
Acronyme de l'entité : ENS PSL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1925875.0 €

Learning and adaptation play a central role in interacting with a changing environment, yet the neural substrate underlying such flexible, goal-directed behaviors has remained elusive. Neuroscience experiments have traditionally focused on how individual brain regions perform abstract, highly simplified tasks. However, recent technological advances, coupled with powerful AI-accelerated software, have rapidly enabled the monitoring of large populations of neurons over many days, across multiple brain regions, and during increasingly complex, naturalistic behaviors. Yet even with such data within our reach, we still lack the theoretical and quantitative tools that are necessary to understand the fundamental principles guiding learning in neural populations. DULCE aims to fill this gap by establishing a unified framework to understand learning in complex environments. The core hypothesis of DULCE is that in naturalistic conditions, learning engages multiple co-occurring learning processes that are distributed across the brain, and which work together to reshape neural dynamics to perform new tasks. As such, DULCE aims to uncover the behavioral, population- level, and synaptic learning rules responsible for guiding learning in complex environments. By interweaving statistical modelling, dynamical systems theory and machine learning, DULCE will: i) Develop hierarchical models of behavior that can disentangle the rules governing simultaneously occurring learning processes. ii) Provide a unified theory of how region-specific learning rules in the cortex, cerebellum, and striatum coordinate to form a distributed learning system. iii) Develop interpretable dimensionality reduction methods to identify the rules governing how task-relevant dynamics evolve in large-scale neural data over learning. Through this three-pronged attack, DULCE aims to lay the foundation necessary to uncover the neural mechanisms controlling the Dynamics Underlying Learning in Complex Environments.

Mots-clés : learning,naturalistic behavior,neural population data,cerebellum,motor cortex,basal ganglia,machine learning,recurrent neural networks,dimensionality reduction,motor control
Projet ERC : ModERN (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : École normale supérieure PSL — Pays : France — Rôle : PI
Acronyme de l'entité : ENS PSL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 745655.0 €

The Enlightenment has long been associated with the rise of modern Europe, and more generally with the concept of a typically European Modernity that took root in its wake. What it means to be ‘modern’ is indelibly bound up with our understanding of the Enlightenment’s core concepts: reason, religious toleration, civic virtue, political liberty, and scientific progress, to name but a few. For some, the Enlightenment is an essentially philosophical matter; for others it was and remains deeply political. Whatever the case may be, one thing is certain: for better or worse, it is widely accepted that the Enlightenment ushered in a new, modern era in both politics and philosophy, beginning in the 1790s and continuing today. The role of 18th-century ideas in this modernising process, and by proxy, the books that came to embody them, has long been the subject of intense scholarly debate, primarily concerned with the social and intellectual causes of the French Revolution. As a result, the field of Enlightenment studies today continues to privilege a relatively small canon of writers—primarily those that participated in the more ‘radical’ strains of Enlightenment thought in France. This is only one version, or vision, of the Enlightenment, however, albeit one that tends to dominate contemporary discourse. This project aims to fundamentally re-evaluate this interpretation of the Enlightenment and its actors by expanding the knowledge base on which these previous claims have been made; not only in terms of the diversity of authors and texts included, but also in the development of new digital techniques for identifying and analysing 18th-century information networks and their subsequent reception. In so doing, ModERN will move Enlightenment studies in a decidedly new direction; one that is both more comprehensive and more systematic in terms of its relationship to the existing digital cultural record, and one that likely challenges subsequent narratives of European Modernity.

Mots-clés : digital humanities,enlightenment studies,intellectual history,book history
Projet ERC : LUX-INVENTA (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Université Jagellonne — Pays : Pologne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1751250.0 €

Visible light provided by the Sun is the cleanest energy source one could ever imagine. Harvesting it is crucial for further development of science and technology as well as for reducing the ecological footprint of humanity. The efficient use of the visible spectrum of the Sun can take many forms and the direct photoexcitation of molecules resulting in a dramatic magnetization change - the so called photomagnetic effect - is one of them. In other words, sunlight photons could write, read and erase magnetic states of photomagnets. Photomagnets can be designed and prepared via a bottom-up modular approach using low-energy preparation methods developed by coordination, organometallic chemistry, supramolecular chemistry and crystal engineering with the support from physical and computational sciences. Photomagnets belong to the class of smart multifunctional molecular materials that become paramagnetic, ferromagnetic or simply change their magnetic properties upon illumination - a feature that is hardly accessible in conventional magnetic solids - metal alloys and oxides. Currently known photomagnets are merely laboratory curiosities due to extremely low operation temperatures below the boiling point of nitrogen (-196?C). Hence, the overarching goal of LUX-INVENTA is the discovery of room temperature (RT) photomagnets that would show light-induced ON/OFF ferromagnetic switching under normal conditions. This goal will be pursued alongside the deep understanding of the processes occurring during the absorption of a photon by photomagnetic chromophores - the molecular components responsible for the photomagnetic effect. The proposed research focuses on (i) the design and synthesis of novel photomagnetic chromophores, (ii) investigation of the mechanism of the photomagnetic switching and (iii) preparation of RT photomagnets by a rational incorporation of the photomagnetic chromophores in the structure of coordination polymers and metal-organic frameworks

Mots-clés : molecular magnetism,photomagnetism,photoswitching,light induced excited spin state trapping,light induced ferromagnetism,room temperature photomagnetism
Projet ERC : DEEPCONTROL (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : KTH Institut royal de technologie — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1876748.0 €

Over the past decades, aviation has become an essential component of today’s globalized world: before the current pandemic of coronavirus disease 2019 (COVID-19), over 100,000 flights took off everyday worldwide, and a number of studies indicate that after the pandemic its relevance in the transportation mix will be similar to that before COVID-19. Aviation alone is responsible for 12% of the carbon dioxide emissions from the whole transportation sector, and for 3% of the total CO2 emissions in the world. Due to the major environmental and economical impacts associated to aviation, there is a pressing need for improving the aerodynamic performance of airplane wings to reduce fuel consumption and emissions. This implies reducing the force parallel to the incoming flow, i.e. the drag, and one of the strategies to achieve such a reduction is to perform flow control. DEEPCONTROL aims at using high-fidelity simulations and deep reinforcement learning to develop a framework for real-time prediction and control of the flow around wing sections and three-dimensional wings based only on sparse measurements. We will first perform high-order spectral-element simulations of wing sections and three-dimensional wings at high Reynolds numbers. Using sparse measurements at the wall, we will reconstruct the velocity fluctuations above the wall within a region of interest. To this end, we will employ a generative adversarial network (GAN), together with a fully-convolutional network (FCN) and modal decomposition. Then, we will perform flow control based on deep reinforcement learning (DRL), which will enable discovering novel solutions in terms of flow actuation and design of winglet geometry. In order to assess the robustness of the framework for real-time applications, we will carry out detailed wind-tunnel experiments at KTH.  This framework will constitute a breakthrough in aviation sustainability, and will enable developing more efficient aeronautical solutions worldwide.

Mots-clés : computational fluid dynamics deep learning turbulence turbulent wings
Projet ERC : RHYTHM IN DEMENTIA (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 1610128.75 €

Circadian rhythm (CR) regulates body functions over the 24-hour day/night period; sleep/wake cycle is its most visible manifestation. CR disruptions have long been observed in patients with dementia and emerging evidence points to their presence in the preclinical period of dementia. This suggests that certain aspects of CR could be useful in identification of high-risk individuals and could serve as potential targets for interventions to delay dementia onset and progression. This requires an in-depth understanding of the role of CR in dementia pathogenesis. As population ageing increases dementia burden, it is critical to find strategies to identify patients at risk of dementia with precision, prevent, and slow its progression. Building on recent advances in accelerometery (to assess CR features comprehensively) and dementia biomarkers (deep-phenotyping of dementia pathogenesis), RHYTHM IN DEMENTIA will make a decisive step-change in knowledge by determining CR features involved in dementia processes along the course of the disease. The aims are: 1) identify core CR features that shape 10-year risk of dementia in a community-dwelling cohort of 4000 older adults; 2) uncover specific CR disruptions that characterise major dementia subtypes and stages of Alzheimer’s disease (determined by biomarkers) in a new cohort of 1500 patients recruited from two memory clinics in Paris; and 3) ascertain how CR affects dementia prognosis in the patient cohort by examining cognitive and functional decline, hospitalisation, institutionalisation, and mortality. This project will yield new insight into the nature of the association between CR and dementia progression. These findings will ultimately inform the potential for a cost-effective and easy to use tool to assess CR features to facilitate both identification of patients at risk of dementia and tailored secondary prevention interventions that address CR disruptions in dementia patients and slow progression of dementia.

Mots-clés : circadian rhythm,dementia,alzheimer s disease,accelerometer
Projet ERC : AIMIX (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Aga Khan University Nairobi — Pays : Kenya — Rôle : Partner
Acronyme de l'entité : AKU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 573245.0 €

Artificial intelligence (AI) is widely regarded as one of the most promising and disruptive technologies for future healthcare. As AI algorithms such as deep neural networks are suited for the processing of large and complex datasets, radiology is the medical speciality that has seen some of the most important applications of AI in the recent years. However, despite these advances, a major limitation of current AI developments in medical imaging is that they have overwhelmingly, and almost entirely, targeted applications in high-income countries. There is a concern, if the current trend continues, that AI will increase the already pronounced inequalities in global health, in particular for resource-limited settings such as rural Africa, where the majority of the African population lives.  AIMIX will develop the first scientific framework for inclusive imaging AI in resource-limited settings. The project will greatly advance the current state-of-the-art, from existing AI methods mostly developed for high-income settings, towards new imaging AI algorithms that are fundamentally inclusive, i.e. (1) affordable for resource-limited clinical centres, (2) scalable to under-represented population groups, and (3) accessible to minimally trained clinical workers. Furthermore, AIMIX will investigate the socio-ethical principles and requirements that govern inclusive AI, and examine how they compare, conflict or complement those of trustworthy AI developed thus far in high-income settings. These innovations will be demonstrated for affordable and accessible AI-powered obstetric ultrasound screening by minimally trained clinicians such as midwives in rural Africa.  Ultimately, AIMIX’s scientific breakthroughs will enhance the democratisation of imaging AI in resource-limited settings, which will result in an important social impact, by empowering local communities, promoting inclusion, and reducing disparities between populations from low- and high-income societies.

Mots-clés : inclusive artificial intelligence,affordable medical imaging,low and middle income countries,obstetric ultrasound screening