Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : RADHEART (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Studies of Cultures and Arts
Entité participante : Université de Bergen — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1995676.0 €

More than two decades of intense radical religion research since 9/11 has brought attention to radicalisation, violence, and radical beliefs, and a strong emphasis on Islam in the contemporary era. Yet, radical religion is as burning an issue for societies today as ever, and individuals persist in staying committed. Strong, individual commitment shapes any form of radical religion, but it is rarely studied empirically, let alone historically. RADHEART ambitiously proposes to analyse how strong individual commitment is expressed and cultivated in ancient forms of Judaism and Christianity. Strong, religious commitment is approached as radical habits of the heart, i.e. emic models of the self’s felt experience of strong commitment. With an innovative theoretical framework that combines the aesthetics of religion and experience-oriented anthropology, RADHEART focuses on how an emotionally intense, strong religious commitment is expressed in and cultivated by ancient media. RADHEART offers high-gain insights by 1) comparing radical habits of the heart across the two ancient religions that were most seminal for later formations, 2) reframing the study of radical ancient religion by tackling the pervasive vocabulary of interior organs and the body in ancient poetry and narratives about strong commitment, and 3) instead of focusing on beliefs, terms, and conceptual reflections, RADHEART scrutinises the roles of the embodied self and emotionality in radical religion. Research has focused on the collective character of ancient religions, disregarding the crucial role of individual strong commitment and it has seen ancient emotions as lacking in affectivity. RADHEART breaks with these trends and enquires into strong, individual religious commitment in two media forms: poetry and narrative. RADHEART asks how they express and model strong commitment and how they affect their audiences across the axes of textuality, mediality, and practice.

Mots-clés : ancient jewish and christian religious poetry and narrative,radical religion,individual commitment,emotions,embodiment,the self
Projet ERC : DecipherAD (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université de Bergen — Pays : Norvège — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 451200.0 €

Worldwide, 50 million people suffer from dementia, which is caused by Alzheimer’s disease (AD) in 70% of the cases. There is no treatment to stop, reverse or prevent AD. AD is pathologically defined by amyloid plaques and tau tangles in the brain, implying that it is a single disease entity. Still, patients vary greatly in rate of decline and underlying pathophysiology, which hampers the search for cures. I have discovered and replicated 5 AD subtypes in patients based on cerebrospinal fluid proteomics (CSF). Subtypes had distinct pathophysiology, including differences in amyloid metabolism and clearance, as well as in cognitive decline. This indicates that they would need tailored treatments.  The goal of this project is to understand AD subtype specific mechanisms, and how these are related to cognitive decline, taking CSF proteomics as a starting point. I will address the following scientific needs: 1. Understand which AD subtype molecular processes change over time, and how those changes relate to cognitive decline. This requires large datasets of individuals with repeated CSF proteomics. I have access to two large, deeply phenotyped cohorts with already collected repeated CSF samples over 5 years from 700 individuals, in which I will measure proteomics. 2. Study drivers of AD subtypes with genetics and in a subset of n=50 with tissue proteomics. 3. Develop markers in blood for subtype detection, which would remove barriers for clinical use. 4. Test if AD subtypes differently respond to amyloid modifying drugs, which is the strongest proof that AD subtypes need tailored therapy.  If successful, DecipherAD will provide proof of concept that AD subtypes have use as a theragnostic tool, show which genetic factors drive molecular subtypes, how molecular signatures change over time and how these changes relate to cognitive decline, with tools in blood to facilitate implementation in clinical practice. This will catalyse AD subtype tailored treatment development.

Mots-clés : alzheimer s disease,heterogeneity,cerebrospinal fluid proteomics,disease mechanisms
Projet ERC : HELIO4CAST (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : GeoSphere Austria — Pays : Autriche — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1999417.5 €

A major unsolved problem in space weather involves predicting the solar wind at the Sun-Earth L1 point, specifically its speed and the north-south (Bz) magnetic field component. Knowledge of the future solar wind time evolution would allow us to drive any models for magnetospheric processes, such as the aurora, the radiation belts, the ionosphere or the currents induced in power lines with much higher reliability and forecast lead time than currently possible. Our modern society increasingly depends on space borne technology and predicting extreme space weather conditions at Earth is therefore of pivotal importance. Our hypothesis is that we can predict the strongest Bz fields in magnetic flux ropes in solar coronal mass ejection (CMEs) with a novel combination of hyper-fast semi-empirical models in our new HELIO4CAST simulation, capable of running millions of ensemble members within minutes. Due to the coherence of flux ropes, it will be possible to forecast geomagnetic storms with lead times of 12 hours or more. Additionally, for clarifying unsolved problems on the CME global shape and magnetic structure, a window of opportunity has opened at the start of solar cycle 25 with the successful launches and operations of Solar Orbiter, Parker Solar Probe, and BepiColombo, forming an unprecedented fleet of spacecraft to study CMEs. Groundbreaking numbers of multipoint lineup events, Solar Orbiter imaging for the first time from higher latitudes, and novel in situ data from Parker Solar Probe close to the Sun will lead to new discoveries. These unique observations in the solar wind will also deepen our knowledge of stellar CMEs. The team is lead by an accomplished PI with the necessary broad scientific expertise. This ERC project provides an unconventional, direct feedback loop between answering open scientific questions and the application of forecasts in real time that will bring decisive progress in making a reliable space weather prediction part of our daily lives.

Mots-clés : heliophysics,space weather,solar wind,solar storms,solar coronal mass ejections,interplanetary magnetic fields,solar physics,solar wind prediction
Projet ERC : ZincMRI (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999549.0 €

To reveal the multiple aspects (molecular, cellular and anatomical) of a studied biological process (in health or disease), it is necessary to have the ability to spatially map the multiplexity and dynamicity of intra- and inter-cellular events in the context of a whole organism. We here propose a conceptually novel approach to spatially map the multicomponent information of a studied biological phenomenon, from the deep tissue of a studied subject using a single imaging setup. In realizing the importance and diverse roles of labile Zn2+ in specific tissues, we aim to develop ZincMRI. ZincMRI is a molecular imaging toolbox designed to provide orthogonal MRI readouts, with which we aim to monitor the multiple facets of Zn2+ biology through: (i) quantitatively mapping dynamic changes in intra- and extra-cellular levels of Zn2+; (ii) spatially monitoring Zn2+-induced gene expression, and (iii) providing complementary high-resolution anatomical views of the studied subject. To establish ZincMRI, we will design, develop, and implement: (i) fluorinated synthetic compounds as MRI responsive agents for quantitatively mapping changes in labile Zn2+ levels using 19F-MRI (Aim 1); and (ii) conditional MRI reporter genes for mapping Zn2+-induced transcription with 1H-CEST MRI (Aim 2). Capitalizing on the orthogonality of the signals obtained with 19F-MRI and 1H-CEST MRI, ZincMRI will be applied to map, in vivo, from the hippocampus region of the brain, both the dynamic changes in Zn2+ levels and the transcription of Zn2+ regulatory elements in response to physiological and pathological stimuli (Aim 3). We envision that ZincMRI, which unconventionally aims to study two aspects of Zn2+ biology using a single imaging modality, and is also applicable for the study of deep tissues, may affect not only the way we study this ion, but could also be further extended to study other metal ions with biological relevance by capitalizing on the scientific paradigm proposed here.

Mots-clés : mri reporter genes,mri responsive agents,19f mri,molecular and cellular mri,zinc mri
Projet ERC : ORIGINEURO (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université de Bergen — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

The evolutionary origin of first neurons was key for animals as it allowed them to rapidly detect environmental cues and to coordinate responses to threats or opportunities. The evolutionary origin of neurons however remains a highly debated and largely enigmatic subject since there is no broad agreement on the relationships at the base of the animal tree and not all non-bilaterian animals have neurons. Strikingly, early branching animals, as well as their closest unicellular relatives already contain many components of the molecular toolkits for neuronal functions. ORIGINEURO addresses fundamental questions regarding the evolutionary origin of synapses and neurons from molecular to cellular scales. My recent studies on choanoflagellates, the closest living relatives of all animals, and ctenophores (comb jellies), strong candidates for one of the first animal lineages, are providing exciting, new and surprising clues into the ancestry of synaptic proteins including the discovery of a neurosecretory apparatus in choanoflagellates and a unique nervous system in ctenophores. The proposed 5-year programme brings together correlative volume electron microscopy, super-resolution imaging, quantitative live cell imaging, state-of-the-art molecular biology and single cell RNA sequencing focusing on a ctenophore as model organism. Objective 1 will provide a detailed understanding of the ultrastructure and connectivity of ctenophore neurons forming the subepithelial nerve net. Objective 2 will shed light on the so far elusive ctenophore neuron development. By functionally characterizing ctenophore neurons (Objective 3) I will understand how they work and what they do. ORIGINEURO fills a research gap and will provide insights into how many ways to build a neural network. Thus, ORIGINEURO aims at challenging the paradigm of network activity emerging through cellular diversification and synaptic connections.

Mots-clés : ctenophore,synapse,neuron,evolution,neuropeptides
Projet ERC : DATA-DRIVEN OFFSHORE (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Bergen — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

A massive upscaling of offshore wind turbines is necessary to reach the goals of the European Green Deal. However, current methodologies for analysis and design are at their limits. One of the major bottlenecks is that it is so far not possible to directly integrate experimental data into aerohydroelastic simulations of offshore wind turbines. By and large, including these data into the aerohydroelastic analysis is indirectly accomplished through the offline adjustment of those parameters that define instances of existing models. Although such a practice can reasonably improve the short-time predictive capability, the underlying models remain unmodified. Thus, further physics available in the data remains inaccessible. In the numerical simulation context, this represents a main challenge to taking advantage of the experimental data in their entirety. In this context, DATA-DRIVEN OFFSHORE proposes to simultaneously integrate these highly-valuable data into aerohydroelastic simulations through data-driven computational mechanics. Such an approach is one of the most advanced computing frameworks, and relies on the reformulation of classical boundary and initial value problems in solid and fluid mechanics such that constitutive models, boundary conditions and/or applied loads are directly replaced by some form of experimental data. DATA-DRIVEN OFFSHORE will thus enable for the first-time investigation of the aerohydroelastic behavior of an offshore wind turbine relying truly on experimental data, capturing the hidden features that these contain. This will greatly improve the predictive capabilities with respect to existing models, allow the conception of less-conservative designs, and enable upscaling beyond 20 MW of rated power, increasing the efficiency while reducing the cost per unit of power produced. Thus, it will contribute to triggering a change of paradigm for future generations of offshore wind turbines.

Mots-clés : offshore wind turbines aerohydroelastic analysis data driven computational mechanics theoretical foundations computational procedures interaction among data,solids and fluids
Projet ERC : SEISPY (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2228750.0 €

More efficient rechargeable batteries must be developed for utilizing sustainable energy sources and stopping the rapidly advancing climate change. The current technology cannot be merely extended for the next-generation storage systems. New approaches are required, especially for understanding and controlling the complex chemistry at the electrode-electrolyte interface. It has already been established that such control can, in principle, be realized by the solid electrolyte interphase (SEI), a stable passivating layer formed on the electrode. Such a layer should enable continuous transport of ions across it, but the fundamental understanding of what SEI components and architectures may give rise to such transport is not yet available. The ultimate goal of this ERC project is to establish structure-function correlation for the SEI by implementing methodologies for directly probing interfaces at the atomic-molecular level and for guiding the design of novel interphases. We will achieve this goal by introducing to materials science a set of NMR 'tools' based on chemical exchange saturation transfer (CEST), commonly used to study dynamics in biomolecular-NMR. Here we propose to develop variants of CEST to probe ion dynamics across the SEI. Implementing these new approaches in situ, we will disentangle the multistep transport process at the electrolyte-SEI-electrode interfaces. Coupled with sensitivity enhancement by Dynamic Nuclear Polarization from inherent polarization sources, we will identify the SEI components participating in the ion exchange processes. Integrating our results with the battery performance, we will determine the pathways and bottlenecks for transport across the SEI. Applying advanced NMR methods combined with controlled surface chemistry to state-of-the-art battery materials, such as lithium and beyond metal anodes, high-energy cathodes and composite electrolytes, we will establish design rules for next-generation energy storage systems.

Mots-clés : rechargeable batteries,solid electrolyte interphase,ion transport,solid state nmr spectroscopy,dynamic nuclear polarization,metal anodes,high energy cathodes,solid electrolytes
Projet ERC : C-NORA (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Université technique de Crète — Pays : Grèce — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Although "transport" may imply different notions for different scientific fields, the feature of incorporation of interacting system components through which "information'' is propagated remains invariant. Biological transport systems is an example whose significance has become evident with the recent outbreak of COVID-19 spreading. Blood transport in cardiovascular systems falls also under this category. The urgent need of design of efficient/safe, epidemics spreading suppression and congested blood transport monitoring, strategies is apparent, considering the potential, significant socioeconomic impact. However, the continuum, spatiotemporally-varying nature of such interconnected systems, in addition to dynamic complexity and limited available control authority, hamper development of systematic feedback control design and analysis methodologies. C-NORA aims at introduction of a pioneering holistic framework for systematic, computationally tractable control design and analysis of large-scale, interacting, distributed parameter transport systems, which i) harmonizes control at micro-macro levels, ii) accounts in design for all essential dynamic phenomena, iii) compensates adverse effects of limited control authority in design, and iv) develops ad hoc tools for system-specific analysis. C-NORA new control design and analysis tools will be demonstrated in distributed parameter, epidemiological/cardiovascular transport systems and will be validated in numerical simulation. C-NORA high risk lies in unification and complexity of heterogenous, unexplored infinite-dimensional systems, whose treatment requires rethinking of fundamental control-theoretic tools. C-NORA high scientific gain lies in that, on the way of executing its key ideas, novel, interdisciplinary concepts and groundbreaking control/analysis methodologies will be introduced, while unprecedented research arenas will open for systems and control, transport, mathematicians, and systems biologists.

Mots-clés : control of delay systems control of partial differential equation pde systems
Projet ERC : CC4DYN (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed Matter Physics
Entité participante : Université technique de Vienne — Pays : Autriche — Rôle : PI
Acronyme de l'entité : TU Wien
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999288.0 €

Computational materials science, using ab initio simulations and high-performance computing, is expected to play a key role in realizing the vision of ‘materials by design’. However, the goal to discover game-changing materials with scientific and industrial relevance requires highly accurate ab initio methods for excited state as well as ground state properties of atoms, molecules and solids. So far, due to the computational complexities involved, methods with systematically improvable accuracy for condensed matter systems, such as coupled-cluster theories, are mostly limited to the study of ground state properties in the clamped-nuclei approximation. This ambitious proposal aims at inducing a computational paradigm shift in the study of vibrational and optical properties of real materials by implementing a multitude of novel methods. On the one hand, we propose to reduce the computational cost of time-dependent equation-of-motion coupled-cluster theory by several orders of magnitude compared to existing approaches. On the other hand, coupled-cluster atomic forces will be implemented for machine-learning force fields in the Gaussian approximation potentials framework. Together, the proposed methods have the potential to achieve an unprecedented level of accuracy and system size for the prediction of a wide range of material properties including optical spectra and phonon frequencies. We seek to employ the newly developed approaches to resolve a number of long-standing discrepancies between theoretical predictions and experimental findings for dynamic properties of defects, molecular crystals and layered materials. These carefully selected systems highlight key problems of currently available ab initio methods and novel approaches that go beyond the state of the art will have an enormous impact in all areas of physics, chemistry and computational materials science.

Mots-clés : first principles simulation,many electron theories,ab initio,quantum chemistry,coupled cluster theory
Projet ERC : Cocoquest (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Université technique de Vienne — Pays : Autriche — Rôle : PI
Acronyme de l'entité : TU Wien
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1865833.75 €

Developing a comprehensive theory of thermodynamics at the quantum scale requires a fundamental change of perspective with regards to its classical counterpart. On the one hand, measuring a quantum system will induce a non-negligible back-action and an energy cost that is at least comparable to the energy scale of the system. On the other hand, controlling microscopic degrees of freedom and harnessing quantum effects provides novel opportunities with no classical counterpart. In light of these facts, control over different quantum features and quantum measurements themselves become valuable resources that need to be integrated into any self-contained theory of quantum thermodynamics. In this project, we aim to address this grand challenge. First we will develop a formal theory that includes control over quantum systems with fixed complexity to incorporate these concepts into thermodynamic considerations at the quantum scale. Second, we will unveil the fundamental thermodynamic limitations on information acquisition by constructing a thermodynamically self-contained description of the quantum measurement process. Finally, we will carefully study current quantum technologies and, with the help of our own lab and experimental colleagues, we will devise experimental proposals and perform proof-of-principle experiments based on existing quantum technologies, to make sure that the theoretical considerations describe relevant features.