Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PURPOSE (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Carlos III University of Madrid — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1497506.87 €

Dynamic fragmentation of metals is typically addressed within a statistical framework in which material and geometric flaws limit the energy absorption capacity of protective structures. This project is devised to challenge this idea and establish a new framework which incorporates a deterministic component within the fragmentation mechanisms. In order to check the correctness of this new theory, I will develop a comprehensive experimental, analytical and numerical methodology to address 4 canonical fragmentation problems which respond to distinct geometric and loading conditions which make easily identifiable from a mechanical standpoint. For each canonical problem, I will investigate traditionally-machined and 3D-printed specimens manufactured with 4 different engineering metals widely used in aerospace and civilian-security applications. The goal is to elucidate whether at sufficiently high strain rates there may be a transition in the fragmentation mechanisms from defects–controlled to inertia–controlled. If the new statistical-deterministic framework is proven to be valid, defects may not play the major role in the fragmentation at high strain rates. This would bring down the entry barriers that the 3D-printing technology has found in energy absorption applications, thus reducing production transportation and repairing, energetic and economic costs of protective structures without impairing their energy absorption capacity. It is anticipated that leading this cutting-edge research project will enable me to establish my own research team and help me to achieve career independence in the field of dynamic behaviour of ductile solids.

Mots-clés : continuum mechanics,dynamic fragmentation,constitutive modelling,3d printing
Projet ERC : HYPERTRANS (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Radboud University Nijmegen — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Dynamic metabolic imaging with hyperpolarized substrates is a new and unique non-invasive magnetic resonance imaging tool. It opens the window to metabolic aberrations at the heart of many diseases, and the ability to image these changes provides the opportunity to fundamentally improve clinical diagnosis and treatment follow-up. Our long-term ambition is to make hyperpolarized substrates for metabolic imaging with MRI available for every clinical institution. The short-term goal to be reached first, is to make the technique of dynamic metabolic imaging available to the wide scientific community. We will implement a concept in which we can polarize substrates at one central location and store these hyperpolarized substrates for transport and use in other academic institutions. This solution overcomes the current need for an on-site dynamic nuclear polarizer when performing preclinical metabolic imaging with MRI, allows an efficient use of resources, and enables scientific institutions to easily adopt this powerful emerging imaging tool. Once our proposed concept is proven, and in line with the existing infrastructure and legal license of our institution to manufacture, provide and transport radionuclide tracers to other hospitals, we propose to set up a spin-off company to manufacture, provide and transport hyperpolarized substrates to pre-clinical research institutions. We have currently contacted 11 pre-clinical research sites within transportation distance of our site, of whom 6 have already expressed serious interest in the possibilities of on-demand hyperpolarized substrates. When, in the long run, pre-clinical research has identified and validated the use of dynamic metabolic imaging for use in patients (e.g. in monitoring treatment response in oncology), this company can take the next step to provide hyperpolarized substrates to clinical institutions and general hospitals.

Mots-clés : transport of substrates,magnetic resonance spectroscopy,dynamic nuclear polarization,rapid melting
Projet ERC : SYSDYNET (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Eindhoven University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU/e
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499690.0 €

Dynamic models play a key role in many branches of science. In engineering they have a paramount role in model-based simulation, monitoring, control and optimization. The accuracy of the models is key to their subsequent use in model-based operations. With the growing spatial complexity of engineering systems, e.g., in power networks, transportation networks and industrial production systems, also referred to as cyber-physical systems of systems, there is a strong need for effective modelling tools for dynamic networks, being considered as interconnected dynamic systems, whose spatial topology may change over time. Data-driven modelling and statistical parameter estimation are established fields for estimating models of dynamical systems on the basis of measurement data from dedicated experiments. The currently available methods, however, are limited to relatively simple structures, as open-loop or closed-loop (controlled) system configurations. In this project I will make the fundamental step towards data-driven modelling (identification) methods for dynamic networks by developing a comprehensive theory with the target to identify local dynamical models as well as the interconnection structure of the network. I will incorporate the selection of sensing and excitation locations, data synchronization, and the optimal accuracy of estimated models in view of their use for distributed control. Solving these problems is by far beyond the current abilities of the existing identification frameworks in the systems and control community. My internationally recognized expertise in the field of system identification and model-based control, together with recent work on dynamic networks, warrants the feasibility of the project. Identification methods for dynamic networks will become essential tools in the high-level future ICT environment for monitoring, control and optimization of these cyber-physical systems of systems, as well as in many other domains of science.

Mots-clés : system identification
Projet ERC : HOLOGRAM (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Technische Universität Berlin — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : TUB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 91170.5 €

Dynamical systems play an important role all over science, from celestial mechanics, evolution biology and economics to mathematics. Specifically holomorphic dynamics has been credited as “straddling the traditional borders between pure and applied mathematics”. Activities of numerous top-level mathematicians, including Fields medalists and Abel laureates, demonstrate the attractivity of holomorphic dynamics as an active and challenging research field. We propose to work on a research project based in holomorphic dynamics that actively connects to adjacent mathematical fields. We work on four closely connected Themes: A. we develop a classification of holomorphic dynamical systems and a Rigidity Principle, proposing the view that many of the additional challenges of non-polynomial rational maps are encoded in the simpler polynomial setting; B. we advance Thurston’s fundamental characterization theorem of rational maps and his lamination theory to the world of transcendental maps, developing a novel way of understanding of spaces of iterated polynomials and transcendental maps; C. we develop an extremely efficient polynomial root finder based on Newton’s method that turns the perceived problem of “chaotic dynamics” into an advantage, factorizing polynomials of degree several million in a matter of minutes rather than months – and providing a family of rational maps that are highly susceptible to combinatorial analysis, leading the way for an understanding of more general maps; D. and we connect this to geometric group theory via “Iterated Monodromy Groups”, an innovative concept that helps solve dynamical questions in terms of their group structure, and that contributes to geometric group theory by providing natural classes of groups with properties that used to be thought of as “exotic”.

Mots-clés : msc2010 37fxx  complex dynamical systems,teichm ller theory,root finding,iterated monodromy groups
Projet ERC : ELDAR (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Oslo — Pays : Norvège — Rôle : PI
Acronyme de l'entité : UiO
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

ELDAR will investigate three aspects of autocratic politics: 1) the emergence of autocratic regimes; 2) policy-making (“life”) in autocracies in the areas of education, infrastructure, pensions and media regulation; 3) autocratic regime breakdown. ELDAR offers a comprehensive perspective, highlighting the interconnections between these three aspects – for example, the particular policies chosen may mitigate or exacerbate specific risks to the regime – and studying them jointly in one framework. ELDAR will address the preferences and capacities of vital actors in autocratic politics – the leader, regime support groups, and mobilized opposition groups. Special attention will be directed towards identifying and linking the different actors entering support and opposition coalitions to constituent social groups (e.g., industrial workers and landowners). Team members will also study the specific, and diverse, institutions that underpin autocracies, such as characteristics of regime parties or legislative elections. In extension, ELDAR will explicitly model – theoretically and empirically – how support- and opposition groups and institutions interact in affecting regime change and policy making in autocracies. Examples of more specific questions include: Are autocracies less willing to use the education system for ideological indoctrination if the regime tightly controls the media environment? Are autocracies less likely to break down if they provide generous special pensions to military officers? To investigate such questions empirically, ELDAR will collect data, with global coverage and long time-series, on the numbers, social identity and other features of groups that support and oppose regimes. These efforts yield unprecedented opportunities for large-n studies of autocratic emergence and demise. Three other datasets, on education systems, buildings, and pensions, will also enable pioneering empirical studies on core policy areas in autocracies.

Mots-clés : autocracy,authoritarian regime,regime change,regime survival
Projet ERC : ELFO (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Italian Institute of Technology — Pays : Italie — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1980000.0 €

ELFO will provide the foundations of a new enabling technology for disruptive edible electronic systems, with applications in advanced biomedical devices for continuous monitoring of the health status within the gastro-intestinal (GI) tract, as well as in electronic tags for food monitoring, serving public health and providing at the same time a very powerful tool against counterfeiting. These systems will be unperceivable and mass produced mainly with mask-less, printing and direct-writing methods. Besides being completely safe for ingestion, such devices will also be perceived as food, favouring public acceptance. Such an ambitious plan will be implemented by: i) creating knowledge on electronic properties of food and food derivatives and complementing them with edible solution-processable, mainly carbon-based semiconductors, thus developing an extended library of edible electronic materials; ii) developing large-area, solution-based, printing and direct-writing scalable processes with high lateral resolution for the precise patterning of edible functional materials; iii) developing edible electronic components required in systems, from logic to power and sensors; iv) validating the progress with two proof-of-concept systems, an edible radio-frequency pill with controlled drug delivery, answering the need for compliance monitoring devices and actuators within the gut, and an edible passive food Radio-Frequency identification tag, answering the need for certification and anti-counterfeiting devices directly onto or into food products. ELFO will give solid engineering grounds to the visionary perspectives of edible electronics, introducing imperceptible intelligence in any edible item, thus accessing more information on what we eat, how it is assimilated and enabling biomedical devices for mass health screening.

Mots-clés : edible electronics,printed electronics,smart pills,food chain,biomedical devices
Projet ERC : EnBioN (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1495430.0 €

ENBION will engineer a platform to direct the differentiation of stem cells by developing principles for the rational design of the biointerface of nanowires. It is increasingly evident that efficient tissue regeneration can only ensue from combining the regenerative potential of stem cells with regulatory stimuli from gene therapy and niche engineering. Yet, despite significant advances towards integrating these technologies, the necessary degree of control over cell fate remains elusive. Vertical arrays of high aspect ratio nanostructures (nanowires) are rapidly emerging as promising tools to direct cell fate. Thanks to their unique biointerface, nanowires enable gene delivery, intracellular sensing, and direct stimulation of signalling pathways, achieving dynamic manipulation of cells and their environment. This broad manipulation potential highlights the importance and timeliness of engineering nanowires for regenerative medicine. However, developing a nanowire platform to direct stem cell fate requires design principles based on the largely unknown biological processes governing their interaction with cells. Enabling localized, vector-free gene therapy through efficient transfection relies on understanding the still debated mechanisms by which nanowires induce membrane permeability. Directing cell reprogramming requires understanding the largely unexplored mechanosensory processes and the resulting epigenetic effects arising from the direct interaction of nanowires with multiple organelles within the cell. Engineering the cell microenvironment requires yet undeveloped strategies to localize signalling and transfection with a resolution comparable to the lengthscale of cells. ENBION will develop this critical knowledge and integrate it into guidelines for dynamic manipulation of cells. Beyond the nanowire platform, the principles highlighted by this unique interface can guide the development of nanomaterials with improved control over cellular processes.

Mots-clés : nanowires,regenerative medicine,biointerface,nanotopography,gene therapy,mechanotransduction,epigenetics,patterning,porous silicon
Projet ERC : ENERGYA (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Ca' Foscari University of Venice — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1082187.5 €

ENERGYA will improve our understanding of how energy and energy services can be used by households and industries to adapt to the risk posed by climate change. Specifically, the project will develop an interdisciplinary and scalable research framework integrating data and methods from economics with geography, climate science, and integrated assessment modelling to provide new knowledge concerning heterogeneity in energy use across countries, sectors, socioeconomic conditions and income groups, and assess the broad implications adaptation-driven energy use can have on the economy, the environment, and welfare. The key novelty of ENERGYA is to link energy statistics and energy survey data with high spatial resolution data from climate science and remote sensing, including high-resolution spatial data on meteorology, population and economic activity distribution, electrification, and the built environment. ENERGYA has three main objectives. First, it will produce novel statistical and econometric analyses for OECD and major emerging countries (Brazil, Mexico, India, and Indonesia) to shed light on the underlying mechanisms driving energy use. Second, it will infer future potential impacts from long-run climate and socioeconomic changes building on historical empirical evidence. Third, it will analyse the macro and distributional implications of adaptation-driven energy use with an economy-energy model characterising the distribution of energy use dynamics across and within countries. Given the central role of energy as multiplier for socioeconomic development and as enabling condition for climate resilience, the research proposed in ENERGYA will result in timely insights for the transition towards sustainability described by the Sustainable Development Goals adopted by the United Nations as well as the Paris International Climate Agreement.

Mots-clés : climate change,adaptation,energy,scenarios,econometrics
Projet ERC : FibreRemodel (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Trinity College Dublin — Pays : Irlande — Rôle : PI
Acronyme de l'entité : TCD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1521875.0 €

Each year cardiovascular diseases such as atherosclerosis and aneurysms cause 48% of all deaths in Europe. Arteries may be regarded as fibre-reinforced materials, with the stiffer collagen fibres present in the arterial wall bearing most of the load during pressurisation. Degenerative vascular diseases such as atherosclerosis and aneurysms alter the macroscopic mechanical properties of arterial tissue and therefore change the arterial wall composition and the quality and orientation of the underlying fibrous architecture. Information on the complex fibre architecture of arterial tissues is therefore at the core of understanding the aetiology of vascular diseases. The current proposal aims to use a combination of in vivo Diffusion Tensor Magnetic Resonance Imaging, with parallel in silico modelling, to non-invasively identify differences in the fibre architecture of human carotid arteries which can be directly linked with carotid artery disease and hence used to diagnose vulnerable plaque rupture risk. Knowledge of arterial fibre patterns, and how these fibres alter in response to their mechanical environment, also provides a means of understanding remodelling of tissue engineered vessels. Therefore, in the second phase of this project, this novel imaging framework will be used to determine fibre patterns of decellularised arterial constructs in vitro with a view to directing mesenchymal stem cell growth and differentiation and creating a biologically and mechanically compatible tissue engineered vessel. In silico mechanobiological models will also be used to help identify the optimum loading environment for the vessels to encourage cell repopulation but prevent excessive intimal hyperplasia. This combination of novel in vivo, in vitro and in silico work has the potential to revolutionise approaches to early diagnosis of vascular diseases and vascular tissue engineering strategies.

Mots-clés : diffusion tensor imaging,tissue engineering,vascular mechanobiology
Projet ERC : NeuroMag (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Research Institute of Molecular Pathology — Pays : Autriche — Rôle : Partner
Acronyme de l'entité : IMP
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 497376.25 €

Each year millions of animals undertake remarkable migratory journeys, across oceans and through hemispheres, guided by the Earth’s magnetic field. While there is unequivocal behavioural evidence demonstrating the existence of the magnetic sense, it is the least understood of all sensory faculties. The biophysical, molecular, cellular, and neurological underpinnings of the sense remain opaque. In this application we aim to remedy this situation, exploiting an established assay, our unique infrastructure, and state-of-the-art methodology, using pigeons as a model system. The proposal will address three questions: 1) Where are the primary magnetosensors? 2) Where is magnetic information processed in the brain? 3) How is magnetic information encoded in the brain? In Aim 1 we will explore whether inner ear hair cells are the primary sensors, and if the detection of magnetic stimuli depends on the presence of magnetic crystals or electromagnetic induction. We will employ a range of physical methods to locate magnetite, and a molecular approach to identify putative electroreceptors. In Aim 2 we will use light sheet microscopy coupled with clearing methods to undertake whole brain mapping of magnetically-induced neuronal activation in the pigeon. We will complement these studies with transcriptomic methods to molecularly and anatomically define magnetosensitive circuits within the pigeon brain. We will build on this work in Aim 3 utilising in vivo 2-photon microscopy to investigate how cells within the pigeon brain encode magnetic information. We will determine whether neurons encode for specific components of the magnetic field (i.e. inclination, intensity, and polarity) and explore whether there are spatially restricted ensembles, providing a dynamic picture of magnetically induced neuronal activity. We anticipate that these experiments will reveal a secret that nature has kept hidden for millennia; How do animals detect magnetic fields?

Mots-clés : magnetoreception,pigeons,magnetite,electromagnetic induction,neuronal circuits,hippocampus