Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SURPRISE (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Radboud University Nijmegen — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Humans, like many other species, build models of themselves and their environment, to understand the past and predict the future. These models are constantly evaluated and updated based on new, surprising input. Surprise (i.e., the distance between one’s prior and current beliefs) appears an essential ingredient in various cognitive faculties such as perception, learning, motivation and action and it strongly drives brain activity in both sub-cortical and cortical networks underlying goal-directed behavior. Yet, we currently lack a good understanding of the form and function of surprise signals in the brain. The overall aim of this research proposal is to elucidate how surprise is computed within sensory circuits and how it influences information seeking behavior. To achieve this, I will: 1) test the theoretical proposition that surprise signals emerge from the discrepancy between prediction signals and input signals that are represented in distinct layers of the neocortex, using ultra-high field neuroimaging in human volunteers; 2) investigate how sensory surprise signals may be communicated to downstream areas to update the brain’s attentional sampling policies; and 3) investigate the relationship between sensory surprise and the explicit drive for information that we call curiosity. This proposal bridges several levels of analysis (from laminar circuit models that calculate sensory surprise to systems neuroscience and computational models of behavior) and several cognitive domains (perception, attention, motivation and curiosity). This multi-scale and multi-method investigation of surprise signals is critical for a more complete and integrated understanding of what may be one of the most important drivers of cognition and behavior.

Mots-clés : prediction,surprise,curiosity,information seeking
Projet ERC : HyMAP (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Madrid Institute for Advanced Studies — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IMDEA
Type d'entité : Recherche
Financement ERC de l'entité : 2506738.0 €

HyMAP aims to develop a new generation of multifunctional hybrid photocatalysts and solar photoreactor which would allow the exploitation of at least the 1 % of the sunlight energy for the CO2 photoreduction using water as electron donor. This will imply a CO2 conversion in the range of 12 to 35 Ton/y•ha, depending on product distribution, which represents at least a 20-fold improvement over the state of the art. To achieve this goal, I propose an interdisciplinary research program through which several breakthroughs at different scales will be achieved: Development of efficient multifunctional organic/inorganic semiconductors and metal-organic frameworks photocatalysts with separated reduction/oxidation active sites. The fact of having independent multiple redox sites combined in a single material would maximize charge separation and transport processes, as well as sunlight harvesting. Characterization and modelling of the structural and opto-electronic properties of the proposed materials. Evaluation of the materials in artificial photosynthesis devices. At this stage, a solar photoreactor that would allow good transmission, uniform light distribution and maximize the energy harvesting in the overall spectra will be developed. HYMAP will provide me with an excellent opportunity to lead a consolidated research group. During my scientific career I have demonstrated creative thinking, autonomy and an excellent capacity to carry out state of the art research in heterogeneous catalysis, characterization, modelling and reactor engineering. I have a meritorious research track reflected by a good number of scientific publications, broad professional expertise, innovative project conception and a consolidate network of international collaboration. This, along with my leadership and management abilities, will assure the successful achievement of the mentioned goals of this project. HyMAP is a revised version of a proposal scored with A (2nd stage) of last ERC-CoG call.

Mots-clés : artificial photosynthesis,organic,inorganic semiconductors,computational chemistry,in situ characterization,solar photoreactor engineering,surface plasmon and up coversion nanoparticles
Projet ERC : RareDiamond (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Université Sorbonne Paris Nord — Pays : France — Rôle : Partner
Acronyme de l'entité : USPN
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 27500.0 €

Hybrid materials associate distinct components to achieve new functionalities. The key challenge in these composite systems is to harness new effects that cannot be obtained by a single material while preserving the necessary underlying properties of each component - a tremendously difficult task in materials science. The fantastic achievements of micro-electronics in this field have boosted similar developments in optics, and especially in the infrared range, where integrated optical chips combine a variety of functionalities like light sources, modulators, and detectors in circuits based on low-loss waveguides. In particular, silicon integrated optics have witnessed impressive scientific and technological progress as well as industrial production, since this architecture offers seamless integration between optics and electronics. Among optically active materials, NV- color centers in diamond and rare earth doped crystals have both exceptional properties that are separately used in, or investigated for, a broad range of applications such as lasers, lighting, fluorescence-based sensing and imaging, and quantum technologies like quantum processing, sensing and communications. In RareDiamond, I will design and grow hybrid materials in which rare earth ions and NV- centers can interact on the nanoscale while preserving their outstanding properties. This will be achieved using techniques allowing the growth of complex, high-quality structures with extreme localization of active centers, combined with advanced spectroscopy. These materials will enable interfacing diamond NV- centers with infrared light, a capability currently out of reach that I will exploit for innovative demonstrations in magnetometry, fluorescent imaging, and quantum light-matter interfacing. RareDiamond hybrid materials will open the way to diamond NV- integration with photonic chips and telecom fibers, for unprecedented functionalities in sensing, quantum processing, and quantum communications.

Mots-clés : light matter interface,luminescence,sensing,energy transfer,up conversion
Projet ERC : HHAIR (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Radboud University Nijmegen — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499248.0 €

Hybrid systems combining artificial and human intelligence hold great promise for training human skills. I propose to develop Hybrid Human-AI Regulation (HHAIR) to develop learners’ Self-Regulated Learning (SRL) skills within Adaptive Learning Technologies (ALTs). HHAIR targets young learners (10-14 years) for whom SRL skills are critical in today’s society. Many of these learners use ALTs to learn mathematics and languages every day in school. ALTs optimize learning based on learners’ performance data but even the most sophisticated ALTs fail to support SRL. In fact, most ALTs take over (offload) control and monitoring from learners. HHAIR on the other hand aims to gradually transfer regulation of learning from AI-regulation to self-regulation. Learners will increasingly regulate their own learning progressing through different degrees of hybrid regulation. In this way HHAIR supports optimized learning and transfer (deep learning) and development of SRL skills for lifelong learning (future learning). This project is ground-breaking in developing the first hybrid systems to train human SRL skills with AI. The design of HHAIR resolves four scientific challenges: i) identify individual learner’s SRL during learning; ii) design degrees of hybrid regulation; iii) confirm effects of HHAIR on deep learning; and iv) validate effects of HHAIR on SRL skills for future learning. The four design challenges are addressed by investigating ALTs’ trace data in exploratory studies (WP1), applying these insights to develop HHAIR in design studies (WP2), investigating immediate effects on deep learning in short-term field studies (WP3) and effects on SRL-skills for future learning in long-term field studies (WP4). The AI@EDU infrastructure will connect HHAIR to ALTs used daily in schools across Europe. The project will develop advanced measurement of SRL and algorithms to drive hybrid regulation for developing SRL skills in ALTs.

Mots-clés : self regulated learning,adaptive learning technologies,artificial intelligence,hybrid systems,learning analytics,dashboards
Projet ERC : HyGate (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Sapienza University of Rome — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1496250.0 €

Hydrophobic gating is the phenomenon by which the flux of ions or other molecules through biological ion channels or synthetic nanopores is hindered by the formation of nanoscale bubbles. Recent studies suggest that this is a generic mechanism for the inactivation of a plethora of ion channels, which are all characterized by a strongly hydrophobic interior. The conformation, compliance, and hydrophobicity of the nanochannels – in addition to external parameters such as electric potential, pressure, presence of gases – have a dramatic influence on the probability of opening and closing of the gate. This largely unexplored confined phase transition is known to cause low frequency noise in solid-state nanopores used for DNA sequencing and sensing, limiting their applicability. In biological channels, hydrophobic gating might conspire in determining the high selectivity towards a specific ions or molecules, a characteristic which is sought for in biosensors. The objective of HyGate is to unravel the fundamental mechanisms of hydrophobic gating in model nanopores and biological ion channels and exploit their understanding in order to design biosensors with lower noise and higher selectivity. In order to achieve this ambitious goal, I will deploy the one-of-a-kind simulation and theoretical tools I developed to study vapor nucleation in extreme confinement, which comprises rare-event molecular dynamics and confined nucleation theory. These quantitative tools will be instrumental in designing better biosensors and nanodevices which avoid the formation of nanobubbles or exploit them to achieve exquisite species selectivity. The novel physical insights into the behavior of water in complex nanoconfined environments are expected to inspire radically innovative strategies for nanopore sensing and nanofluidic circuits and to promote a stepwise advancement in the fundamental understanding of hydrophobic gating mechanisms and their influence on bio-electrical cell response.

Mots-clés : rare events simulations,molecular dynamics,nanopore sensing,capillary evaporation,neuron models
Projet ERC : InflammaTENSION (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Edinburgh — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 165243.75 €

Hypertension is a common disease impacting 1 billion people worldwide, which leads to catastrophic cardiovascular complications. The cause of primary hypertension is unknown and the disease remains uncontrolled in many patients. By interrogating the key hypothesis that inflammatory dysregulation fundamentally controls development of hypertension and vascular remodelling, InflammaTENSION provides a new paradigm for the management of the disease, with the potential to lead to identification of novel therapeutic targets to control hypertension. InflammaTENSION will result in the discovery of novel biomarkers, capable of identifying patients who could benefit from such immune targeted therapies. Importantly, we already made the seminal observation that the immune system not only mediates target organ damage, but is essential for the development of hypertension. This finding has initiated numerous studies, that defined the roles of pro-inflammatory T cells, monocytes and anti-inflammatory T regulatory cells. However, our current knowledge remains very fragmented and so far has not been applied to human pathology. InflammaTENSION will for the first time advance the knowledge procured in rodent models into human studies. By combining clinical translational and model mechanistic studies it will identify novel inflammatory factors that can control immune mechanisms of hypertension. We will: (1) characterize the immunophenotypic signature of human hypertension; (2) define key concepts in cytokine biology of hypertension with TNF-α and IL-6 as key exemplars; (3) understand how chronic cytokines regulate the T cell dependent mechanisms of hypertension. InflammaTENSION will go beyond current state-of-the-art through comprehensive combination of immunology and cardiovascular medicine to create a new understanding of how the immune system may lead to human hypertension and will have major impact on the field, enabling translation of these exciting findings to clinical practice.

Mots-clés : hypertension,blood pressure,endothelium,inflammation,vascular,perivascular
Projet ERC : Pros-RODAM (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Amsterdam University Medical Centers — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999438.0 €

Hypertension is the most important modifiable cardiovascular risk factor. Migrants, especially people of Sub-Saharan African heritage, are extremely affected for reasons that are unclear. This project aims to understand the mechanisms underlying the high risk of hypertension among African migrants by assessing the role of epigenetic modifications that result from rapid socio-environmental and behaviour change. To achieve this, Agyemang and his team will establish an innovative transcontinental prospective cohort study of a homogeneous group of Sub-Saharan African migrants (Ghanaians) living in the Netherlands and non-migrant Ghanaians living in rural and urban Ghana. We will first examine and identify the key changes in modifiable environmental factors influencing the high risk of hypertension among migrants. Second, we will examine changes in epigenetic modifications and their effects on hypertension risk in migrants. Third, we will identify the key environmental factors that are driving the epigenetic changes. Last, we will estimate for the first time the individual and combined effect of environmental factors, and epigenetic modifications to the high risk of hypertension in migrants relative to non-migrant Europeans and Ghanaian counterparts living in Africa. This project will yield new insights into the key drivers of hypertension and deliver a major breakthrough in knowledge about prevention and treatment among African and other population groups.

Mots-clés : migration and health,sub sahara africa,hypertension,lifestyle,psychosocial factors,social determinants of health,epigenteics,intercontinental prospective cohort
Projet ERC : PlanArt (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Queen Margaret University — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : QMUC;QMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 10627.5 €

I address major controversies relating to the basic underpinnings of the human speech production system. These concern a) the nature of the mental representations of speech sounds (symbolic vs. spatiotemporal; phonemic vs. non-phonemic gestural), b) the goals of movement (articulatory vs. explicitly acoustic; with emergent vs. explicit surface durations), and c) the processes for planning and generating speech articulations (oscillator-based mechanisms vs. Optimal Control Theory and Lee’s Tau theory). PlanArt will offer the first systematic attempt to determine which theoretical assumptions about each of these three fundamental components are required to provide an adequate account of human speech production behaviour. This ambitious task requires a cutting-edge two-pronged approach. First, through novel experiments I will test predictions of theoretical alternatives for types of phonological representations, output goals, and planning processes. Many of these experiments are inspired by theory and techniques in the non-speech motor literature, which are new to the field of speech production. In the second prong of my research, I will provide a comparison of the articulatory outputs of computational models based on particular sets of core theoretical assumptions. This second, modelling prong will include the development of a flexible, modular platform allowing for parallel implementation, testing, and comparison of competing theoretical assumptions in terms of model outputs, as well as the development of a computational implementation of a new approach, proposed by team members Turk & Shattuck-Hufnagel (2020a) to address shortcomings in the literature. Taken together, this work will provide converging evidence for the nature of the bedrock elements and processes of speech production and will deliver answers to longstanding questions in phonology and phonetics about the way we plan the pronunciations of words in different contexts.

Mots-clés : speech planning,speech articulation,phonology,phonetics
Projet ERC : PlanArt (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Edinburgh — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2134545.0 €

I address major controversies relating to the basic underpinnings of the human speech production system. These concern a) the nature of the mental representations of speech sounds (symbolic vs. spatiotemporal; phonemic vs. non-phonemic gestural), b) the goals of movement (articulatory vs. explicitly acoustic; with emergent vs. explicit surface durations), and c) the processes for planning and generating speech articulations (oscillator-based mechanisms vs. Optimal Control Theory and Lee’s Tau theory). PlanArt will offer the first systematic attempt to determine which theoretical assumptions about each of these three fundamental components are required to provide an adequate account of human speech production behaviour. This ambitious task requires a cutting-edge two-pronged approach. First, through novel experiments I will test predictions of theoretical alternatives for types of phonological representations, output goals, and planning processes. Many of these experiments are inspired by theory and techniques in the non-speech motor literature, which are new to the field of speech production. In the second prong of my research, I will provide a comparison of the articulatory outputs of computational models based on particular sets of core theoretical assumptions. This second, modelling prong will include the development of a flexible, modular platform allowing for parallel implementation, testing, and comparison of competing theoretical assumptions in terms of model outputs, as well as the development of a computational implementation of a new approach, proposed by team members Turk & Shattuck-Hufnagel (2020a) to address shortcomings in the literature. Taken together, this work will provide converging evidence for the nature of the bedrock elements and processes of speech production and will deliver answers to longstanding questions in phonology and phonetics about the way we plan the pronunciations of words in different contexts.

Mots-clés : speech planning,speech articulation,phonology,phonetics
Projet ERC : POLBUSNETWORKS (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Central European University — Pays : Hongrie — Rôle : PI
Acronyme de l'entité : CEU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1833214.0 €

I explore the role of networks involving firms---networks between firms and politicians, and networks between firms and firms--for economic outcomes. I focus on two broad questions. (1) What are the determinants and implications of political favor networks? Although political favoritism affects allocations in many countries, its mechanisms are not well understood. I develop a new model based on the idea of trust embedded in favor networks, and test in Hungarian data the model's implications about how political centralization shapes favoritism. I also quantify the welfare cost of misallocation created by favoritism. My results help understand how political institutions shape economic outcomes. (2) What is the impact of supply chain networks on firm performance? Inputs from suppliers account for the majority of firm sales, yet we know little about the contribution of suppliers to firm performance. I use a field experiment in China to measure the causal effect of suppliers and the underlying mechanisms. I then use observational data from Hungary to quantify the contribution of differences in suppliers to differences in firm performance. The results help understand how supply chains and their misallocation shape firm and aggregate productivity. My approach to both of these questions emphasizes the role of trust embedded in firm networks and how these trust-based networks create misallocation of resources. A key component of this research is the development of original datasets. Beyond documenting and explaining facts, I also hope to obtain policy implications on reducing favoritism and improving firm performance in developing countries.