Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ENHANCEDQMMR (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Cologne — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 940262.5 €

Over the last 20 years, qualitative methods in political science have developed rapidly on three dimen-sions. First, set theory was formulated as an alternative to what is called the quantitative worldview. Second, process tracing for the analysis of mechanisms evolved as a complement to the estimation of marginal effects. Process tracing has also been tied to Bayesianism as opposed to frequentism. Third, process tracing became an element of multi-method research (MMR), integrating it with frequentist statistics or Qualitative Comparative Analysis (QCA). An important element of the development of qualitative methods is its contrast with quantitative methods. At the same time, quantitative researchers critically commented on that development. The constant exchange has contributed to the progress of qualitative methods, but the debate has reached an impasse in some respects, or has pursued one line of development while neglecting others. Building on state-of-the-art qualitative methods, ENHANCEDQMMR seeks to overcome this impasse and to explore new ground.It makes four significant contributions to the progress of standalone qualitative methods and as part of MMR. First, it examines experimentally how researchers decide between a set-relational and correlational view on causation and whether they can realize designs in accord with their initial decision. Second, it develops tools for sensitivity analyses, diagnostics, and the modeling of diverse data structures via QCA for strengthening QCA-based inference. Third, it com-pares the performance of QCA and regression analyses under simulated data-generating processes with the goal of generating comparative diagnostics, possibly allowing one to adjudicate between both methods in observational research. Fourth, it formulates standards for Bayesian MMR by combining Bayesian process tracing with Bayesian statistics and Bayesian QCA, respectively. The insights of the project will be implemented in freely available software.

Mots-clés : alphabetically  case studies,causal inference,multi method designs,nested analysis,political science methods,process tracing,qualitative comparative analysis  qca,research design,set theory
Projet ERC : PALAEOFARM (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : University of London — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Over the last 50 years, chicken production has increased fivefold, chicken growth rate has tripled, and milk production per cow has doubled. Yet, many of the biotechnological tools responsible for this accelerated trend are now under threat of becoming obsolete. While the causes are numerous, one significant driver is a dramatic reduction of genetic diversity in livestock populations. Cycles of agricultural productivity growth and decline have occurred throughout European history, spurred by major historical forces such as the spread of empires and continent-wide epidemics. For example, productivity crashed between the 4th-13th centuries, only to rebound during the Agricultural Revolution of the 13-18th centuries. Fluctuating levels of genetic diversity were likely both cause and remedy to these cycles. Genetic diversity acts as a fuel for selection: the lower it is, the more difficult it is to improve traits, and the more likely that epidemics will develop and spread. Given this importance, maintaining diversity amongst livestock is recognised as one of the UN’s Sustainable Development Goals. Despite this, we lack any understanding of how much genetic variability was present, and subsequently lost, before, during, and after either the Green or Agricultural Revolutions, nor do we understand how efficiently it was utilised. PALAEOFARM will assess the long-term sustainability of modern breeding practices by unravelling how genetic variability was leveraged across major agricultural transitions in European history. Using an innovative combination of ancient DNA, archaeozoology, and experimental immunology, I will explore how livestock populations withstood epidemics and selective breeding in a world without antibiotics or quantitative genetic techniques. This will provide a novel perspective on how a multi-billion euro industry, responsible for feeding billions of people, can be sustained in the face of major biotechnological obsolescence.

Mots-clés : livestock genomics,population genomics,ancient dna,immunology
Projet ERC : 3D MAGiC (Horizon 2020, appel 2019, Synergy grants)
Entité participante : Forschungszentrum Jülich — Pays : Allemagne — Rôle : CO-PI
Acronyme de l'entité : FZJ
Type d'entité : Recherche
Financement ERC de l'entité : 6841603.0 €

Over the past 150 years, many of the greatest questions in physics, spanning astronomical dimensions to quarks, have addressed how particles can emerge in continuous fields. In this highly exploratory project, we will open a window into the behavior and control of some of the least explored and most puzzling objects in nanomagnetism: three-dimensional (3D) magnetic solitons (MSs). These are spatially localized stable magnetization textures that have particle-like properties and are expected to move and interact in 3D in magnetic crystals and heterostructures in a similar manner to ordinary particles. Until now, their theoretical study has been restricted to simple models, while the experimental study of individual 3D MSs is nearly unexplored as a result of their deep-sub-micron size and a current lack of suitable characterization techniques. We bring together four complementary research groups with expertise in theoretical descriptions of magnetism, device physics and magnetic characterization with high spatial and temporal resolution. Methodological breakthroughs by the partners will enable new fundamental theoretical and experimental insights into the nucleation, stability, dynamics and transport of 3D MSs, which are predicted to be influenced strongly by their nontrivial topology. Particular attention will be paid to the manner in which 3D MSs can be controlled and manipulated dynamically. This project will open the field of 3D magnetization textures at the nanoscale to fundamental science,with a view to enabling disruptive applications. 3D MSs are foreseen to play the role of information carriers that can move freely in any spatial direction and to offer a key advance over conventional 2D magnetization textures. Results from the project will provide guidelines for their use in applications that include magnetic storage technology and neuromorphic information processing systems and enable the realization of pervasive new 3D device concepts.

Mots-clés : transmission electron microscopy,off axis electron holography,skyrmions,hopfions
Projet ERC : DBScontrol (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : National University of Ireland — Pays : Irlande — Rôle : PI
Acronyme de l'entité : NUI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Over the past 25 years deep brain stimulation (DBS) has emerged as an effective treatment for the symptoms of Parkinson's disease (PD). Despite its success, the mechanisms of DBS are not yet fully understood. Moreover, patients experience side effects and poor control of symptoms associated with suboptimal programming of stimulus parameters. Current DBS systems operate in an 'open-loop' configuration with stimulus parameters (pulse amplitude, duration and frequency) empirically set and remaining fixed over time. Closed-loop DBS offers an alternative approach that has the potential to overcome current limitations and increase therapeutic efficacy, while reducing side-effects and increasing battery life, by automatically adjusting stimulation parameters as required. Although the potential benefits of closed-loop DBS are widely recognised, these systems have not yet been implemented clinically. Under the parent ERC project DBSmodel, we have developed biophysically detailed computational models of the neural circuits in the brain during DBS and are using these to develop and test novel algorithms for closed-loop DBS. Before these can be trialled in humans, however, feasibility must first to be demonstrated through implementation on a prototype device and pre-clinical testing in animal models. ERC proof of concept funding will enable us to do this by implementing and testing a novel closed-loop DBS system in an animal model of PD. The experimental validation will confirm the efficacy of a prototype solution suitable for translation to human studies.

Mots-clés : deep brain stimulation,closed loop control,parkinson s disease,pre clinical testing,medical device
Projet ERC : NCST (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : University of Edinburgh — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1497425.0 €

Over the past 30 years, deep connections between Chern–Simons theory, supersymmetric (SUSY) gauge theory, and representation theory of quantum groups, have caused an avalanche of research in mathematics and physics. In this proposal I use quantum cluster varieties to develop positive representation theory of quantum groups and a non-compact analogue of Chern–Simons theory. I also obtain new invariants of links and 3-manifolds, and establish new connections between SUSY gauge theories and quantum character varieties. This proposal builds on my prior work, where I prove fundamental cases of the Fock–Goncharov modular functor conjecture in higher Teichmüller theory, and Gaiotto’s conjecture on the existence of cluster structure on K-theoretic Coulomb branches of 3d N = 4 SUSY gauge theories. The proposal is split into the following four projects: 1. Prove the modular functor conjecture and extend it to a non-compact analogue of Chern–Simons theory. Obtain new powerful invariants of links and 3-manifolds. 2. Develop positive representation theory: construct continuous braided monoidal category from positive representations, prove non-compact Peter–Weyl theorem, obtain explicit formulas for finite-dimensional 6j-symbols, prove that the category of positive representations of quantum groups in type A is equivalent to a fusion category in Toda conformal field theory. 3. Describe cluster structure on K-theoretic Coulomb branches of 3d N = 4 SUSY gauge theories, conjectured by Gaiotto. Obtain cluster structure on spherical double affine Hecke algebra, and Slodowy intersections. Provide an algorithm, identifying certain theories of class S with quiver gauge theories. 4. Relate cluster quantization of character varieties with the topological quantum field theory constructed by Ben-Zvi, Brochier, and Jordan. Use it to obtain a canonical quantization of the A-polynomial.

Mots-clés : quantum character varieties,cluster varieties,higher teichmuller theory,modular functor,non compact chern simons theory,positive representations,quantum coxeter toda system,coulomb branches of 3d n 4 gauge theories,gelfand tsetlin representations,factorization homology
Projet ERC : MetalloRadiCat (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : RWTH Aachen University — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : RWTH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Over the past decades, metal catalysis has had a tremendous impact in chemistry, its adjacent disciplines and society overall, having gained an omnipresence in academic and industrial research worldwide. Numerous previously unthinkable transformations can nowadays be achieved in a selective and relatively mild manner owing to the metals' unique ability to trigger bond-making and breaking via pathways and principles that are inaccessible to metal-free processes. In this context, the global community has focused primarily on closed-shell, two electron processes for synthetic transformations. By comparison, the field of metalloradical catalysis has seen much less development, although metalloradicals are nature's preferred species to tame radical reactivities under non-precious metal-catalysis in numerous metalloenzymes. This is likely due to our currently limited understanding of metalloradical reactivity and its associated principles, and as such also limited ability to rationally design metalloradical catalysts and catalytic processes. A multidisciplinary approach, which capitalizes on the principles and insights of organic, organometallic and biological processes, will likely be key to meet the next frontier in this promising field. The objective of this proposal is to combine the tools of mechanistic, computational and synthetic organic/organometallic chemistry to explore catalysis with metalloradicals in synthesis, materials research and enzymatic processes. The proposed program will investigate some of the most pertinent questions in relation to the emerging area of remote functionalizations for the selective synthetic access to tailored molecules, olefin migrations and manipulations, and naturally occurring (enzymatic) metalloradical-catalyzed processes in the context of methane production and activation.

Mots-clés : catalysis,mechanistic studies,organometallic,reactivity design,computation,synthesis,radical
Projet ERC : blackQD (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1499903.0 €

Over the past decades, silicon became the most used material for electronic, however its indirect band gap limits its use for optics and optoelectronics. As a result alternatives semiconductor such as III-V and II-VI materials are used to address a broad range of complementary application such as LED, laser diode and photodiode. However in the infrared (IR), the material challenge becomes far more complex. New IR applications, such as flame detection or night car driving assistance are emerging and request low cost detectors. Current technologies, based on epitaxially grown semiconductors are unlikely to bring a cost disruption and organic electronics, often viewed as the alternative to silicon based materials is ineffective in the mid-IR. The blackQD project aims at transforming colloidal quantum dots (CQD) into the next generation of active material for IR detection. CQD are attracting a high interest because of their size tunable optical features and next challenges is their integration in optoelectronic devices and in particular for IR features. The project requires a combination of material knowledge, with clean room nanofabrication and IR photoconduction which is unique in Europe. I organize blackQD in three mains parts. The first part relates to the growth of mercury chalcogenides nanocrystals with unique tunable properties in the mid and far-IR. To design devices with enhanced properties, more needs to be known on the electronic structure of these nanomaterials. In part II, I propose to develop original methods to probe static and dynamic aspects of the electronic structure. Finally the main task of the project relates to the design of a new generation of transistors and IR detectors. I propose several geometries of demonstrator which for the first time integrate from the beginning the colloidal nature of the CQD and constrain of IR photodetection. The project more generally aims to develop a tool box for the design of the next generation of low cost IR.

Mots-clés : nanocrystals optoelectronic,quantum dot device,infrared photodetection,mercury chalocogenides
Projet ERC : BioArchitecture (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Leibniz Association — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LG
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Over the past ten years, 3D bioprinting has emerged as a powerful tool to fabricate human tissue models ex vivo. These models can be used for drug discovery, to obtain a better understanding of physiological and pathological mechanisms, and in the future to replace diseased or injured tissues and organs. To successfully fabricate functional tissues, 3D bioprinted constructs should emulate the anatomical features of the native tissue’s extracellular matrix (ECM). However, current bioprinting technologies can neither mimic the nano- and microscale fibrillar ECM, nor replicate the anisotropic and spatially organized architecture and gradients of complex tissues, such as cartilage, cornea, and the heart. Within BioArchitecture, we aim to develop a novel 3D bioprinter platform, capable of bioprinting hierarchical and organized biomaterial constructs at high resolution to instruct and guide cell growth and tissue maturation. The BioArchitecture platform will allow researchers and pharmaceutical companies to perform better drugs target identification in native-like bioprinted human tissues ex vivo, which will better predict the efficacy and safety of the tested drugs and significantly decrease healthcare costs by reducing the required amount of personnel, infrastructure, an animal experiments associated to a new drug development.

Mots-clés : 3d bioprinting,magnetic orientation,tissue model,anisogel,3d printing
Projet ERC : SUPRANET (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Ulm — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Over the past two decades, a branch of organic chemistry has emerged that breaks with the paradigm of synthesizing pure compounds and focusses instead on complex (macro)molecular networks akin to those found in nature. In this proposed project, we aim to address unmet challenges in supramolecular chemistry and systems chemistry by developing original dynamic reaction networks whose building blocks are capable of supramolecular (self-)recognition. The first two objectives of SUPRANET focus on the use of dynamic covalent orthoester networks for the discovery of anion, cation and ion pair receptors, whose unique properties may pave the way towards the utilization of inorganic ions as drugs. For instance, we will develop self-assembled ion pair cages for the electro-neutral transport of medicinally relevant anions across phospholipid membranes. Our network approach will also allow us to “imprison” ionic guests for the first time in self-assembled receptors that could be used for the transport and controlled release of ions, even against osmotic pressure. Objectives three and four of SUPRANET go beyond the equilibrium state and, as such, are relevant to the chemistry of life, in which key processes depend on dissipative steady states. The proposed reaction networks will feature biologically relevant ribose building blocks that are continuously assembled and disassembled by two different irreversible reactions, resulting in steady state mixtures of either RNA oligomers or ribose-derived vesicles. It is our hope that these studies will provide insights into open questions regarding the molecular origins of life, such as the non-enzymatic formation of RNA oligomers capable of self-recognition and the simultaneous emergence of compartmentalization and self-replication. SUPRANET thus seeks to break new ground in both equilibrium and far-from-equilibrium dynamic networks and is equally motivated by applied and fundamental challenges.

Mots-clés : systems chemistry,dynamic covalent chemistry,origins of life
Projet ERC : RD-ADVANCE (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of Mannheim — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : UMA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 878970.0 €

Over the past two decades, regression discontinuity (RD) designs have become one of empirical economics' most popular strategies for estimating causal effects from observational data. In such designs, units are assigned to the treatment group if and only if a special covariate, or running variable, falls above a known cutoff value. Under mild conditions, those units close to the cutoff are as good as randomly assigned to receive the treatment, which provides a simple and transparent source of identification of the treatment's causal effect. This project extends the range of methodological tools available to applied researchers working with data from RD designs. It is divided into three parts. The first part develops methods for incorporating covariates and group structures into the analysis of RD designs by adapting modern machine learning methods and empirical Bayes approaches. The second part considers RD designs with a discrete running variable. It shows that current state-of-the-art inference procedures are likely to be misleading in such settings, and develops new confidence intervals for causal effects. The third part develops methods for estimation and inference that account for manipulation in RD designs. Here manipulation refers to any strategic action taken by the actors within the respective institutional context that leads to observational units on different sides of the cutoff being non-comparable. The part develops a general framework for manipulation with corresponding nonparametric methods for estimation and inference, and considers various extensions. Given the huge popularity of RD designs, and the proposal's focus on practical methods, this project has the potential to have a sizable impact on empirical economic research in a number of policy relevant areas, including education and public finance; but also on other branches of science where researchers commonly work with observational data, such as sociology or epidemiology.

Mots-clés : causal inference,nonparametric estimation,clustering