Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ELECT (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University College Dublin — Pays : Irlande — Rôle : PI
Acronyme de l'entité : UCD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499998.75 €

ELECT falls within the methodological framework of “grounded normative theory”. It combines normative democratic theory with a mixed-methods and comparative research design to investigate the moral agency of key stakeholders involved in contemporary election campaigns: candidates, campaign professionals, political journalists and citizens. The moral agency of electoral stakeholders becomes a subject of concern when they are confronted with normatively charged situations involving motivations to behave in ways that undermine democratic norms or political trust. The context in which electoral stakeholders exercise their moral agency has been changing, presenting them with new normative challenges relating to their respective electoral conduct. Recent changes include the strategic and communicative possibilities provided by big data and new media and the evolving competitive landscape relating to the emergence of new electoral challengers. Existing research on the tensions between contemporary election campaigns and democracy and political trust has primarily taken campaign outputs as its objects of study. Far less studied are the moral dimensions of the inputs concerning the role that the attitudes, beliefs and motivations of stakeholders play in influencing their conduct and how their moral decision-making is affected by institutions and regulations. Neglect of this input perspective leaves major knowledge gaps that limits our ability to accurately diagnose normative problems with campaigning and prescribe effective solutions. ELECT will attempt to fill these gaps by exploring the moral agency of electoral stakeholders in four countries that have been subject to recent disruptions in the campaign context, namely Germany, Italy, the UK and the US. Empirical data will be gathered using surveys, elite interviews and citizen focus groups. Diagnostic and prescriptive analyses based on this data will employ state of the art methods in normative democratic theory.

Mots-clés : democratic theory grounded normative theory moral agency election campaigns
Projet ERC : REGAL (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université métropolitaine d'Oslo — Pays : Norvège — Rôle : PI
Acronyme de l'entité : OsloMet
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1462766.0 €

The Kohn-Sham approach of density-functional theory (DFT) is the most widely used method in quantum chemistry and its usefulness as a practical tool can hardly be overestimated. The central object is the universal density functional. However, this density functional is nondifferentiable, leaving many practical aspects of the theory unfounded. Nevertheless, extensive work has been done establishing exact conditions for the density functional, constituting one of the cornerstones of functional development. The aim of the proposal is to apply a generalization of the Moreau-Yosida regularization to DFT. This achieves not only differentiability, but also mitigates the problem of potential-representability and provides global solutions of the underlying variational problem. This unconventional approach may have transformative impact on the development of approximate functionals as well as the iterative Kohn-Sham scheme.  The first objective is to establish the mathematical foundation of a regularized DFT, akin to the unregularized setting of standard DFT. Close interplay between different theories that use more than just the particle density as variables will be a guide for the regularized theory.  Equipped with a regularized formulation, the aim of the second objective is to develop new and understand existing exact constraints for the density functional. This intends to open up a whole new axis of method development for approximate functionals. Since the regularization transformation considered is lossless, REGAL opens up for a new theoretical bridge between formal DFT and density-functional approximations.  The third objective is the study of the regularized Kohn-Sham iteration scheme. Here a proof of guaranteed convergence is the ultimate aim. Furthermore, regularization effects to speed up convergence using bounds on the energy curvature will be studied.  The feasibility is increased by the PI’s strong background in both applied mathematics and quantum chemistry.

Mots-clés : density functional theory,moreau yosida regularization,exact constraints,kohn sham iteration scheme,current density functional theory,density functional approximations
Projet ERC : FASTPROOF (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1435000.0 €

A proof-system is a protocol that enables a powerful prover to convince a weaker verifier of the validity of a computational statement. Proof-systems have been central to the theory of computing since its inception. Some of the most important results, concepts and open problems in this field revolve around notions of efficient proof-systems.  In recent years, due to the surging need for large scale computation coupled with advances such as cloud computing and blockchains, these computational proof-systems, which originated in the theory literature, are now being implemented and deployed also in practice. However, their widespread deployment is impeded by key bottlenecks on the theory side. The goal of the FASTPROOF project is to identify, study and mainly to resolve these bottlenecks:  1. Minimizing the amount of back and forth interaction between the prover and the verifier, aiming at proofs that are non-interactive. Non-interactive proofs offer game-changing advantages: in contrast to their interactive counterparts, such proofs can simply be posted online and shared between different clients.  2. In current proof-systems the time that it takes for a prover to prove correctness of a computation is significantly longer than the time that it takes to simply perform the computation. The second major challenge is to reduce the complexity of proving correctness to be linear in the computation time. 3. Making the memory, or space complexity, needed to generate the proof be proportional to the space requirements of the computation, in contrast to most protocols in the literature in which the space required to prove correctness is proportional to the running time of the computation.  The goal of the FASTPROOF project is to resolve these key challenges while relying on well-founded cryptographic assumptions. While the focus of this project is theoretical, we believe that it stands to have an important impact also on the future development of practical proof-systems.

Mots-clés : proof systems,interactive proofs,zero knowledge
Projet ERC : GENERALIZATION (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1433750.0 €

Recent years have witnessed tremendous progress in the field of Machine Learning (ML). Learning algorithms are applied in an ever-increasing variety of contexts, ranging from engineering challenges such as self-driving cars all the way to societal contexts involving private data. These developments pose important challenges (i) Many of the recent breakthroughs demonstrate phenomena that lack explanations, and sometimes even contradict conventional wisdom. One main reason for this is because classical ML theory adopts a worst-case perspective which is too pessimistic to explain practical ML: in reality data is rarely worst-case, and experiments indicate that often much less data is needed than predicted by traditional theory. (ii) The increase in ML applications that involve private and sensitive data highlights the need for algorithms that handle the data responsibly. While this need has been addressed by the field of Differential Privacy (DP), the cost of privacy remains poorly understood: How much more data does private learning require, compared to learning without privacy constraints? Inspired by these challenges, our guiding question is: How much data is needed for learning? Towards answering this question we aim to develop a theory of generalization which complements the traditional theory and is better fit to model real-world learning tasks. We will base it on distribution-, data-, and algorithm-dependent perspectives. These complement the distribution-free worst-case perspective of the classical theory, and are suitable for exploiting specific properties of a given learning task. We will use this theory to study various settings, including supervised, semisupervised, interactive, and private learning. We believe that this research will advance the field in terms of efficiency, reliability, and applicability. Furthermore, our work combines ideas from various areas in computer science and mathematics; we thus expect further impact outside our field.

Mots-clés : theoretical computer science,statistical learning theory,differentially private learning,mathematical models
Projet ERC : HOFGA (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université de Lisbonne — Pays : Portugal — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1039809.18 €

This is a project in Computational Complexity. The project aims to answer the following question: How hard is it to find a good algorithm for a given computational problem?  This question can be asked in several different settings, depending on what one means by "algorithm" (what is the computational model?), "computational problem" (is it a decision problem? a search problem? a communication problem?), and by "good" (do we want an algorithm that uses little time? little memory? few logical gates?).  This question has a deep connection with the problem of proving lower-bounds, and in almost every setting where the question has been answered, either the answer was discovered while attempting to prove lower-bounds, or obtaining the answer required the development of new lower-bound methods. It is also known that several variants of the above question are equivalent to fundamental open questions in cryptography, pseudorandomness, and learning theory.  The goal of this project is to answer this question in various settings where the answer is unknown: in circuit complexity, communication complexity, data structures, and algebraic models of computation. For each of these settings, we will either provide explicit methods for finding efficient algorithms, or show that the problem of finding such efficient algorithms is NP-hard.
Projet ERC : ForestFuture (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université Adam-Mickiewicz de Poznań — Pays : Pologne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1482050.0 €

The capacity of future forests to support biodiversity and deliver ecosystem services will depend on reproductive capacities that keep pace with 21st century climate change. The European continent is warming and drying out fast, and similar changes are happening word wide. The decade-scale trends in biodiversity will be governed by tree fecundity?the capacity of trees to produce seed and to disperse it to the habitats where populations can survive in the future. From the boreal to the tropical forests, including in majority of European tree species, reproduction happens through synchronized, quasi-periodic, non-stationary variation in fruit production, termed masting or mast seeding. Despite the crucial role of mast seeding in plant regeneration and wider ecological processes, our understanding of this process is rudimentary. Poor understanding of the mechanisms that govern it are challenges for anticipating alternations in forest reproduction and function. Reliable predictive models are consequently not available, and the unpredictable recruitment of trees has become a key obstacle to understanding forest change. Recruitment, including reproduction and dispersal, is the most undeveloped demographic process in Earth system models. This work will transform our understanding of mechanisms governing trees reproduction and deliver tools for predicting forest reproduction trajectories under climate change. The main outcomes will be the first experimental description of how masting emerge at proximal level, and how this is conserved among species. This will be also the first explicit test of how variation in masting patterns matters for forest regeneration trajectories. Together with analysis of global reproductive patterns, our work will deliver a step-change in identifying species and regions of special conservation care.
Projet ERC : MMS (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Tel Aviv — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2247481.0 €

Sensory input in integrated systems is expected to increase with the entrance of AI and Internet-of-Things, requiring systems to become efficient and autonomous. The proposed research aims to introduce and study a new type of smart structure, dubbed meta-structures (MS), composed of repeating a unit cell to create a structure with new abilities such as multistability, non-volatility, and configurability. Such structures can be used to design autonomous sensors with built-in memory and computational abilities, allowing the formation of a new class of smart micro-electromechanical systems (MEMS) with edge computation and in-memory programming (IMP). In the aggregate, such smart sensors can lessen the dependency on a CPU and increase the autonomy of an overall system, while enabling distributed and parallel computations. Current MEMS-based structures are mono- or bistable, and as such are limited to registering one or two values in a sensor/mechanical memory/logical gate. However, recent studies have shown that an MS can break free from a two-bit structure. Indeed, in a recent breakthrough, we have shown that in the presence of electrostatic actuation, a micro-MS becomes multi-valued, with three stable equilibria, thus opening a gateway to a paradigm shift that goes beyond the study of new structures, to the formation of new class of MEMS. This new class of MEMS will be able to incorporate mechanical-based computation with IMP capabilities. Such an unconventional approach has the potential to augment traditional capabilities, introducing new abilities such as reduced leakage and power consumption, reconfigurability, decreased footprint, as well as compatibility with harsh environments (i.e., high temperatures or electromagnetic radiation), as well as reversible computing.

Mots-clés : stability multistability bifurcations basin of attraction limit points latching chaos transient dynamics dynamic trapping nonlinear dynamics
Projet ERC : Mechano-Wolbachia (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université Jagellonne — Pays : Pologne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Animals and microbes interact in intricate ways. Wolbachia, a common intracellular insect symbiont, can manipulate reproduction and protect hosts from viruses. Thus, Wolbachia is an asset in the control of insect-borne diseases. However, as Wolbachia cannot be cultured outside of host cells or genetically manipulated, the mechanisms of its antiviral phenotype remain poorly understood, and this inhibits wider exploitation. I have been working to remedy these deficiencies, and now stand poised to discover the mechanisms of Wolbachia-conferred antiviral protection by answering the following questions: 1) Where does the protection originate? Up to now, mechanisms of protection have been studied in whole organisms, often lacking resolution, or in cultured cells, which lack emergent properties. I will identify tissues and cell types of the host where protection starts. To do this, I will: a) quantify titers of Wolbachia and virus at early time points post-viral infection in insect tissues, b) measure gene expression of host and microbes to identify candidates for further molecular characterisation, and c) test the extent of the utility of widely adopted, yet unvalidated, cell-culture models of antiviral protection. 2) Which Wolbachia genes effect protection? Wolbachia research has historically been impeded by a lack of tools to study gene function. Here, I will deploy antisense technology, which I have recently developed, to interrogate function of candidate Wolbachia genes in the native system. I will also engineer new methods to target Wolbachia genes and proteins, based on my data on cell-penetrating peptide-mediated delivery of bioactive cargo to Wolbachia. This project has two major outcomes: it will uncover Wolbachia factors responsible for Wolbachia-conferred antiviral protection, and it will transform Wolbachia and symbiosis research by creating tools to study symbiont gene function.

Mots-clés : defensive symbiosis,wolbachia,host microbe interactions,antiviral protection,antisense inhibition,transcriptomics,novel tools to study unculturable bacteria
Projet ERC : IndUncon (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université de Tel Aviv — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Consciousness is often described as the tip of the iceberg, under which a rich unconscious world exists. But is this metaphor accurate?The literature provides a mixture of contradicting findings, with some claiming that almost any cognitive function can be performed without awareness, while others arguing that unconscious processes are limited to routine, simple operations.Currently, there are two gaps in this body of knowledge, though; first, the field has almost solely examined group-level findings, without taking individual differences into account. Second, it is based on studies probing specific processes at specific time points; no study to date has tried to take a more global approach, looking for common mechanisms that persist over time, and potentially over tasks.  Here, I aim at bridging over these two gaps, providing a novel framework: I suggest that individuals consistently differ in their Susceptibility to Unconscious Processing (SUP). I hypothesize that SUP is a stable trait that can explain conflicting findings and shed new light on the interplay between conscious and unconscious processes. Starting with a task for which evidence for stable individual differences exist, I suggest three possible neural mechanisms that can explain such differences. These mechanisms will be tested using electrophysiology, neuroimaging, and developmental studies. I also introduce a novel protocol for pitting conscious and unconscious processing against each other, and biasing this competition via feedback.Finally, I will conduct a large-scale study testing the riskier hypothesis that SUP might not only be stable over time, but also across tasks.Together, this study will provide a much needed, unparalleled systematic investigation of the reliability and replicability of key findings in the field.  This research strives for a paradigmatic shift in the way we conceptualize, study and utilize unconscious processes, laying the foundations for a new science of the unconscious.

Mots-clés : unconscious processing personality traits electrophysiology neuroimaging child development
Projet ERC : AlternativeEnds (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Université Adam-Mickiewicz de Poznań — Pays : Pologne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1444600.0 €

The human genome contains only ~20.000 genes, however, most of them encode multiple transcripts resulting from alternative promoter usage, splicing, and 3’ end selection. Gene 3’ ends can be defined by the positions of RNA 3’ cleavage, or the location where RNA polymerase II terminates transcription. Alternative 3’ ends determine the properties of the encoded protein: typically its abundance, but sometimes also domain structure – as for immunoglobulin M heavy chain which is membrane-bound or secreted depending on the 3’ cleavage site. Widespread changes in 3’ end usage are characteristic of many processes e.g. differentiation and cancer like neuroblastoma. We do not understand what drives this selectivity. In this research project I will answer the fundamental question of how the location and timing of RNA polymerase II entering into termination mode impacts on the choice of the alternative cleavage and polyadenylation site (Aim 1). I will use biochemical and genetic approaches to elucidate the sequence determinant of alternative cleavage and termination (Aim 2), and investigate sequence-independent components of alternative termination (Aim 3). I recently pioneered the measurement of 3’ cleavage positions together with locations of transcription termination by a novel transcriptomic method. I will apply this method to investigate the timing of changes in cleavage and termination relative to each other on an averaged cell population level, and use a new technique to test this for single molecules. I will also determine the baseline for cleavage site selection utilizing a newly developed in vitro system. Combining those unique integrative and separation-of-function approaches will yield a comprehensive view of alternative gene end regulation. Ultimately, understanding the complex crosstalk between RNA cleavage and transcription termination in alternative 3’ end selection will enable the manipulation of this process e.g. to alleviate diseases such as neuroblastoma.

Mots-clés : transcription termination,pre mrna 3 processing,alternative polyadenylation,rna polymerase ii,pausing,human,mammalian,transcription,chromatin