Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet CoTraDy (Horizon 2020, appel à projets 2015)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Mathematics
Statut du projet : CLOSED

Complex dynamics studies the evolution of a complex manifold under the action of a holomorphic map. In this proposal we study the dynamical systems generated by transcendental (either entire or meromorphic) maps acting on the complex plane. By using a wide range of classic and new techniques, we investigates epecially the combinatorics of these maps: that is to say, we build relations between the dynamics of the transcendental map on some specific subset of the complex plane and the dynamics of the shift map on the space of infinite sequences over the integers. Combinatorics in this setting is a powerful tool to understand the dynamics of transcendental maps and to understand the structure of specific families of transcendental maps. The study of combinatorics for transcendental maps is also likely to offer new insights in the combinatorics for rational maps and possibly in other areas of complex dynamical systems, like the systems generated by the iteration of holomorphic maps on manifolds with more than one complex dimension.

Mots clés : one dimensional complex dynamical systems, holomorphic dynamics, mlc conjecture, transcendental dynamics, rigidity

Participants :
- University of Barcelona (Espagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 170121.6 €
Projet InvestorCliques (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Economic Sciences
Statut du projet : CLOSED

Complex networks theory during the last two decades has gained novel results and profound insights into many complex systems in engineering, social and biological and also financial fields. This proposed data-driven research programme will apply cross-disciplinary complex network approaches to identify investor cliques in stock markets and to explain the impact of investor behaviour on asset price dynamics. My research extends current knowledge on investor networks by focusing on the identification of investor cliques to understand how different groups of investors (i.e. cliques) drive the market in certain direction. This research helps to understand the mechanism between investor behaviour and transitions in stock markets, an important information to identify early warning signal and detect market manipulation. Also, it justifies regulators to get a better access for investor level transaction data, such unique data set we use in this project, to plan effective policies. Moreover, information diffusion in financial markets is a fundamental question, which will be addressed by this research, especially focusing on information transfer between and within investor cliques. Methodologically, the project utilizes and develops clique enumeration techniques to identify network clusters. By analyzing the structure evolution of the investor multiplex networks and cliques, I am to detect if and how the structural changes are coupled between the different layers of the network and how the changes spread over all of the market. By using Vector Autoregression, inter-dependencies among multiple time series on investor networks and stock price processes can be identified with time-lagged influences. This computationally intensive research is implemented on a parallel computation platform. I use a unique data and massive investor registration data that allows me to track investors’ trading decisions over 20 years.

Mots clés : financial engineering, big data, complex network, maximum clique

Participants :
- Tampere University (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 191325.6 €
Projet LLAMA (Horizon 2020, appel à projets 2020)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

Computational learning theory is a branch of computer science that studies the mathematical and algorithmic underpinnings of machine learning. It provides the concepts and methods to classify the computational feasibility of different learning problems. This project lies at the intersection of computational learning theory and logic, and it builds on recently identified new connections between learning theory and universal algebra. Its high-level goals are (i) to improve our understanding of learnability for fragments of first-order logic, motivated by applications in data management and knowledge representation, and (ii) to further develop and exploit the recently identified connections with universal algebra (as well as combinatorial graph theory, finite model theory, and fixed point logics), to developing a rich technical framework for proving new results. More concretely, we will study aspects of computational learning theory for fragments of first order logic under constraints (that is, in the presence of a background theory), with applications in data management and knowledge representation.

Mots clés : logic, computational learning theory

Participants :
- University of Amsterdam (Pays-Bas) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 175572.48 €
Projet AniStyle (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Computer animation is a key technology for the creative industries and has strong links to many key sectors of digital economy, including gaming and post-production. Its annual global market value is €200 billion and it is growing 7% annually. Although the European Commission has established policies and initiatives for creative industries, 60% of the global animation market is shared between the US (supported by strong finance and advanced technology) and the Asia-Pacific countries (bolstered by low labour costs). To gain market share in computer animation, the EU needs novel technologies that can produce rich content and special effects at a competitive price. This fellowship project describes how novel Animation Stylization Techniques (ASTs) can be developed to enrich content without high labour costs, by bringing to the UK a high calibre researcher with 9 patents and 28 publications. Novel ASTs are needed because most of animations stylized through suffer from various artefacts such as flickering which can only be removed via laborious manual correction. This problem encompasses the two current main trends of ASTs: mark-based and texture-based approaches, either of which allows 2D and 3D computer graphics to be converted into a wide variety of expressive styles including line drawing, pen-and-ink, cartoon, watercolour and oil painting. The central, innovative aim of this project is to develop novel computer graphics and animation approaches which not only address the issue of artefacts, but also enable creation of new styles for animation. To underpin the development, we will investigate visual factors that underlie perceived quality of stylization by developing a mathematical model to quantitatively measure the effectiveness of techniques. To date, few researchers have assessed stylization effectiveness, and their techniques of aesthetic evaluation are crude and subjective, which we believe has hindered the advance of ASTs.

Mots clés : computer animation, computer graphics, texture mapping, non photorealistic rendering, 3d modeling and animation

Participants :
- Bournemouth University (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 183454.8 €
Projet GLOBALTOX (Horizon 2020, appel à projets 2015)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

Concept: Global climate change is displayed as a set of stressors (increasing temperature and CO2 levels, decreasing soil moisture content, higher UV radiation exposure) potentially impairing both biotic and abiotic ecosystem components. This may worsen in environments degraded by human activities where organisms have to deal with multiple stress factors, i.e. in multi-stressed environments, and the toxicity of the contaminants present may change depending on climate conditions. GLOBALTOX aims at assessing how the toxicity of anthropogenic multi-stressed soils may be affected under the current global warming perspective, using soil invertebrates as bioindicators along with soil physicochemical and microbiological parameters. Methodology: An inter/multidisciplinary ecotoxicological approach will be applied to soils from different environments with high human pressure (metal mining and agricultural areas), different soil invertebrate species (collembolans and enchytraeids) and single and multiple combinations of different climate factors (air temperature, soil moisture content, atmospheric CO2 concentrations and UV radiation). Climate factor combinations will be based on the emission scenarios predicted by the IPCC by the year 2100. For a complete overview of the problem, the project will rely on changes in key soil parameters (pH, organic matter, nutrient cycling, microbial community) and soil invertebrates (body metal concentrations, enzymatic biomarkers, DNA-damage, gene expression) to understand the effects at organism/population level (survival and reproduction). Impact: The foreground derived from the project will improve the environmental risk assessment of anthropogenic-degraded areas under future scenarios of climate change. GLOBALTOX will promote the social perception and awareness of anthropogenic contamination under a global warming perspective and the suitability of using soil invertebrates as bioindicators of toxicity changes.

Mots clés : climate change, air temperature, soil moisture, atmospheric co2, uv radiation, contamination, anthropogenic degraded soils, ecotoxicology, soil invertebrates, exposure, multiple stress factors

Participants :
- University of Aveiro (Portugal) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 148635.6 €
Projet ConceptNet (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : CLOSED

Concepts are mental representations that organize experience. They are the building blocks of ideas (e.g., the thought “birds are animals” requires the knowledge of both the concepts “birds” and the concept “animal”). They enable inductive reasoning and predictive inferences which guide behavior and explanation. Some concepts are already present in infancy. These early concepts are richer than previously thought. However, much of the abstract and sophisticated concepts that make human cognition so special (e.g., scientific concepts) are not present at birth. Thus one of the most exciting challenges in psychology is to understand how abstract concepts develop. Much of the abstract concepts that form the basis of our ability to organize the world and make inferences (e.g. “animal”, “artefact”, “alive beings”) have non-observable shared properties (e.g., a cat and a flower are perceptually quite different, but both belong to the concept alive beings). Thus, the refinement of abstract concepts requires access to cultural cues, mostly via language, which provide information beyond what can be obtained through the senses.,, The goal of this project is to explore how children’s conceptual development can benefit form the language they hear around them. To capture the complexity of the linguistic input as well as the children developing conceptual knowledge, I use methods from the growing field of dynamic networks. I will carry out my research at the Institute of Complex Systems, Paris Île-de-France (ISC-PIF). I will also use the model to provide insights about how scientific concepts can be taught efficiently at school. To this end, I will collaborate with experts in science education at the secondment foundation La Main à La pâte (LAMAP), which is the leading French NGO in developing and promoting best practices in science education.

Mots clés : conceptual development, conceptual change, network science

Participants :
- Centre national de la recherche scientifique (France) — Coordinator, beneficiary, Recherche, subvention : 184707.84 €
Projet ATMCinsituNMR (Horizon 2020, appel à projets 2014)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : CLOSED

Concerns about finite energy resources and the need to decrease greenhouse gas emissions have increased the use of intermittent renewable energies on the electric grid. This is not without its challenges requiring more efficient ways to store electrical energy to balance demand with supply. Li-ion batteries (LIBs) are the most desirable form of energy storage (high energy / power densities) but an increasing demand of Li commodity chemicals combined with geographically-constrained reserves will drive up prices in the future. Due to the high abundance, low costs and very suitable redox potential, Na-ion batteries (NIBs) should open new avenues of research and engineering as complementary alternatives to LIBs. This shift has to be accompanied with a deeper understanding of the chemical reactions involving the multiple cell components. The proposed project focuses on a next step of in situ NMR spectroscopy, offering the unique possibility of non-invasive real-time studies of batteries under operating conditions – to track the formation of intermediate phases and investigate electrolyte decomposition during cycling of LIBs and NIBs. Significantly different shifts of the multi-component samples, resonance broadening as well as interferences of the NMR and external battery cycler (EBC) circuit impair the experiments. Hence, we will set up a novel NMR probe system allowing “on-the-fly” adjustment of the NMR circuit during the measurement and sample orientation changes via an automated goniometer. Moreover, an entirely new NMR-EBC-connection design will benefit the real-time experiments. This next level Automatic Tuning Matching Cycler (plus Goniometer) – ATMC(+G) – in situ NMR approach will be established in a comparative study on lithium vs. sodium iron phosphate cathodes in LIBs and NIBs, respectively, including the application of new electrolytes to improve battery safety and cost factors. The application to a wider range of systems will include Na-Sn anodes for NIBs.

Mots clés : energy storage, energy materials, lithium ion batteries, sodium ion batteries, in situ nmr, automating, paramagnetism, bms effect, lifepo4, nafepo4, naxsn

Participants :
- University of Cambridge (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 183454.8 €
Projet VeSPA (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Concurrent computation, organised as a decentralised collection of interacting components, is now ubiquitous. Our society increasingly relies on such systems for sensitive and critical infrastructure: to make this safe and sustainable we need a formal approach to analyse and certify the correctness of concurrent software. Our trust in concurrent systems is based on three key properties: 1. Safety: can the system crash? 2. Progress: will the system be reactive to requests? 3. Security: no secret is ever leaked. Proving such properties of concurrent systems must take into consideration all possible executions, a space is so huge and complex that we lack proper tools to reason about it, both manually and automatically. This is called the analysis scalability problem. While the case of Safety has been extensively studied, Progress and Security still lack a scalable methodology for verification. The VeSPA project attacks the analysis scalability problem for Progress and Security, from the point of view of Specification. Good specifications enable true encapsulation of behaviour in the reasoning, addressing scalability by allowing correctness proofs to be more modular and organised in layers of abstractions. VeSPA will reach this goal by: 1) studying specifications for verification of progress in fine-grained blocking concurrent programs (building on Gardner's work); 2) apply this specification theory to the industrial case of the Erlang programming language (building on D'Osualdo's experience); and 3) develop a compositional verification method for security protocols (advancing recent work of D'Osualdo) The approach of VeSPA incorporates work in neighbouring but disjoint sub-fields of Concurrency Theory (automata theory, process algebra, type systems and software specification) bringing together the unique expertise of Dr. D'Osualdo and Prof. Gardner, unifying and generalising the approaches.

Mots clés : verification, liveness, separation logics, linearizability

Participants :
- Imperial College London (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 195454.8 €
Projet Operation Condor (Horizon 2020, appel à projets 2015)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Social Sciences and Humanities
Statut du projet : CLOSED

Confronting past atrocities is essential to consolidate democracy and human rights protection. Truth and justice initiatives investigating crimes perpetrated at the national level have long been occurring. Yet, accountability for transnational crimes is a pending issue in scholarship and practice. This project fills this gap and addresses the transnational dimension of past atrocities in South America. In 1975, the dictatorships of Argentina, Bolivia, Brazil, Chile, Paraguay, and Uruguay established a secret transnational network of intelligence and counterinsurgency operations to persecute political opponents in exile called Operation Condor, kidnapping and murdering hundreds of people. The project aims to study transnational crimes, by focusing on Operation Condor’s Uruguayan victims, and probe the response of Uruguay’s national justice system to transnational atrocities. Uruguay was selected to analyse Operation Condor: one Uruguayan was kidnapped in each Condor country; thus, investigating its Uruguayan victims permits to also study the entire network and its modus operandi. The project creatively adopts a regional focus and uses data from recently opened archives. The broader question behind the research agenda is: how can we respond to atrocities that transcend state borders? Studying accountability for Operation Condor crimes will offer lessons of potential application to past and present forms of transnational crimes, such as the smuggling of migrants across the Mediterranean Sea. The outputs include three articles, a book, a policy brief, op-eds, a workshop for legal professionals, seminar and conference presentations, and training sessions for PhD students and early career researchers. The Fellowship will directly benefit Dr Lessa’s career prospects, equipping her with new skills, knowledge, and specialised training in archival research and analysis of case files, placing her at the forefront of her field as an established interdisciplinary researcher.

Mots clés : transitional justice, transnational crimes, south america, uruguay, accountability

Participants :
- University of Buenos Aires (Argentine) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- University of the Republic (Uruguay) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- University of Oxford (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 212463.0 €
Projet SENSHOR (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Chemistry
Statut du projet : CLOSED

Connected devices that monitor human biology in real-time represent the next frontier in biosensors. Monitoring hormones is of significant interest as hormones play critical roles in multiple physiological processes including stress adaptation, blood pressure control, reproductive rhythms, and body odor. However, the real-time monitoring of hormones is challenging from a biology, chemistry, and engineering perspective, insulin detection being the one notable success. This project proposes to design a novel wearable device to sense estradiol (through sweat), a hormone responsible for fertility issues and mood disorders in women. This project is highly innovative and ambitious since it combines microbial genetics and protein identification, new polymer and nanoparticles compositions, and a novel sensor design. The wearable device (i.e., bracelet) will contain an optical-to-electrical interface for recording the fluorescence output of a biosensor, based on estradiol sensitive transcription factor isolated from a microbial organism. The biosensor is composed of biopolymers (dendrimers and polypeptides nanoparticles) functionalized with fluorescent molecular beacons (MB) and a hormone-sensitive transcription factor. Without the hormone, the two fluorescent entities of the MB are linked by the protein and no signal is emitted because of fluorescence resonance energy transfer (FRET), while in the presence of estradiol, the MB separate and a fluorescent signal is emitted. The project will be conducted in two international prestigious laboratories in France and in the USA to give to the applicant the best interdisciplinary scientific environment, and ensure the ultimate success of this project. The applicant will be the main spokesperson and lead investigator of the project. This international exposure and this fellowship will provide the applicant a unique and multidisciplinary profile, while facilitating her future academic career as a researcher in France.

Mots clés : biosensor, hydrogel, connected device, polypeptide, dendrimer, molecular beacon, bioengineering, synthesis, hormone

Participants :
- Boston University (Etats-Unis) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Bordeaux (France) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 264668.4 €