Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet Disconnect2Reconnect (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

Mobile devices, and the ‘always on’ connectivity they enable via numerous social media services, are increasingly blamed for a decline in well-being among young people. In today’s ‘poly-social-media’ landscape where people often make use of multiple platforms for different purposes, the increasing pressure to check updates combined with an overload of information available can lead to increased emotional exhaustion and declines in physical health (e.g., sleep disturbance). Consequently, there is a growing trend of users desiring to disconnect from or to use social media more mindfully, but many struggle to do so effectively. While the idea of ‘digital detoxes’ is increasingly adverted in mainstream media and gaining public popularity, academic research is still in its infancy. This is problematic, as ‘social media fatigue’ – a state whereby people suffer from mental exhaustion after experiencing technological, informative and communicative overloads through their participation different social media platforms – might become a serious mental health issue due to the ubiquitous nature of mobile and social media. Fostering citizen’s digital competences and skills to effectively navigate digital society highly fits with the aims and scope of the European Commission’s 21st century ‘Digital Competence Framework’. Using a multi-method approach, combining mobile experience sampling methods and panel surveys, this action develops and tests a theory-driven model to explain the antecedents of social media fatigue, the strategies people use to disconnect from social media, and the short-term and long-term consequences for subjective well-being among young adults. The resulting Disconnect2Reconnect model advances theory and methods, offers actionable recommendations to practitioners on mindful media use in an increasingly digital society, and is fundamental for developing tailored guidelines and educational interventions to promote healthy media use and digital well-being.

Mots clés : social media, mobile communication, disconnection, health, well being, experience sampling methods, panel survey

Participants :
- University of Zurich (Suisse) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 203149.44 €
Projet NomadicN (Horizon 2020, appel à projets 2015)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

Mobile pastoral systems, despite being highly adaptive to harsh and unpredictable environments, are faced with increasing challenges worldwide, due – among other factors – to a fast extension of irrigated agriculture and a fragmentation of landscapes. Understanding how they react and adapt to these changes is a key contemporary issue, concerning almost every region in the world, including Europe. The aim of the NomadicN project is to increase our understanding of the complex processes at play when mobile pastoralists navigate across fast-changing densely-cultivated landscapes. For this, we will develop a new approach to the analysis of the pastoral movements, by integrating into a single framework data on ecological variations and data on the social interactions that are necessary to mediate access to privately-owned resources. The objectives of the project are a) to identify the key ecological and social processes that underlie the migration dynamic, b) to analyze how these two sets of drivers interact and influence the decision-making process along migration stages, and c) to study, at the landscape scale, how the intertwinement of these processes shapes – or not - the mobility patterns of transhumant groups and how it affects their resilience. By enabling mobility to an outstanding research centre, this fellowship will allow the applicant to benefit from a multidisciplinary range of expertises to successfully implement the envisioned research and receive high-level training in state-of-the-art methods. The foreseen stay will effectively strenghten his academic profile and foster the developpement of an independant academic career. The close and complementary interests and skills of the host and the applicant will set the ground for fruitful future collaborations and scientific exchanges.

Mots clés : interdisciplinary, movement ecology, niche construction, nomadic peoples, social network analysis

Participants :
- Centre national de la recherche scientifique (France) — Coordinator, beneficiary, Recherche, subvention : 185076.0 €
Projet ReConDa (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Model predictive control (MPC) is widely used in process industries to control constrained systems with multiple input and outputs. Traditionally, the MPC is used in a two layer architecture where the upper layer gives the economic optimal operating point and the MPC is used in the lower layer tracks the optimal operating point. Recent studies shows that a significant improvement in the economic performance of the plant can be obtained if both the layers are combined together. One of the pressing issues preventing the process industries from adopting the aforementioned control scheme is the presence of plant-model mismatch. The work on this project uses ideas form the linear control theory to handle the structural plant-model mismatch in a robust NMPC framework, efficiently. We develop a model-error model (MEM) which uses plant measurements to improve the knowledge of the plant. We focus on developing a systematic way of choosing the MEM structure based on the data collected from an industrial production plant and use them for monitoring and control purposes. We develop an algorithm which works in parallel with the commercially available advanced process control solutions and makes them robust to plant model mismatch. Our project builds a computationally tractable scheme for model-based NMPC robust against the plant-model mismatch. As a result, a safe, reliable and resource-efficient operation is established. The theoretical developments of the project are implemented into a software package and released as an open-source project such that the collaboration with academia and industrial stakeholders is fostered. A demonstration on an industrial production plant and a laboratory pilot plant is also planned to showcase the benefits of the developed techniques in the real-world environment. A sound dissemination plan of the project ensures that the project reaches its target audience.

Mots clés : predictive control, robust control, optimal control, chemical process control, data based learning

Participants :
- Slovak University of Technology in Bratislava (Slovaquie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 155364.48 €
Projet MAGNET (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Mathematics
Statut du projet : CLOSED

Models and Algorithms for Graph centrality grounded on Nonlinear Eigenvalues Techniques The main objective of the project is to use nonlinear eigenvalue equations to model the importance of components in complex, large-scale and time-varying networks. Based on the nonlinear Perron-Frobenius theory, we will develop the theory to rigorously formalize the model from a mathematical viewpoint (existence, uniqueness, maximality). Based on the nonlinear spectral method for multi-homogeneous functions, we will develop numerical methods to compute the vector of nonlinear importances of the nodes. We will develop convergence analysis and quality guarantees for the algorithms and will use the methods to investigate the influence of nodes in large-scale networks arising from real-world applications. These theoretical and algorithmic advances will contribute the highly active research field of network centrality. Current tools for network centrality are based on linear models, and they can be shown to be inadequate in many realistic scenarios. The new methods developed here will have provably better performance. In addition to theoretical validation, the tools will be tested and refined on realistic data sets supplied by collaborators and external partners associated with the Institute for Future Cities at the University of Strathclyde. The Researcher's expertise include nonlinear eigenvalue theory, graph theory and their use in machine learning. The Host and the research group at University of Strathclyde have strong internationally recognized experience in mathematics of network science and numerical mathematics. Thus the two-way transfer of knowledge will ensure to reach the research goals with highest quality and impact. Moreover, this will represent a great training opportunity for the researcher to jump-start his academic career.

Mots clés : networks, centrality, nonlinear eigenvalues, perron frobenius

Participants :
- University of Strathclyde (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 183454.8 €
Projet N2N (Horizon 2020, appel à projets 2017)
Action : Doctoral Networks - Industrial Doctorates
Panel : Information Science and Engineering
Statut du projet : CLOSED

Modern aeronautical structures are increasingly made of composite materials due to their well-known benefits. Despite their superior structural characteristics, composite structures exhibit poor dynamic and acoustic isolation levels compared to conventional metallic ones. As a result and in order to maintain the comfort levels in the passenger and payload compartments within acceptable limits, additional acoustic and vibrational isolation technologies (sound packages) are necessary in several transport applications. If non-optimally designed for a certain application, these sound packages can add substantial weight to the structure, compromising the weight benefits gained by the employment of composites. The aforementioned challenges imply an urgent and genuine need for development of lightweight and multifunctional structures, for modern industrial transport applications. The N2N Training Network aims at developing a high-fidelity and efficient Multidisciplinary Design Optimization (MDO) scheme for multifunctional composites having poroelastic inclusions and combining minimum mass with maximum damping and comfort levels. On the research side, N2N will focus on developing multiscale models for obtaining a comprehensive description of random poroelastic materials coupled to a composite structural segment. Understanding the interaction of acoustic waves with such complex materials is another scientific challenge that the Network will tackle. N2N aims at developing reliable tools for providing accurate optimal designs for multifunctional composite structures that combine lightweight properties with exceptional acoustic and vibration isolation. On the training side, N2N will provide a fully supportive environment for 3 ESRs. A training programme aiming at developing both the research as well as the transferable skills of the Fellows has been designed. All Fellows will have the opportunity to work in a multidisciplinary (industrial and academic) research environments.

Mots clés : vibroacoustics, poroelastic materials, multidisciplinary optimization, composite structures

Participants :
- Matelys-research lab (France) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 262875.6 €
- University of Bristol (Royaume-Uni) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Sherbrooke (Canada) — Partner, organization partner, Organismes privés (hors enseignement), subvention : 0.0 €
- École nationale des travaux publics de l'État (France) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- UNSW Sydney (Australie) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- University of Nottingham (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 546575.76 €
Projet OptiMACS (Horizon 2020, appel à projets 2017)
Action : Doctoral Networks - Industrial Doctorates
Panel : Information Science and Engineering
Statut du projet : CLOSED

Modern aeronautical structures are increasingly made of composite materials due to their well-known benefits. Optimizing the design of aerospace composites vis-à-vis the entire range of operational constraints (i.e. reliability, stability, strength, weight, noise, manufacturability and cost) to which the aircraft structures are subject, results in a particularly challenging task for the structural designer. Despite the volume of recent work dedicated to new Multidisciplinary Design Optimization (MDO) models and techniques, the ‘No free lunch theorem in optimisation’ is constantly confirmed. A genuine need is therefore identified for a programme that will: i)Develop, deliver and implement novel and efficient structural MDO technological tools for the European aerospace industry, ii)Nurture and train the next European generation of MDO research professionals. OptiMACS has an intersectoral character, drawing know-how from both academic and industrial research and innovation teams. It also has an intensely multi-disciplinary character, coupling expertise from mechanical, aerospace, manufacturing and software engineering, as well as from the area of applied mathematics. On the research side, OptiMACS will focus on improving the accuracy and efficiency of the MDO platform currently employed by AIRBUS. This will be achieved by enhancing the design models and criteria related to composites failure and manufacturing, developing and implementing multiscale models for composites as well as investigating advanced MDO algorithms and architectures for enhancing efficiency. On the training side, OptiMACS will provide a fully supportive environment for 5 ESRs. A training programme aiming at developing both the research as well as the transferable skills of the Fellows has been designed. All Fellows will have the opportunity to work in a multi-disciplinary environment, spending at least 50% of their time at the premises of the industrial beneficiaries.

Mots clés : multidisciplinary design optimization, industrial composite structures, multiscale modelling, efficient optimization architectures

Participants :
- Airbus (Germany) (Allemagne) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 492964.04 €
- University of Porto (Portugal) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 119178.18 €
- RISC Software (Austria) (Autriche) — Partner, beneficiary, Recherche, subvention : 142185.6 €
- University of Nottingham (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 498902.21 €
Projet GREENEDGE (Horizon 2020, appel à projets 2020)
Action : Doctoral Networks
Panel : Information Science and Engineering
Statut du projet : SIGNED

Modern communication networks are rapidly evolving into sophisticated systems combining communication and computing capabilities. Computation at the network edge is key to supporting many emerging applications, from extended reality to smart health, smart cities, smart factories and autonomous driving. Multi-access edge computing (MEC) technology is being developed to deliver the required computation functionalities closer to user devices, directly at mobile access points. GREENEDGE is motivated by the fact that the large scale adoption of MEC technology, while benefiting human productivity and efficiency, will result in a surge of data and computation in mobile networks, which, in turn, will exacerbate their energy consumption. GREENEDGE is set out to tame the growing carbon footprint of MEC technology, devising highly energy efficient communication and computing functionalities for the network edge, combining them with ambient energy sources and with new energy storage and supply paradigms. As a result, GREENEDGE technology will allow mobile systems to offer the much anticipated communication and computing services in a sustainable manner. Fifteen early stage researchers (ESRs) will be trained by a consortium of world-class leaders across the fields of energy harvesting, storage, edge computing, optimization, machine learning and wireless communications. Ample inter-sectoral opportunities will be offered thanks to secondments among academy/research centers, two network operators, and other prominent industrial partners operating in the domains of Internet of Things, smart cities, critical infrastructure management and data analytics. A carefully planned and coordinated training and research program will ensure excellent employability prospects for the ESRs after the project completion.

Mots clés : edge computing, energy sustainability, ambient energy harvesting, mobile communication networks

Participants :
- CERCA Institution (Espagne) — Partner, beneficiary, Recherche, subvention : 752714.64 €
- Worldsensing (Spain) (Espagne) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 250904.88 €
- KU Leuven (Belgique) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 512640.0 €
- University of Padua (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 784499.04 €
- Commissariat à l’énergie atomique et aux énergies alternatives (France) — Partner, beneficiary, Recherche, subvention : 549604.08 €
- Toshiba (United Kingdom) (Royaume-Uni) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 303172.56 €
- University of Oulu (Finlande) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 280805.76 €
- Imperial College London (Royaume-Uni) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 606345.12 €
Projet RCADE (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Modern computing devices execute complex software to provide every-day services and applications. The development of such software is challenging, time consuming and costly. It involves writing a program code, testing it and debugging it, namely finding an error in the code and correcting it. It is estimated that debugging costs an estimated 312 billion USD a year. The most successful commercial debugging tools are reversible debuggers. They allow the users to undo an execution of a faulty program, to find and correct errors, and then to run the corrected code forwards again. UndoDB by Undo Software is the top reversible debugger currently on the market. However, even the best reversible debuggers are not suited very well to debugging of concurrent programs. Moreover, it is not universally agreed yet how to reverse the code of concurrent or distributed software. This project aims at addressing these shortcomings by exploiting the promising notion of causally-consistent reversibility as the basis for reversible debugging tools. Novel formal models and new techniques for recording, analysis and replay of concurrent programs will be created. An execution engine for the shared-memory and message-passing styles of programs will be developed in a close collaboration with Undo Software and Erlang Solutions, the leading software companies. The scientific outcomes will be turned into an experimental prototype software, called Reversible CAusally-consistent DEbugger (RCADE), which will extend and enhance commercial debugging tools, especially for concurrency. The Fellow will undertake a world-class programme of research, industrial and academic training and collaboration. He will obtain formal lecturer qualification and deliver an undergraduate module. The knowledge and experience gained on the fellowship will be transferred to academia and industry in Europe. The project will develop his scientific independence, create a new network and enforce a senior academic position.

Mots clés : debugging, reversible computation, concurrency, debugging software tools, process calculi, logics

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

Modern laser microsurgery requires compact ultrafast laser sources and miniature fibre-optic probes. The aim of this project is to develop the world’s first scanner-free and ultra-thin (<1mm) single multimode optical fibre scalpel to perform image-guided high-precision microsurgery. In this timely project, we will tackle the key challenges in the field of laser microsurgery: i) The lack of robust and compact ultrafast laser sources; ii) bulky laser-pulse delivery probes; and iii) the lack of simultaneous high-resolution imaging modalities to guide the surgery. In this proposed research, the Fellow will first develop a new dissipative-soliton-resonance (DSR) ultrafast fibre laser and will then integrate the DSR laser to the single multimode fibre imaging system in the supervisor’s group. This multidisciplinary research is expected to make new advancements and discoveries in a number of emerging topics at the forefront of Photonics, such as DSR ultrafast fibre laser technology, single multimode fibre imaging, and ultrafast laser microsurgery. In addition, the results arising from nonlinear imaging (two-photon and second-harmonic-generation imaging) of the biological tissue and ultrafast-laser-tissue interaction will inform clinical and biomedical research on biomaterials properties and disease pathology. These are central to the research theme priority of personalising health and care in Horizon 2020 - producing knowledge that will be applied in the area of health and medicine. The commercial value of the new ultrafast fibre-based light sources and the medical instrument for in-vivo endoscopic imaging and microsurgery will also be explored during this project.

Mots clés : fibre optics, optical fibre laser, optical imaging, laser surgery

Participants :
- University of London (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 195454.8 €