Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
High-order Numerical Schemes for Kinetic Models with Applications in Plasma Physics (HNSKMAP)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Mathematics
Countries involved: France,France
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-02-01
End date: 2018-01-31
Duration (months): 24.0
Total project cost (EUR): 185076.0
EU funding (EUR): 185076.0
Participants: 2
Project status: CLOSED

In the proposed research, we will devote to the mathematical and numerical analysis of kinetic models. Kinetic theory has wide applications in physical and social sciences, such as plasma physics, semi-conductors, polymers, traffic networking etc. On the one hand, we want to propose and analyse systematic numerical methods for nonlinear kinetic models which have some challenging difficulties such as physical conservations, asymptotic regimes and stiffness. On the other hand, applications to plasma physics will be investigated, which are mainly high dimensional problems with multi-scale and complex geometries. Moreover collisions between particles for large time scale simulation need to be taken into account. We would like to develop a class of less dissipative high order Hermite methods together with weighted essentially non-oscillatory (WENO) reconstructions to control spurious numerical oscillations, and high order asymptotic preserving (AP) discontinuous Galerkin (DG) schemes with implicit-explicit (IMEX) time discretizations for multi-scale stiff problems under unresolved meshes. More importantly, these developed numerical methods would satisfy the positivity preserving (PP) principle, such as positive density distribution functions for kinetic descriptions, which is often violated by high order numerical methods with physical meaningless values. This project will combine the expertise of the Experienced Researcher Dr. Tao Xiong in high order PP flux limiters and high order AP DG-IMEX schemes, and the Host Dr. Francis Filbet in mathematical modellings and numerical tools for kinetic equations. The developed approaches will be translated to the study of turbulent plasma physics such as 4D drift kinetic, 5D gyro-kinetic and 6D kinetic models etc.

Keywords: numerical scheme,kinetic model,plasma physics,high order,vlasov boltzmann,imex,hermite weno,positivity preserving
CO2 capture from cement production (CEMCAP)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Low-cost, low-carbon energy supply
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Germany,Germany,Germany,Germany,Germany,Italy,Spain,Italy,Switzerland,Norway,Sweden,Norway,United States,Netherlands
Call: Enabling decarbonisation of the fossil fuel-based power sector and energy intensive industry through CCS (H2020-LCE-2014-1, 2014)
Start date: 2015-05-01
End date: 2018-10-31
Duration (months): 42.0
Total project cost (EUR): 9976415.57
EU funding (EUR): 8778701.0
Participants: 18
Project status: CLOSED

The European cement industry has committed itself to contributing to climate protection measures and therefore to curbing its CO2 emissions. CO2 capture technologies, although an essential part of all CO2 reduction scenarios, are not yet ready for large-scale deployment in the cement industry. Hence, the primary objective of CEMCAP is To prepare the ground for large-scale implementation of CO2 capture in the European cement industry To achieve this objective, CEMCAP will - Leverage to TRL 6 for cement plants the oxyfuel capture technology and three fundamentally different post combustion capture technologies, all of them with a targeted capture rate of 90%. - Identify the CO2 capture technologies with the greatest potential to be retrofitted to existing cement plants in a cost- and resource-effective manner, maintaining product quality and environmental compatibility. - Formulate a techno-economic decision-basis for CO2 capture implementation in the cement industry, where the current uncertainty regarding CO2 capture cost is reduced by at least 50%. For successful large-scale deployment of CO2 capture in the cement industry, technologies must be developed beyond the current state of the art. In order to bring the most high-potential retrofittable CO2 capture technologies to a higher TRL level and closer to implementation, CEMCAP will - Describe the routes for the development required to close technology gaps for CO2 capture from cement and assist technology suppliers along the related innovation chains. - Identify and follow up minimum five potential innovations springing from CEMCAP research. Technologies suitable for CO2 capture retrofit are focused on in CEMCAP, because cement plants typically have a lifetime of as long as 30-50 years. However, the results from CEMCAP will enable looking beyond this horizon. Therefore, CEMCAP will - Create pathways for the low to near-zero CO2 emission cement production of the future.

Keywords: co2 capture,cement production,energy intensive industries
National institutional autonomy within the EU legal order: uncovering and addressing its distinctive appearances, origins and impact on Member States' administrations (EUDAIMONIA)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: Belgium
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-09-01
End date: 2026-08-31
Duration (months): 60.0
Total project cost (EUR): 1497687.0
EU funding (EUR): 1497687.0
Participants: 1
Project status: SIGNED

Despite significant advancements in European integration, the institutional design and organisation of administrative structures implementing and enforcing EU law had traditionally remained the responsibility of EU Member States. Over the past decade, however, EU legislation has increasingly come to impose more organisational requirements on those Member States’ administrative structures. That evolution is most remarkable as EU law has long recognised the existence of a principle of national institutional/administrative autonomy. That principle is to guarantee Member States’ freedom to designate and structure the administrative bodies responsible for the application and enforcement of EU rules. How far does the EU’s more extensive involvement in Member States’ administrative design decisions actually reach and can one find parallels between different fields of regulation? If so or if not, what are the implications for our understanding of institutional autonomy as a principle of EU (administrative) law? So far, legal scholarship, including the PI’s previous work on EU market supervision, has paid only scarce attention to those important questions. The principal objective of this project will be to analyse the scope of Member States’ administrative autonomy and to uncover, explain and conceptualise the limits that are imposed on it by EU law. To do so, it will first of all map and compare EU law’s influence over Member States’ administrative designs across 18 domains of regulation influenced by the EU. Since the traditional legal scholarship toolkit insufficiently allows to grasp the different factors having given rise to Member States’ administrative design decisions, the project will subsequently rely on actor-network theory (ANT) to uncover those factors. Using that particular research methodology, new and more extensive data obtained through in-depth case studies and questionnaires will allow to formulate theoretical modifications and policy recommendations.

Keywords: european union law,institutional,administrative autonomy,relationship with member states,principles of law,actor network theory,comparative law
Large-Scale Learning with Deep Kernel Machines (SOLARIS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: France
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-03-01
End date: 2022-02-28
Duration (months): 60.0
Total project cost (EUR): 1498465.0
EU funding (EUR): 1498465.0
Participants: 1
Project status: CLOSED

Machine learning has become a key part of scientific fields that produce a massive amount of data and that are in dire need of scalable tools to automatically make sense of it. Unfortunately, classical statistical modeling has often become impractical due to recent shifts in the amount of data to process, and in the high complexity and large size of models that are able to take advantage of massive data. The promise of SOLARIS is to invent a new generation of machine learning models that fulfill the current needs of large-scale data analysis: high scalability, ability to deal with huge-dimensional models, fast learning, easiness of use, and adaptivity to various data structures. To achieve the expected breakthroughs, our angle of attack consists of novel optimization techniques for solving large-scale problems and a new learning paradigm called deep kernel machine. This paradigm marries two schools of thought that have been considered so far to have little overlap: kernel methods and deep learning. The former is associated with a well-understood theory and methodology but lacks scalability, whereas the latter has obtained significant success on large-scale prediction problems, notably in computer vision. Deep kernel machines will lead to theoretical and practical breakthroughs in machine learning and related fields. For instance, convolutional neural networks were invented more than two decades ago and are today’s state of the art for image classification. Yet, theoretical foundations and principled methodology for these deep networks are nowhere to be found. The project will address such fundamental issues, and its results are expected to make deep networks simpler to design, easier to use, and faster to train. It will also leverage the ability of kernels to model invariance and work with a large class of structured data such as graphs and sequences, leading to a broad scope of applications with potentially groundbreaking advances in diverse scientific fields.

Keywords: deep learning,kernel methods,large scale optimization
Defining the role of lysosomal trafficking in age-associated anabolic resistance in human skeletal muscle (LYSOTRACK)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-09-01
End date: 2018-08-31
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The reduced ability of skeletal muscle to grow, termed anabolic resistance (AR), is thought to be a major cause of age-associated muscle loss (sarcopenia). At the cellular level, AR is caused by an impaired activation of the protein kinase mTORC1, which in turn blunts protein synthetic responses to anabolic stimuli. Lysosomal trafficking is critical for the full activation of mTORC1, with the blocking of this event creating anabolic resistance in otherwise healthy cells. However, to date, this phenomenon has not been examined in human skeletal muscle. Therefore, our working hypothesis is that alterations in lysosomal trafficking may be an underlying mechanism to explain impaired mTORC1 activity and AR in elderly individuals. To address this hypothesis, we will define, for the first time, the role and regulation of lysosomal trafficking in age-associated AR in human skeletal muscle. Through a combination of in-vitro and in vivo studies we will examine (1) whether genetic induction of lysosomal trafficking can activate mTORC1 and overcome chemical/nutrient induced AR in human primary myotubes, (2) whether genetic knockdown of proteins that stimulate lysosomal trafficking can inhibit mTORC1 activity and cause AR, and (3) examine whether lysosomal trafficking differs between young and elderly subjects, in vivo, in response to anabolic stimuli such as amino acids and resistance exercise. The importance of this work should not be understated, given that the number of individuals aged over 60 and 80 years is expected to triple and quadruple respectively by 2050. By advancing the understanding of why elderly individuals exhibit AR and how this phenomenon may contribute to the development of sarcopenia, the work proposed herein has great potential for the development of novel therapeutic approaches to prevent or reduce the occurrence of AR, reduce the severity of sarcopenia which in turn will dramatically improve quality of life.

Keywords: muscle wasting,sarcopenia,anabolic resistance,lysosomal trafficking,muscle protein synthesis in ageing,mtorc1 localisation
Spatial super-resolution of electrophysiological measurements (NETEEG)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Israel
Call: ERC Proof of Concept Grant (ERC-2014-PoC, 2014)
Start date: 2015-04-01
End date: 2016-09-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Electroencephalography (EEG) is the non-invasive recording of electrical brain activity, and is an indispensable diagnostic and research tool. A significant advantage of EEG compared to other brain imaging modalities is its high temporal resolution. The downside of EEG is, however, its poor spatial resolution, which is one of the reasons for its gradual replacement by costlier alternatives. It results mainly from the sharp discontinuity in the electric conductivity of the skull bones acting as a strong low-pass filter and limiting the amount meaningful information that can be extracted from EEG signals. We propose a novel concept of EEG measurement hardware which, in combination with signal processing techniques, will increase the spatial resolution of EEG by as much as an order of magnitude. Our idea is based on the observation that by connecting a dynamic network of controllable impedances between pairs of measurement electrodes, one can alter the shape of the spatial filter constituted by the skull. Since EEG is a relatively narrow-band signal (about 100Hz, limited by the time constants of basics units of neural activity), we expect to be able to measure tens or hundreds of different configurations of the network, either directly or by using a compressed sampling scheme, without compromising the temporal resolution. This will introduce many independent equations to the EEG inverse problem and improve source estimation, having critical impact on the diagnostic capabilities of EEG as well as on its use in emerging applications such as neuro-feedback and brain-computer interface (BCI).

Keywords: inverse problem,compressed sensing
Neither Dwarf nor Leviathan: Explaining Territorial and Functional Variation in State Capacity (STATE CAPACITY)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Netherlands,United States
Call: Marie Skłodowska-Curie Individual Fellowships (IF-GF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-07-01
End date: 2018-12-30
Duration (months): 24.0
Total project cost (EUR): 174864.6
EU funding (EUR): 174864.6
Participants: 2
Project status: CLOSED

Citizens live longer, happier lives where states are able to perform their core functions effectively. Even though weak states have received considerable attention from scholars and policy-makers, the concept of state weakness has remained under-theorized. The shortcomings of current conceptualizations are revealed by mounting empirical evidence that (1) state capacity does not extend homogeneously across national territories and (2) that a state’s capacity to control and coerce citizens is distinct from its capacity to care for them by providing education and public health. Previous work mostly assumed that the reason why states do not exercise coercion and care throughout the territory is simply their inability to do so. This perspective, however, cannot explain why states invest more in building capacity in some regions than in others, or why coercive and caring capacity are geographically uneven. To understand this, it is crucial to acknowledge that states in the developing world can and do invest in building capacity, but are also confronted with the need to ration resources. This project conducts a subnational comparative analysis of Mexico, which scores well on conventional measures of state capacity, but is perceived by some security experts as critically weak. The project’s research aims are twofold: 1) To conceptualize and map intra-country differences on the basis of a new geo-referenced dataset of infrastructure for coercion and care (empirical goal) 2) To theorize and explain the state’s decision to invest resources in a hospital, school, police station or military barracks in a specific place (analytical goal) To accomplish these goals, the applicant will participate in advanced training in Geographic Information Systems (GIS) at the University of California, San Diego, a leader for the collection and analysis of spatial data. The acquired skills will strengthen the emerging GIS expertise at the University of Amsterdam, which houses the return phase.

Keywords: political science,state capacity,weak states,political institutions,subnational comparative method,latin america
ATMOSPHERIC IMPACT CALCULATOR ENGINE FOR AIR TRAFFIC MANAGEMENT (ICE4ATM) (ICE4ATM)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-11-01
End date: 2021-10-31
Duration (months): 24.0
Total project cost (EUR): 1739375.0
EU funding (EUR): 1212563.0
Participants: 1
Project status: CLOSED

Atmospheric dispersion of hazardous substances (mainly volcanic ash, but also mineral dust or SO2) influences many economic markets, and poses a variety of problems to the aviation industry. For example, the presence of airborne volcanic ash at low and jet-cruise atmospheric levels compromises the safety of aircraft operations and forces delays, cancelations and/or re-routing of aircraft to prevent encounters with volcanic ash clouds. Volcanic eruptions are recurrent events with more that 500 active volcanoes and an average of 80 eruptions a day affecting the aviation industry. Despite the existing demand for solutions capable to evaluate and manage these natural hazards, and to provide credible operational expertise to improve risk management across multiple industries, to date, no commercial product is available in the market to solve these problems. MITIGA Solutions (www.mitigasolutions.com) is a firm specialized in evaluating and mitigating the impacts of volcanic eruptions for the aviation industry. MITIGA develops and commercializes, amongst others, products to quantify volcanic risks in order to improve air traffic management, insurability and urban resilience. In particular, MITIGA specializes in the development of the first operational system (ICE4ATM: Solutions on Real Time for Air Traffic Management) to forecast and mitigate the impact of volcanic ash across different aviation stakeholders in real-time. MITIGA’s core members have a wide experience and expertise in developing and implementing local and regional modeling systems for quantifying impacts of volcanic hazards and provide support to volcanic risk reduction and disaster management. MITIGA Solutions is a spin-off of the Barcelona Supercomputing Center (www.bsc.es), a world renamed institution with over two decades of experience in developing and implementing models in the fields of geophysics, volcanology and atmospheric impacts.

Keywords: volcanic hazards,early warnings systems,aviation,atmospheric dispersion,numerical simulations,operational systems,risk management
To leave or to stay? Rethinking the mobility of young people in Brazil (MigYouBra)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Portugal,Brazil
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-09-01
End date: 2024-08-31
Duration (months): 36.0
Total project cost (EUR): 237768.0
EU funding (EUR): 237768.0
Participants: 2
Project status: SIGNED

The recent migration research agenda emphasises the need to advance the conceptual framework to understand the unique circumstances of the “generation on the move”. In particular, researchers in the field stress the need to connect research on youth and migration studies. Research on immobility is also required to overcome the “mobility bias” that persists in migration studies. The central proposition of the MigYouBra project is to explore how young people in the Global South decide and manage to "stay put" in a context of high transnational mobility and how they perceive the desirability of staying put compared with that of migrating. The research will examine the different ways of staying put, investigating the motivations, degree of (in)voluntariness, and narratives of young people who remain. The project will be centered on Governador Valadares, the “national capital” of transnational migration in Brazil. The context of Governador Valadares allows focuses on the protagonism of youth migration, and its relation not only to transnational migration but also to mobility. The key research approach of the project is mixed-method ethnography based on field research and quantitative and qualitative data collection techniques. The multidisciplinary nature of the project is strong, combining approaches from geography, youth studies, migration studies, and ethnography. The project will create extra-European opportunities for long-term research partnership. This proposal includes both the transfer of knowledge to the host institution and the training of the candidates in new advanced research techniques. Project results will increase understanding the drivers of young people's migration while also developing and strengthening the research skills of the Experienced Researcher.

Keywords: migration aspirations,youth im mobility,transnational mobility,brazil,governador valadares