Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Moduli spaces of curves and integrable hierarchies (MSCIH)

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: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-03-19
End date: 2020-03-18
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The proposal is devoted to the study of a large class of systems of partial differential equations which on one hand appear in classical problems of mathematical physics and on the other hand they provide an efficient tool for description of enumerative invariants in algebraic geometry. These systems are called the hierarchies of topological type or the Dubrovin-Zhang hierarchies. Based on the new approach to such systems, which I suggested recently, I aim to prove certain conjectures about the structure of hierarchies of topological type, describe them explicitly in important examples and also find connections to other areas in the theory of integrable systems.

Keywords: moduli spaces of curves,intersection theory,integrable hierarchies of partial differential equations
Open social transport network for urban approach to carpooling (SocialCar)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Italy,Italy,Italy,Spain,Italy,Switzerland,Belgium,Hungary,Slovenia,North Macedonia,Croatia,Greece,Poland,Netherlands,Netherlands,Netherlands,United Kingdom,United Kingdom,Luxembourg,United Kingdom,United Kingdom,United Kingdom
Call: Connectivity and information sharing for intelligent mobility (H2020-MG-2014_TwoStages, 2014)
Start date: 2015-06-01
End date: 2018-05-31
Duration (months): 36.0
Total project cost (EUR): 5953083.0
EU funding (EUR): 5384645.5
Participants: 31
Project status: CLOSED

SocialCar is an Intelligent Transport System based on an innovative approach to transport demand management, and more specifically to carpooling in urban and peri-urban areas. SocialCar’s main objective is devopping a new communication network for intelligent mobility, sharing information of car-pooling integrated with existing transport and mobility systems. It will be achieved by means of powerful planning algorithms and integration in a liveable environment of big data related to public transport, carpooling and crowdsourcing in order to provide the final user with a simplified travel experience allowing comparison and choice between multiple options/services. SocialCar will take advantage Social Media to communicate, share information and provide the best just-in-time notifications to the travellers. SocialCar will take advantage of the ever growing connectivity of people and objects and the propagation of Internet services, the potential of Future Internet and the availability of GNSS based location and social media to create an integrated mobility service with the potential to sensibly reduce mobility problems of European citizens. SocialCar will capitalise on a strong pan European team with a solid background in social, psychological and economic sciences, the involvement of 10 European urban sites will prove the concepts' validity and business case. SocialCar General Objectives are to: • contribute to the EU2020 targets on energy efficiency and renewable energy sources reducing congestion by improving and maximising connectivity and information in real-time • overcoming the limitations of current carpooling practices moving from long trips to effective urban and peri-urban use • validate green driving support systems, active management based on European GNSS • identify a suitable big data management architecture for integrating mobility data • produce a city-based open integrated mobility repository of public transport and traffic city-based data

Keywords: crowdsourcing,integration of open public data city authorities with real time information crowd data from citizens
Search for electric dipole moments using storage rings (srEDM)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Germany,Italy,Germany
Call: ERC Advanced Grant (ERC-2015-AdG, 2015)
Start date: 2016-10-01
End date: 2022-09-30
Duration (months): 72.0
Total project cost (EUR): 2379276.0
EU funding (EUR): 1072207.25
Participants: 3
Project status: CLOSED

One of the great mysteries in the natural sciences is the dominance of matter over antimatter in the universe. According to our present understanding, the early universe contained the same amount of matter and antimatter. If the universe had behaved symmetrically as it developed, every particle would have been annihilated by one of its antiparticles. We therefore owe our very existence to mechanisms that have led to a world where something that we call matter remains. We propose to study such mechanisms by searching for electric dipole moments (EDMs) of charged hadrons in a new class of precision storage rings. Our project will lay the foundations for a new European flagship research infrastructure. The breaking of the combined charge conjugation and parity symmetries (CP-violation) in the Standard Model is not strong enough to explain the observed excess of matter and further sources of CP-violation must be sought. These sources could manifest themselves in Electric Dipole Moments of elementary particles, which occur when the centroids of positive and negative charges are mutually and permanently displaced. The observation of an electric dipole moment will elucidate the mechanisms which led to the matter that dominates the universe. Although the measurement principle, the time development of the polarization vector subject to a perpendicular electric field, is simple, the smallness of the effect makes this an enormously challenging project. This can only be mastered through the common effort of an international team of accelerator and particle physicists, working closely with engineers. The proponents of this design study and the research environment at the Forschungszentrum Jülich (Germany), including the conventional storage ring COSY, provide the optimal basis for one of the most spectacular possibilities in modern science: finding an EDM as a signal for new physics beyond the Standard Model and perhaps explaining the puzzle of our existence.
An innovative, non-invasive and de-risked system to enable the transdermal delivery of fragile therapeutic compounds for a better management of painful diseases (NANO-GROWTH)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: SME instrument
Countries involved: Spain
Call: Supporting innovative SMEs in the healthcare biotechnology sector (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2017-02-01
End date: 2017-05-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Chronic pain affects +1.5 billion people worldwide, which means that pain affects more people than diabetes, heart disease and cancer combined. Since chronic pain persists for years, it becomes unbearable. Chronic pain is often the result from neuropathy (nerve damage), which increases with age but also due to chronic diseases. For instance, 34% of diabetes cases develop painful neuropathy, which means 143 million people affected globally. Since there is no cure, patients receive analgesics and other meds for pain relief. To avoid inflicting further pain, medication is administered transdermally using topical solutions like creams or patches. However, there are important barriers to the dermal delivery of analgesics: scarcity of viable compounds, high biodegradation rate, short effect, poor efficiency and severe adverse effects. In response, we at Astracime have developed an innovative solution that overcomes the limitations of transdermal pain relief. This NANO-GROWTH project aims to bring to market a unique dermal patch loaded with encapsulated therapeutic compounds. The customized capsule protects the integrity of the compounds as they travel through the skin layers and bloodstream. In addition, we have engineered the capsule to provide target-mediated release. Altogether, our method secures a longer and safer pain relief. After been proven at the lab scale, we now aim to take a step further towards the mature stage. Thus, in Phase 1 we aim to assess the subsequent steps needed to secure this project from all technical, commercial and financial perspectives. This project encloses significant growth potential for Astracime, allowing us to consolidate a leader position in the field of pain management. Indeed, we expect to gain €41 million in revenues and hire 30 new people in 5 years. In turn, this project will contribute to improve the quality of life of millions of patients suffering from pain, while helping to reduce costs to our saturated healthcare system.

Keywords: efficient therapeutic delivery,pain management,transdermal delivery,encapsulated pain inhibitors,nerve growth factor,transdermal patches,safer management
A new tool in drug development: mapping of compound-protein interaction using forward genetics (ACUSLABS)

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: Germany
Call: ERC-Proof of Concept (ERC-2017-PoC, 2017)
Start date: 2017-07-01
End date: 2018-12-31
Duration (months): 18.0
Total project cost (EUR): 149563.0
EU funding (EUR): 149563.0
Participants: 1
Project status: CLOSED

Development of new medicines such as chemotherapeutic drugs requires a detailed understanding of their biological mechanism of action. What are the desired and undesired interactions with biological molecules? It is our goal to found a start-up company that will provide a solution to this challenge. Using novel and ground-breaking approaches we can identify target structures and interaction partners of small bioactive molecules at an unmatched and unprecedented resolution. ERC PoC funding will be essential to support our activities to identify optimal strategies and initial customers for our service.

Keywords: drug development,genetic screen,haploid stem cells,compound protein interaction mapping
Dynamic-Regime Shifts in Forests: Trajectories from Science to Management (RESET)

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: Environment and Geosciences
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-03-01
End date: 2023-02-28
Duration (months): 24.0
Total project cost (EUR): 184707.84
EU funding (EUR): 184707.84
Participants: 1
Project status: CLOSED

The increasing incidence of extreme events (e.g. fires, insect outbreaks) in combination with ramp and press disturbances such as climate and land-use changes are seriously threatening the persistence of forest services on which human well-being depends. In this context, forest resilience to disturbances has become a paradigm for researchers, practitioners, and policymakers. Whereas many indicators have been proposed in different empirical studies, most of them are based on a static view of ecosystem states and overlook that ecosystem states, in fact, represent dynamic regimes. In contrast, many advanced theoretical approaches remain unexplored in specific forest systems. In this sense, incorporating theoretical resilience concepts into empirical studies poses a key challenge to developing realistic management practices and policies that promote forest resilience to upcoming disturbances. This proposal aims to fill an important scientific gap by applying resilience concepts from theoretical ecology into empirical case studies. The main objective is to contribute to the conservation of forests and prevent their degradation and loss by improving our capability to identify resilient and tipping-point communities, assessing the mechanisms underlying post-disturbance forest dynamics, and supporting forest management and policy through useful information and tools. This project proposes an innovative framework to assess forest resilience to pulse (e.g. insect outbreaks, fire), ramp (climate change) and press (land-use change) disturbances accounting for forest dynamic regimes as reference to compare post-disturbance dynamics. The collaboration with theoretical and quantitative ecologists and researchers in the science-policy-practice interface from some of the most prestigious institutions in the EU will guarantee a strong contribution to the understanding of post-disturbance forest dynamics and the preservation of forest services under changing conditions.

Keywords: resilience,resistance,dynamic regimes,forest dynamics,disturbances,climate change,land use change,trajectory analyses,hypervolume,cluster
Improving Building Information Modelling by Realtime Tracing of Construction Processes (BIMprove)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Technologies enabling energy-efficient systems and energy-efficient buildings with a low environmental impact
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Spain,Germany,Spain,Switzerland,Switzerland,Norway,Norway,Finland,Norway
Call: Digital Building Twins (RIA) (H2020-NMBP-ST-IND-2020-singlestage, 2020)
Start date: 2020-09-01
End date: 2023-08-31
Duration (months): 36.0
Total project cost (EUR): 5593676.25
EU funding (EUR): 5593676.25
Participants: 13
Project status: SIGNED

In the past 20 years, productivity in the European construction industry has increased by 1% annually only, which is at the lower end compared to other industrial sectors. Consequently, the sector has to step up its digitization efforts significantly, on the one hand to increase its competitiveness and on the other hand to get rid of its image as dirty, dangerous and physical demanding working environment. Construction industry clearly needs to progress beyond Building Information Modelling when it comes to digitizing their processes in such a way that all stakeholders involved in the construction process can be involved. The true potential of comprehensive digitization in construction can only be exploited if the current status of the construction work is digitally integrated in a common workflow. A Digital Twin provides construction companies with real-time data on the development of their assets, devices and products during creation and also enables predictions on workforce, material and costs. B¦IMprove facilitates such a comprehensive end-to-end digital thread using autonomous tracking systems to continuously identify deviations and update the Digital Twin accordingly. In addition, locations of construction site personnel are tracked anonymously, so that B¦IMprove system services are able to optimize the allocation of resources, the flow of people and the safety of the employees. Information will be easily accessible for all user groups by providing personalized interfaces, such as wearable devices for alerts or VR visualizations for site managers. B¦IMprove is a cloud-based service-oriented system that has a multi-layered structure and enables extensions to be added at any time. The main goals of B¦IMprove are a significant reduction in costs, better use of resources and fewer accidents on construction sites. By providing a complete digital workflow, B¦IMprove will help to sustainably improve the productivity and image of the European construction industry.

Keywords: building information modelling,digital twin,construction automation,human robot collaboration,digital thread,mobile robotics,unmanned areal vehicle,automated progress monitoring
Coordination Action for implementation and alignment activities of the Joint Programming Initiative (JPI) 'More Years – Better Lives – the Challenges and Opportunities of Demographic Change' (J-Age II)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Active ageing and self-management of health
Action type: Coordination and support actions
Countries involved: Italy,Germany,Spain,Italy,Finland,Sweden,France,Netherlands,Canada,United Kingdom
Call: Joint programming: Co-ordination action for the joint programming initiative (JPI) 'more years better lives the challenges and opportunities of demographic change' (H2020-HCO-2014, 2014)
Start date: 2015-03-01
End date: 2018-05-31
Duration (months): 39.0
Total project cost (EUR): 2028049.0
EU funding (EUR): 2028049.0
Participants: 11
Project status: CLOSED

J-AGEII, the Coordination Action for implementation and alignment activities of the Joint Programming Initiative (JPI) 'More Years Better Lives – the Challenges and Opportunities of Demographic Change', will support and foster the overall management of the JPI, update the Strategic Research Agenda and support implementation through joint activities between Member States. Furthermore, the work plan will include dissemination and information exchange with scientific and societal stakeholders, policy makers and research funders as well as an evaluation and monitoring exercise. Ultimately, the project and the JPI seek to stimulate the alignment of relevant national programmes and EU initiatives, strengthen the base of multi-disciplinary and holistic ageing research in Europe and to provide scientific evidence for policy responses to demographic change.

Keywords: implementation,joint activities,alignment,demographic change
Deep LEarning on MANifolds and graphs (LEMAN)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Switzerland,United Kingdom,United Kingdom
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-10-01
End date: 2023-09-30
Duration (months): 72.0
Total project cost (EUR): 1997875.0
EU funding (EUR): 200000.1
Participants: 4
Project status: SIGNED

The aim of the project is to develop a geometrically meaningful framework that allows generalizing deep learning paradigms to data on non-Euclidean domains. Such geometric data are becoming increasingly important in a variety of fields including computer graphics and vision, sensor networks, biomedicine, genomics, and computational social sciences. Existing methodologies for dealing with geometric data are limited, and a paradigm shift is needed to achieve quantitatively and qualitatively better results. Our project is motivated by the recent dramatic success of deep learning methods in a wide range of applications, which has literally shaken the academic and industrial world. Though these methods have been known for decades, the computational power of modern computers, availability of large datasets, and efficient optimization methods allowed creating and effectively training complex models that made a qualitative breakthrough. In particular, in computer vision, deep neural networks have achieved unprecedented performance on notoriously hard problems such as object recognition. However, so far research has mainly focused on developing deep learning methods for Euclidean data such as acoustic signals, images, and videos. In fields dealing with geometric data, the adoption of deep learning has been lagging behind, primarily since the non-Euclidean nature of objects dealt with makes the very definition of basic operations used in deep networks rather elusive. The ambition of the project is to develop geometric deep learning methods all the way from a mathematical model to an efficient and scalable software implementation, and apply them to some of today’s most important and challenging problems from the domains of computer graphics and vision, genomics, and social network analysis. We expect the proposed framework to lead to a leap in performance on several known tough problems, as well as to allow addressing new and previously unthinkable problems.

Keywords: geometric deep learning,convolutional neural networks,intrinsic geometry,shape analysis,shape correspondence,signal processing on graphs,spectral methods,face analysis,social network analysis
Novel microengineered environments for mouse embryonic stem cell (mESC) differentiation towards cardiomyocytes (NEVADA)

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: Information Science and Engineering
Countries involved: Switzerland
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-09-01
End date: 2020-10-01
Duration (months): 24.0
Total project cost (EUR): 175419.6
EU funding (EUR): 175419.6
Participants: 1
Project status: CLOSED

Cardiomyocytes (CMs) are the contractile cells of the heart. Their regenerative capacity is lost after birth. Embryonic stem cells (ESCs) are able to differentiate into functional CMs, however this process is not yet efficient. The elucidation of ESCs’ differentiation into CMs could provide an additional avenue for therapeutic interventions and disease modeling. This interdisciplinary project will result in a unique platform that targets precise quantification of the fundamental molecular mechanisms underlying mouse ESC cardiac differentiation at the single cell level. The platform takes the advantages of 3D tailored conductive microscaffolds (3DTCMSs) to deliver precise mechanical and electrical stimulation patterns to individual cells in vitro. Co-integrated 3DTCMSs have the necessary infrastructure for long-term cell culturing. The platform is accessible for in situ high-resolution, real-time microscopic observation of essential molecular information due to transparent materials. Advanced two-photon polymerization photolithography will be utilized for the exact reconstruction of 3DTCMSs based on a novel optically transparent, conductive ionic liquid-polymer composite. ESC pluripotent factors and CM markers will be monitored comparatively by live microscopy and molecular analysis. This project aims to integrate expertise in materials science, engineering, cellular and molecular biology. As a result, a novel in vitro CM differentiation model will be developed, which has a potential to open a completely new window of research in systems biology.

Keywords: biosensor,biomimetic,mechanical and electrical stimulation,stem cells