Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Novel concept of cost-effective and simplified in-situ concrete tower of 140m for harnessing higher and more consistent wind velocities and enhancing the power output of wind turbines (LiraTower)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Spain
Call: Stimulating the innovation potential of SMEs for a low carbon energy system (H2020-SMEINST-1-2015, 2015)
Start date: 2015-08-01
End date: 2015-10-31
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

INGECID is a renowned engineering company focused on developing innovative constructive processes applied to wind energy, where the cost of installations is dominated by the CAPEX of wind turbines (ca. 84%). While the need of minimizing the costs per installed MW has not been yet successfully addressed, the cost-effective redesign of taller wind turbine towers is now indispensable due to: a) the limited height (ca. 85m) and the fatigue vulnerability of actual towers, which hamper wind turbines harnessing higher wind velocities, at greater altitudes and for longer times (thus from delivering more electric power: P≈v3); b) the load needs for bearing heavier turbines (150 tons), and c) the costs of actual alternatives (hybrid steel/concrete and precast concrete towers) that have avoidable expenses of lifting, maintenance and transport. In this context, INGECID will become a reference within the tower manufacturing business (predicted global market investment of 17.11 bn€ by 2020, at a CAGR of 6.9%) by offering a 140m cost-competitive in-situ monolithic concrete tower solution for 3 MW wind turbines: LiraTower. This novel tower design, patent requested, surpasses actual solutions due to: a) its height (above hitherto reports of 120-137m); b) its unique design of internal and external tendons, which allow for excellent compressive strength (slender diameter of 4m), fatigue resistance and stiffness; and c) the cost reduction (ca. 30-40%) that in-situ technology offers over available solutions in market. With the proposed construction process and tower design, wind velocity increments of up to 8% and 26% higher output powers in comparison to 80m are now feasible at a competitive cost. Additionally, the drawbacks and transport costs of large tower sections, nearby prefabrication plants and on-site mechanizing are totally eliminated. Once in market, LiraTower would have a return on investment of 3.8 years, generating cumulative revenues of 9.53 M€ and 55 new direct jobs.

Keywords: wind energy,in situ tower,tower design,wind energy output,monolithic,tower fatigue resistance,wind concrete tower greater wind velocity,enhanced output power,cost efficiency
Integrated study of the role of B-cell receptor signaling in the development of Follicular Lymphoma (LYMPHOSIGN)

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: Life Sciences
Countries involved: France,United States
Call: Marie Skłodowska-Curie Individual Fellowships (IF-GF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-12-01
End date: 2018-10-31
Duration (months): 27.0
Total project cost (EUR): 200119.5
EU funding (EUR): 200119.5
Participants: 2
Project status: CLOSED

Signaling through the B cell receptor (BCR) is central to the development and maintenance of B cells. In light of the numerous proliferative and survival pathways activated downstream of the BCR, it comes as no surprise that malignant B cells would co-opt this receptor to promote their own growth and survival. However, direct evidence for BCR signaling in human lymphoma has only come to light recently. In this proposal, I aim to better understand the role for antigen-dependent vs. antigen-dependent BCR signaling as a pathogenic mechanism in the progression of Follicular lymphoma (FL), a indolent lymphoid malignancy that retain BCR expression during malignant progression. Further investigating the intrinsic role of BCR might lead to the development of new therapeutic approaches based on the inhibition of the BCR pathways. Using an innovative loss-of -function RNA interference genetic screen together with an engineered in vitro system allowing to test FL patients's BCR reactivity and identify putative ligands, we will 1) determine whether BCR signalling in FL relies to "chronic active" or "tonic" signals and 2) identify the nature of antigen(s) recognized by FL's BCR that may sustain signalling; each signalling pathway offering different opportunities for therapeutic intervention. For this project, I decided to chose the Louis Staudt’s group at the National Cancer Institute (NIH) for the outgoing phase since his group has been looking for years how to target B-cell receptor signaling as a treatment strategy. The unique expertise in the state-of the art functional genomic methodologies acquired during my stay at the NCI will be crucial for setting-up new scientific projects, promote extended collaborations and strongly support my re-establishement in Europe to reach an independent position.

Keywords: follicular lymphoma,b cell receptor,signaling pathways,rna interference genetic screen,functionnal genomics
Proactive communication and marketing measures for SMEs (TargetSME)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Estonia,Spain,Lithuania,Poland
Call: Peer learning of innovation agencies (H2020-INNOSUP-2018-2019-05, 2019)
Start date: 2019-09-01
End date: 2020-08-31
Duration (months): 12.0
Total project cost (EUR): 50000.0
EU funding (EUR): 50000.0
Participants: 4
Project status: CLOSED

The main project’s aim is to enhance the agencies’ management efficiency in the field of seeking the ways how to attract innovative SMEs by using emerging communication and marketing tools and facilitating interaction and partnerships with various actors of innovation ecosystem. Four innovation agencies involved in the project will work using twinning+ methodology in order to create valuable Design Options Paper regarding communication, branding and marketing strategy for strengthening the position of innovation centres on the national as well as on the international arena as a high value added business support organisations. The solutions developed in the paper will be implemented in the agencies as new or improved programmes based on these given approaches. The result of peer learning activities within the project will be developing an effective approach to identify new topics in the field of communication, find the attractive methods od engaging inovative SMEs and put them into practice. It involves designing the whole proactive marketing process from the identification of the target group, marketing channels and campaigns, attractive offer, diagnostics of individual needs, consequent support delivery and follow up of the process till key performance indicators. The results of the project will be communicated to regional and national authorities as the topic of reaching the right SMEs is very common with regard to efficiency of policies aiming to enhance SMEs competitiveness, especially their growth on national and international markets as well as their engagement in innovation processes.

Keywords: proactive approach,sme s support,innovation support,marketing tools,communication actvities,service portfolio management
Ai for New Devices And Technologies at the Edge (ANDANTE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Public-private partnerships
Destination: Electronic Components and Systems
Action type: Research and Innovation actions
Partnership: ECSEL (Art-187)
Countries involved: Germany,Germany,Germany,Germany,Spain,Spain,Germany,Spain,Switzerland,Switzerland,Belgium,France,France,France,France,Netherlands,Portugal,Portugal
Call: ECSEL-2019-2-RIA (H2020-ECSEL-2019-2-RIA, 2019)
Start date: 2020-06-01
End date: 2024-02-29
Duration (months): 45.0
Total project cost (EUR): 40584497.04
EU funding (EUR): 11846230.27
Participants: 31
Project status: SIGNED

The fundamental goal of the ANDANTE project is to leverage innovative hardware platforms to build strong hardware / software platforms for artificial neural networks (ANN) and spiking neural networks (SNN) as a basis for future products in the Edge IoT domain, combining extreme power efficiency with robust neuromorphic computing capabilities and demonstrate them in key application areas. The main objective of ANDANTE is to build and expand the European eco-system around the definition, development, production and application of neuromorphic hardware through an efficient cross-fertilization between major European foundries, chip design, system houses, application companies and research partners, as presented by the European Leader Group (ELG). The project brings together world class expertise to bring the world class expertise and infrastructures of Imec, CEA and FhG together with semiconductor companies, fabless, system houses, SMEs and application experts to explore and demonstrate the capabilities provided by the developed technologies. In the project, several applications will be assessed in key domains where Europe is strong (automotive, digital farming, digital industry, mobility and digital life). The aim is to reinforce and maintain strong leadership in these areas by bringing industry in contact with future memory technologies at a low TRL level (MRAM, OXRAM, FeFET). These cross-disciplinary efforts will lead to development of innovative hardware / software deep learning solutions, based on high TRL level RRAM/PCM and FeFET, to enable future products which combine extreme power efficiency with robust cognitive computing capabilities. This new kind of computing technology, combining ANN and SNN capabilities, will open new perspectives, for instance, environmental monitoring, and wearable electronics.
Graded constraints in semantic cognition: How do we retrieve knowledge in a flexible way? (FLEXSEM)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2018-04-01
End date: 2024-09-30
Duration (months): 78.0
Total project cost (EUR): 1999860.0
EU funding (EUR): 1999860.0
Participants: 1
Project status: SIGNED

For any concept, we have knowledge about diverse features – for example, a dog is furry, can chase rabbits, and is “man’s best friend”. How, at a specific moment, do we flexibly retrieve relevant conceptual knowledge that suits our current goals and context? We can promote coherence between weakly-related aspects of knowledge as required, and also achieve the timely release from patterns of retrieval when the situation changes. These effects are likely to play a central role in our mental lives – yet they are poorly understood because past research has largely focused on how the conceptual store captures what is generally true across experiences (i.e. semantic representation). This project alternatively examines the cognitive and brain mechanisms that promote currently-relevant semantic information. We consider whether flexible semantic retrieval involves the recruitment of additional brain regions, organised within large-scale distributed networks, that place constraints on patterns of retrieval in the semantic store. In this way, semantic flexibility might relate to the evolving interaction between distinct brain networks. We examine whether specific brain regions support distinct cognitive processes (e.g., “automatic retrieval”; “selection”) or, alternatively, whether the functional organisation of these networks is non-arbitrary, with brain regions further away from the semantic store supporting retrieval when there is a greater mismatch between ongoing retrieval and the pattern required by the context. We test this “graded constraints” hypothesis by combining parametric manipulations of the need for constraint with convergent neuroscientific methods that characterise functional recruitment in space (magnetic resonance imaging) and time (magnetoencephalography). We investigate causality (neuropsychology; brain stimulation) and the broader implications of our account (using an individual differences approach).

Keywords: semantic,executive control,aphasia,neuropsychology,brain stimulation,transcranial magnetic stimulation,fmri,brain network,retrieval,automatic,selection,concept
Algorithmic Hexahedral Mesh Generation (AlgoHex)

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: Switzerland
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-02-01
End date: 2025-01-31
Duration (months): 60.0
Total project cost (EUR): 1482156.0
EU funding (EUR): 1482156.0
Participants: 1
Project status: SIGNED

Digital geometry representations are nowadays a fundamental ingredient of many applications, as for instance CAD/CAM, fabrication, shape optimization, bio-medical engineering and numerical simulation. Among volumetric discretizations, the "holy grail" are hexahedral meshes, i.e. a decomposition of the domain into conforming cube-like elements. For simulations they offer accuracy and efficiency that cannot be obtained with alternatives like tetrahedral meshes, specifically when dealing with higher-order PDEs. So far, automatic hexahedral meshing of general volumetric domains is a long-standing, notoriously difficult and open problem. Our main goal is to develop algorithms for automatic hexahedral meshing of general volumetric domains that are (i) robust, (ii) scalable and (iii) offer precise control on regularity, approximation error and element sizing/anisotropy. Our approach is designed to replicate the success story of recent integer-grid map based algorithms for 2D quadrilateral meshing. The underlying methodology offers the essential global view on the problem that was lacking in previous attempts. Preliminary results of integer-grid map hexahedral meshing are promising and a breakthrough is in reach. We identified five challenges that need to be addressed in order to reach practically sufficient hexahedral mesh generation. These challenges have partly been resolved in 2D, however, the solutions do not generalize to 3D due to the increased mathematical complexity of 3D manifolds. Nevertheless, with our experience in developing and evaluating the 2D techniques, we identified the key properties that are necessary for success and accordingly propose novel volumetric counterparts that will be developed in the AlgoHex project.

Keywords: hexahedral mesh generation,geometry processing,differential geometry,volumetric mappings,finite element method,simulation,mixed integer optimization
VIZTA sounds for Vision, Identification, with Z-sensing Technologies and key Applications. (VIZTA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Public-private partnerships
Destination: Electronic Components and Systems
Action type: Innovation actions
Partnership: ECSEL (Art-187)
Countries involved: Spain,Germany,Spain,Germany,Germany,Spain,Hungary,Sweden,Greece,Latvia,France,France,France,France,France,United Kingdom,Luxembourg
Call: ECSEL-2018-1-IA (H2020-ECSEL-2018-1-IA-two-stage, 2018)
Start date: 2019-05-01
End date: 2022-10-31
Duration (months): 42.0
Total project cost (EUR): 86765712.88
EU funding (EUR): 21144567.8
Participants: 28
Project status: SIGNED

VIZTA project, coordinated by ST Micrelectronics, aims at developing innovative technologies in the field of optical sensors and laser sources for short to long-range 3D-imaging and to demonstrate their value in several key applications including automotive, security, smart buildings, mobile robotics for smart cities, and industry4.0. The key differentiating 12-inch Silicon sensing technologies developed during VIZTA are: • Innovative SPAD and lock-in pixel for Time of Flight architecture sensors • Unprecedent and cost-effective NIR and RGB-Z filters on-chip solutions • complex RGB+Z pixel architectures for multimodal 2D/3D imaging For short-range sensors : advanced VCSEL sources including wafer-level GaAs optics and associated high speed driver These developed differentiating technologies allows the development and validation of innovative 3D imaging sensors products with the following highly integrated prototypes demonstrators: • High resolution (>77 000 points) time-of-flight ranging sensor module with integrated VCSEL, drivers, filters and optics. • Very High resolution (VGA min) depth camera sensor with integrated filters and optics For Medium and Long range sensing, VIZTA also adresses new LiDAR systems with dedicated sources, optics and sensors Technology developments of sensors and emitters are carried out by leading semiconductor product suppliers (ST Microelectronics, Philips, III-V Lab) with the support of equipment suppliers (Amat, Semilab) and CEA Leti RTO. VIZTA project also include the developement of 6 demonstrators for key applications including automotive, security, smart buildings, mobile robotics for smart cities, and industry4.0 with a good mix of industrial and academic partners (Ibeo, Veoneer, Ficosa, Beamagine, IEE, DFKI, UPC, Idemia, CEA-List, ISD, BCB, IDE, Eurecat). VIZTA consortium brings together 23 partners from 9 countries in Europe: France, Germany, Spain, Greece, Luxembourg, Latvia, Sweden, Hungary, and United Kingdom.

Keywords: time of flight,heterogeneous integration,single photon avalanche diode,vcsel,lidars,optical phase array,biometrics,security,industry4 0,smart buildings,sciences
Species persistence in changing seasonal environments: A new holistic framework integrating demography and biotic interactions (SEASON)

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: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-07-01
End date: 2022-06-30
Duration (months): 24.0
Total project cost (EUR): 172932.48
EU funding (EUR): 172932.48
Participants: 1
Project status: CLOSED

Most species show seasonal variation in survival and reproduction, which determines and is affected by biotic (intra- and interspecific) interactions. Such demography-biotic-interaction feedbacks, in turn, mediate community responses to seasonal patterns in environmental factors. Changing these seasonal patterns and thereby adversely affecting the demography of interacting species, is one important way in which global environmental change alters biodiversity. However, as population and community responses to changes in seasonality are typically studied separately, we lack a mechanistic understanding of the processes that threaten the persistence of interacting species, posing a major challenge to biodiversity conservation. SEASON aims to bridge this fundamental knowledge gap by linking demographic processes and biotic interactions under changes in the seasonality of environmental factors across time and space. Integrating theoretical and empirical analyses, the two main objectives of this project are to (i) develop an analytical framework which assesses how demography-biotic-interaction feedbacks mediate multi-species population responses to seasonality change; and (ii) apply the framework on empirical systems to synthesize novel information on the importance of the feedbacks. By developing an integrative framework to assess simultaneous responses of several species to seasonality, a key but understudied aspect of environmental change, this research will substantially contribute to global-change ecology. It will also assist researchers and managers in developing new strategies beyond single target populations or annual demographic censuses to mitigate global threats. As SEASON aims to develop a flexible tool that can be expanded in the future and relies on collaboration between two research institutes and several conservation initiatives, the MSCA fellowship will be critical in building a long-lasting research line and a global network of collaborators.

Keywords: multi species demographic analyses,seasonal life cycles,vital rates,vital rate models,global environmental change,bayesian models
Experience Effects on early language acquisition (ExELang)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: France
Call: ERC CONSOLIDATOR GRANTS (ERC-2020-COG, 2020)
Start date: 2021-11-01
End date: 2026-10-31
Duration (months): 60.0
Total project cost (EUR): 2007023.0
EU funding (EUR): 2007023.0
Participants: 1
Project status: SIGNED

To what extent does experience affect child language acquisition? Answering this is crucial for our understanding of human cognition, but current evidence is insufficient because causal links between experience and outcomes cannot be established with typical approaches. We will study how the speech infants hear affects their learning of the sounds and structures of their native language, as represented in the speech the same infants produce, using an innovative and ecological technique: Audio-recordings collected with a recorder worn by the child throughout a normal day. Fifteen large-scale corpora will be combined, totaling over 25,000h of audio, collected from over 1,400 infants, living in rural and urban sites in every peopled continent, and learning a wide variety of mostly unrelated languages. We will develop cutting-edge machine learning algorithms to automatically analyze these long, messy, and multilingual recordings. This will yield measures representing infants' experiences (the speech addressed to them, and the speech they overhear) as well as how advanced their own vocalizations are. A subset of data come from Randomized Control Trials (RCTs) where treatment groups have received behavioral interventions aimed at increasing the quantity of speech infants are addressed. We aim to establish to what extent speech addressed to the infants and overheard speech affect their development by triangulating analyses of variation across individuals, cultures, and treatment-control contrasts. In parallel, we will use a reverse-engineering approach to assess the theoretically-predicted effects of experience. A variety of learning mechanisms will be implemented in unsupervised learning systems which take as input audio like that heard by infants and produce as output "vocalizations". If a system yields the same experience-outcome curves found in the infants’ data, then those learning mechanisms plausibly resemble those used by infants.