Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Novel Educational Model Enabling Social Innovation Skills development (NEMESIS)

Framework: Horizon 2020 — Societal Challenges
Programme: Europe in a changing world - inclusive, innovative and reflective societies
Theme: Inclusive societies
Action type: Innovation actions
Countries involved: Spain,Spain,Spain,Germany,Greece,Greece,France,Netherlands,United Kingdom,United Kingdom,United Kingdom,Portugal
Call: Education and skills: empowering Europe’s young innovators (H2020-SC6-CO-CREATION-2017, 2017)
Start date: 2017-10-01
End date: 2021-07-31
Duration (months): 46.0
Total project cost (EUR): 2237875.0
EU funding (EUR): 2132912.5
Participants: 14
Project status: CLOSED

NEMESIS designs, develops and tests an educational model for equipping students of primary and secondary education with Social Innovation Skills, values and tools. This process will enable students to become creative social thinkers, develop entrepreneurial mindsets, and become social change makers into a world where inequality, poverty and social exclusion are still quite evident. The NEMESIS model builds on a combination of innovative pedagogies and learning models, open technologies and participatory relations and processes. It also creates bridges between the learning communities and real world social innovation experiences by creating a European wide community of social innovation practitioners eager to interact with students, facilitating interdisciplinary and intergenerational learning. To foster its potential to scale and be adopted by educational institutions around Europe, the project develops a Social Innovation Open Learning Platform to grant access to the specific educational model and resources to all with emphasis on those from disadvantaged environments. This platform also facilitates the creation of a Community of Practice of teachers, school leaders and relevant stakeholders willing to break silos, engage in dialogue, drive organizational change and experience the value of the NEMESIS educational model. NEMESIS will be piloted in Greece, Spain, UK, France and Portugal engaging stakeholders into co-creation of educational resources, collective learning through the development of projects and digital storytelling as well as into online learning and knowledge sharing communities of peers. In that way, the project builds a contemporary educational model that will act as a catalyst in innovative skills based education in Europe that is expected to improve current teaching and learning practices and drive students’ passion for sustainable social change.

Keywords: educational model,social innovation skills,co creation,collaborative learning,real world experimentation,interdisciplinary leaning
Biological Valorization of Methane Emissions (CH4BioVal)

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-2016, 2016)
Start date: 2017-09-18
End date: 2019-09-17
Duration (months): 24.0
Total project cost (EUR): 170121.6
EU funding (EUR): 170121.6
Participants: 1
Project status: CLOSED

This action aims to obtain new methanotroph strains able to transform methane into valuable user products, in particular the bio-polymer PHA and ectoine. This will contribute to couple the abatement of a gas with high green-house power, to the production of useful chemicals and bio-consumables, which is in agreement with the objectives of H2020. This action combines the isolation of methanotroph strains using suitable selective pressures, with state of the art bioinformatic techniques to understand the metabolism of the selected strains and select thargeted genetic modifications aiming to improve the performance of the strains. The action is expected to result in patents of high producer methanotroph strains. A secondment in industry will allow to explore the posibilities for industrial aplications of the developed technologies.

Keywords: metabolic engineering,methanotrophy,biorefinery
agROBOfood: Business-Oriented Support to the European Robotics and Agri-food Sector, towards a network of Digital Innovation Hubs in Robotics (agROBOfood)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Germany,Spain,Ireland,Austria,Germany,Spain,Italy,Spain,Belgium,Lithuania,Greece,Serbia,Bulgaria,Belgium,Finland,Serbia,Belgium,Greece,Greece,France,France,France,France,France,Netherlands,Netherlands,Netherlands,Netherlands,Netherlands,Denmark,Portugal,Denmark,United Kingdom
Call: Robotics - Digital Innovation Hubs (DIH) (H2020-DT-2018-1, 2018)
Start date: 2019-06-01
End date: 2023-05-31
Duration (months): 48.0
Total project cost (EUR): 16658044.74
EU funding (EUR): 15999768.0
Participants: 43
Project status: SIGNED

agROBOfood is dedicated to accelerate the digital transformation of the European agri-food sector through the adoption of robotic technologies. It will consolidate, extend and strengthen the current ecosystem by establishing a sustainable network of DIHs. This will boost the uptake of robotic solutions by the agri-food sector: a huge challenge requiring an inclusive approach involving all relevant European players. The agROBOfood consortium has 39 partners, led by Wageningen University & Research and other core partners of previous key projects such as IoF2020, ROBOTT-NET, PicknPack and I4MS, to leverage the ecosystem that was established in those projects. The heart of the project is formed by Innovation Experiments (IEs), organized and monitored by the DIHs. In each of the 7 Regional Clusters, an initial IE will demonstrate the robotics innovations in agri-food in a manner that ensures replicability across Europe, wide adoption and sustainability of the DIHs network. agROBOfood will work in lockstep with the European robotics community, ensuring synergetic effects with initiatives such as EU-Robotics. This will maximize the return of European, including private capital, investments in the digital transformation of agri-food. A key instrument to achieve this objective is the Industrial Advisory Board. They will provide strategic guidance and also define priorities for the selection of solutions to be funded. Open Calls of 8MEUR will attract additional Innovation Experiments (12) and Industrial Challenges (8). These will expand the network and ensure that vast technological developments and emerging challenges of the agri-food sector are incorporated in the service portfolio of DIHs. Through its inclusive structure and ambitious targets, agROBOfood aims to bring the entire European ecosystem together; connecting the dots in a way that ensures effective adoption of robotics technologies in the European agri-food sector.

Keywords: digital innovation hubs,robotics,agri food,business innovation,open call,innovation experiment,competence centers,standards,platforms,demonstrators,industry support
Gemination Harmony (GeHa)

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: Social Sciences and Humanities
Countries involved: France
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-09-01
End date: 2017-12-22
Duration (months): 24.0
Total project cost (EUR): 173076.0
EU funding (EUR): 173076.0
Participants: 1
Project status: CLOSED

The goal of this project is to investigate long-distance anticipatory effects from word-medial geminates across three unrelated languages – Italian, Tashlhiyt Berber and Japanese. In particular, it examines whether defining- and enhancing- features associated with geminates are already anticipated on the non-adjacent word-initial consonant (e.g., whether in the Italian [palla] “ball” the properties of the word-medial [ll] geminate are already foreshadowed on the word-initial [p]). In relation to the geminate-singleton distinction, Italian, Tashlhiyt Berber and Japanese present similarities (e.g. duration of the word-medial geminate consonant as primary correlate) and differences that are relevant for testing the following issues a) the type of length-related vs. strength-related properties that are spread from the word-medial geminate to the word-initial consonant; b) the domain of the harmonic process, and more precisely, the role played by the intervening vowel (e.g. the [a] in [palla]). In addition to the language factor, long-distance anticipatory effects induced by geminates will be tested against segmental factors (i.e. type of word-medial geminate consonant), prosodic factors (i.e. focus) and performance-related factors (i.e. speech rate). Two acoustic and articulatory experiments (measurements of tongue-to-palate contact and intraoral pressure) will be designed to address these issues. The main contribution of this project lies in determining the articulatory and acoustic bases of harmony as induced by gemination (‘gemination harmony’) within a cross-linguistic perspective. As such, it may provide important insights into the interplay between phonetics and phonology and have crucial implications for the understanding of long-distance effects in speech production.

Keywords: geminate,phonetics,phonology,long distance effects,articulatory study,cross linguistic,italian,japanese,tashlhiyt berber
Supramolecular Protective Groups Enabling Antibiotics and Bioimaging (SUPRABIOTICS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Synthetic Chemistry and Materials
Panel description: New materials and new synthetic approaches, structure-properties relations, solid state chemistry, molecular architecture, organic chemistry
Countries involved: Germany,Netherlands
Call: ERC Advanced Grant (ERC-2015-AdG, 2015)
Start date: 2016-09-01
End date: 2022-01-31
Duration (months): 65.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 1970906.1
Participants: 2
Project status: CLOSED

The pharmaceutical sector has a huge demand for new active compounds including natural products to fill the drug pipelines and to stop the global decline in novel approved active pharmaceutical ingredients. Therefore, developing new tools to fabricate complex molecular structures in a fast and reliable way is paramount. This holds especially true for the field of antibiotics. Multidrug resistant (MDR) pathogens evolve at a terrifying rate and confer resistance to all presently available antibacterial treatments and therefore WHO has identified MDR bacteria as major threat to human health. In this ERC Advanced Grant, I propose a radically new approach to fabricate very complex molecules with minimal synthetic effort. The technology is based on nucleic acid binders (aptamers), which are evolved in a selection protocol and block several functional groups within a target molecule while allowing other functionalities not in contact with the aptamer to be selectively modified in a single reaction step. Here, we aim to establish this groundbreaking aptameric protective group (APG) method as a novel tool that gives access to compounds that would otherwise be too difficult to obtain by multistep synthesis. Toward this end, the specific objectives are: • To develop reagents and reactions that are compatible with aptamer-mediated reactions • To control the site of chemical modification within complex molecules by APGs • To establish APGs as a general paradigm in natural product derivatization to modify several kinds of substrates • To achieve site selective modification of proteins by aptamers • To synthesize novel antibiotics that kill MDR bacteria • To fabricate “image-and-activate” antibiotics by the APG technology • To employ the aptamer-target complexes for live-cell imaging of RNA The outcomes will enable future advances in drug discovery and drug design, bioimaging technologies, and the site-specific modification of therapeutic proteins.
Constitutive and numerical modelling of saturated and unsaturated soils (Coupled)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-02-01
End date: 2019-01-31
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The proposal focusses on investigating the incorporation of microstructural aspects of soil fabric into an existing coupled mechanical and retention framework for saturated and unsaturated soils. Particular emphasis will be given to two challenging patterns of microstructural behaviour: (1) Soils exhibiting a highly directional-dependent response, as a consequence of a particular orientation of their internal structure (anisotropic behaviour); (2) Soils exhibiting large swelling deformations on wetting, as a consequence of the presence in the soil of highly expansive clay minerals (expansive behaviour). Both of these aspects are intimately related to the internal clay fabric (micro-level) and an improved understanding of the influences that the microstructural fraction has on the global soil response (macro-level) is central to the development of a novel constitutive model capable to represent comprehensively these advanced features of soil behaviour. Full implementation of such constitutive model into a finite element formulation will provide a unique computational tool from where practitioners and researchers will be able to assess, in a unified manner, simple and advanced geotechnical engineering applications involving both saturated and unsaturated soil behaviour. Effectively, the use of a more reliable material representation in geotechnical designs, by means of the implemented model, will facilitate a safer construction and serviceability of civil infrastructures supported on the ground while potentially reducing associated costs.

Keywords: unsaturated soils,saturated soils,mechanical behaviour,water retention behaviour,constitutive modelling,coupling,anisotropy,irreversible swelling,soil fabric,microestructure,finite element
Unlocking the Entire Wood Matrix for the Next Generation of Carbon Fibers (WoCaFi)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Finland
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-01-01
End date: 2022-03-31
Duration (months): 63.0
Total project cost (EUR): 1481008.0
EU funding (EUR): 1481008.0
Participants: 1
Project status: CLOSED

WoCaFi envisions a game-changing approach for the production of bio-based carbon fibers in which the drawbacks of traditional cellulose and lignin fibers are entirely bypassed by a new type of hybrid precursor fibers containing simultaneously all wood biopolymers cellulose, hemicellulose and lignin. These unique fully wood-based multi-component filaments are accessible via a novel ionic liquid-based dry-jet wet spinning technique. The process provides the possibility to orientate lignin and hemicellulose embedded in a cellulose matrix. The special morphology of the resulting composite filaments is envisioned to increase the mechanical properties of thereof derived carbon fibers significantly, targeting 2000 MPa tensile strength and 200 GPa tensile modulus. These bio-based, low cost carbon fibers will reduce the dependency on non-renewable petroleum-based feedstocks and are highly suitable for lightweight applications in the automotive, sports and leisure sectors. Most distinctively, our technique also enables us to spin wood almost in its native form. Thus, the pretreatment steps and intensity can be reduced drastically and pronounced synergistic effects between the bio-polymers are created. This will lead to higher carbon yields and a significantly enhanced graphitization. In very recent initial trials on a continuous single tow carbonization line we found indicators that the oxidation step, typically accounting for almost 50% of the carbonization heating energy costs, can be reduced or omitted completely depending on the lignin content of the precursor fiber. This – in combination with activated wood as low cost raw material – would be the absolute game changer in developing low-cost, bio-based carbon fibers. In this project the PI, who has developed the spinning technique and a strong background in organic chemistry and spinning physics, will lead a group of 2 PhD students and 1 Postdoc. The Postdoc will complement the team with enhanced spectroscopic knowledge.
Hubs of Innovation and Entrepreneurship for the Transformation of Historic Urban Areas (HUB-IN)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Cultural heritage
Action type: Innovation actions
Countries involved: Italy,Cyprus,Romania,Slovenia,France,France,Netherlands,Netherlands,Portugal,United Kingdom,United Kingdom,United Kingdom
Call: Transforming historic urban areas and/or cultural landscapes into hubs of entrepreneurship and social and cultural integration (H2020-SC5-2019-2, 2019)
Start date: 2020-09-01
End date: 2024-08-31
Duration (months): 48.0
Total project cost (EUR): 8135105.12
EU funding (EUR): 7998797.5
Participants: 22
Project status: SIGNED

Hubs of Innovation and Entrepreneurship for the Transformation of Historic Urban Areas HUB-IN aims to foster innovation and entrepreneurship in Historic Urban Areas (HUA), while preserving the unique identity of the historic sites regarding their natural, cultural and social values. HUB-IN adopts the innovation and entrepreneurship as the main drivers of urban regeneration in HUAs and it´s fully aligned with the International agendas for Cultural Sustainable Development (UNESCO) and Cultural Heritage Strategy (Council Europe). HUB-IN will have two main stages. In the first stage, a network of Hubs of innovation and entrepreneurship (Hubs) will be developed in the HUAs of eight city partners and in the second stage, the resulting methods and tools will be upscaled to a global network of HUAs of follower cities. The Hubs of Innovation and Entrepreneurship (Hubs) will test, demonstrate and pilot activities of co-creation and co-design in three meaningful clusters with potential for sustainable transformation of HUA: i) Cultural and creative industries, ii) New lifestyles and iii) Endogenous Natural & Social Resources. HUB-IN defines 12 specific goals, that will be achieved by the following methodology: i) Building an ecosystem of interconnected Hubs to accelerate urban regeneration in eight HUAs, ii) Creating value in pilot Hubs, piloting social innovation and accelerating sustainable entrepreneurship in HUAs, iii) Packaging, upscaling and exploiting the results and create collaborative global network of Hubs of innovation and entrepreneurship in HUA, iv) Creating the HUB-IN digital space. HUB-IN expect to contribute to reverse trends of abandonment and neglect of historic heritage in a systemic way through the creation of networks of Hubs where innovation will be the main driver. HUB-IN will also have a direct impact on the creation of new sustainable opportunities for local traditional businesses and for the development of new creative skills and jobs.

Keywords: historic urban areas,hubs of innovation and entrepreneurship,sutainability
Deep Learning for Dynamic 3D Visual Scene Understanding (DeeViSe)

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: Germany
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2018-04-01
End date: 2023-03-31
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: SIGNED

Over the past 5 years, deep learning has exercised a tremendous and transformational effect on the field of computer vision. However, deep neural networks (DNNs) can only realize their full potential when applied in an end-to-end manner, i.e., when every stage of the processing pipeline is differentiable with respect to the network’s parameters, such that all of those parameters can be optimized together. Such end-to-end learning solutions are still rare for computer vision problems, in particular for dynamic visual scene understanding tasks. Moreover, feed-forward processing, as done in most DNN-based vision approaches, is only a tiny fraction of what the human brain can do. Feedback processes, temporal information processing, and memory mechanisms form an important part of our human scene understanding capabilities. Those mechanisms are currently underexplored in computer vision. The goal of this proposal is to remove this bottleneck and to design end-to-end deep learning approaches that can realize the full potential of DNNs for dynamic visual scene understanding. We will make use of the positive interactions and feedback processes between multiple vision modalities and combine them to work towards a common goal. In addition, we will impart deep learning approaches with a notion of what it means to move through a 3D world by incorporating temporal continuity constraints, as well as by developing novel deep associative and spatial memory mechanisms. The results of this research will enable deep neural networks to reach significantly improved dynamic scene understanding capabilities compared to today’s methods. This will have an immediate positive effect for applications in need for such capabilities, most notably for mobile robotics and intelligent vehicles.