Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
XPRESS ENGINE - The Future of Affective Market Research (XPRESS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Poland
Call: Open Disruptive Innovation Scheme (implemented through the SME instrument) (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

Focus group market research recruit persons to watch advertisements for products that fit their demographic and give their opinion. Current focus groups require large mobilization of resources (venue, staff, equipment, targets, analysts) and face a common problem with target positive bias which makes the costly focus group results unreliable for assessing true consumer acceptance. Xpress Engine proposes a solution to transform the current model of focus groups, offering more reliable results at lower cost through disruptive innovation in emotion analytics. How? By detecting involuntary emotional response in real time and completely bypassing any bias, positive or negative, and by allowing the entire focus group to be performed without mobilizing any resources. The revolutionary Xpress Engine emotion recognition system detects emotions in real time by processing expressions in response to stimuli, achieving a detection accuracy of 95% with the six principal emotions and allowing the focus group to be done online with mobile or laptop, with targets registering their real time emotional response to a video or presentation from the comfort of their homes. Market research groups excited about Xpress Engine because it will add value to their current services and create opportunities for new services, revenue sources and growth. Studies show that the more emotions appear in the ad, the better it is remembered and the greater consumer involvement it generates. The key is in the real time detection, which allows the “flow of emotions” to be mapped and analysed. Emotion awareness is a new frontier in ICT development and the platforms being developed today will pave the way for an explosion of innovative applications. Having validated our system as a mobile service platform, we propose to change the rules of focus group market research and create new growth opportunities through replication in other markets including medical, retail, online training and others.

Keywords: facial recognition,emotions analysis,market research,focus groups,affective computing,saas platform,health solution,retail solution,customer analytics,online learning,recruitment
New photoswitchable materials based on electron transfer process (ETSMM)

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: Chemistry
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-04-01
End date: 2019-03-31
Duration (months): 24.0
Total project cost (EUR): 173076.0
EU funding (EUR): 173076.0
Participants: 1
Project status: CLOSED

Design and synthesis of molecular materials whose physical properties can be controlled by external stimuli are of the most advanced research interests. In this project we aim to synthesize and study in-depth a family of molecular compounds with adjustable electronic properties based on an intramolecular electron transfer (ET) mechanism. The ET phenomenon defines two stable states that can be controlled by temperature, light, electric field, pressure or a chemical stimulus and can be used to design new molecular switches. Following an innovative bottom-up approach, we will generate a family of new switches from the association of donor (LFe(CN)x) and acceptor (L’Co(solv)) building blocks. The obtained systems will be then associated within assemblies in order to produce functional networks with specific, sought-after electronic, optical and magnetic properties, such as photo-induced Single-Molecule Magnet behavior. The ET phenomenon has a high potential technological importance since the photo-induced changes in optical and magnetic properties could in principle allow the design of storage devices with exceptional high density.

Keywords: electron transfer,photomagnetism,switchability,photoinduced single molecule magnet behaviour
Modelling cortical information flow during visuomotor adaptation as active inference in the human brain (ViMoAct)

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: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-11-01
End date: 2020-05-02
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Recent research suggests that to control bodily movements the brain relies on Bayes-optimal predictive models that are updated by sensory prediction error. This assumption may be generalised within a new formal account of motor control as active (Bayesian) inference. Active inference explains motor control in terms of hierarchical Bayesian filtering or predictive coding, i.e., as belief updating and suppression of prediction error to optimise a hierarchical generative model in the brain; thereby the weighting of prediction errors by their predicted precision determines their relative impact on hierarchical inference. This novel proposal still lacks concrete empirical investigation. The proposed project will close this research gap by testing whether cortical information flow during manual actions, requiring visuomotor adaptation and cognitive control of attention, follows the principles of active inference. In two fMRI experiments and one MEG experiment, participants will move a photorealistic virtual hand model via an MR-compatible data glove to perform simple manual tracking tasks in a virtual reality environment. The precision of prediction errors at multiple levels of a previously established cortical motor control hierarchy will be experimentally manipulated via visuoproprioceptive conflicts (introduced by delayed visual movement feedback) and via attentional allocation – either stimulus-driven (via increased sensory noise) or endogenous (instructed) – to visual or proprioceptive movement feedback. Active inference’s specific predictions about information flow between and within cortical areas will be tested with recently established dynamic causal modelling of the modelled hemodynamic (fMRI) or spectral (MEG) responses. Active inference appeals to a general free-energy principle of brain function; this contribution will thus promote interdisciplinary exchange of knowledge about self- and world-representation in the brain and will be of general public interest.

Keywords: visuomotor adaptation,motor control,active inference,precision weighting,fmri,dynamic causal modelling
European Plant Phenotyping Network 2020 (EPPN2020)

Framework: Horizon 2020 — Excellent Science
Programme: Research Infrastructures
Theme: Research infrastructures
Destination: Integrating activities and infrastructures
Action type: Research and Innovation actions
Countries involved: Italy,Germany,Germany,Germany,Australia,Belgium,Finland,Slovakia,Belgium,Hungary,Poland,France,France,France,Netherlands,Netherlands,Denmark,Denmark,United Kingdom,United Kingdom,United Kingdom
Call: Integrating Activities for Advanced Communities (H2020-INFRAIA-2016-1, 2016)
Start date: 2017-05-01
End date: 2021-10-31
Duration (months): 54.0
Total project cost (EUR): 10220249.5
EU funding (EUR): 9999999.5
Participants: 23
Project status: CLOSED

EPPN2020 will provide European public and private scientific sectors with access to a wide range of state-of-the-art plant phenotyping facilities, techniques and methods. It will aid the community in progressing towards excellence across the whole phenotyping pipeline, involving sensors and imaging techniques, data analysis in relation to environmental conditions, data organization and storage, data interpretation in a biological context and meta-analyses of experiments. It builds upon the starting community project EPPN and will coordinate its activities with the ESFRI infrastructure EMPHASIS and with national programs. EPPN2020 involves: - Access to 31 key installations (15 infrastructures), chosen for excellence and avoidance of redundancy, with capacity of hundreds of genotypes and dedicated to innovative non-invasive measurement of traits at different levels of plant organization. - Three Joint Research Activities. JRA1 develops novel techniques and methods for environmental and plant measurements, in particular for assessing the spatial variability of environmental conditions in each platform. JRA2 develops tools for statistical analysis of phenotyping experiments across platforms and scales of plant organization. JRA3 develops a European Phenomic Information System, based on novel information technologies and standardization strategies. - Networking Activities. NA1 organises access and selection of projects, NA2 establishes cooperation and increases integration between facilities both within and outside EPPN2020. EPPN2020 (i) extends the infrastructure offered to the community; (ii) develops synergies between infrastructures and cross fertilization between disciplines, via common experiments in JRAs; (iii) builds a European information system to manage the information generated by installations, with an open data strategy; (iv) provides training at all career levels; (v) is closely linked with industry, both SMEs providing technology and breeding companies

Keywords: plant,non invasive imaging,functional imaging,whole plant,phenomics,controlled conditions,genetic variability,information system,environment,climate change,plant performance,tolerance
TECHNOLOGY FOR THE REUSE OF BRINES FROM REVERSE OSMOSIS (USEFUL WASTES)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-06-01
End date: 2018-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

USEFUL WASTES is a new company that has developed an innovative technology that allows the complete reutilization of brines from reverse osmosis process in food industry, transforming this waste into different valuable byproducts. Reverse osmosis is widely used to treat water in food industry due to the water quality requirements when it is used to clean, freeze or cook food, obtaining 75% of high quality water and 25% of brine that is discarded. With the aim of reducing this waste of water USEFUL WASTES was founded in 2016, and its main strengths are: - Improvement in water production, from the current 75% to 95-97%; - Circular economy: the remaining 1% is transformed into different valuable byproducts, such as bleach, salts or hydrogen gas; - Bleach self-production: this product is massively used in the food industry for cleaning and disinfection. Its production as a byproduct will allow the company not only to reduce costs but also to not be dependent on bleach suppliers. But most of all, the main advantage of USEFUL WASTES that guarantees its success is that it is profitable. Operating costs are smaller than the cost associated to bleach purchase (estimated savings are 4c€ per litre), without taking into account the savings obtained in water supply (22-24% of water that was being discarded is now transformed into fresh and soft water). Regarding the main competitors, brine management sector is completely dedicated to solving the problem caused by desalination plants’ brines, potentially dangerous for the marine ecosystems where they are discharged due to its high content in nitrates, so there are no solutions in the market targeting food industry. During phase 1, USEFUL WASTES will elaborate a detailed business plan which will set the strategy to commercialize successfully its innovation all over Europe.

Keywords: reverse osmosis,brine,electrolysis,water scarcity,circular economy,zero wastes
Eagre/Aegir: high-seas wave-impact modelling (EAGRE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Industrial Doctorates
Action type: Marie Skłodowska-Curie actions
Panel: Mathematics
Countries involved: Netherlands,United Kingdom
Call: Innovative Training Networks (H2020-MSCA-ITN-2019, 2019)
Start date: 2020-01-01
End date: 2023-12-31
Duration (months): 48.0
Total project cost (EUR): 606345.12
EU funding (EUR): 606345.12
Participants: 2
Project status: SIGNED

The overall objective is to create and deliver computational/mathematical modelling tools for solving problems in maritime engineering, based on advanced mathematical/numerical analysis and efficient implementation and testing in a general finite-element simulation environment offered by Firedrake (Imperial College with Leeds). Our key task is to offer training/research such that a so-called "numerical wavetank" is established by two ESRs for use in maritime-engineering wave basins, such as operational for consulting at the Maritime Research Institute Netherlands (MARIN Academy). Our research will provide the ESRs with a skill set that is highly attractive in the job market to employers engaged in high-end consulting. The integrated objectives are to create: (i) a numerical wavetank “ExtremeWaves” (ESR1) concerning modelling of extreme or rogue waves in wave basins integrated with (ii) a numerical wavetank “WaveTurbineImpact” (ERS2) concerning wave-structure interactions, especially wave-impact, on a dynamic wind-turbine mast. The overall objectives build on our recent and current collaborative work (between U. of Leeds and MARIN Academy) on the modelling of water waves and wave-structure interactions with (dis)continuous Galerkin finite-element methods. The above objectives offer challenging demands, not least because the prediction of wave motion around moving or flexible structures is a difficult computational task as a result of the requirement to track (generally using a sophisticated approximation) the a-priori-unknown nonlinear air-water and water-structure interfaces (and their cross-section, the waterline). Conquering these demands is timely because numerical simulations are cheaper than laboratory tests. Moreover, because in realistically motivated challenges mathematical modelling, laboratory testing and cross-validation via computational simulation are inextricably entwined, we view them all as essential components in our so-called "Research Trinity".

Keywords: maritime engineering,water waves,rogue waves,wave impact on wind turbines,finite element modelling
Responsible research and Innovation Policy Experimentations for Energy Transition (RIPEET)

Framework: Horizon 2020 — Science with and for Society
Programme: Integrate society in science and innovation issues, policies and activities in order to integrate citizens' interests and values and to increase the quality, relevance, social acceptability and sustainability of research and innovation outcomes in various fields of activity from social innovation to areas such as biotechnology and nanotechnology
Action type: Coordination and support actions
Countries involved: Spain,Italy,Austria,Belgium,Finland,Netherlands,United Kingdom
Call: Supporting the development of territorial Responsible Research and Innovation (H2020-SwafS-2020-1, 2020)
Start date: 2021-02-01
End date: 2024-01-31
Duration (months): 36.0
Total project cost (EUR): 1999831.25
EU funding (EUR): 1999831.25
Participants: 12
Project status: SIGNED

The RIPEET project will support Responsible Research and Innovation (RRI) policy experimentations for energy transition in three European territories - in Extremadura (ES), Highlands and Islands of Scotland (UK) and Ostrobothnia (FI). The methodology builds on RRI, transformative innovation, transition management and the Multi-Level-Perspective. RIPEET brings together quintuple helix actors of the territorial socio-technical energy regime in Transition Labs in order to envisage and implement a place-based energy transition process. Building on this evolutionary model of socio-technical transitions, RIPEET will use existing landscape and regime-level pressures to facilitate the development of territorial socio-technical futures based on RRI actions. The governance and agency in this transformative process will be organised within the Transition Labs. These Labs will bring together stakeholders to co-create common visions based on the potentials and priorities of territorial eco-systems (mapping and visioning), generate transition pathways and innovation needs, launching a call for immediate bottom-up solutions to these (pathways and piloting) and anchor the process on organisational as well as policy level (sustainability and exploitation). The framework conditions, processes, and outcomes of these experiments will be mapped, monitored, and evaluated. This constitutes an evidence-base for the revision of sectoral policies, strategies and research and innovation (R&I) instruments as well as for establishing a European RIPEET community. Thereby, RIPEET will support territories in establishing experimental spaces to address the territorial dimensions of the European Green Deal. The consortium consists of 11 renowned and EU-FP-experienced universities, research organisations, SMEs, CSOs, business and innovation centres and regional authorities from seven European countries, with the competences and territorial anchoring necessary to implement the approach.

Keywords: smart specialisation,transformative innovation,transition management,energy transition,innovation policy,european green deal,co creation
Big Splash: Efficient Simulation of Natural Phenomena at Extremely Large Scales (Big Splash)

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: Austria
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-03-01
End date: 2020-08-31
Duration (months): 66.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: CLOSED

Computational simulations of natural phenomena are essential in science, engineering, product design, architecture, and computer graphics applications. However, despite progress in numerical algorithms and computational power, it is still unfeasible to compute detailed simulations at large scales. To make matters worse, important phenomena like turbulent splashing liquids and fracturing solids rely on delicate coupling between small-scale details and large-scale behavior. Brute-force computation of such phenomena is intractable, and current adaptive techniques are too fragile, too costly, or too crude to capture subtle instabilities at small scales. Increases in computational power and parallel algorithms will improve the situation, but progress will only be incremental until we address the problem at its source. I propose two main approaches to this problem of efficiently simulating large-scale liquid and solid dynamics. My first avenue of research combines numerics and shape: I will investigate a careful de-coupling of dynamics from geometry, allowing essential shape details to be preserved and retrieved without wasting computation. I will also develop methods for merging small-scale analytical solutions with large-scale numerical algorithms. (These ideas show particular promise for phenomena like splashing liquids and fracturing solids, whose small-scale behaviors are poorly captured by standard finite element methods.) My second main research direction is the manipulation of large-scale simulation data: Given the redundant and parallel nature of physics computation, we will drastically speed up computation with novel dimension reduction and data compression approaches. We can also minimize unnecessary computation by re-using existing simulation data. The novel approaches resulting from this work will undoubtedly synergize to enable the simulation and understanding of complicated natural and biological processes that are presently unfeasible to compute.

Keywords: computer animation,physics simulation,fracturing solids,liquid simulation,computational fluid dynamics,animation control
DEgradation TRIggered by MOdular DEsign (DETRIMODE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-05-21
End date: 2020-07-30
Duration (months): 24.0
Total project cost (EUR): 168277.2
EU funding (EUR): 168277.2
Participants: 1
Project status: CLOSED

The project DETRIMODE (DEgradationTRIggered by MOdular Design) aims at the development of a methodology for the modular synthesis of Targeted Protein Degradation Inducers (TPDI), designed as bifunctional molecules apt to the degradation of target proteins via recruitment of the ubiquitin proteasome system, a process with therapeutic prospects if applied to disease driving proteins. TPDIs are comprised of an E3 ligase ligand and a target protein ligand joined by a spacer (linker), to bring the ubiquitinating system and the target protein in close proximity, so to promote degradation of the latter. The formation of the ternary complex (target protein-TPDI-E3 ligase) is an articulated process influenced by a series of factors, such as ligands affinity, linker length and composition and molecular features of the proteins involved. The project tackles this endeavour in stages of increasing innovation, progressively incrementing the scope, flexibility and efficiency of modular synthetic access to arrays of tripartite molecules via protected, solid grafted intermediates, combinable with a variety of target ligands. New chemical entities TPDIs will be generated targeting selected purinome proteins oncology-related. This project will be pursued within the Chemical Core Technologies Dept. of a fully integrated company (NMS), engaged in the discovery and development of new small molecule based drugs. Organic and solid phase chemistry, computational and structural chemistry, molecular and cell biology, among others, will be exploited to achieve the project’s goal. In such multidisciplinary environment, this new technology will grow at the same speed with the researcher’s medchem competence, increasing the chance of mutual success. DETRIMODE outcomes will be shared with peers, while updates on its progresses as well as general information on how EC-funded research have impact on the general public will be communicated by a number of means, bringing science closer to society