Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Acoustics-based drone navigation and interaction (EARS)

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: Israel
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-09-01
End date: 2026-06-30
Duration (months): 70.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: SIGNED

Autonomous multi-rotor aerial vehicles (MAVs) are an emerging technology, which has a large number of current and potential applications in a wide range of industries. These airborne vehicles are becoming growingly autonomous thanks to modern artificial intelligence technologies, with their navigation and interaction capabilities based predominantly on visual sensing. While vision navigation has attracted considerable attention, it suffers from a poor performance in low light, limited field of view, and direct sunlight and is vulnerable to occlusions. Acoustic sensing can complement and even replace vision in many situations, and it also benefits from lower system cost and energy footprint, which is especially important for small form-factor aircraft. While novel acoustic technologies based on phased microphone arrays are making their way into the Internet of Things and home automation markets, their use in MAVs is currently impeded by the strong self-noise generated by the drone propulsion system. Consequently, existing commercial and research aerial platforms have advanced vision capabilities, yet no acoustics. This project targets to change this situation, endowing drones with "ears". The proposed research aims at the development of novel machine learning-based algorithms and real-time systems for acoustic-based autonomous mapping, localization, and interaction of MAVs. One of the key ideas of the proposal consists of actively controlling and shaping the aircraft self-noise for the benefit of the navigation and interaction tasks, instead of considering it a harmful nuisance. Our end goal is to demonstrate a flying proof-of-concept system which, to the best of our knowledge, will be the first of its kind. While the primary goal of the project is very specific, achieving it will require a considerable amount of scientific and methodological innovation in modelling, signal processing, and machine learning that we expect to have a significant impact on broad domains.

Keywords: acoustic imaging,inverse problem,intelligent systems,simultaneous localization and mapping
R-MESH radio development project (R-Mesh radio)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Finland
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-05-01
End date: 2018-07-31
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Refecor Oy has been developing new R-Mesh radio technology that brings more resilience and reliability to critical radio communications for harsh industrial applications (mines, tunnels, logistics in harsh environments) and for public safety and security (emergency units, communications between ambulances and hospitals, fire cars and public safety, police operations...). Our plan is to get funding to boost up our capability to enter into international markets and co-operation in EU area. We have good track record and a number of customers in smaller scale, but with EU support we can grow our business fast and create new product platform for commercial and public safety markets. Refecor has excellent engineering skills (ex-Nokia) and experience of building products (over 20years) and with this new radio technology we have a chance to offer disruptive solutions for many new customers. We want to grow fast and take our place in the global market.

Keywords: public safety,emergency applications,mesh networks,wireless hd video transmission,sensor network,marine applications,communications in mines,industrial digital communications,resilience
Complex microbial ecosystems multiscale modelling: mechanistic and data driven approaches integration. (E-MUSE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Training Networks
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Italy,Spain,Malta,Belgium,Hungary,France,France,Netherlands,Netherlands,Denmark
Call: Innovative Training Networks (H2020-MSCA-ITN-2020, 2020)
Start date: 2021-01-01
End date: 2025-06-30
Duration (months): 54.0
Total project cost (EUR): 3901305.6
EU funding (EUR): 3901305.6
Participants: 10
Project status: SIGNED

European dairy industry is an important agri-food sector; it represents more than 300,000 jobs and 10 billion € positive trade balance. Five out of the ten top global dairy companies are European and more than 80% of European companies are SMEs. More than 300 cheeses and dairy products are sold all over the world and are protected as geographical indications or traditional specialties. Mastering cheese-ripening processes to avoid sanitary risk and waste, and produce typical cheeses with organoleptic properties valued by the consumers is of economic and social significance. E-MUSE aims to develop innovative modelling methodologies to improve knowledge about complex biological systems and to control and/or predict their evolution by combining artificial intelligence and systems biology. This multidisciplinary strategy integrating genome-scale metabolic models, dynamic modelling methodologies, together with the design of efficient statistical and machine learning tools, will allow analysing of multi-omics data and linking the results to macro-scale properties related to cheese ripening and consumer preference. Bioinformatics has addressed this issue by data mining; however, a gap still exists between the molecular scale information and the macroscopic properties that E-MUSE will contribute to fill. Moreover, in the context of sustainable development, more and more consumers are diversifying their diet and consume plant-based food. Introduction of plant-based proteins in the cheese process brings issues such as bitterness or safety. Modelling strategies from the E-MUSE project will help to target and solve these issues. Finally, E-MUSE will train researchers with multidisciplinary skills in mathematics, bioinformatics and/or biology to design and use innovative multiscale modelling methodologies, with the ultimate outcome of a dynamic modelling software giving researchers a harmonised language to address future research questions about complex biological systems.

Keywords: omics data,species interactions,applied microbiology,cheese process,plant based food
Centre of Excellence in Digital Health and Personalised Medicine (Clinnova)

Framework: Horizon 2020 — Spreading excellence and widening participation
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Action type: Coordination and support actions
Countries involved: Germany,Luxembourg,Denmark
Call: Teaming Phase 1 (H2020-WIDESPREAD-04-2017-TeamingPhase1, 2017)
Start date: 2017-09-01
End date: 2018-08-31
Duration (months): 12.0
Total project cost (EUR): 399800.0
EU funding (EUR): 399800.0
Participants: 5
Project status: CLOSED

We propose to establish a Centre of Excellence in Digital Health and Personalised Medicine (CLINNOVA), addressing future medical and societal needs. A prerequisite for personalised medicine is the establishment of clinical research in Luxembourg, the current weakness that we would like to overcome with the programme. The Centre will build on the previous investments into fundamental biomedical research and link to the hospitals in Luxembourg to ensure that innovation from the bench will reach the clinic and patient care. The Centre will fully incorporate personalised medicine approaches integrating medical history from eHealth records with newly generated molecular and phenotypic data as well as environmental and/or health data from mobile devices. Teaming up with the Center for Innovativ Medicinsk Teknologi, Region Syddanmark (CIMT-RSD) and the Nationale Centrum für Tumorerkrankungen, Deutsches Krebsforschungszentrum (NCT-DKFZ) will allow us to benefit from the immense experience and world-leadership has in setting up modern eHealth infrastructures and translational cancer research. We will focus on areas where there is both existing excellence in pre-clinical research and an important clinical unmet need, namely the disease areas of cancer and neurodegenerative diseases with the transversal axis immunology as important element in both disease areas. Environmental, nutritional and social influences interpreted together with the medical history of patients and molecular diagnostic information will be key to gain an understanding of the diseases for the individual person. A strong ICT component will be a major success factor: data integration and interpretation are needed to derive computational models and predictions on disease development. The Centre will combine all aspects of technological innovation with clinical care and bring innovations to patients and doctors serving as an attractor for companies and further develop the local ecosystem.

Keywords: digital health,personalised medicine,electronic health records,translational medicine
Advanced bioinformatics for genome and metagenome analyses and discovery of novel biocatalists from extremophiles: implications for improving industrial bioprocesses (MeTABLE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Italy,Italy,Italy,Türkiye,France,United Kingdom,Pakistan
Call: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (H2020-MSCA-RISE-2014, 2014)
Start date: 2014-12-01
End date: 2018-11-30
Duration (months): 48.0
Total project cost (EUR): 337500.0
EU funding (EUR): 337500.0
Participants: 8
Project status: CLOSED

The aim of this proposal is to acquire new insights about the mechanisms of environmental adaptation, particularly for cold-adapted organisms, and to discover novel metabolic pathways and enzymes with potential industrial value. We intend to accomplish this goal by establishing a collaboration and a knowledge-exchange network between industrial and academic partners aiming at developing bioinformatic tools for genomic analysis and biotechnology tools for directed evolution. The partners present high complementarity: UNICAM holds genomic sequences from psychrophilic and mesophilic ciliates that need to be annotated and analysed. Sabanci provides environmental samples for the isolation and characterization of new extremophiles. CAMBRIDGE provides the know-how for the discovery of new metabolic pathways valuable for understanding environmental adaptation. BMR Genomics and COMSATS possess all the facilities for genome sequencing and annotation and bioinformatic expertise with the purpose of developing new tools to analyse genomes of microorganisms from extreme environment. UNIMIB owns the facilities for the heterologous expression of gene sequences in bacteria and yeasts and technologies to assess and implement the properties of novel enzymes towards industrial application. We are confident that the establishment of the international research network proposed, with its synergistic effects, will significantly contribute to push all the involved laboratories to the top level in the field of production of active biomolecules and in the discovery of mechanisms of molecular adaptation under extreme environmental conditions. These discoveries may help the manufacturing of a new generation of ordinary facilities, as cleaning agents, biofuels, with a significant impact on the everyday life of European citizens.

Keywords: sequence annotation,environmental adaptation,molecular evolution,microorganisms,ciliates,psychrophiles
Detergent-free process for dishwashers with cleaning and disinfecting properties (AquaPure)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Nanotechnologies
Action type: SME instrument
Countries involved: Israel
Call: Accelerating the uptake of nanotechnologies, advanced materials or advanced manufacturing and processing technologies by SMEs (H2020-SMEINST-1-2014, 2014)
Start date: 2015-01-01
End date: 2015-04-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Ten years ago, our innovative Israeli SME company, Aqua Solutions Ltd. was founded. Since the beginning, our CEO, Mr. Ahmed Alimi, focused all our efforts on the optimisation of laundering processes by means of cleaning and disinfecting solutions without the usage of detergent. This led us to develop a process that has a strong cleaning ability and a strong disinfecting ability consuming only three elements: electricity, water and salt. With AquaPure our aim is to develop a detergent free process for industrial and household dishwashers. This apparatus will be integrated in the dishwashers and will be capable of reducing the energy consumption per cycle (70%), reduce water consumption (50%), and decrease each washing cycle duration (20%). The innovative technology helps significantly reduce costs per cycle (Energy: household: 200kWh/year; industrial: 330-2830kWh/year; water used: household: 780L/cycle; industrial: 1.200-75.200-40L/year ) and dramatically reduce environmental impact.

Keywords: dishwasher,free detergent,electrolysis,cleaning,disinfecting
Truth and Reconciliation Commissions and the Political Economy of Gender Justice: Discursive Power, Authority and the Subaltern (GenderJust)

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: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-08-01
End date: 2019-07-31
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

This project aims to better understand how Truth and Reconciliation Commissions (TRCs) shape and legitimize international norms on gender justice and how local contexts respond to these norms. While many research projects have focused on the way domestic powerful actors and institutions actively reconstruct new norms to make them fit their own cognitive prior (Acharya 2009; Wiener 2009), the extent to which marginalised actors, such as women victims or victim survivors of mass atrocities, experience and respond to international norms directed to them remains largely unexplored. I consider the cases of South Africa, Rwanda and Colombia. The first objective is to examine the variability of inclusion of gender justice narratives in the TRCs proceedings and policy formulation. I attempt to do this by analysing institutional inputs and networks of actors (Mackay, Kenny and Chappell 2010). The second objective is to understand the role of female witnesses and women collectives in shaping accepted narratives on gender justice (Krizsan and Lombardo 2013). This project is a continuation of the candidate's previous research on local contestation and adaptation of international norms in post-conflict settings. For so doing, the project will follow a qualitative analysis based on TRCs transcripts and semi-structured interviews with strategic groups, providing original empirical evidence of this unexplored level. Data collection will take place during monthly mobilities to each of the countries. These data will then be analysed following grounded theory techniques and critical discourse analysis. The research will be conducted at the Department of Politics and International Studies at the University of Cambridge where the candidate will receive high level training to improve her methodological skills (qualitative data analysis and theory producion) and will greatly benefit from the host organisation's experience in interdisciplinary research on international norms.

Keywords: gender justice,transitional justice,truth and reconciliation commissions,life cycle of international norms,norm contestation,local civil society,women organisations
Transparent and flexible electronics with embedded energy harvesting based on oxide nanowire devices (TREND)

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: Portugal
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-01-01
End date: 2022-09-30
Duration (months): 69.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: CLOSED

The Internet of Things is shaping the evolution of information society, requiring an increasing number of objects with embedded electronics, sensors and connectivity. This spurs the need for systems where summing to performance and low cost, multifunctionality has to be assured. In this context, TREND aims to take transparent electronics into as-of-yet unexplored levels of integration, by combining on flexible substrates transparent and high-speed nanocircuits with energy harvesting capabilities, all based on multicomponent metal oxide nanowires (NWs). For this end, sustainable and recyclable materials as ZnO, SnO2, TiO2 and Cu2O will be synthesized in different forms of heterostructured NWs, using low-temperature and low-cost solution processes. For precise positioning, NWs will be directly grow on flexible substrates using seed layers patterned by nanoimprint lithography. This will be crucial for integration in different nanotransistor structures, which will be combined into digital/analog nanocircuits following planar and 3D approaches. Energy will be provided by piezoelectric nanogenerators with innovative structures and materials. Final platform of nanocircuits+nanogenerators will make use of NW interconnects, bringing a new dimension to the systems-on-foil concept. The research will be carried out at FCT-UNL, in a group pioneering transparent electronics. My PhD on oxide materials/devices and proven expertise on circuit integration, oxide nanostructure synthesis and nanofabrication/characterization tools will be a decisive contribute to the implementation of the proposal. TREND is an ambitious multidisciplinary project motivating advances in materials science, engineering, physics and chemistry, with impact extending from consumer electronics to health monitoring wearable devices. By promoting new ideas for practical ends, it will contribute to place Europe in the leading position of such strategic areas, where sustainability and innovation are key factors.

Keywords: transparent electronics,oxide nanowires,transistors,device integration,energy harvesting
Statistics, Prediction and Causality for Large-Scale Data (CausalStats)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Switzerland
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2018-10-01
End date: 2024-03-31
Duration (months): 66.0
Total project cost (EUR): 2184375.0
EU funding (EUR): 2184375.0
Participants: 1
Project status: SIGNED

Understanding cause-effect relationships between variables is of great interest in many fields of science. However, causal inference from data is much more ambitious and difficult than inferring (undirected) measures of association such as correlations, partial correlations or multivariate regression coefficients, mainly because of fundamental identifiability problems. A main objective of the proposal is to exploit advantages from large-scale heterogeneous data for causal inference where heterogeneity arises from different experimental conditions or different unknown sub-populations. A key idea is to consider invariance or stability across different experimental conditions of certain conditional probability distributions: the invariants correspond on the one hand to (properly defined) causal variables which are of main interest in causality; andon the other hand, they correspond to the features for constructing powerful predictions for new scenarios which are unobserved in the data (new probability distributions). This opens novel perspectives: causal inference can be phrased as a prediction problem of a certain kind, and vice versa, new prediction methods which work well across different scenarios (unobserved in the data) should be based on or regularized towards causal variables. Fundamental identifiability limits will become weaker with increased degree of heterogeneity, as we expect in large-scale data. The topic is essentially unexplored, yet it opens new avenues for causal inference, structural equation and graphical modeling, and robust prediction based on large-scale complex data. We will develop mathematical theory, statistical methodology and efficient algorithms; and we will also work and collaborate on major application problems such as inferring causal effects (i.e., total intervention effects) from gene knock-out or RNA interference perturbation experiments, genome-wide association studies and novel prediction tasks in economics.

Keywords: application in biology and economics,causal inference,genetic pertubations,genomics,high dimensional inference,invariant prediction