Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Predictive Energy Management in Plug-in Hybrid Electric Vehicles (pPHEV)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-01-01
End date: 2018-06-30
Duration (months): 18.0
Total project cost (EUR): 146591.1
EU funding (EUR): 146591.1
Participants: 1
Project status: CLOSED

Plug-in hybrid vehicles (PHEV) offer an ample alternative for low-carbon road mobility, which however impose a significantly challenge on maximising energy efficiency and driving autonomy. This pPHEV project aims at addressing this challenge by developing a predictive energy management system for PHEVs as well as realise an advanced career development for the experienced researcher using a clearly defined training-through-research approach. This proposed predictive control management will benefit from and integrate driver driving style information, and dynamic traffic and speed information within this project, along with a few on-going vehicle electrification and intelligence research activities at Cranfield University. This fellowship provides an excellent opportunity for the experienced researcher to advance the career training to secure a leading independent position at the end of the fellowship. The research outcomes will offer a step change in PHEV energy management, and promote knowledge sharing among different EV/HEV-related communities. The pPHEV project will not only advance the research, innovation and development of future PHEVs, but will also improve public awareness of smart green transport.

Keywords: predictive energy management,driving style recognition,dynamic traffic and speed prediction,plug in hybrid electric vehicles
Promoting societal engagement under the terms of RRI (PROSO)

Framework: Horizon 2020 — Science with and for Society
Programme: Develop the governance for the advancement of responsible research and innovation by all stakeholders, which is sensitive to society needs and demands and promote an ethics framework for research and innovation
Action type: Research and Innovation actions
Countries involved: Germany,Austria,Belgium,Bulgaria,United Kingdom,United Kingdom,Portugal
Call: Fostering RRI uptake in current research and innovations systems (H2020-GARRI-2014-1, 2014)
Start date: 2016-01-01
End date: 2018-02-28
Duration (months): 26.0
Total project cost (EUR): 1414812.5
EU funding (EUR): 1414812.5
Participants: 8
Project status: CLOSED

The main objective of PROSO is to foster societal engagement under the terms of RRI in the research and innovation systems in Europe through generation of a policy guide for developing governance for the advancement of societal engagement under RRI in relation to three fields of R&I. The policy guide will be based on the results that PROSO will achieve through an analysis of barriers and incentives for engaging Third sector actors and citizens under the terms of RRI in relation to publicly funded research including public-private partnership research initiatives. This analysis will be carried out across three R&I domains (nanotechnology; food & health; bio-economy) focusing on selected cases of R&I situations in each domain and be based on an investigation of the points of view of Third sector actors and citizens and of other stakeholders/actors contributing significantly to RRI including science/technology policy makers, research funders, academics, and industry/businesses. Main methods used will be semi-structured interviews with the major actors contributing to RRI; national citizen panels that will be carried out in five European countries; an European multi-actor deliberation event on promising approaches to encourage and implement societal engagement under the terms of RRI; and a couple of expert/stakeholder workshops on selected topics.

Keywords: societal engagement,barriers,incentives,third sector organizations,citizen science,policy guide,food and health,nanotechnology,bio economy
Rationally optimized, nanostructure-based biosensors for multi-biomarker cancer diagnostics (TopNanoBiosen)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-09-01
End date: 2025-06-30
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: SIGNED

While electrochemical biosensors are attractive methods of cancer detection, thanks to their low cost and ease of use, nanostructured materials (NSM) are being widely utilized as their biosensing elements due to large surface-to-volume ratio and high sensitivity to external charge transfer. Despite the promise of high performance, current NSM-based electrochemical biosensors for cancer detection focus on one NSM analyzing only a single biomarker type, which makes them unsuitable for low-concentration biomarker detection as required in the analysis of bodily fluids. The combination of several biomarkers has both conceptual and experimental challenges, since different biomarkers have different requirements on the NSM type with different chemistry and transduction mechanisms. Thus, the morphological and physical differences have to be considered for co-integrating such diverse NSMs. I propose to elucidate the effect of NSM morphologies, compositions, and junctions on the operation, sensitivity, and fabricability of biosensors for cancer detection. This goal will be achieved by employing realistic carrier conduction simulations of state-of-the-art NSM assemblies with varying morphology, geometry, and transduction mechanisms to external stimuli. Using my expertise on complex-network-based modelling, the proposed project will provide guidelines for the design of nanostructured devices for optimal biosensors, and allow extrapolation towards the highest achievable performance. This knowledge will inform the fabrication of assay-type electrochemical biosensors for applications in cancer diagnostics. The strong multidisciplinary nature of the project will benefit from the complementary expertise between me and the host institution, enabling a synergy of fundamental advances and application-oriented research. My proposal opens up a new route for achieving high sensitivity biosensing for future diagnostics and therapeutics.

Keywords: nanostructured materials,complex network,cancer detection,biosensor
Feasibility study for an innovative direct drive tidal turbine (Direct Drive TT)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: United Kingdom
Call: Stimulating the innovation potential of SMEs for a low carbon energy system (H2020-SMEINST-1-2014, 2014)
Start date: 2014-10-01
End date: 2015-03-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Nova Innovation is a leading designer and manufacturer of tidal turbines. We have designed, built, deployed and are currently operating a grid-connected turbine in Scotland. In this project we will conduct a feasibility study into the market potential for our direct-drive tidal turbine design. One way to reduce the cost and increase the reliability of tidal turbines is to find innovative ways to utilise the benefits of the subsea environment by using seawater to lubricate and cool the turbine drive train. Another is to reduce the number of offshore components by eliminating the gearbox to produce a direct-drive turbine. These steps reduce or eliminate the need for expensive and failure-prone equipment such as high pressure shaft seals, watertight bulkheads and cooling systems. This reduces operational costs and increases device reliability and yield. No company to date has developed a direct drive tidal turbine that is reliable and economically viable. Our design is innovative in the particular combination of drive train, blade and support structure design, which is optimised to minimise the lifetime cost of the integrated system. Potential customers are tidal energy project developers seeking to generate predictable, reliable energy from the tides at minimum lifetime cost. The market for tidal power is global, but Europe is taking a lead with potential clients in the UK, France and Ireland. Once proven in Europe the technology can be exported worldwide, with a potential global market of 800 TWh per annum (IEA-OES), or annual electricity sales of over €40 billion. In Phase 1 we will conduct a feasibility study including a detailed IP review and strategy development, supply chain and market study and risk assessment to reinforce our business plan for exploiting this invention. In Phase 2 we will conduct a full-scale demonstration of the technology in a real-world setting: Nova Innovation’s existing, permitted, in-sea, grid-connected tidal energy site.

Keywords: tidal energy marine renewable
Material counting technologies in numerical cognition (MaCoTech)

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: Norway
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-06-15
End date: 2020-06-14
Duration (months): 24.0
Total project cost (EUR): 208400.4
EU funding (EUR): 208400.4
Participants: 1
Project status: CLOSED

Material counting technologies (MaCoTech) play a critical role in developing human numerical concepts like numbers, numerical relations, and arithmetical operations. Yet today, our understanding of how these concepts emerge is still very restricted, as the influential effects of prehistoric MaCoTech and Ancient Near Eastern (ANE) mathematics are difficult to assess and have been mostly neglected in modern-day research. The comparison of ANE MaCoTech to its extant counterparts of Oceania will allow investigating the impact of multiple MaCoTech on numerical elaboration, and to gain a deeper understanding of the evolution of numerical concepts in socio-historical contexts. This will include the first-ever generation of a dataset of ANE and Oceanian MaCoTech and the development of innovative strategies for cross-cultural data analysis. The project will apply state-of-the-art paradigms on the nature of human cognition to improve our understanding of how MaCoTech structure numerical concepts, which will generate novel insights into numerical origins and the role of materiality in human cognition. It will also engender new understandings of psychological–behavioral–material interactions with potential utility in cognitive-psychological research. As a cognitive archaeologist with a strong background in the materiality of numbers, I want to be among the first to work at a novel interdisciplinary crossway connecting the fields of archaeology, psychology, anthropology, linguistics, and Assyriology. With a renowned researcher in numerical cognition as my supervisor and my own expertise in ANE number systems, ANE archaeology, and philosophy of mind, this will bring me in the optimal position to foster an international high-level career in numerical cognition research at the interface of multiple disciplines. This will be substantiated by the mutual transfer of knowledge as well as national and international long-term research synergies.
Advanced Data Mining Procedures Applied to Raman Spectroscopy Investigations of Interactions between Drugs and Cells. (Spectro-Metrics)

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: Ireland
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-05-28
End date: 2021-02-03
Duration (months): 24.0
Total project cost (EUR): 187866.0
EU funding (EUR): 187866.0
Participants: 2
Project status: CLOSED

Spectro-Metrics focuses on the development and validation of advanced chemometric procedures for investigating drug intake and metabolism in cells using confocal Raman micro Spectroscopy (RS). The project will develop and optimize data mining procedures such as Multivariate Curve Resolution-Alternate Least Squares (MCR-ALS), Supported Vector Machines (SVM) and Science Based Calibration (SBC) for the extraction of biologically relevant information from RS of cells. The applicability of the procedures will be thoroughly validated in vitro including studies on the effect of drug concentration, incubation time and drug distribution within cells. Research activities will include the use of simulated and real spectroscopic data obtained from in vitro studies for investigating the effect of inoculation with the commercial drugs, doxorubicin (DOX) and actinomycin (ACT) in lung cancer cells, as a function of time and dose, as model systems. Upon completion, the project will produce validated methodologies and procedures for resolving Raman spectra which will lead to the elucidation of the modes of drug action and validation of Raman as a preclinical screening technique for drug design and discovery. The knowledge, grant writing skills and publication record acquired during the fellowship will place the Experienced Researcher (ER) in an invaluable position for achieving research independence, becoming a leading expert of chemometric treatment of RS data and eventually becoming a professor in one of the leading European universities in the field of clinical spectroscopy.

Keywords: raman spectroscopy,vibrational spectroscopy,clinical spectroscopy,chemometrics,data mining,pharmacology
Role of Metabolic INteractions in the Eco-evolutionary dynamics of bacteRial communities in the VAgina (MINERVA)

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: Life Sciences
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-04-01
End date: 2023-03-31
Duration (months): 24.0
Total project cost (EUR): 184707.84
EU funding (EUR): 184707.84
Participants: 1
Project status: CLOSED

Bacterial vaginosis (BV) is a polymicrobial syndrome that modifies vaginal secretions and increases risks of reproductive complications and most sexually transmissible infections. This syndrome is associated with a shift in vaginal microbiota composition from lactic-acid producing bacteria to specific bacterial communities. Concomitant with such shift, sialidases can be detected in vaginal secretions where they release sialic acids (SA), sugar molecules that some bacteria can use as a nutrient source and to escape host’s immunity. While the presence of sialidases is used as a BV diagnosis method, we still know little about SA metabolism in the species associated with BV, and even less about SA-related interactions in the community. The proposed project will directly address this question with the ultimate aim of understanding the role of SA metabolism in the transition from health to disease. I will focus my research on the three most prevalent BV-associated bacteria: Gardnerella vaginalis, Prevotella bivia and Atopobium vaginae. First, I will investigate the genomic organization and distribution of the genes involved in SA metabolism. Second, I will link these genotypes to phenotypes by experimentally assessing the expression of those genes in clinical samples from BV-positive and negative women. Third, I will assess the evolutionary stability of SA metabolism genes and bring insight into the respective roles of SA availability and host’s immune system in the evolution of bacterial SA metabolism. Finally, I will create ex-vivo minimal model communities of BV bacteria and examine the ecological interactions between species. By going beyond a taxonomic description to better understand eco-evolutionary functioning, this project will expand our view of the BV microbiome both at the species level, examining in particular intraspecies diversity in genetic composition and expression, and at the community level through the investigation of SA-related interactions.

Keywords: bacterial vaginosis,genomics,microbiome,metabolic interactions,experimental evolution
Modelling of Generic Extreme mass-ratio inspirals (MoGEs)

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: Physics
Countries involved: Germany
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-03-01
End date: 2019-02-28
Duration (months): 24.0
Total project cost (EUR): 171460.8
EU funding (EUR): 171460.8
Participants: 1
Project status: CLOSED

Inspiralling binaries of compact objects are a promising source of gravitational waves (GWs) in the upcoming era of GW astronomy. The MoGEs project proposes to take the next step in modelling the evolution of compact binaries using the gravitational self-force (GSF) formalism. Until now, the linear-in-mass-ratio GSF has only been calculated under the simplifying assumptions of non-spinning, circular, and/or equatorial binaries. MoGEs will, for the first time, calculate linear-in-mass-ratio GSF including all effects of spin, eccentricity and inclination. This is achieved by reconstructing the local metric perturbation produced by a particle from solutions of the Teukolsky equation, which in turn are obtained using the semi-analytical MST formalism. The regular correction to the motion of the particle is then extracted using a mode-sum regularization scheme. The applicant has previously proven this combination of methods effective in the simpler case of equatorial orbits. Knowledge of the GSF will allow the modelling of the evolution of extreme mass-ratio inspirals (EMRIs) and the GWs that they generate. Accurate modelling of the latter is essential if they are to be observed by future GW observatories such as eLISA. Observation of GWs from an EMRI would yield a wealth of physical information, from precise measurements of physical characteristics of the observed system (including mass, angular momentum, and redshift) to fundamental tests of general relativity by providing an accurate map of the spacetime geometry generated by the system. More immediately, MoGEs will capitalize on the new GSF data by combining the expertise of the applicant and the hosts at the Albert Einstein Institute (AEI) to improve the effectiveness of effective-one-body (EOB) models for eccentric spinning binaries. Any such improvements can directly be deployed in the ongoing GW searches at LIGO and Virgo, that already use EOB models in their detection pipelines.

Keywords: extreme mass ratio inspirals,gravitational self force,effective one body,gravitational waves
Provision of a prediction system allowing for management and optimization of snow in Alpine ski resorts (PROSNOW)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Fighting and adapting to climate change
Action type: Innovation actions
Countries involved: Austria,Austria,Italy,Austria,Italy,Switzerland,France,France,France,France,France
Call: Exploiting the added value of climate services (H2020-SC5-2016-TwoStage, 2016)
Start date: 2017-09-01
End date: 2020-08-31
Duration (months): 36.0
Total project cost (EUR): 3557865.5
EU funding (EUR): 3209615.61
Participants: 15
Project status: CLOSED

The PROSNOW project ambitions to build a demonstrator of a meteorological and climate prediction system from one week to several months ahead applied to snow management, specifically tailored to the needs of the ski industry using a co-design approach. This novel climate service holds significant potential to increase the resilience of socio-economic mountain stakeholders and supports their real-time climate change adaptation potential. PROSNOW will apply state-of-the-art knowledge relevant to the predictability of atmospheric and snow conditions, then develop products well beyond state-of-the-art operational tools. Improved anticipation capabilities at all time scales, spanning from “weather forecast” (up to 5 days typically) to “climate prediction” at the seasonal scale (up to several months), will be achieved through a seamless integration of weather and seasonal prediction products, together with snowpack models, in-situ and remotely-sensed observations and cutting-edge statistical tools in support of the decision making process. The project proposes an Alpine-wide system (France, Switzerland, Germany, Austria and Italy). It will associate research institutions for weather forecasts, climate predictions at the seasonal scale and snowpack modeling, a group of providers proposing high tech solutions for snow monitoring and management, and a relevant ensemble of eight representative resorts in the Alps. The added value of such services for ski resorts will be investigated and documented, making it possible to initiate a commercial exploitation of the service at the end of the project.

Keywords: snow,winter tourism,seasonal prediction