Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
In-situ Total Nutrient Analyser System for Natural Waters (H2OMon)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Ireland
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-11-01
End date: 2021-10-31
Duration (months): 24.0
Total project cost (EUR): 1447812.5
EU funding (EUR): 1013468.0
Participants: 1
Project status: CLOSED

The H20Mon project will address the findings of an in-house feasibility study conducted by Tellab and enable rapid commercialisation of our low-cost in-situ multi-parameter nutrient water pollutant monitoring system. The most commonly used method for measuring pollutants is the physical collection of a sample that is then analysed in a laboratory. This has a number of disadvantages, including cost, the results often become available only after several days and that it only shows a snapshot of the situation at the instant of sampling. The complexity, short deployment endurance and high cost of current in-situ monitoring systems make them unaffordable and impractical for many users to put into practice - especially true for small operations. Also, many current systems themselves create pollution due to the emission of chemical reagents used in the analysis. The H20Mon integrated nitrate/phosphorous/ammonia all natural water monitoring system, is rooted in the clear market-pull caused by the industrial and domestic need to comply with increasingly tightly policed water nutrient pollution regulations, infringements of which carry heavy fines. Our solution is a multi-parameter autonomous microfluidic device with in-situ calibration and high -frequency measurements over long deployment periods. Its in-built communication system and process control add-on enable the user to remotely monitor water quality in lakes, rivers, estuaries and coastal zones; alerting them via immediate warning on the detection of a pollutant and enabling immediate action to be taken to limit environmental damage. H20Mon can reduce operating costs by 5%, saving users up to €125,000 p.a. The solution addresses the large and growing in-situ water monitoring market, which is projected to increase from €875m to over €1bn in 2021. Through the H20Mon project, we expect to create accumulated revenue of €27.3m and profit of €18.6m over 5 years creating 22 FTEs in our firm and c.150 in our supply chain.

Keywords: nutrient pollution sensors,affordability,nitrates,phosphates,ammonia,saltwater,freshwater
THAWing permafrost: the fate of Soil Organic Matter in the aquatic Environment (THAWSOME)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Earth system science
Panel description: Physical geography, geology, geophysics, atmospheric sciences, oceanography, climatology, cryology, ecology, global environmental change, biogeochemical cycles, natural resources management
Countries involved: Netherlands
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-12-01
End date: 2022-09-30
Duration (months): 70.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: CLOSED

As the Arctic permafrost region warms, its large organic carbon (OC) pool becomes vulnerable to decomposition. This generates greenhouse gases (GHG) that in turn fuel increased surface warming: the permafrost carbon feedback. Higher temperatures will jump-start the coupling between the carbon and hydrological cycle, allowing for the introduction of previously frozen OC pools in aquatic systems. This lateral, or horizontal, aquatic flux remains largely unknown in contrast to the relatively well-studied vertical flux, GHG emission on land. Horizontal OC release either occurs via gradual thaw, slowly leaching OC into aquatic systems, or abrupt thaw, where ground-ice melt causes destructive surface collapse and slumping of OC into aquatic systems. Both types of thaw facilitate decomposition of OC (generating GHG) but also re-bury OC into sediments (sequestering OC). The relative importance of decomposition versus burial is unknown. For THAWSOME, I have developed a multi-scale approach combining detailed process-based field studies with up-scaling techniques on multiple levels: (i) observational, using large Arctic rivers as natural integrators, (ii) numerical, using a coupled hydrological-biogeochemical model, and (iii) spatial, using GIS-based analysis. For the first time, decomposition of particulate OC from permafrost will be quantified with a recently developed incubation method. Burial rates of permafrost OC will be assessed through molecular isotope analyses of both sources (river OC) and sinks (sediment OC) across the land-to-shelf route. THAWSOME will generate critically needed quantitative data on the amount of decomposition versus burial of permafrost OC, as well as qualitative insights into the processes that control this. This will allow a true coupling of the carbon and hydrological cycle into the 'boundless Arctic carbon cycle', and integration of horizontal OC release into estimates of the impact of the permafrost carbon feedback on global climate.
Enabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach (DREAM-GO)

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: Information Science and Engineering
Countries involved: Germany,Spain,Germany,United States,Portugal,Portugal
Call: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (H2020-MSCA-RISE-2014, 2014)
Start date: 2015-02-01
End date: 2019-01-31
Duration (months): 48.0
Total project cost (EUR): 2385000.0
EU funding (EUR): 2160000.0
Participants: 7
Project status: CLOSED

Smart Grid (SG) concepts are rapidly being transferred to the market and huge investments have been made in renewable based electricity generation and rolling out smart meters. However, the present state of the art does not ensure neither a good return of investment nor a sustainable and efficient power system. The work so far in the EU involves mainly larger stakeholders, namely power utilities and manufacturers more focused on production and grid resources. A closer attention to the demand side of the system is required, and especially in the interaction with the new methods for SG management. Efficient power systems require the optimal use of the available resources to cope with demand requirements and Demand Response (DR) programs with adequate business models can leverage demand flexibility both on centralized and distributed models, as renewable energygeneration is highly dependable of uncontrolled factors (as wind and solar radiation) for which anticipated forecasts are hardly trustful. DREAM-GO puts together research teams from the EU and US thus taking advantage of US experience in DR, teaming up academic partners with pioneer work in smart grid management and non-academic partners (SMEs) with the required know how and infrastructure to jointly produce relevant advancements in the state of the art. SME participation will ensure cross-fertilization of ideas and competences to build a knowledge network targeting the scientific community and other smart grid actors, as power resource managers, grid operators and resource aggregators, and ultimately targeting consumers (through consumers organisations and curtailment service providers) on the demand side. The main goal is to create a framework with the required methods and solutions to facilitate the adoption of the results in final applications, by providing grounded scientific knowledge to possible pathways for future implementation of a more efficient SG system in the EU.

Keywords: demand response,electricity market simulation,load management,metaheuristic optimization,multi agent systems,real time simulation,smart grids,wireless sensing networks
Systemic expansion of territorial CIRCULAR Ecosystems for end-of-life FOAM (CIRCULAR FOAM)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Action type: Innovation actions
Countries involved: Germany,Germany,Germany,Austria,Germany,Germany,Ireland,Italy,Germany,Germany,Germany,Germany,Switzerland,Poland,Belgium,Poland,Poland,Netherlands,Netherlands,Netherlands,Netherlands,Luxembourg
Call: Demonstration of systemic solutions for the territorial deployment of the circular economy (H2020-LC-GD-2020-3, 2020)
Start date: 2021-10-01
End date: 2025-09-30
Duration (months): 48.0
Total project cost (EUR): 19192150.0
EU funding (EUR): 15756499.01
Participants: 26
Project status: SIGNED

CIRCULAR FOAM aims at the demonstration of a territorial cross-sectorial systemic solution for the circularity of high performance plastics from diverse applications on the example of rigid polyurethane foams used as insulation in refrigerators and in construction. The waste streams will be upcycled chemically, which means that they will be valorised to become new virgin-equivalent feedstock for the chemical industry to produce new high performance plastics. In this way, it will become possible to replace limited fossil-based resources by the renewable waste-based ones, thus not only reducing waste, but also becoming more sustainable and making a step forward to climate neutrality. The project and the demonstration are targeting a concrete implementation of the solution in question in the selected regions after the project and developing a blueprint for both the geographical transferability to other regions and for the technological extension of the circularity principle to a number of further waste materials from further applications. We consider here two carefully selected regions: NRW/Germany, Silesia/PL and Greater Amstedam Region. The consortium is composed of all actors required to close the circular value chain (process industries, manufacturing, waste management, technology providers, incl. also research partners, logistics, social scientists and economist working with with public sector and citizens. After practical implementation and replication in EU of the systemic solution, following reductions will have been attained by 2040: 586.000 tons per year less waste, 18,6 mln. tons less CO2 emission; 118 mln EUR less cost for incineration for the PU producers. The system will signifficantly contribute to resilience in regions.

Keywords: alternative raw materials,chemical recycling,plastics recycling,defossilisation,carbon neutrality
Artificial Intelligence techniques for ice core analyses (ICELEARNING)

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: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-01-15
End date: 2022-01-14
Duration (months): 24.0
Total project cost (EUR): 171473.28
EU funding (EUR): 171473.28
Participants: 1
Project status: CLOSED

The detection of insoluble particles trapped in ice or sediment cores, like pollen grains, foraminiferal and diatom assemblages, volcanic and dust particles represents the basis for paleoresearch on the biosphere, volcanism and oceanic and atmospheric realms. To date, except for ice core dust, this analytical goal is achieved during years of particle observations by manual microscopy. Artificial Intelligence predictive models are already applied to several research fields within geoscience, but up to date its implementation to paleoclimate is missing. With ICELEARNING, I aim to develop a two-phase routine for the automatic quantification of insoluble particles trapped in ice cores. The routine is based on a commercial Flow Imaging Microscope producing particle images from within melted ice samples. The images are then analyzed by Pattern Recognition algorithms which will be developed for automatic particle classification and counting. The routine will be specifically developed in order to be implemented in Continuous Flow Analysis (CFA) systems, therefore surpassing the traditional methods by providing continuous particle records from ice cores. ICELEARNING methodology is suitable to any diluted sample, thus representing a ground-breaking analytical advancement from ice core science to marine geology. This innovative routine is automatic and non-destructive, imperative prerequisites for the future Antarctic ice core project analytical measurements, aiming to retrieve a continuous climatic and environmental record covering the last 1.5 Myr. ICELERNING will be developed at Ca’ Foscari University of Venice with Prof. Carlo Barbante, leading expert in trace and ultra-trace level impurity detections in ice cores and with the University of Bergen, a top institution in marine geology and paleoceanography. This unique synergy, in addition to the proposer’s knowledge of CFA systems and machine learning techniques will provide the best preconditions for the project success.

Keywords: pattern recognition,image analysis,core
For a full data privacy on the go. (LPS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: France
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-10-01
End date: 2020-02-29
Duration (months): 5.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

AllPriv is developing next generation nomadic cybersecurity set to entirely disrupt the way data privacy is protected out of the office. Recipient of a CES innovation award, early stages of its technology have already drawn the attention of large enterprises (banks, energy giants…). The growth of telework and the need for productivity during business travel entails exposures such as connection to unsecured WiFi, device loss, and compromised data exchange. Each of these factors pose major security threats to enterprises. Current lead vendors offer partial solutions only, mostly via software embedded in laptops, a far-cry from the level of sophistication offered within the walls of the enterprise. Allpriv has decided to tackle this unresolved problem by formulating a disruptive plan: shield user laptops upstream of them instead embedded in them, miniaturize an entire security stack into a portable hardware format that embeds advanced Blockchain, Artificial Intelligence and several more protection techniques. This approach requires overcoming major technology hurdles that no vendor or even research lab has succeeded in doing so far. After implementing just our first feature (WiFi), Europe’s 3rd largest bank found it compelling enough to request paid testing. Allpriv plans to develop now the most groundbreaking part of its technology by turning the inventions listed above into a concrete design, and jointly testing them with early adopters such as the aforementioned bank. These objectives are tough but attainable: the company filed 6 patents, and has hired a team of expert PhDs. The company CEO, a repeat entrepreneur, has already grown an IT venture to the 3rd largest of its kind in Europe. Both the team capability and early results demonstrate our ability to reach our objectives. Allpriv seeks an SMEi1 grant to accelerate R&D. It has a unique opening to respond to a burning demand by overcoming major technology challenges and hence contribute to employment in EU.

Keywords: cybersecurity,gdpr,data privacy,hacking,wifi,cyber danger,data protection,encryption,fintech,blockchain,machine learning,laptop,traveller,teleworking,cyber risks,ciso,self destruction
Non-Invasive Technology for Intracranial Pressure (ICP) Measurement (ICPstatu)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Denmark
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-12-01
End date: 2020-05-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Elevated IntraCranial Pressure (ICP) is a critical condition derived from diseases or brain trauma. If not treat promptly elevated ICP can cause severe damage on the brain or even death. The gold-standard method to monitor ICP is an invasive and highly complex procedure, which requires drilling a hole in the cranium and proper insertion of catheters in the brain ventricles, exposing the patients to high risk of complications, such as infections and haemorrhage. Due to the high complexity of the procedure and need of expertise, it is very often applied too late, hampering early diagnosis and successful treatments. StatuManu has developed the first non-invasive method to measure variations of ICP with adequate accuracy and precision to be accepted in clinical practices. It is a very user-friendly procedure, consisting of recording a video of the eye fundus by off-the-shelf fundus cameras and further analysis by our software (cloud-based) hosting our unique algorithm capable to deliver a result in less than 1min. StatuManu software will greatly benefit: 1) Healthcare professionals (end-users) by having a decision support tool based on early and accurate assessment of ICP variations, 2) healthcare institutions (customers) by improving services workflow and physicians decision making, saving costs and offering higher quality care; 3) patients by having access to a faster, accurate and non-invasive assessment (anytime, anywhere, whenever needed), and consequently early treatments. ICPstatu project will enable the development of a comprehensive business plan, including a business model compatible with market expansion and growth. We are supported by clinical development partners and our team has the right combination of expertise in image analysis, deep learning, software development and business to perform this project and fulfill all the needs and requests of end-users and customers and benefiting the society as whole.

Keywords: intracranial pressure,decision making tools,trauma brain injury,deep learning
Estuaries shaped by biomorphodynamics, inherited landscape conditions and human interference (ESTUARIES)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Earth system science
Panel description: Physical geography, geology, geophysics, atmospheric sciences, oceanography, climatology, cryology, ecology, global environmental change, biogeochemical cycles, natural resources management
Countries involved: Netherlands
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-12-01
End date: 2021-05-31
Duration (months): 66.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: CLOSED

ESTUARIES are shallow coastal water bodies with river inflow shaped by biomorphological processes, with patterns of channels and shoals, sand/mud flats, tidal marshes, vegetated banks and peat. Development was influenced by early Holocene landscape that drowned under sealevel rise, and by human interference. Estuaries harbour highly productive natural habitats and are of pivotal economic importance for food production, access to harbours and urban safety. Accelerating sealevel rise, changing river discharge and interference threaten these functions, but we lack fundamental understanding and models to predict combined effects of biomorphological interactions, inherited landscape and changing drivers. We do not understand to what extent present estuary planform shape and shoal patterns resulted from biomorphological processes interacting with inherited conditions and interference. Ecology suggests dominant effects of flow-resisting and sediment de/stabilising eco-engineering species. Yet abiotic physics-based models reproduce channel-shoal patterns surprisingly well, but must assume a fixed planform estuary shape. Holocene reconstructions emphasise inherited landscape- and agricultural effects on this planform shape, yet fossil shells and peat also imply eco-engineering effects. My aims are to develop models for large-scale planform shape and size of sandy estuaries and predict past and future, large-scale effects of biomorphological interactions and inherited conditions. We will significantly advance our understanding by our state-of-the-art eco-morphological model, my unique analogue landscape models with eco-engineers and a new, automated paleogeographic reconstruction of 10 data-rich Holocene estuaries on the south-east North Sea coast. We will systematically compare these to modelled scenarios with biomorphological processes, historic interference and inherited valley geometry and substrate. Outcomes will benefit ecology, archeology, oceanography and engineering

Keywords: estuaries,tidal bars,shoals,freshwater tidal marshes,riparian vegetation,holocene,sea level rise,scale experiments,analogue modelling,numerical modelling,paleogeographical reconstruction
Asymptotic approach to spatial and dynamical organizations (ADORA)

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: France
Call: ERC Advanced Grant (ERC-2016-ADG, 2016)
Start date: 2017-09-01
End date: 2023-02-28
Duration (months): 66.0
Total project cost (EUR): 2192500.0
EU funding (EUR): 2192500.0
Participants: 2
Project status: SIGNED

The understanding of spatial, social and dynamical organization of large numbers of agents is presently a fundamental issue in modern science. ADORA focuses on problems motivated by biology because, more than anywhere else, access to precise and many data has opened the route to novel and complex biomathematical models. The problems we address are written in terms of nonlinear partial differential equations. The flux-limited Keller-Segel system, the integrate-and-fire Fokker-Planck equation, kinetic equations with internal state, nonlocal parabolic equations and constrained Hamilton-Jacobi equations are among examples of the equations under investigation. The role of mathematics is not only to understand the analytical structure of these new problems, but it is also to explain the qualitative behavior of solutions and to quantify their properties. The challenge arises here because these goals should be achieved through a hierarchy of scales. Indeed, the problems under consideration share the common feature that the large scale behavior cannot be understood precisely without access to a hierarchy of finer scales, down to the individual behavior and sometimes its molecular determinants. Major difficulties arise because the numerous scales present in these equations have to be discovered and singularities appear in the asymptotic process which yields deep compactness obstructions. Our vision is that the complexity inherent to models of biology can be enlightened by mathematical analysis and a classification of the possible asymptotic regimes. However an enormous effort is needed to uncover the equations intimate mathematical structures, and bring them at the level of conceptual understanding they deserve being given the applications motivating these questions which range from medical science or neuroscience to cell biology.

Keywords: non linear partial differential equations,asymptotic analysis,mathematical biology