Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Deep sub-micron microprocessor for spAce rad-Hard appLIcation Asic (DAHLIA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling European competitiveness, non-dependence and innovation of the European space sector
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Greece,France,France,France
Call: Technologies for European non-dependence and competitiveness (H2020-COMPET-2016, 2016)
Start date: 2017-01-01
End date: 2021-06-30
Duration (months): 54.0
Total project cost (EUR): 4520555.04
EU funding (EUR): 4249148.75
Participants: 9
Project status: CLOSED

We propose the development of a Very High Performance microprocessor System on Chip (SoC) based on STM European 28nm FDSOI technology with multi-core ARM processors for real-time applications, eFPGA for flexibility and key European IPs, enabling faster and cost-efficient development of products for multiple space application domains. The performance is expected to be 20 to 40 times the performance of the existing SoC for space and more than 2 times the performance of the future quad core LEON4 chip. This performance level, combined with a large set of integrated peripherals including dedicated on-chip functions for GNSS, TM and TC support, will enable key space applications to be executed within the same microprocessor significantly reducing cost and mass and boosting competitiveness of future European space equipments. With the highest cumulative number of European satellites and electronics equipments successfully operating in orbit, Airbus and TAS represent together the indisputable best positioned companies in Europe to ensure the maximum relevance of the DAHLIA SoC for its future use by the whole European Space community. Beyond Space applications, the adoption of the ARM processor will enable the convergence with terrestrial applications benefiting from the strong ARM ecosystem while the new SoC will ensure European strategic non dependence for the most critical component on board.

Keywords: microprocessor,real time,system on chip,28nm fdsoi technology,digital telecommunication payload,semiconductor technology,asic
Small cEllS coordinAtion for Multi-tenancy and Edge services (SESAME)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Future Internet: Software, hardware, Infrastructures, technologies and services
Action type: Research and Innovation actions
Countries involved: Spain,Spain,Spain,Italy,Italy,Spain,Italy,Switzerland,Greece,Greece,Greece,France,United Kingdom,United Kingdom,United Kingdom,United Kingdom,Luxembourg
Call: Advanced 5G Network Infrastructure for the Future Internet (H2020-ICT-2014-2, 2014)
Start date: 2015-07-01
End date: 2017-12-31
Duration (months): 30.0
Total project cost (EUR): 8266932.76
EU funding (EUR): 7488432.76
Participants: 21
Project status: CLOSED

SESAME targets innovations around three central elements in 5G: the placement of network intelligence and applications in the network edge through Network Functions Virtualisation (NFV) and Edge Cloud Computing; the substantial evolution of the Small Cell concept, already mainstream in 4G but expected to deliver its full potential in the challenging high dense 5G scenarios; and the consolidation of multi-tenancy in communications infrastructures, allowing several operators/service providers to engage in new sharing models of both access capacity and edge computing capabilities. SESAME proposes the Cloud-Enabled Small Cell (CESC) concept, a new multi-operator enabled Small Cell that integrates a virtualised execution platform (i.e., the Light DC) for deploying Virtual Network Functions (NVFs), supporting powerful self-x management and executing novel applications and services inside the access network infrastructure. The Light DC will feature low-power processors and hardware accelerators for time critical operations and will build a high manageable clustered edge computing infrastructure. This approach will allow new stakeholders to dynamically enter the value chain by acting as 'host-neutral' providers in high traffic areas where densification of multiple networks is not practical. The optimal management of a CESC deployment is a key challenge of SESAME, for which new orchestration, NFV management, virtualisation of management views per tenant, self-x features and radio access management techniques will be developed. After designing, specifying and developing the architecture and all the involved CESC modules, SESAME will culminate with a prototype with all functionalities for proving the concept in relevant use cases. Besides, CESC will be formulated consistently and synergistically with other 5G-PPP components through coordination with the corresponding projects.

Keywords: small cell,network function virtualisation,small cell as a service,mobile edge computing,virtual network function vnf,self x,network management,orchestration,multi tenancy
Data Justice: Understanding datafication in relation to social justice (DATAJUSTICE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Social World and Its Diversity
Panel description: Sociology, social psychology, social anthropology, education sciences, communication studies
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2017-STG, 2017)
Start date: 2018-01-01
End date: 2023-12-31
Duration (months): 72.0
Total project cost (EUR): 1383920.0
EU funding (EUR): 1383920.0
Participants: 1
Project status: SIGNED

This project explores the meaning of social justice in an age of datafication. It is premised on two significant developments: 1) the shift to a focus on the collection and processing of massive amounts of data across social life and 2) the increasing concern with the societal implications of such processes. Whilst initial concern with the technical ability to ‘datafy’ and collect information on ever-more social activity focused on surveillance and privacy, increasing emphasis is being placed on the fact that data processes are not ‘flat’ and do not implicate everyone in the same way, but, rather, are part of a system of ‘social sorting’, creating new categories of citizens, and premised on an emerging order of ‘have’ and ‘have nots’ between data profilers and data subjects. In such a context, questions of social justice and datafication require detailed study. This project frames this research agenda around the notion of ‘data justice’. It will provide a European framework of study and take a holistic approach by situating research on data processes in the context of a) the concrete experiences and practices of particular communities; b) technological analyses of data sources, algorithmic process and data output; c) policy frameworks that relate to the interplay between digital rights and social and economic rights; and d) conceptual engagement with new social stratifications emerging with datafication. The project is ground-breaking in five different respects: i) it conceptually advances the meaning of social justice in a datafied society; ii) it shifts and challenges dominant understandings of data by highlighting its relation to social and economic rights; iii) it addresses an uncharted but rapidly growing response to datafication in civil society; iv) it breaks down disciplinary boundaries in understandings of technology, power, politics and social change; and v) it pursues a combination of engaged research and socio-technical modes of investigation.

Keywords: big data,social justice,algorithms,automation
Precise predictions for extreme mass ratio inspirals (PreciseEMRIs)

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: Ireland
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-09-01
End date: 2022-08-31
Duration (months): 24.0
Total project cost (EUR): 184590.72
EU funding (EUR): 184590.72
Participants: 1
Project status: CLOSED

The gravitational-wave sky has been opened by the first measurement of a gravitational-wave inspiral in 2015 by LIGO. Now, the European detector Virgo has joined the network, and more terrestrial detectors are underway. Furthermore, the European space agency has approved the space-based Laser interferometer space antenna (LISA) as one of its three highest-priority missions for the 2030s. The scientific capabilities of LISA provide European science with a chance to be at the absolute cutting edge of gravitational-wave astronomy. The sensitivity of LISA will be in the in the millihertz gravitational-wave band. One of the most prominent and interesting sources seen in this band are the so-called extreme mass ratio inspirals (EMRIs), where a light, stellar-mass compact object spirals into a super-massive black hole. However, at the moment the precise predictions for the evolution of EMRIs are not ready, and this, if not rectified, would imply lower yields of valuable science to be obtained from the LISA mission. The subject of this proposal is to contribute to the development of these precise predictions, and to prepare for the discovery of new fundamental science with LISA and other gravitational-wave detectors. Even though the launch of LISA is more than 10 years in the future, the mathematical and technical challenge of providing the precise predictions is extremely non-trivial, and intense work must thus be initiated now. This research project will not only contribute a significant part of the work needed, but it will also allow the applicant to acquire the necessary skill and network to become one of the leading figures in the field of gravitational-wave theory.

Keywords: black hole physics,methods analytical,methods numerical,multimessenger astronomy
“MICROMETABOLITE” – Research Training Network on the Microbial Enhancement of Bioactive Secondary Metabolite Production in Plants (MICROMETABOLITE)

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: Environment and Geosciences
Countries involved: Germany,Austria,Belgium,Belgium,Greece,Greece
Call: Innovative Training Networks (H2020-MSCA-ITN-2016, 2016)
Start date: 2017-05-01
End date: 2021-10-31
Duration (months): 54.0
Total project cost (EUR): 2732872.32
EU funding (EUR): 2732872.32
Participants: 6
Project status: CLOSED

Plant-derived natural products or, more specifically, plant secondary metabolites are backbones of today’s pharmaceutical and cosmeceutical industry. Plant-associated microorganisms have been implicated an important role in sustaining plant growth and, through inducing or influencing synthesis pathways, in the production of plant secondary metabolites. MICROMETABOLITE aims at exploring the plant-associated microflora for improving the production of bioactive secondary plant metabolites that are of high value for industrial applications. The network will focus on members of the Boraginaceae plant family including Lithospermum and Alkanna species, which produce the naphtoquinones shikonin and alkannin derivatives (A/S). These plants are used for the production of several pharmaceutical and cosmeceutical preparations that are already on the market or in the final stages of development. Specifically, we will analyse relationships between the content of A/S or other secondary metabolites, the plant genotype, and the plant-associated microflora. Further, we will explore in which ways microorganisms beneficially influence metabolite production, and we will establish novel production systems, enabling that raw materials for industrial applications can be cultivated under Good Agricultural Practices (GAP). MICROMETABOLITE aspires to create an environment that will foster synergistic cooperation between researchers in relevant, currently hardly inter-linked scientific disciplines and maximize the exploitation of plant biotechnology in accordance with the needs of the European pharmaceutical and cosmetic industries. As the first network in this area, it will train some of the most talented European young scientists (ESRs) to become future leading scientists, technologists and entrepreneurs, who can take on leadership in the required scientific and technological discovery and in the development of next-generation pharmaceutical and cosmeceutical applications.

Keywords: plant associated microorganisms,plant secondary metabolites
Improved breast cancer care by innovative diagnostic test MammaPrint (MammaPrint)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: SME instrument
Countries involved: Netherlands
Call: Clinical research for the validation of biomarkers and/or diagnostic medical devices (H2020-SMEINST-2-2014, 2014)
Start date: 2015-07-01
End date: 2018-12-31
Duration (months): 42.0
Total project cost (EUR): 4048407.0
EU funding (EUR): 4048407.0
Participants: 1
Project status: CLOSED

Agendia NV, a Dutch SME, was founded in 2003 as spin-off from the Netherlands Cancer Institute. They pursue the commercialization of molecular diagnostics using DNA microarray technology for cancer. Agendia aims to be one of the key market players in genomic breast cancer profiling. One of the products Agendia is developing is MammaPrint, a breast cancer recurrence test. This test identifies the risk of recurrence of cancer after surgical treatment, so that the appropriate adjuvant treatment can be selected personalized on the patients tumor characteristics. Breast cancer is the most commom cancer in the world and the principle cause of death of cancer among women worldwide. Currently guidelines recommend that adjuvant therapy is to be considered for all patients with early invasive breast cancer after surgery. However this 'one size fits all approach' leads to a proportion of patients being over- or under treated as the risk of recurrence is difficult to determine. The advancements in molecular diagnostics are starting to improve the prognosis and treatment of breast- and other cancers. MammaPrint is a molecular diagnostic based on analyzing the entire human genome. Agendia’s solution therefore enables better clinical decisions, reducing over- and under-treatment and therefore leading to better health outcomes and less costs. MammaPrint can be used for all early stage breast cancer patients, which is unique in the field of breast cancer recurrence tests. As MammaPrint will be developed for more accurately identifying which breast cancer patients will gain the most benefit of adjuvant chemotherapy, the potential market for introducing MammaPrint is worldwide. In order to reach this full scale adoption, this project is focused to achieve the last clinical evidence for the clinical utility of this test needed for the uptake in EU and US clinical guidelines and reimbursement arrangements. This uptake is necessary for adoption of MammaPrint by physicians worldwide.

Keywords: gene expression biomarkers,risk of recurrence,clinical utility,personalized cancer treatment
Probabilistic neuromorphic architecture for real-time Sensor fusion applied to Smart, water quality monitoring systems (ProbSenS)

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: Switzerland
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-09-01
End date: 2019-08-31
Duration (months): 24.0
Total project cost (EUR): 175419.6
EU funding (EUR): 175419.6
Participants: 1
Project status: CLOSED

“ProbSenS” will develop a novel low-power event-driven probabilistic Very Large-Scale Integration (VLSI) architecture for real-time, adaptive and robust multisensor integration. Multisensor integration exploits the extended coverage of multiple detectors to increase perceptual confidence in Smart Systems, but embedded implementations are yet in their infancy due to the lack of hardware able to infer from the multivariate, nonlinear, time-dependent and noisy signals supplied by modern sensors. By using principles of how biological systems promptly combine multisensory information and generate meaningful features in dynamic and uncontrolled real-world conditions, bioinspired Generative Deep Neural Network (GDNN) models are emerging as a powerful, CMOS-amenable computing paradigm to accelerate sensor fusion and enable quick, reliable self-learning and context-awareness under these constraints. This project aims to develop such technology into a smaller, smarter, calibration-free multisensor solution, tolerant to sensor drifts and suited to process low-latency data from a varied set of solid-state transducers in critical real-world monitoring/diagnosis scenarios where information is acquired on-line and mostly unlabelled, e.g. security, health and environmental care. ”ProbSenS” will broaden state-of-the-art insight in the following multidisciplinary areas: (i) The modelling of GDNNs as probabilistic processors for adaptive event-based sensor fusion in Smart Systems; (ii) the investigation of novel ultra-low-power VLSI circuits to realise their computational units in low-cost CMOS technologies; (iii) the yet unexplored event-driven fusion of electrochemical and optical microsensors using a GDNN; and (iv) the benchmark of this technology in a true EU societal challenge: the real-time monitoring of water pollutants. The final outcome will be a functional working prototype of the GDNN validated in the field together with Agbar, the largest water management company in Spain.

Keywords: sensor fusion,event driven sensors,brain inspired generative models,mixed signal vlsi design,neuromorphic engineering,real time water quality monitoring
GRid ASsiSting modular HydrOgen Pem PowER plant (GRASSHOPPER)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Public-private partnerships
Destination: Fuel Cells and Hydrogen
Action type: Research and Innovation actions
Partnership: FCH2 (Art-187)
Countries involved: Italy,Spain,Germany,Slovenia,Netherlands,United Kingdom
Call: Development of flexible large fuel cell power plants for grid support (H2020-JTI-FCH-2017-1, 2017)
Start date: 2018-01-01
End date: 2022-03-31
Duration (months): 51.0
Total project cost (EUR): 4387063.75
EU funding (EUR): 4387063.75
Participants: 6
Project status: CLOSED

The GRASSHOPPER project aims to create a next-generation MW-size Fuel Cell Power Plant unit (FCPP), which is more cost-effective and flexible in power output, accomplishing an estimated CAPEX below 1500 EUR/kWe at a yearly production rate of 25 MWe. Large MW size PEM FCPP have been demonstrated, such as in the DEMCOPEM-2MW project, however at too high Capex level and without dynamic operation features for grid support. Grasshopper tackles these issues enabling a controlled, renewables-based energy infrastructure. The power plant will be demonstrated in the field as 100 kW sub-module pilot plant, implementing newly developed stacks, MEA’s and BoP system components, combining benefits of coherent design integration. Cost and technical optimisation will be achieved with improvements targeting MEAs (increasing current density, active area, reducing material costs incl. Pt loading), stack design (increasing stack size, power density and operating pressures, while streamlining manufacturability) and overall system balance of plant (modular design, simplified header and manifolds for gas distribution, high efficiency PV inverters, using off-the-shelf equipment where possible). This unit will be operated continuously for 8 months in industrially-relevant environment for engaging grid support modulation as part of an established on-site Demand Side Management (DSM) programme. This consortium unites component suppliers (JMFC, NFCT), research institutions (ZBT, Polimi) and integrators (AI, INEA) who will partner with existing energy market stakeholders (DSO, TSO) and EU smart grid projects committed to participate as advisory board members. This collaboration maximises the business case value proposition, by ensuring the delivered technology will respond to grid services’ requirements for flexible dynamic power operation. Innovative DSM programmes will be completed to establish the best path forward for commercialization of the technology for a fast response FCPP.

Keywords: pem fuel cell power plant,stationary application,grid support,flexibility,demand side management,power2power
Compact X-Ray Fluorescence borehole probe for uniquely flexible, efficient and complete underground material analysis (IBERIA XRF)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Germany
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-01-01
End date: 2019-05-31
Duration (months): 5.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

J&C Bachmann is specialized in the design and development of industrial measurement and control equipment for the mining industry. We develop physical and image based analysis and measuring methods for the determination of material properties, quality assurance and process automation. With an experienced team of physicists and engineers, we provide highly specialized and high added value measuring and control products and services. In the mining industry and for any other environmental and geologic research applications, exploration investigations are frequently accompanied by large scale drilling and blasting. Traditional methods of elemental analysis of samples in laboratories or through complex on-site equipment are both time consuming and extremely expensive, while also involving significant environmental damage: Over €10 billion are spent every year on prospecting and exploration tasks worldwide. For a particular site, this process can take up to 8 years to complete and cost over €15 million. Over the last years of R&D, we have conceived a miniaturized probe that uses X-Ray Fluorescence analysis to measure with outstanding accuracy the ground’s mineral composition along small, low-impact boreholes. Without any radioactive sources, the compact probe directly collects precise and real-time elemental analysis information directly inside the borehole. Our probe will help improve the efficiency of the prospecting and exploration stages, by reducing its cost and duration by 80%. At a fraction of the cost of larger, bulkier radioactive neutron-based probes, IBERIA XRF will also provide us with a key market advantage, allowing us to sell an estimated 250 units by 2025 and generate over €20 million in revenues. It will also provide us increased visibility and allow us to consolidate our brand as a reference in mining equipment market, leading to the creation of over 50 high grade jobs in the EU.

Keywords: mining exploration,prospecting,x ray fluorescence