Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Accelerating Galactic Archaeology (GREATDIGINTHESKY)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Universe sciences
Panel description: Astro-physics/-chemistry/-biology; solar system; planetary systems; stellar, galactic and extragalactic astronomy; cosmology; space sciences; astronomical instrumentation and data
Countries involved: France,France
Call: ERC Advanced Grant (ERC-2018-ADG, 2018)
Start date: 2019-10-01
End date: 2024-09-30
Duration (months): 60.0
Total project cost (EUR): 2472738.0
EU funding (EUR): 2472738.0
Participants: 2
Project status: SIGNED

Why most of the matter in the Universe appears to be dark, and constituted of some unknown particles, is one of the most important open questions in physics today. Here we propose to investigate the relative merits of different possibilities for the nature of this dark matter, as well as alternative proposals for the nature of the gravitational interaction, by comparing their predictions to new high spatial resolution measurements of the 3D acceleration field in the Milky Way. These measurements will be achieved primarily by finding and analysing the many stellar streams that criss-cross our Galaxy. We have already built a stream-finding prototype that we have used with the Gaia mission’s second data release (DR2) to detect 13 new beautiful phase-space streams in the Milky Way. This project aims to develop analysis techniques that will allow us to combine data from all relevant sky surveys together with future Gaia releases to identify many other Galactic star streams. It is plausible that 100 or more streams may be identified by the end of our project. The conjoint analysis of these interwoven structures will provide us with the means to derive, for the very first time, the three-dimensional acceleration field on scales of 1-100 kpc. The streams will be used to probe the granularity of the dark matter distribution, testing whether their kinematics and sub-structure are consistent with interaction with the expected sub-halos of the standard Λ Cold Dark Matter (ΛCDM) paradigm. We will also simulate star streams in several alternative scenarios, including fuzzy dark matter, dipolar dark matter, superfluid dark matter, and modified Newtonian dynamics, and quantify their relative merits to simulations in ΛCDM. Together, these studies will test theories of gravity and dark matter theories, place the best constraints on the distribution of dark matter in our Galaxy, and probe the substructure of the dark matter, thereby setting the state of the art for the next decade.

Keywords: dark matter,gravitation
Efficient and Robust Oxide Switching (EROS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced 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: United Kingdom
Call: ERC Advanced Grant (ERC-2019-ADG, 2019)
Start date: 2021-05-01
End date: 2026-04-30
Duration (months): 60.0
Total project cost (EUR): 1913521.0
EU funding (EUR): 1913521.0
Participants: 1
Project status: SIGNED

We are at the beginning of a Data Age. Data is exploding. In 2016, 90% of the world’s data ever created was in the two previous years. AI and data analytics are further increasing the growth. The power demand is huge and growing. Within a few years some developed countries will not have sufficient power to sustain the growth. The negative effects on the planet are serious. Non-volatile memory (NVM) technology (including memory and neuromorphic computing elements in a single device) could strongly help to solve the problem, giving two orders of magnitude power reduction and, by removing the data transfer bottleneck, increased speed. Oxide memristors have significant advantages over competing NVM technologies, particularly in terms of speed, cost and temperature stability. However, after more than a decade of intense effort, serious challenges remain in terms of scaling, uniformity and robustness. The challenges all relate to a lack of precise control of the materials. Completely new thinking in thin film materials engineering is needed. EROS provides this new thinking by designing and engineering new forms of nanostructured oxide films to give highly Efficient, Robust Oxide Switching in an ultra-dense, ultra-low power, reliable oxide memristor system, with potential to change the technology landscape in AI, IoT, and security. ‘Ideal’ films will first be designed, fabricated, and understood. These will direct the way to simple industry-platform devices. Stochastic effects will be eliminated by creating films with separate vertical nanoscale ionic and electron channels with highly controlled vacancy and electronic concentrations, allowing scaling to a few nm, in a forming-free system. Also, multifunctional hybrid structures will be developed to give robustness. Furthermore, ferroelectricity will be induced, allowing simpler and smaller devices. Confidence in the proposed approach comes from proof-of-concept model systems shown by the PI.

Keywords: memristor,functional oxides,materials engineering
Modcam – vision sensors with onboard analytics for retail customer analysis (MODCAM)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Sweden
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2017-01-01
End date: 2017-06-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Advances in camera and sensor technology are unlocking remarkable opportunities for in-store retail customer behaviour analysis, enabling retailers to optimize operations based on rich data insights. Using vision sensors, retailers can track customer flow to determine hot and cold zones, promotion effectiveness and queue speed, and gather demographic data. This is far more effective than methods used by chains such as IKEA, which still counts visitors manually bi-monthly, costing €1600. The first generation of retail analytics technology is now hitting pain points. Video holds an immense amount of data, and analytics are currently conducted on a remote server, meaning network bandwidth becomes a barrier. Modcam has developed a cost-efficient technology solution for retail analytics using powerful proprietary vision sensors that can conduct video analytics in the device. This means only statistical information is distributed over the network rather than pixels. Using Modcam, a retailer can set up a complete customer analytics system for at least 50% lower costs than current solutions. Modcam is a Swedish-based SME that launched in 2013 by 4 senior technical professionals combining world-class expertise in computer vision and mobile telecoms. It has obtained one patent and two provisional patents for its methods, and has already produced a commercial batch of its compact sensors. It has four paying customers, and is in advanced negotiations with eleven companies including IKEA and H&M, with potential full-scale roll-out in up to 6816 stores. Modcam earns revenue by charging a monthly fee of between 200 SEK and 300 SEK per device. It aims to capture 2% of the retail analytics market in 4 countries by 2020, which translates into 26,000 unit sales annually. This will result in revenue of 75M SEK, an EBIT of 17M SEK and 40 employees. This feasibility study will prepare Modcam to scale up across new European markets.

Keywords: analytics,big data,vision sensors,camera,retail,video
Launching the next generation of Self Organising Networks for Telecoms (CellSON)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Israel
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-2-2016-2017, 2016)
Start date: 2016-12-01
End date: 2018-11-30
Duration (months): 24.0
Total project cost (EUR): 1523910.0
EU funding (EUR): 1066737.0
Participants: 1
Project status: CLOSED

Today’s telecom operators face an unprecedented array of issues with profound implications for the future performance of their businesses mainly the need for huge investments to service the growth in data traffic. CellSON is proposing a novel and disruptive technology, installing and using smart repeaters for improving the overall network efficiency based on available resources. The repeaters incorporate a novel sensing capability for measuring the radio frequency environment. In addition, they also incorporate a multi directional ability (donor antenna) in order to select the most convenient Base Station. CellSON will solve a real problem that could escalate into a collapse of mobile telecom infrastructures due to the gigantic increase of mobile data traffic expected for the coming years. This solution will allow mobile operators to increase the performance of their current and future infrastructures, and therefore gain time to upgrade to new mobile technologies in a more gradual and sustainable manner. The main objectives of the project is to integrate the overall technology and deploy a demonstrator site into a real mobile network that will be provided by MER group Telecom a multinational System Integrator. We, CellO, an Israeli company count on 10 years of providing innovative wireless solutions that deliver spotless coverage and superior capacity to mobile devices. The CellSON project represents the most important innovative solution developed by CellO. This solution is tested, protected by patents, and several worldwide operators are willing to incorporate this technology into their infrastructures.

Keywords: self organising networks,wireless telecom operators,relay nodes,small repeaters,multiple beam antenna,simple network management system,artificial intelligence,management information base
A labour-efficient, organic herbicide-free and micronutrient infused seed tape and delivery mechanism aiding the growth and harvest of agri-products (BioSeedMat)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Theme: Sustainable agriculture and forestry
Action type: SME instrument
Countries involved: United Kingdom
Call: Stimulating the innovation potential of SMEs for sustainable and competitive agriculture, forestry, agri-food and bio-based sectors (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-05-01
End date: 2016-07-31
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The demand from food retailers to provide food which is grown according to organic standards rather than through the use of inorganic herbicides has placed enormous pressure on crop growers. The underlying cause for this change has been the increase in demand from consumers for food which has been grown organically or with reduced agrochemical inputs. Existing organic solutions such as mechanical hoeing, poly mulching beds and thermal treatment (heat/foam/electricity) are mostly unable to eliminate weeds within the crop rows, with the exception of expensive hand weeding. The prevalent use of labour intensive weed control methods has contributed to the higher production cost, and hence retail price, of organic food compared to food grown with the use of herbicides. Our paper seed mat consists of a physical barrier made up of an absorbent lower layer and a very thin upper layer made from paper. Seeds are placed between these two layers in rows, broadcasted or with precision placement. The absorbent lower layer retains moisture and controls weeds. The key benefits of our product are that it eliminates manual labour for weed control and allows for mechanised laying during the growing cycle, increases crop yield by 10% per season, has 100% crop coverage, provides even germination, protects crops from microbiological and foreign body soil contamination, degrades through the growing cycle and saves time and money in production. Our target market is vegetable and salad producers, a significant market with over 450,000 ha of relevant crops grown in Europe plus 270,000 ha in readily accessible international markets (e.g. USA, South Africa and Australia). Our concept has been tested and validated in target markets, with very encouraging early sales of our beta version. Based on the early market interest and end user feedback we have forecast sales of €19.2 million and a return on investment of 154% over the five years following commercialisation.

Keywords: terraseed,bioseedmat,weeds,organic,seed mat,herbicides,crops,yield,barrier layer,agronomy
The evolution of mesoderm and its differentiation into cell types and organ systems (EVOMESODERM)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: Norway
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-06-01
End date: 2022-05-31
Duration (months): 84.0
Total project cost (EUR): 1999500.0
EU funding (EUR): 1999500.0
Participants: 1
Project status: CLOSED

Mesoderm, the embryonic germ layer between ectoderm and endoderm, gives rise to major organs within the circulatory and excretory systems and to stabilizing tissues (muscles, bones, connective tissue). Although mesoderm is a key-innovation in evolutionary history, its origin and further diversification into the different organs and cell types of a broad range of animals has not been elucidated. Our knowledge of mesoderm development is mainly based on work performed in prominent model systems including vertebrates (fish, frog and mouse) and invertebrates that are distantly-related and considered to be highly derived (Drosophila and C. elegans). The project proposed herein aims to study mesoderm development in a variety of highly informative animal taxa and trace its differentiation into cell types and organs, with the ultimate aim of reconstructing the history of mesoderm during animal evolution. Our approach combines advanced bioinformatics, live-imaging and molecular methods, and will be carried out in nine representative species belonging to under-investigated animal groups. We will describe the morphological and molecular development of mesoderm in these species, and the differentiation of two important mesodermal cell types: nephridia and blood. Using this information we will be able to infer the embryology and mesodermal cell type composition of ancestors at six important nodes in the animal tree of life. We will also be able to comprehend when shifts in mesoderm development have occurred and how these shifts have remodeled the animal body plans. Further, our implementation of advanced methods in under-studied species will provide new model systems and a more comprehensive framework for further studies in evolutionary developmental biology as well as in other research fields.

Keywords: evolution,development,zoology,mesoderm,gastrulation,cell types,bodyplan,evo devo,timelapse microscopy,nephridia,embryology,blood vascular system,rnaseq,comparative genomics
European AIDS Vaccine Initiative 2020 (EAVI2020)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Preventing disease
Action type: Research and Innovation actions
Countries involved: Germany,Australia,Italy,Austria,Spain,Spain,Italy,Austria,Germany,Sweden,Hungary,France,France,Netherlands,United States,United Kingdom,United Kingdom,United Kingdom,Canada,United Kingdom
Call: PHC 9 – 2015: Vaccine development for poverty-related and neglected infectious diseases: HIV/AIDS (H2020-PHC-2015-single-stage_RTD, 2015)
Start date: 2015-11-01
End date: 2022-12-31
Duration (months): 86.0
Total project cost (EUR): 24088765.0
EU funding (EUR): 22948022.25
Participants: 29
Project status: SIGNED

HIV-1 is responsible for a global pandemic of 35 million people, and continues to spread at a rate of >2 million new infections/year. It is widely acknowledged that a protective vaccine would be the most effective means to reduce HIV-1 spread and ultimately eliminate the pandemic, while a therapeutic vaccine may help mitigate the clinical course of disease and lead to strategies of viral eradication. However despite 30 years of research, we do not have a vaccine capable of protecting from HIV-1 infection or impacting on disease progression. This in part represents the challenge of identifying immunogens and vaccine modalities with reduced risk of failure in late stage development. To overcome this bottleneck some of the most competitive research groups in vaccine discovery from European public institutions and biotechs from 9 EU countries together with top Australian and Canadian groups and US collaborators, have agreed to join forces in EAVI, providing a pool of international expertise at the highest level. EAVI2020 will provide a platform for the discovery and selection of several new, diverse and novel preventive and/or therapeutic vaccine candidates for HIV/AIDS. Emphasis will be placed on early rapid, iterative, small Experimental medicine (EM) human vaccine studies to select and refine the best immunogens, adjuvants, vectors, homologous and heterologous prime–boost schedules, and determine the impact of host factors such as gender and genetics. Animal models will be used to complement human studies, and to select novel immunization technologies to be advanced to the clinic. To shift the “risk curve” in product development we will develop innovative risk prediction methods, specifically designed to reduce the risk associated with late stage preventive or therapeutic vaccine failure, increasing the chance of discovery of an effective vaccine.
Accurate Roms for Industrial Applications (ARIA)

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: Mathematics
Countries involved: Spain,Italy,Italy,Italy,Germany,France,France,France,United States
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2019, 2019)
Start date: 2019-12-01
End date: 2024-11-30
Duration (months): 60.0
Total project cost (EUR): 924600.0
EU funding (EUR): 924600.0
Participants: 18
Project status: SIGNED

The project Accurate Roms for Industrial Applications aims at developing an array of mathematical methods for constructing predictive reduced-order models (ROMs) with guaranteed accuracy, robustness, reliability and efficiency for applications involving complex physical phenomena. New approaches to this challenge are proposed here with a focus on the Euler and Navier–Stokes equations of fluid flow, two of the most challenging continuum models with an extraordinary rich range of industrial applications. The mathematical modeling and solution of the Euler and Navier-Stokes equations is sometimes cited as the greatest challenge in continuum modeling of physical phenomena. This topic is selected as our principal focus because of its intrinsic importance, but also because the mathematical methods developed in addressing this very challenging task may well have an impact on other fields of knowledge. We plan to tackle these challenging objectives in this staff exchange program by combining the unique expertise of our extended research team whose members have made significant progress in ROM research during the past decade. This academic expertise is cross-fertilized by the exchange with knowledge intensive SMEs ans start up and well established industrial partners that will benefit from the scientific and technological results of the team and will challenge the solutions found with applications in real world problems.

Keywords: reduced order models
Low Energy Toolset for Heterogeneous Computing (LEGaTO)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Israel,Germany,Germany,Spain,Switzerland,Sweden,United Kingdom
Call: Customised and low energy computing (including Low power processor technologies) (H2020-ICT-2017-1, 2017)
Start date: 2017-12-01
End date: 2020-11-30
Duration (months): 36.0
Total project cost (EUR): 5514182.5
EU funding (EUR): 5514182.5
Participants: 10
Project status: CLOSED

Recently system integrators have dramatically increased their efforts in heterogeneous computing by integrating heterogeneous cores on die (ARM), utilizing general purpose GPUs (NVIDIA), combining CPUs and GPUs on same die (Intel, AMD), leveraging FPGAs (Altera, Xilinx), integrating CPUs with FPGAs (Xilinx), and coupling FPGAs and CPUs in the same package (IBM-Altera, Intel-Altera). Heterogeneity aims to solve the problems associated with the end of Moore´s Law by incorporating more specialized compute units in the system hardware and by utilizing the most efficient compute unit. However, while software-stack support for heterogeneity is relatively well developed for performance, software stack support for power- and energy-efficient computing it is severely lacking. Given that the ICT sector is responsible for 5% of global electricity consumption, software stack-support for energy-efficient heterogeneous computing is critical to the future growth of the ICT industry. The primary ambition of the LEGaTO project is to address this challenge by starting with a Made-in-Europe mature software stack, and by optimizing this stack to support energy-efficient computing on a commercial cutting-edge European-developed CPU-GPU-FPGA heterogeneous hardware substrate, which will lead to an order of magnitude increase in energy efficiency.

Keywords: low energy,heterogeneous hw,micro servers,task based programming model,dataflow,fpga,smart cities,homes,machine learning,stream processing,distributed computing,resilience,security