Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Scalable Policy-awarE linked data arChitecture for prIvacy, trAnsparency and compLiance (SPECIAL)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Partnership: BDVA (cPPP)
Countries involved: Austria,Germany,Germany,Germany,Italy,Belgium,Belgium,France,United Kingdom
Call: Big data PPP: privacy-preserving big data technologies (H2020-ICT-2016-1, 2016)
Start date: 2017-01-01
End date: 2019-12-31
Duration (months): 36.0
Total project cost (EUR): 3991388.75
EU funding (EUR): 3991388.75
Participants: 10
Project status: CLOSED

The SPECIAL project will address the contradiction between Big Data innovation and privacy-aware data protection by proposing a technical solution that makes both of these goals realistic. We will develop technology that: (i) supports the acquisition of user consent at collection time and the recording of both data and metadata (consent, policies, event data, context) according to legislative and user-specified policies; (ii) caters for privacy-aware, secure workflows that include usage/access control, transparency and compliance verification; (iii) demonstrates robustness in terms of performance, scalability and security all of which are necessary to support privacy preserving innovation in Big Data environments; and (iv) provides a dashboard with feedback and control features that make privacy in Big Data comprehensible and manageable for data subjects, controllers, and processors. SPECIAL shall allow citizens and organisations to share more data, while guaranteeing data protection compliance, thus enabling both trust and the creation of valuable new insights from shared data. Our vision will be realised and validated via real world use cases that - in order to be viable - need to overcome current challenges concerning the processing and sharing of data in a privacy preserving manner. In order to realise this vision, we will combine and significantly extend big data architectures to handle Linked Data, harness them with sticky policies as well as scalable queryable encryption, and develop advanced user interaction and control features: SPECIAL will build on top of the Big Data Europe and PrimeLife Projects, exploit their results, and further advance the state of the art of privacy enhancing technologies.

Keywords: privacy,data protection,big data,transparency,compliance,legislation,scalable,robust
An integrated approach to understanding the impact of de novo mutations on the mammalian genome (DENOVOMUT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced 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: Germany,United Kingdom
Call: ERC Advanced Grant (ERC-2015-AdG, 2015)
Start date: 2017-01-01
End date: 2024-07-31
Duration (months): 91.0
Total project cost (EUR): 2499331.0
EU funding (EUR): 1680706.72
Participants: 2
Project status: SIGNED

Understanding the process of spontaneous mutation is fundamental for understanding the genetic basis of quantitative variation, the threat posed by declining population size in conservation biology and the distribution of nucleotide variation in the genome. I will address these and other unanswered questions concerning the evolutionary impact of spontaneous mutation using the house mouse as a model system. With the first, highly replicated mutation accumulation (MA) experiment in any vertebrate, I will study the impact of mutation accumulation on fitness and other quantitative traits and on genomic variation. I will pay particular attention to the effects of mutations in the heterozygous state, since this is important for resolving two important questions: 1. The threat posed by deleterious mutation accumulation in humans, where natural selection has weakened in many populations, and in endangered species, where declining effective population size has made selection less effective, and 2. The extent by which new mutations sustain response to artificial selection. By characterizing many thousands of mutation events by genome sequencing of MA lines and wild mice, I will determine the molecular spectrum and the factors explaining mutation rate variation across the genome. I will exploit this new knowledge to address the long-unanswered question of the causes of correlations between nucleotide diversity and the recombination rate and the density of conserved genomic elements. I will develop new approaches, incorporating the simultaneous action of mutation, selection, drift and recombination, to determine the contributions of background selection and selective sweeps to variation in nucleotide diversity, and to quantify the contributions of coding and noncoding mutations to fitness variation. The project will lead to substantial advances in the understanding of the role of new mutations in explaining phenotypic and molecular diversity in mammals.
Biomimetic mineralization for enamel regeneration (ENAMULATE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: United Kingdom
Call: ERC-Proof of Concept-2016 (ERC-2016-PoC, 2016)
Start date: 2017-11-01
End date: 2019-04-30
Duration (months): 18.0
Total project cost (EUR): 149728.0
EU funding (EUR): 149728.0
Participants: 1
Project status: CLOSED

Dental enamel has a unique chemical composition and a remarkable well-defined hierarchical structure, which together are responsible for its outstanding properties and critical functionality. Once lost, this tissue cannot be regenerated and is directly involved in a variety of dental problems that affect a large percentage of the world population. This ERC PoC project (ENAMULATE) aims to develop the world’s first human dental enamel regeneration material capable of recreating natural enamel in structure and chemical composition; treating dental defects; and replacing restorative materials currently used in dental clinics. The project builds on findings from the ERC Starting Grant STROFUNSCAFF on the development of an elastin-like protein (ELP) self-assembling process capable of triggering and guiding the hierarchical growth of hydroxyapatite as biocompatible, flexible, and robust coatings in vitro over large uneven areas and directly on human enamel and exposed dentinal tubules. ENAMULATE will optimize the crosslinking mechanism to facilitate its clinical use in the operating room, confirm its efficiency in vitro, and validate its performance in an established animal model. The project will also focus on setting up and moving forward a path towards commercialization by consolidating the intellectual property, investigating the industrial viability, and identifying potential markets.

Keywords: tissue engineering,biomineralisation,biomaterials,tissue regeneration,dental implant
Next generation 3D print technology (PICSIMA), which for the first time enables the direct full colour printing of silicone to make soft tissue prostheses, orthoses and removable partial dentures. (PICSIMA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Nanotechnologies
Action type: SME instrument
Countries involved: United Kingdom
Call: Accelerating the uptake of nanotechnologies, advanced materials or advanced manufacturing and processing technologies by SMEs (H2020-SMEINST-1-2014, 2014)
Start date: 2015-06-01
End date: 2015-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Prostheses are artificial body parts, which can also be soft tissue such as the nose and ears, and orthoses are external artificial devices for supporting the limbs or spine or to prevent/assist relative movement. The current manufacturing process of these involves first taking an impression from the patient, making the mould, hand painting it and then modifying it to fit. The making of moulds is prone to error and occasionally leads to sub-optimal designs involving re-makes, alterations and repairs. Moulding also has severe constraints particularly where complex geometries and thin walled parts are required and it does not allow for varying of softness and tear strength within the moulded part. The multiplicity of stages in the manufacture of these custom parts makes the moulding process very expensive and time consuming. Fripp Design and Research, one of Europe's leading providers of innovative 3D print solutions, seeks to commercialise a new method for the rapid manufacture of soft tissue prostheses by developing the world’s first full colour silicone 3D Printer to replace the current moulding manufacturing method that is time consuming, highly variable and very costly. The use of faster and highly accurate 3D printing technology in the medical devices industry will not only lower costs by up to 72% but will also open up new design freedoms that prior to this were only dreams. The 3D printer developed can also be used in making orthoses and removable partial dentures (RPD) frameworks using silicone. The market opportunity goes beyond medical devices, into the high growth industrial gaskets and seals, where the market size surpasses €20 billion. The Feasibility Study will establish the technological and manufacturing capabilities of the printing device and determine the potential medical and industrial markets for the application of our product. Final prototype assembly, testing and validation will be done within the Phase 2 project.

Keywords: prostheses,soft tissue,3d printing,medical
Introducing the Internet of Bees: A Smart Beehive System (Pollenity)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Bulgaria
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2020-03-01
End date: 2020-06-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

We rely on one third of all the food on our tables to be pollinated by honeybees. However, their number is dwindling. This obvious shortage has created a new industry - “pollination on demand”. Beekeepers move their beehives from farm to farm in order to provide this service. But beekeepers are not used to such large-scale operations and bees are not used to be moved too often. This results in honeybee colony losses of 32% to 45%. Pollenity sets off to fix this fundamental disconnect between plants and pollinators. We are offering a smart beehive monitoring system that allows beekeepers to remotely monitor their honeybee colonies, measure their productivity, identify threats and react accordingly and on time. Our product portfolio consists of three products – Beebot, HiHive and the BBoard. The in-hive sensor device, called the Beebot is complimented by a robust weight scale – the HiHive. The beekeeping industry in Europe features 17 million beehives and 600,000 beekeepers, which is also our serviceable obtainable market. We follow a two-tier revenue model with assets sales of the Beebot sensor and the HiHive scale, and a SaaS subscription model for the access to the software at a small fee per month. At Bee Smart Technologies, our mission is to assist agriculture with IoT by adopting advanced technologies focusing on sustainability and re-establishing a caring relationship with nature. Our efforts have already been internationally recognized. In 2017, we became part of the IEEE network, received “The best IoT start-up” award from Central European Startup Awards, were featured in Financial Times, received FCC certification and have generally made a lot of buzz over social media. The objective of the Phase 1 project is to prepare the Phase 2 project that will help Pollenity for large scale market uptake.

Keywords: bees,honey,internet of things
Lab Based Searches for Beyond Standard Model Physics Using Traps (TRAPLAB)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Israel
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2016-12-01
End date: 2021-11-30
Duration (months): 60.0
Total project cost (EUR): 1297812.99
EU funding (EUR): 1297812.99
Participants: 1
Project status: CLOSED

In this project I will measure a critical constant (beta-nu correlation) of the standard model to a precision of at least 0.1%, an order of magnitude improvement over the state of the art. The project will provide a platform for beyond standard-model (BSM) explorations, based on modern atom/ion trapping and a new accelerator facility. High precision measurements of beta decay correlations in trapped radioactive atoms and ions are one of the most precise tools with which to search for BSM physics. The recently published US National Science Advisory Council 2015 Long Range Plan states: ``Measurements of the decays of neutrons and nuclei provide the most precise and sensitive characterization of the charge-changing weak force of quarks and are a very sensitive probe of yet undiscovered new forces. In fact, weak decay measurements with an accuracy of 0.1% or better provide a unique probe of new physics at the TeV energy scale``. Ne and He isotopes are particularly attractive due to calculable SM values, high sensitivity to several manifestations of BSM physics, ease of production, and lifetimes in the useful range for such experiments. This program combines a Magneto-Optical Trap (MOT) and an Electrostatic Ion Beam Trap (EIBT) to perform a high-precision, competitive, measurement of correlations in the decay of such nuclei. The MOT program focuses on the neon isotopes, where existing measurements are of insufficient quality, and have unique sensitivities to aspects of BSM physics. The EIBT program focuses on measurements using 6He (where a comparison with existing measurements is of great import) and the aforementioned neon isotopes, allowing a direct comparison between the two systems within the same facility (a unique worldwide capability). The combination of these methods will allow an extraction of the beta-nu coefficient to the 0.1% level, making this proposal a forerunner in the field, which will provide a leap-step in the current set of world data.

Keywords: beta decay,beyond standard model
A Cross-Species Investigation of Memory Replay During Reconsolidation (ReconsolidationDynamics)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Netherlands,United States
Call: Marie Skłodowska-Curie Individual Fellowships (IF-GF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-06-01
End date: 2018-05-31
Duration (months): 36.0
Total project cost (EUR): 242929.8
EU funding (EUR): 242929.8
Participants: 2
Project status: CLOSED

A primary treatment for anxiety disorders is exposure therapy, which is based on the principles of extinction, but has the drawback that fear can return. This risk of relapse highlights a need for treatments that persist. Research on reconsolidation has shown that upon reactivation old fear memories can be updated, preventing the return of fear. However, studies targeting reconsolidation to reduce fear have reported mixed results because its boundary conditions are poorly understood. To live up to its clinical potential it is necessary to understand how to most effectively utilize paradigms targeting reconsolidation. The proposed research attempts to address this issue by providing a neural measure of the reconsolidation process itself. This will be achieved by determining whether dynamic patterns of neural network activity that occur during initial learning re-occur during offline ‘rest’ periods, and test whether this ‘replay’ of memory is linked to reconsolidation. The first objective of this grant application is to identify and quantify a neural marker of reconsolidation that predicts the absence of fear recovery. During the outgoing phase these questions will be addressed employing an innovative cross-species (humans, rats) approach using similar behavioural tasks, complementary recording techniques (functional magnetic resonance imaging, multi-unit recordings) and state-of-the-art analyses methods. Acquired knowledge and experience will be applied during the return phase where the second objective is to use this neural marker to determine how context serves as one critical boundary condition to inducing reconsolidation. Findings will significantly advance fundamental understanding of reconsolidation and have important implication for applied and preclinical psychiatric research.

Keywords: memory,reconsolidation,neural network dynamics,replay,context
European Network for Cyber-security (NeCS)

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: Information Science and Engineering
Countries involved: Germany,Spain,Italy,Spain,Spain,Italy,Italy,United Kingdom,United Kingdom
Call: Marie Skłodowska-Curie Innovative Training Networks (ITN-ETN) (H2020-MSCA-ITN-2015, 2015)
Start date: 2015-09-01
End date: 2019-08-31
Duration (months): 48.0
Total project cost (EUR): 3882227.76
EU funding (EUR): 3882227.76
Participants: 12
Project status: CLOSED

The European Network for Cybersecurity (NECS) was formed in response to the increased need of highly qualified experts able to cope with all the aspects of the European cybersecurity strategy that is currently under implementation. There is indeed an evident need and opportunity to grow a new generation of young researchers able to answer this demand for expertize, trained to the changing nature of the challenges to be faced. These challenges include evolvable threats and new technological means to exploit network and information security vulnerabilities of cyber systems that have eventually consequences in the physical world. Starting from these considerations, the European Commission proposed the “DIRECTIVE OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL concerning measures to ensure a high common level of network and information security across the Union” . This directive proposal, on the one hand, recognizes the relevance for the European economy of cybersecurity, on the other one, poses the regulatory basis for achieving a common level of cybersecurity preparedness among the main European public/private stakeholders. This 4-year project for a cybersecurity research and training network aims at contributing to answer this increased demand of human expertise in the field. The project; by fosters ing a multi-sectorial/disciplinary approach that is clearly necessary for tackling all cybersecurity aspects - as also recognized by the European Network and Information Security (NIS) platform recently established by the EU to contribute to the strategy that is firmly based on a public/private cooperation. Being cybersecurity inherently multi-sectorial, NECS has participants (beneficiaries and partners) both from the academic sector (7) and non-academic one (5). In the NECS research and training network, multi-disciplinary expertise has been collected and interlinked in order to have as a centre of gravity the cybersecurity security area.

Keywords: cyber security,risk assessment and management for cyber security,information,sharing,security metrics
SQ Building – Solving the Trilemma of Comfort, Energy and Operational Costs in Buildings (SQ Building)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Belgium
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2018)
Start date: 2018-06-01
End date: 2020-06-30
Duration (months): 25.0
Total project cost (EUR): 2495000.0
EU funding (EUR): 1746500.0
Participants: 1
Project status: CLOSED

Modern office buildings are routinely using up to 3.5 times more energy than expected. This incredible performance gap is mainly due to badly adjusted control settings. Beyond the energy bill, these buildings offer bad thermal comfort and generate a lot of work for management of complaints and manual tweaking of the controls. 3E has developed an Artificial Intelligence based tool to improve comfort & decrease energy, operational costs and CO2 emissions of buildings & building portfolios. Technically speaking, SQ Building is a machine learning technology which predicts the behaviour of a building in function of its characteristics (glazing, orientation, building materials), occupation of the building (people & equipment), and the meteo forecasting. Based on this, SQ Building continuously optimizes the building management. Our clients are the asset, property and facility managers. SQ Building will empower them to finally trade off the trilemma of comfort, energy and operational costs. SQ Building achieves a drastic improvement in thermal comfort, between 15 and 40% reduction of energy costs and a significant reduction of operational effort (less interventions), validated and demonstrated in different real-world pilots since 2015. In 2016, we concluded a strategic collaboration agreement with Sodexo Belgium for whom we run a commercial pilot since February 2017. We have currently contracted 67,000 m² of buildings and have issued offers for more than 1,000,000 m². Commercially, we envision €16 million of revenues over the next five years and accelerated scaling after Year 4. These will generate €50-100 million of savings for our clients through better comfort, energy savings and reduced operational efforts. 3E is an independent technology and consultancy company with €10.3 million of revenues in 2017. Over the past eight years, we successfully commercialized four data-driven software services and created three successful spin-offs with different private investors.

Keywords: smart buildings,co2 reduction,heating and cooling,thermal comfort,cost savings,operational costs,optimization,machine learning,system identification,commercial buildings,tertiary sector