Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
BENCHTOP NMR FOR LAB-ON-CHIP (BLOC)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Novel ideas for radically new technologies
Action type: Research and Innovation actions
Countries involved: Spain,Switzerland,France,United Kingdom
Call: FET-Open Challenging Current Thinking (H2020-FETOPEN-2018-2019-2020-01, 2019)
Start date: 2020-01-01
End date: 2023-12-31
Duration (months): 48.0
Total project cost (EUR): 2911780.0
EU funding (EUR): 2911780.0
Participants: 6
Project status: SIGNED

Organ-on-a-chip (OOC) devices offer new approaches to metabolic disease modelling and drug discovery by providing biologically relevant models of tissues and organs in vitro integrated with sensing technology. As such, OOC devices have the potential to revolutionise the pharmaceutical industry by enabling reliable and high predictive in vitro testing of drug candidates. The capability to miniaturise microfluidic systems and advanced tissue fabrication procedures have enabled researchers to create multiple tissues on a chip with a high degree of control over experimental variables for high-content screening applications. The objective of this project is to develop a new technology based on magnetic resonance spectroscopy and imaging using dynamic nuclear polarisation (DNP-MR) integrated with OOC devices to monitor disease and evaluate drug response in OOC models. As a proof-of-concept, this project will fabricate a biomimetic multi OOC integrated device composed of liver spheroids and pancreatic islets and develop the necessary DNP-MR hardware and software to study metabolic diseases and for future drug screening applications.

Keywords: hyperpolarisation,microfluidics,organs on a chip,radiofrequency engineering,magnetic resonance spectroscopy mrs
Accelerating market introduction of the first real-time diagnistic and monitoring device for upper gastrointestinal bleeding (UGIB) (PillSense)

Framework: Horizon 2020 — Industrial Leadership
Action type: Innovation actions
Countries involved: Ireland,Ireland,Poland,Czechia,Czechia
Call: Fast Track to Innovation (FTI) (H2020-EIC-FTI-2018-2020, 2018)
Start date: 2019-01-01
End date: 2021-06-30
Duration (months): 30.0
Total project cost (EUR): 3822508.92
EU funding (EUR): 2675756.25
Participants: 6
Project status: CLOSED

Upper gastrointestinal bleeding (UGIB) is a potentially life-threatening condition that affects approx. 2 million people annually in Europe and in the United States. Current UGIB diagnosis comprises a long and slow set of laboratory tests and culminates ultimately with an endoscopy which is the only conclusive mean for UGIB diagnosis. This results in an over usage of endoscopic resources every time there is a suspicion of a bleed. Clinical data shows that up to 60% of the time endoscopy and consequent hospital admission is not necessary. In addition, endoscopy is invasive, expensive (approx. €2433) and cannot deliver prolonged monitoring. Multi-disciplinary consortium led by EnteraSense are developing a disruptive technology ‘PillSense’ which enables real-time detection of UGIB and subsequent monitoring of high risk patients without the need of endoscopy. The product includes an ingestible capsule and an external receiver. The capsule contains an optical based sensor to detect bleeding in the upper gastrointestinal tract. EnteraSense development team has already proven the core technology through lab-testing and in-vivo clinical studies. During this FTI project, the consortium aims to optimise PillSense product design, gain regulatory approvals, develop a commercial scale manufacturing process and gain clinical approval through two stages in-human clinical trials. Successful development and commercialisation will enable consortium to generate revenues of €59million and a gross profit of €29million over five years- post commercialisation.

Keywords: diagnostic medical device,upper gastrointestinal bleeding ugib,endoscopy,advance process development,accelerating commercialisation
sCience and human factOr for Resilient sociEty (CORE)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Theme: Increase Europe's resilience to crises and disasters
Action type: Research and Innovation actions
Countries involved: Austria,Italy,Germany,Italy,Austria,Israel,Estonia,Italy,Switzerland,Finland,Belgium,Sweden,France,France,France,United Kingdom
Call: Human factors, and social, societal, and organisational aspects for disaster-resilient societies (H2020-SU-SEC-2020, 2020)
Start date: 2021-09-01
End date: 2024-08-31
Duration (months): 36.0
Total project cost (EUR): 4971091.25
EU funding (EUR): 4971091.25
Participants: 19
Project status: SIGNED

CORE contributes to Horizon 2020’s focus on secure societies where citizens are facing increasingly threatening situations. It is built on the activities and results of previous and on-going projects and is driven by end-users within the consortium and their wider stakeholder networks. CORE will develop a harmonized vision of crisis management awareness and overcoming, through a transdisciplinary collaboration involving the environmental science and social science communities. In this way, human factors, social, societal and organizational aspects can be supported by the scientific results obtained in research on environmental and anthropogenic risks. CORE will identify and use best practice and knowledge/learning from certain countries with high levels of risk but where risk awareness is high and will provide optimized actions and solutions to help restructure and rebuild socio-economic structures after a disaster that is essential for the European society. CORE is a multi-disciplinary consortium across and outside Europe established to understand how to define common metrics with respect to the different natural and man-made disaster scenarios, and how to measure, control and mitigate the impact on the populations. Special attention will be given to vulnerable groups: disabled, elderly, poor, as well as women and children. CORE will lead to more efficient policies, governance structures and broad awareness and collaboration among citizens and rescue agencies. Best practices will be identified and reported to policymakers, end-users and disseminated to all stakeholders and NGOs. CORE will devote great attention to education in schools and the training activities are also intended to be an "awareness campaign" for young people about the vulnerability of the weak categories that cannot rely on advanced means of communication and of their importance. The young generation, used to the most advanced technologies, might become a sort of "prevention sentinels".

Keywords: disaster risk management,risk perception,natural and man made risks,cascade events,vulnerable groups,safety culture indicators,youth education,social media misinformation
Data Reliability in Networks and Storage Memories (DaRe)

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: Israel
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-06-01
End date: 2017-05-31
Duration (months): 24.0
Total project cost (EUR): 182509.2
EU funding (EUR): 182509.2
Participants: 1
Project status: CLOSED

Data networks and storage media play a key role in our modern every-day life. However, these systems are highly susceptible to errors which make successful reception/retrieval of the transmitted/stored data impossible. In data networks, errors occur due to interference with other users, due to multipath propagation of the signal, or due to component noise of the receiver. Data storage media like flash memories suffer from manufacturing imperfections, wearout, and fluctuating read/write errors. In order to transmit and store data reliably, high-performance error-correcting codes and efficient decoding algorithms are hence a necessary means. The objective of this project is to provide novel and superior approaches for reliability in data networks and storage media. By means of error-correcting codes and information-theoretic analyses, we will make data transmission and storage more reliable against errors of different types. The first part of this project deals with the construction of better and more efficient coding schemes for networks. In particular, we want to construct subspace codes with high cardinality and low decoding complexity, and improve the reliability of multi-source networks. The second part of this project analyses the physical error model of non-volatile storage memories like flash memories with the objective of developing coding strategies which correct these errors and mask defect cells of the memory. This project will take place at the Technion, in collaboration with Prof. Tuvi Etzion and Prof. Eitan Yaakobi. My experience in coding theory combined with the expertise of my supervisors in network coding/coding for memories is an ideal combination to achieve new excellent research results. The innovative nature of the project will boost my career possibilities and its inter-sectoral orientation will provide new opportunities for Europe’s high-tech industry.

Keywords: coding theory,error correcting codes,data reliability,network coding,coding for memories,information theory
Proof of Concept study for the development of methylation based NIPT for trisomy 21 using droplet digital PCR (Methyl-ddPCR NIPT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Prevention, Diagnosis and Treatment of Human Diseases
Panel description: Medical technologies and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions, pharmacology, preventative medicine, epidemiology and public health, digital medicine
Countries involved: Cyprus
Call: Call for proposals for ERC Proof of Concept Grant (ERC-2020-PoC, 2020)
Start date: 2021-01-01
End date: 2022-06-30
Duration (months): 18.0
Total project cost (EUR): 214285.71
EU funding (EUR): 125000.0
Participants: 2
Project status: CLOSED

Scientific and medical evidence indicate that non-invasive prenatal testing (NIPT) offers to pregnant women a safe option during their pregnancy as it provides no risk of miscarriage. The NIPT is based on a genetic examination of plasma collected from a pregnant woman. The discovery of cell-free fetal DNA (cff DNA) in maternal plasma during pregnancy provides a promising source of fetal genetic material for the development of reliable methods for NIPT. In the last years, NIPT has been widely adopted in the clinical setting as its accuracy has been dramatically improved mainly due to the introduction of new generation sequencing (NGS) employing whole genome or targeted approaches. However, NGS based assays consist of high complexity steps and high cost. This raises concerns about inequity in NIPT access, especially for women from low socioeconomic groups and developed countries who cannot afford NIPT test. The proposed study stems out from a frontier research performed during two previously funded ERC Grants. Our goal is to take the first steps towards adapting and translating our previous findings into a safe, fast, accurate and affordable methylation based non-invasive prenatal test for the detection of Down syndrome using a high precision technology such as droplet digital PCR (ddPCR).

Keywords: ddpcr,nipt,nipd,cell free rna,cell free dna,down syndrome,fetal epigenetic biomarkers,methylation,differentially methylated regions
Innovative controls for renewable sources Integration into smart energy systems (INCITE)

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: Spain,Italy,Germany,Belgium,Belgium,France,Netherlands,Portugal
Call: Marie Skłodowska-Curie Innovative Training Networks (ITN-ETN) (H2020-MSCA-ITN-2015, 2015)
Start date: 2015-12-01
End date: 2019-11-30
Duration (months): 48.0
Total project cost (EUR): 3527432.07
EU funding (EUR): 3527432.07
Participants: 11
Project status: CLOSED

The continuous increase of the share of renewable energy sources is redefining the electrical networks. In future infrastructures, an important number of agents (sources, storage devices and consumers) will have intelligent interfaces allowing the regulation of the injection and extraction of power into the grid. This context will create multiple alternatives to increase the efficiency in electricity generation and consumption, to reduce energy costs and to provide a more reliable operation of electrical grids. These future networks will be only possible with suitable control algorithms. INCITE is a multi-sectoral consortium gathering experts on control and power systems, from academia and industry with the purpose of providing innovative control solutions for the future electrical networks.

Keywords: renewable energy sources,distributed control,optimisation
Automation COncepts and Technologies for Aircraft Assembly Lines in the Aircraft Factory of the Future (ACOTAAL)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Innovation actions
Partnership: CS2 (Art-187)
Countries involved: Spain
Call: Automation in Final Aircraft Assembly Lines and Enabling Technologies (H2020-CS2-CFP01-2014-01, 2014)
Start date: 2016-01-01
End date: 2018-04-30
Duration (months): 28.0
Total project cost (EUR): 599000.0
EU funding (EUR): 599000.0
Participants: 1
Project status: CLOSED

ACOTAAL project responds to the topic Automation in Final Aircraft Assembly Lines and Enabling Technologies (JTI-CS2-2014-CFP01-LPA-02-04). This topic is in turn linked to LPA-IADP WP2.2.3 - Technologies for Future Aircraft Factory. The objective of the ACOTAAL project is to develop new automation concepts for the assembly of aircraft sections and final assembly of aircrafts, addressing novel fuselage architectures which integrate structure, system installation and cabin elements. The automation systems proposed will allow conducting aircraft assembly operations at high production rates with reduced recurring costs, while providing practical strategies for maximum production flexibility, simplified process chains and optimized logistic processes. For achieving this target the automation system concepts developed will smartly integrate and combine key enabling innovative technologies such as lightweight and compact robotics and grippers, collaborative robotics, moveable robotic platforms and large-scale cable-driven robots. Moreover, the concepts proposed will consider the incorporation of advanced ICT technologies and strategies in order to be able to interact with other automation systems and/or humans sharing their same workspace, and to fully integrate into the existing plant production planning and control system infrastructure. The automation scenario concept that will be obtained in the ACOTAAL project will mean a leap forward with regard to flexible, fluent and lean automation of aeronautics assembly production, paving the way for the transformation of aircraft production shops using various advanced manufacturing means, methods and technologies. The proposed scenario will strongly contribute to the Future Aircraft Factory vision envisaged in the Clean Sky work plan by the aeronautic sector, enabling among others: intelligent automation, ergonomic work environment, optimum human-machine interface, zero production defects and flexible manufacturing lines.

Keywords: automation,aircraft assembly,flexible production,lean manufacturing,collaborative robotics,mobile manipulator,cable robot,simplified process chains,optimized logistics,future aircraft factory
Bayesian Networks and Non-Rational Expectations (BAYNET)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: Israel,United Kingdom
Call: ERC Advanced Grant (ERC-2015-AdG, 2015)
Start date: 2016-07-01
End date: 2022-06-30
Duration (months): 72.0
Total project cost (EUR): 1379288.0
EU funding (EUR): 777038.0
Participants: 2
Project status: CLOSED

This project will develop a new framework for modeling economic agents having "boundedly rational expectations" (BRE). It is based on the concept of Bayesian networks (more generally, graphical models), borrowed from statistics and AI. In the framework's basic version, an agent is characterized by a directed acyclic graph (DAG) over the set of all relevant random variables. The DAG is the agent's "type" – it represents how he systematically distorts any objective probability distribution into a subjective belief. Technically, the distortion takes the form of the standard Bayesian-network factorization formula given by the agent's DAG. The agent's choice is modeled as a "personal equilibrium", because his subjective belief regarding the implications of his actions can vary with his own long-run behavior. The DAG representation unifies and simplifies existing models of BRE, subsuming them as special cases corresponding to distinct graphical representations. It captures hitherto-unmodeled fallacies such as reverse causation. The framework facilitates behavioral characterizations of general classes of models of BRE and expands their applicability. I will demonstrate this with applications to monetary policy, behavioral I.O., asset pricing, etc. I will extend the basic formalism to multi-agent environments, addressing issues beyond the reach of current models of BRE (e.g., formalizing the notion of "high-order" limited understanding of statistical regularities). Finally, I will seek a learning foundation for the graphical representation of BRE, in the sense that it will capture how the agent extrapolates his belief from a dataset (drawn from the objective distribution) containing "missing values", via some intuitive "imputation method". This part, too, borrows ideas from statistics and AI, further demonstrating the project's interdisciplinary nature.

Keywords: non rational expectations,graphical models,bayesian networks,coarse reasoning,causality,equilibrium concepts,attribution biases,imputation,entropy,missing data
HApi - Hyperthermia in Apculture - A new product against the Deformed Wing Virus of honey bees. (HApi)

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: Austria
Call: Stimulating the innovation potential of SMEs for sustainable and competitive agriculture, forestry, agri-food and bio-based sectors (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-06-01
End date: 2017-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

HApi – Hyperthermia in Apiculture focuses on the introduction of a new machine for treating honey bees against the Deformed Wing Virus (DWV) by means of hyperthermia. Since currently no specific treatment exists to deal with the DVW infestation, we believe our company can play a role in breaking this downward spiral of collapsing colonies, ruined beekeepers, and the endangered regional pollination. With HApi we want to turn this spiral upwards, and offer beekeepers a new method for integrated pest management, with a high quality machine to care for their hives without any chemicals and avoid colony losses. This has to be understood in the light that Europe has 13 million less honeybee colonies than would be needed to properly pollinate all its crops, keeping healthy bees is fundamental for pollination, sustainable agriculture, and ultimately for our food security. The European honey bee plays a vital role in agro‑ecosystems by mastering the pollination of one third of the world’s food crops. In total apiculture generates an annual value added of 1 billion Euros, but more importantly, it contributes to the total amount of at least 22 billion Euros delivered by pollinators to European agriculture. If we manage with HApi to reduce the rate of hive losses by 3% only in DE, AT and CH, this alone will mean that about 39,750 hives are rescued, with an average economic benefit between 19.9 Mio. to 39.8 Mio. Euro in avoided losses.

Keywords: apiculture,honey bees,virus,food security,hyperthermia
Intelligence Network and Secure Platform for Evidence Correlation and Transfer (INSPECTr) (INSPECTr)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Theme: Fight crime, illegal trafficking and terrorism, including understanding and tackling terrorist ideas and beliefs
Action type: Research and Innovation actions
Countries involved: Ireland,Estonia,Italy,Ireland,Ireland,Cyprus,Belgium,Switzerland,Norway,Romania,Belgium,Latvia,France,Netherlands,Netherlands,United Kingdom,United Kingdom
Call: Technologies to enhance the fight against crime and terrorism (H2020-SU-SEC-2018, 2018)
Start date: 2019-09-01
End date: 2023-02-28
Duration (months): 42.0
Total project cost (EUR): 6997910.0
EU funding (EUR): 6997910.0
Participants: 21
Project status: SIGNED

Intelligence Network & Secure Platform for Evidence Correlation and Transfer (INSPECTr). The principal objective of INSPECTr will be to develop a shared intelligent platform and a novel process for gathering, analysing, prioritising and presenting key data to help in the prediction, detection and management of crime in support of multiple agencies at local, national and international level. This data will originate from the outputs of free and commercial digital forensic tools complemented by online resource gathering . Using both structured and unstructured data as input, the developed platform will facilitate the ingestion and homogenisation of this data with increased levels of automisation, allowing for interoperability between outputs from multiple data formats. Various knowledge discovery techniques will allow the investigator to visualise and bookmark important evidential material and export it to an investigative report. In addition to providing basic and advanced (cognitive) cross-correlation analysis with existing case data, this technique will aim to improve knowledge discovery across exhibit analysis within a case, between separate cases and ultimately, between interjurisdictional investigations. INSPECTr will deploy big data analytics, cognitive machine learning and blockchain approaches to significantly improve digital and forensics capabilities for pan-European LEAs. INSPECTr intends to reduce the complexity and the costs in law enforcement agencies and related actors to use leading edge analytical tools proportionally and in line with relevant legislation (including fundamental rights), with extended options for multi-level and cross-border collaboration for both reactive and preventive policing and facilitate the detection/prediction of cybercrime operations/trends. The final developed platform will be freely available to all LEAs.

Keywords: digital forensics,evidence correlation,evidence analysis