Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Experimental Searches for Oscillating and Transient effects from the Dark Sector (Dark-OsT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Germany
Call: ERC Advanced Grant (ERC-2015-AdG, 2015)
Start date: 2016-08-01
End date: 2021-07-31
Duration (months): 60.0
Total project cost (EUR): 2474875.0
EU funding (EUR): 2474875.0
Participants: 1
Project status: CLOSED

The objective of the proposed project is to pioneer a magnetometry-based experimental framework for the detection of time-varying signatures of the ‘dark sector’. This novel approach will enable systematic searches for particles contributing to the dark matter and for dark-energy components. The nature of dark matter and that of dark energy are among the central open problems in modern physics. There are only few experimental bounds and so far no conclusive observations of dark-sector particles or fields. Experiments enabling a direct coupling to the dark sector and thus a systematic search for and study of the contributing particles and fields would open up new vistas for areas ranging from particle physics to astrophysics and cosmology, and would in particular provide insights into the physics beyond the Standard Model. Here, we propose a framework for such experimental searches based on high-precision magnetometers, and networks thereof. Our approach is distinct from existing efforts in two ways. First, it will enable searches for so-far unexplored couplings to ultra-light bosonic particles present in the Universe that could be components of dark matter and/or dark energy, in particular axions and axion-like particles (ALPs). Second, we will develop and use devices and methods tailored to search for oscillating and transient, rather than time-independent, effects. Specifically, we will use nuclear magnetic resonance (NMR) techniques for detecting spin precession caused by background axion and ALP dark matter, and geographically separated magnetometers for identify transient effects, such as crossing domain walls of ALP fields, which have been proposed as a possible dark-energy component. The devices and methods developed in the framework of this project will provide the essential components for unique searches for a broad class of dark-matter and dark-energy candidates and might enable the key experiments to understanding the dark sector.

Keywords: dark sector,dark energy,dark matter,magnetometry
PJ22:Validation and Demonstration Engineering (PJ22 SEabird)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Single European Sky Air Traffic Management Research
Action type: Coordination and support actions
Partnership: SESAR (Art-187)
Countries involved: Germany,Spain,Spain,Italy,Italy,Italy,Italy,Lithuania,Slovakia,Belgium,Poland,France,France,France,Czechia
Call: Validation and Demonstration Engineering (H2020-SESAR-2015-2, 2015)
Start date: 2016-10-01
End date: 2019-09-30
Duration (months): 36.0
Total project cost (EUR): 3355719.3
EU funding (EUR): 2051333.78
Participants: 20
Project status: CLOSED

The aim of SESAR2020.PJ22 is to address one of the Transversal Activities, specifically Validation & Demonstration Engineering. In SESAR 1, the application of an engineering methodology defining the process for development of verification and validation platforms, was optionally mandated to the primary projects, leading to a different level of information available across the Programme. The delivery of information to SJU did not always reach the necessary consistency and quality, e.g. preventing the understanding of coverage and traceability of operational requirements vs. technical requirements. SE data were typically captured via Word templates requiring significant effort to extract the information with not homogeneous level of details thus insufficient to guarantee the usability and significance for the SESAR Community. In SESAR 2020 there is a demand to improve consistently the situation and PJ22 will provide a System Engineering Data Management Framework (SE-DMF), aiming to support all SESAR Solutions with a (web based) platform for Requirements Management to capture data in a structured way ensuring consistency, coherence and coverage at Programme level. PJ22 will develop an efficient approach based on a data-centric, data-driven rather than document-based paradigm. SE-DMF will be set up as a service and run in a secured IaaS infrastructure to enable cost reduction, high level of ROI, ease of use and scalability. The project will support the SESAR Solution Maturity Lifecycle and Gates. Another challenge is to identify a set of strategic validation tools and interoperability solutions to improve the SESAR 2020 validation process. Maintaining and improving the development methodologies for the SESAR solution and VLSD projects together with managing the catalogue of the V&V and Demonstration Platforms and associated documentation describing their current capabilities and their planned evolution is under the scope of the project.

Keywords: system engineering data management,requirements management,web based system engineering,validation and verification methodology,common tools,sesar platform catalogue,se dmf
SELECT for Cities (Standardized, opEn, data-driven, service-oriented user-centric pLatform Enabling large-scale Co-creation, Testing validation of IoE services for Cities) (SELECT for Cities)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: COFUND actions
Countries involved: Belgium,Belgium,Finland,Denmark,United Kingdom
Call: Pre-commercial procurement open to all areas of public interest requiring new ICT solutions (H2020-ICT-2015, 2015)
Start date: 2015-12-01
End date: 2019-11-30
Duration (months): 48.0
Total project cost (EUR): 5652313.13
EU funding (EUR): 3956618.75
Participants: 7
Project status: CLOSED

Internet of Everything is recognised to be one of the dominant ways transforming the way we manage and live in our urban environments in the future. The extension of the Internet to the physical spaces and objects is a massive opportunity for new services and business for example in the areas of logistics, transport, environment, security and wellbeing. Internet of everything is directly linked to the smart city development, but it has proceeded slower than expected. The key showstoppers are the lack of common standards, fragmented marketplace, and lack of ways to systematically test and introduce new solutions in the cities. The common challenge of the SELECT for Cities PCP is the design, research and development of “cities as linked and large-scale Internet of Everything labs”. The challenge lies in developing an open, standardized, data-driven, service-oriented and user-centric platform that enables large-scale co-creation, testing and validation of urban IoE applications and services. This approach fosters the longer-term goal of evidence-based innovation in cities. The envisaged platform has several requirements, components & features that are currently not available in existing solutions. The platform must allow collaboration between departments and cities, and (automated) testing of IoE services. The design should be based on an open and modular approach, and support cloud-based, data-driven, service-oriented, user-centric, and co-created large-scale testing. The joint effort of the partners procuring this pre-commercial track lies in guarding the integration capabilities of the platform with solutions that exist in the respective cities today. Particular attention will thus need to be paid to technologies and tools that allow smooth communication and integration between these existing solutions. The end goal of SELECT for Cities is taking the idea of the city as a large Internet of Everything Lab and putting it into practice.

Keywords: smart cities,open data,large scale urban living labs,internet of things,internet of everything
The world’s highest Signal-to-Noise ratio MEMS microphone (OptiMEMS)

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

Natural language voice-controlled user interfaces are evolving fast. The automatic speech recognition systems from e.g. Microsoft and Google already perform as well as humans – assuming that the voice signals can be captured perfectly. Speech capture, especially in complex acoustic environments is the limiting factor in speech recognition. There is a growing need for miniature size, affordable and “human-grade” performance microphones. sensiBel has developed a new, patented microphone technology, that is capable of registering sound waves far beyond the range that microphones in this price class can do today. Our microphones are significantly cheaper and smaller than existing microphones with equivalent performance [i.e. studio microphones], which makes it possible to include high-performance microphone arrays also in e.g. small consumer devices. This opens a multi-billion market opportunity for sensiBel, as the total MEMS microphone market is expected to reach 8 billion units in 2022.

Keywords: optical mems,microphone,voice control,high fidelity audio capture,semiconductors
Training network for research into bone Fragility In Diabetes in Europe – towards a personaLised medIcine apprOach (FIDELIO)

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: Life Sciences
Countries involved: Germany,Italy,Austria,Germany,Switzerland,Switzerland,Netherlands,Denmark,United Kingdom
Call: Innovative Training Networks (H2020-MSCA-ITN-2019, 2019)
Start date: 2019-10-01
End date: 2024-03-31
Duration (months): 54.0
Total project cost (EUR): 3810146.38
EU funding (EUR): 3810146.38
Participants: 9
Project status: SIGNED

Diabetes mellitus has emerged as a novel risk factor for fragility fractures. While in type 1 diabetes the 3-fold overall relative risk for fractures may mostly derive from low bone mineral density (BMD) likely due to the lack of the bone-anabolic hormones, in type 2 diabetes, the fracture risk is increased about 2-fold, despite a normal or even higher BMD. This suggests that bone fragility in each form of diabetes develops by distinct mechanisms that to date remain largely unknown and may require an individualized approach for effective treatment. As the diabetes epidemic is increasing worldwide with aging, and the fractures that are associated with diabetes cause an increase in morbidity, mortality, and healthcare costs, diabetes-induced osteoporosis imposes a significant burden on our society and our healthcare system. FIDELIO offers a comprehensive, multidisciplinary training program for Early Stage Researchers (ESRs) in this emerging field, unravelling i) the biological mechanisms that contribute to altered bone quality parameters with subsequent bone fragility in diabetes, ii) identify predictive markers for patient stratification and individualized interventions, and iii) develop novel imaging techniques to determine bone quality aspects. The research will employ well-defined patient cohorts, preclinical models of diabetic bone disease, in vitro studies, genetic databases, artificial intelligence, and cutting-edge imaging technologies in a highly collaborative and interdisciplinary environment. ESRs will be trained through individual research projects, secondments, residential courses, and webinars provided by a broad range of experts, including bone biologists, clinicians, epidemiologists, geneticists, engineers and entrepreneurs, as well as companies supporting this important area of research. The joint training programme will also develop transferable and entrepreneurial skills to help the ESRs succeed in their choice of professional future.

Keywords: diabetes,bone fragility,fractures,personalized medicine,epidemiology,microbiome,geneenvironment,interactions,mirnas,mechanoregulation,functional imaging,cell,signalling,preclinical models
Emergence of wild differentiable dynamical systems (Emergence)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: France
Call: ERC Consolidator Grant (ERC-2018-COG, 2018)
Start date: 2019-09-01
End date: 2026-08-31
Duration (months): 84.0
Total project cost (EUR): 1070343.0
EU funding (EUR): 1070343.0
Participants: 1
Project status: SIGNED

Many physical or biological systems display time-dependent states which can be mathematically modelled by a differentiable dynamical system. The state of the system consists of a finite number of variables, and the short time evolution is given by a differentiable equation or the iteration of a differentiable map. The evolution of a state is called an orbit of the system. The theory of dynamical systems studies the long time evolution of the orbits. For some systems, called chaotic, it is impossible to predict the state of an orbit after a long period of time. However, in some cases, one may predict the probability of an orbit to have a certain state. A paradigm is given by the Boltzmann ergodic hypothesis in thermodynamics: over long periods of time, the time spent by a typical orbit in some region of the phase space is proportional to the “measure” of this region. The concept of Ergodicity has been mathematically formalized by Birkhoff. Then it has been successfully applied (in particular) by the schools of Kolmogorov and Anosov in the USSR, and Smale in the USA to describe the statistical behaviours of typical orbits of many differentiable dynamical systems. For some systems, called wild, infinitely many possible statistical behaviour coexist. Those are spread all over a huge space of different ergodic measures, as initially discovered by Newhouse in the 70's. Such systems are completely misunderstood. In 2016, contrarily to the general belief, it has been discovered that wild systems form a rather typical set of systems (in some categories). This project proposes the first global, ergodic study of wild dynamics, by focusing on dynamics which are too complex to be well described by means of finitely many statistics, as recently quantified by the notion of Emergence. Paradigmatic examples will be investigated and shown to be typical in many senses and among many categories. They will be used to construct a theory on wild dynamics around the concept of Emergence.

Keywords: ergodic theory,non uniform hyperbilicity,blender,bifurcation theory,coexistence of infinitely many attractors
Translational Safety Biomarker Pipeline (TransBioLine): Enabling development and implementation of novel safety biomarkers in clinical trials and diagnosis of disease (TransBioLine)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Public-private partnerships
Destination: Innovative Medicines Initiative 2
Action type: Research and Innovation actions
Partnership: IMI2 (Art-187)
Countries involved: Iceland,Germany,Germany,Spain,Spain,Spain,Spain,Austria,Germany,Germany,Germany,Germany,Spain,Switzerland,Switzerland,Belgium,Switzerland,France,France,United States,Netherlands,United Kingdom,United Kingdom,United Kingdom,United Kingdom,United Kingdom,Luxembourg
Call: Translational Safety Biomarker Pipeline (TransBioLine): Enabling development and implementation of novel safety biomarkers in clinical trials and diagnosis of disease (H2020-JTI-IMI2-2017-13-two-stage, 2017)
Start date: 2019-02-01
End date: 2025-01-31
Duration (months): 72.0
Total project cost (EUR): 27982743.4
EU funding (EUR): 13999997.75
Participants: 29
Project status: SIGNED

Qualified biomarkers help to optimize drug development and patient safety, yet for the regulatory acceptance of safety biomarkers substantial sample sizes are needed to ensure adequate case and control numbers, and robust evidence sufficient for qualification. To address this challenge, a consortium of leading European research institutions and SMEs has been established. The consortium will generate exploratory and confirmatory data enabling regulatory qualification of new safety biomarkers for application in drug development; establish robust datasets on the DILI, DIKI, DIPI, DIVI and DINI biomarkers to enhance diagnosis of disease; develop and validate assays for new safety biomarkers; implement profiles of circulating miRNAs as tissue and mechanism specific diagnostic tool; have key safety biomarkers accepted as qualified drug development tools by EMA, FDA, and PMDA. Given the significant expertise available across the consortium, the group will be able to tackle the key challenges related to successful biomarker qualification. A key driving principle of the consortium is cross-linking via existing networks of top profile research institutions, as well as capitalizing on existing data and resources. The Consortium is embedded into a network of international research collaborations such as the Pro-Euro-DILI-registry, TransQST, eTRANSAFE, the i2b2 tranSMART Foundation, the CIOMS DILI working group, EPoS, LITMUS, and BBMRI. To optimize regulatory interaction, we intend to continue our successful collaboration with non-European consortia such as PSTC, the FNIH Biomarkers Consortium, and US DILIN. A key expected result of the consortium will be a “Safety Biomarker Factory”, regularly qualifying new markers, with an associated “Safety Biomarker Warehouse”, providing to the scientific community, industry, and patients detailed data and information, and knowledge across a large spectrum of advanced safety biomarkers.

Keywords: drug safety,biomarker qualification
Industrial scale recovery of high-grade proteins from food-processing by-products (Recover4Benefit)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Slovenia
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-08-01
End date: 2020-01-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Demand for plant and animal proteins is rapidly growing and will double in 2050. Also, the demand for high-quality dairy proteins is set to rise dramatically as consumers begin to realise their full potential. Alternative sources will need to be exploited to meet the demand. Meanwhile, more than 200 mio tons of whey is produced annually worldwide, and less than 50% is used for human consumption. Much of it still represents an environmental burden (with BOD 35-55gO2/L). While whey is usually further processed by large dairies, small and medium-sized, as well as emerging biotechnology companies that use whey as a substrate, are confronted with a lack of adequate technologies for optimal utilisation of the full potential of whey. On the other side, there is a growing market demand for high-quality (pure and biologically active) individual whey proteins and their hydrolysates. We aim to disrupt the existing market of protein extracts by introducing a novel approach to the extraction of high-valued & high-purity proteins from the food industry by-products. We aim to start with the dairy industry, introducing the extraction of targeted whey proteins with the highest purity and activity in the frame of the integrated whey management concept. Our goal is to establish (1) production facility for extraction of proteins from different resources, starting with own production and sale of superior quality mayor and minor whey proteins with the use of surplus whey of surrounding dairies, (2) proceed with the technology replication to other medium-sized dairies, milk-biorefineries and biotechnology plants, (3) and servicing development of protein extraction methods and scale-up processes from other resources using our IP and infrastructure. The SME1 project will aim at validating the technology concept, refining the analysis on risks and opportunities, fine-tuning the commercialisation strategy and secure pre-commercial trial in SME2.

Keywords: whey proteins,protein recovery,protein purification,dairy by products,food waste,nutraceuticals,sustainable sources of proteins,eco innovative technologies,protein extraction
PROPHETIC:An innovating Personal Healthcare Service for a holistic remote management and treatment of Parkinson patients. (PROPHETIC)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Spain,Spain,Greece,France,France
Call: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (H2020-MSCA-RISE-2014, 2014)
Start date: 2015-01-01
End date: 2017-12-31
Duration (months): 36.0
Total project cost (EUR): 648000.0
EU funding (EUR): 648000.0
Participants: 5
Project status: CLOSED

Parkinson's disease (PD) is a movement disorder characterized by muscle rigidity, tremor, physical movement slowing and in extreme cases, loss of physical movement. Primary symptoms result of decreased motor cortex stimulation caused by insufficient dopamine formation in the brain’s dopaminergic neurons. Secondary symptoms include high level cognitive dysfunctions and subtle language problems. PD is chronic and progressive. Currently there is no cure for PD and associated costs, in terms of quality of life and health and social care expenditures, are expected to rise as the population ages. As none of the existing PD interventions has been really effective the field shows potential for the development of systems to monitor individuals and facilitate symptoms’ management. The design of efficient ICT management system integrating remote monitoring of multi-parametric factors, decision support for medical staff, personalized and adaptable care, and patient and family education is a viable solution. PROPHETIC will exploit modern smart miniaturized systems and advanced information systems towards an infrastructure for remote, continuous, noninvasive acquisition and advanced processing of multi-parametric data and friendly telecare provision based on serious gaming. It will use embedded electronics (suite and cap) capable of measuring neural, psychological, physiological, and biomechanical parameters, and securely communicating them to a Medical Business Intelligence System where pre-processed data will be further analysed hence overcoming real time activity monitoring limitations. Continuous monitoring while aware of the patient’s levodopa medication will help determine health and motor status and avoid levodopa side effects e.g. dyskinesia, freezing, low blood pressure, and falls. It will support caregivers’ decisions and allow early interventions. Appropriate information could be shared between the actors through e.g. smart phones with access according to their role.

Keywords: parkinson disease,remote management,personal healthcar service,serious gaming