Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Measurement-based dynamic control of mesoscopic many-body systems (MECTRL)

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: Denmark
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-05-01
End date: 2020-04-30
Duration (months): 60.0
Total project cost (EUR): 1499406.0
EU funding (EUR): 1499406.0
Participants: 1
Project status: CLOSED

Quantum control is an ambitious framework for steering dynamics from initial states to arbitrary desired final states. It has over the past decade been used extensively with immense success for control of low- dimensional systems in as varied fields as molecular dynamics and quantum computation. Only recently have efforts been initiated to extend this to higher-dimensional many-body systems. Most generic quantum control schemes to date, however, put quite heavy requirements on the controllability of either the system Hamiltonian or a set of measurement operators. This will in many realistic scenarios prohibit an efficient realization. Within this proposal, I will develop a new quantum control scheme, which is minimalistic on system requirements and therefore ideally suited for the efficient and reliable optimization of many-body control problems. The fundamentally new ingredient is the total quantum evolution dictated by a combination of fixed many-body time evolution and the precise knowledge of the quantum back-action due to repeated quantum non-destruction (QND) measurements of a single projection operator. The main focus of this proposal is theoretical and experimental quantum engineering of the dynamics in systems, which are sufficiently small to calculate the measurement back-action exactly and sufficiently large to have interesting many-body properties. Recent experimental advances in single site manipulation of bosons in optical lattices have enabled the high fidelity preparation exactly such mesoscopic samples of atoms (5-50). This forms an ideal starting point for many-body quantum control, and we will i.a. demonstrate engineering of quantum phase transitions and preparation of highly non-classical Schödinger cat states. Finally, using the results from an online graphical interface allowing users of the internet to solve quantum problems we will attempt to build next-generation optimization computer algorithms with a higher level of cognition built in.

Keywords: quantum control,non destructive quantum measurements,optical lattices,quantum engineering
Regulation of mitochondrial expression (REMIX)

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,Germany,Switzerland,Sweden,Sweden,Netherlands,United Kingdom,United Kingdom,United Kingdom
Call: Innovative Training Networks (H2020-MSCA-ITN-2016, 2016)
Start date: 2016-10-01
End date: 2021-01-31
Duration (months): 52.0
Total project cost (EUR): 3920630.04
EU funding (EUR): 3920630.04
Participants: 10
Project status: CLOSED

Mitochondria are essential organelles found in every eukaryotic cell, required to convert food into usable energy. The mitochondrial oxidative phosphorylation (OXPHOS) system, which produces the majority of cellular energy in the form of ATP, is controlled by two distinct genomes: the nuclear and the mitochondrial genome (mtDNA). Mutations in mitochondrial genes encoded by either genome could cause diseases affecting OXPHOS system, called mitochondrial diseases, whose prevalence has been estimated to be ≈1:8500. Moreover, dysfunction of mitochondrial OXPHOS system has emerged as a key factor in a myriad of “common” diseases, including neurodegenerative and metabolic disorders like Parkinson’s and Alzheimer’s Disease, Type 2 Diabetes, and was linked to aging process. Despite all this, it is surprising that our understanding of the mechanisms governing the mitochondrial gene expression and its associated pathologies remain superficial and therapeutic interventions unexplored. The basic machineries for mtDNA replication, mtDNA transcription and mitochondrial translation are known, but the regulation of these processes in response to metabolic demands is poorly understood. The complex nature of mitochondrial gene expression that relies on two different genomes calls for a multidisciplinary approach where different teams of researchers join forces. Studies in this area are not only of basic scientific interest but may also provide new avenues towards treatment of mitochondrial dysfunction in a variety of human diseases. The key aim of the REMIX Network is combine the skills of European research groups to provide strategic training of the next generation of scientists through a programme that will progress in the elucidation of the molecular mechanisms and pathways that regulate mitochondrial gene expression.

Keywords: mtdna maintanance and expression,mitochondrial disease,animal models
Hybrid quantum dot and graphene wearable sensor for systemic hemodynamics and hydration monitoring (GRAPHEALTH)

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: Spain
Call: ERC Proof of Concept Grant (ERC-2015-PoC, 2015)
Start date: 2016-06-01
End date: 2017-11-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

The main goal of GRAPHEALTH is to exploit the inherent properties of hybrid graphene – quantum dot detectors in order to enable constant non-invasive health monitoring through vital parameters. Unlike current bulky systems, our approach enables a flexible, compact and wearable health monitoring system for constant monitoring for consumer health applications and muscle health of athletes during exercise or after injury. The hybrid quantum dot and graphene technology exhibits very high sensitivity and the technology is compatible with flexible electronic manufacturing processes, and also more compact detectors than current commercial devices.

Keywords: health monitoring,wearables,graphene,quantum dot,photodetector,flexible
non-LinEar sigNal processing for solving data challenges in Astrophysics (LENA)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: France
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-09-01
End date: 2021-08-31
Duration (months): 60.0
Total project cost (EUR): 1497411.0
EU funding (EUR): 1497411.0
Participants: 1
Project status: CLOSED

Astrophysics has arrived to a turning point where the scientific exploitation of data requires overcoming challenging analysis issues, which mandates the development of advanced signal processing methods. In this context, sparsity and sparse signal representations have played a prominent role in astrophysics. Indeed, thanks to sparsity, an extremely clean full-sky map of the Cosmic Microwave Background (CMB) has been derived from the Planck data [Bobin14], a European space mission that observes the sky in the microwave wavelengths. This led to a noticeable breakthrough: we showed that the large-scale statistical studies of the CMB can be performed without having to mask the galactic centre anymore thanks to the achieved high quality component separation [Rassat14]. Despite the undeniable success of sparsity, standard linear signal processing approaches are too simplistic to capture the intrinsically non-linear properties of physical data. For instance, the analysis of the Planck data in polarization requires new sparse representations to finely capture the properties of polarization vector fields (e.g. rotation invariance), which cannot be tackled by linear approaches. Shifting from the linear to the non-linear signal representation paradigm is an emerging area in signal processing, which builds upon new connections with fields such as deep learning [Mallat13]. Inspired by these active and fertile connections, the LENA project will: i) study a new non-linear signal representation framework to design non-linear models that can account for the underlying physics, and ii) develop new numerical methods that can exploit these models. We will further demonstrate the impact of the developed models and algorithms to tackle data analysis challenges in the scope of the Planck mission and the European radio-interferometer LOFAR. We expect the results of the LENA project to impact astrophysical data analysis as significantly as deploying sparsity to the field has achieved.

Keywords: signal and image processing,sparsity,sparse representations,deep learning,proximal algorithms,blind source separation,cosmological microwave background
Memory in biological regulatory circuits (YEASTMEMORY)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Integrative Biology: from Genes and Genomes to Systems
Panel description: Genetics, epigenetics, genomics and other ‘omics studies, bioinformatics, systems biology, genetic diseases, gene editing, innovative methods and modelling, ‘omics for personalised medicine
Countries involved: Belgium
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-10-01
End date: 2021-09-30
Duration (months): 60.0
Total project cost (EUR): 1959844.0
EU funding (EUR): 1959844.0
Participants: 1
Project status: CLOSED

The emergence of intelligence –the ability to remember and analyze data to make decisions– was a milestone in evolution. Intelligence and memory are usually associated with plastic neuronal connections in higher organisms. However, new discoveries hint that a rudimentary form of intelligence is rooted in networks that regulate gene expression in a wide range of organisms, including bacteria and yeasts. Specifically, we and others have shown that microbes show plastic behavioral responses to past experiences, such as previously available nutrients or stresses. This implies that information about the past is somehow retained and passed to next generations, where it influences cellular regulation. The goal of this project is to use a simple eukaryotic regulatory circuit as a model to obtain a comprehensive picture of the different genes and molecular mechanisms underlying history-dependence (hysteresis) in cellular regulation. Specifically, we will study maltose (MAL) regulation in budding yeast, because this signaling pathway serves as a model for gene regulation circuits in other organisms, including humans. We will use a combination of genetic screens, live-cell microscopy in custom-built microfluidic devices, and mathematical modeling to pursue four aims: 1. To provide a comprehensive quantitative analysis of hysteresis in MAL regulation 2. To unravel the molecular mechanisms contributing to hysteresis 3. To unravel the epigenetic mechanisms allowing hysteresis to extend over several generations 4. To characterize the ecological relevance of hysteresis This project will establish an innovative model for hysteresis and generate a genome-wide, systems-level view of how past influences can be stored in regulatory cascades to influence cellular decision-making. The results will contribute to a paradigm shift in our view of biological regulation and memory, with possible applications in fields as diverse as industrial microbiology, synthetic biology and medicine.

Keywords: yeast,saccharomyces cerevisiae,fermentation,subtelomeres
Towards harmonised test methods for nanomaterials (NanoHarmony)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Advanced materials
Action type: Coordination and support actions
Countries involved: Germany,Germany,Spain,Italy,Germany,Belgium,France,Netherlands,United Kingdom,Portugal,Denmark,United Kingdom,United Kingdom,Luxembourg
Call: In support of documentary standards (CSA) (H2020-NMBP-TO-IND-CSA-2019, 2019)
Start date: 2020-04-01
End date: 2023-09-30
Duration (months): 42.0
Total project cost (EUR): 2999542.5
EU funding (EUR): 2999542.5
Participants: 15
Project status: SIGNED

Ensuring the health and safety of both population and the wider environment has been entrusted to specialist EU and international organisations such as the OECD, who are tasked with setting up Test Guidelines (TGs) and Guidance Documents (GDs) by which a substance can be assessed. Engineered nanomaterials (ENM) pose a particular problem due to difficulties in analysis and data interpretation. Adopted TGs are not always suitable for nanoforms, but these are needed to ensure that standards are met for assessing and approving ENMs e.g. in European regulation such as REACH. NanoHarmony supports the development of a set of scientifically reliable test methods and good practice documents, based on the translation of existing scientific knowledge and data into a form that has regulatory relevance. NanoHarmony focusses on OECD TGs and GDs. 8 nanomaterial test endpoints have been prioritised with the agreement of the OECD WPMN and WNT, ECHA and the Malta Initiative, forming the core of the NanoHarmony CSA project. NanoHarmony will coordinate the collection and use of available data and information to support the finalisation of the test method development and to organise a sustainable network for the needed exchange, also for future regulatory development needs. NanoHarmony will therefore analyse the processes in test method developments to set up a framework structure for seamless and smooth cooperation between all stakeholders for timely developments of test methods ready for regulation. For both, finalisation of test methods and framework development, interviews, open workshops and stakeholder meetings are seen as a core tool in NanoHarmony to enable active participation and contributions. By identifying gaps and obstacles, and developing an adequate framework for possible implementation, e.g. in a Nano Risk Governance Council (as called for in NMBP 13), future needs for regulatory test methods will be identified and methods developed faster.

Keywords: oecd,test guideline,harmonisation,risk evaluation,regulatory needs,reach,malta initiative,stakeholder involvement
EUropean Heliospheric FORecasting Information Asset 2.0 (EUHFORIA_2.0)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling exploitation of space data
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Finland,Finland,Belgium,Belgium,Belgium,Belgium,France,France,United States,United Kingdom
Call: Space Weather (H2020-SPACE-2019, 2019)
Start date: 2019-12-01
End date: 2022-11-30
Duration (months): 36.0
Total project cost (EUR): 2556401.28
EU funding (EUR): 2556401.25
Participants: 12
Project status: CLOSED

This project aims at developing the world’s most advanced space weather forecasting tool. EUHFORIA 2.0 will address geoeffectiveness, impacts and mitigation, including extreme events, related to solar eruptions, solar wind streams and Solar Energetic Particles, with particular emphasis on its application to forecast Geomagnetically Induced Currents (GICs) and radiation on geospace. We will apply innovative methods and state-of-the-art numerical techniques to extend the recent heliospheric solar wind and CME propagation model EUHFORIA with two integrated key facilities that are crucial for improving its predictive power and reliability, namely 1) data-driven flux-rope CME models, and 2) physics-based, self-consistent SEP models for the acceleration and transport of particles along the magnetic field lines. This involves novel coupling of advanced space weather models. In addition, after validating the upgraded EUHFORIA/SEP model it will be coupled to existing models for geomagnetically induced currents (GICs) and atmospheric radiation transport models. This will result in a reliable prediction tool for radiation hazards from SEP events, affecting astronauts and passengers and crew in high-flying aircraft, as well as the impact of space weather events on power grid infrastructure and telecommunication and navigation satellites. Finally, this innovative tool will be integrated in the both in the Virtual Space Weather Modeling Centre (ESA) and the space weather forecasting procedures at the ESA SSCC in Uccle, so that it will be available to the space weather community and effectively used for improved predictions and forecasts of the evolution of CME magnetic structures and their impact on Earth. The project provides a unique opportunity for Europe to take a leading role in space weather forecasting and to protect its modern technologies and infrastructures both in space and on ground.

Keywords: heliospheric wind,cme propagation,sep model,gic models,radiation models,magnetosphere model
New commercial EUropean RICE (Oryza sativa) harbouring salt tolerance alleles to protect the rice sector against climate change and apple snail (Pomacea insularum) invasion (NEURICE)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Action type: Research and Innovation actions
Countries involved: Italy,Italy,Spain,Italy,Spain,Spain,Argentina,China,France,France,United Kingdom
Call: Strategies for crop productivity, stability and quality (H2020-SFS-2015-2, 2015)
Start date: 2016-03-01
End date: 2020-02-29
Duration (months): 48.0
Total project cost (EUR): 4752725.0
EU funding (EUR): 4608975.0
Participants: 14
Project status: CLOSED

About 2/3 of the rice consumed by European citizens is produced in EU, and its productivity is affected by abiotic and biotic stresses. Of particular concern, global temperature has increased over the last century, especially during the last 50 years (0.13° C / decade). One consequence has been a clear tendency toward salinization, which affects rice as one of the most salt sensitive crop in the region. Associated with changes in temperature and salinity, the biotic stress of the Apple snail species from genus Pomacea now threatens to destroy rice paddy fields eating the sown seed and the rice plantlets, representing one of the worst introduced gastropod crop pest of the recent time. It is calculated that nowadays this pest causes damages in rice fields worldwide that result into losses of tens of billions of Euros a year. Recently, apple snails have been detected in the Ebro river delta (Spain), and now it represents an important thread to Europe’s wetlands biodiversity and rice production. To date, the measures adopted to combat apple snail have failed, but in the autumn of 2013, 2500 ha of infested fields were flooded with sea water. This treatment proved 100% effective in destroying apple snail infestations, nevertheless residual salt concentrations affected negatively rice productivity. Thus, the general objective of the NEURICE project is to identify and introduce genetic variation in European rice varieties for obtaining commercial varieties tolerant to salinity in order to (i) mitigate the imminent effects of salinization and deterioration of water quality in the Mediterranean basins due to climate change, and (ii) to avoid the decline in production observed after seawater treatments performed in rice paddies that successfully controlled the apple snail pest. The availability of commercial salt tolerant rice lines will prevent the climate change derived abiotic stress while avoiding the dispersion of this devastating pest (biotic stress) all over Europe.

Keywords: rice,oryza sativa,abiotic stress,salt tolerance,biotic stress,apple snail,pomacea insularum
AEGLE (Ancient Greek: Αἴγλη) – An analytics framework for integrated and personalized healthcare services in Europe (AEGLE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Content technologies and information management: ICT for digital content, cultural and creative industries
Action type: Innovation actions
Countries involved: Italy,Greece,Sweden,Greece,Greece,Greece,Belgium,France,Netherlands,United Kingdom,United Kingdom,United Kingdom,United Kingdom,Portugal
Call: Big data and Open Data Innovation and take-up (H2020-ICT-2014-1, 2014)
Start date: 2015-03-01
End date: 2018-08-31
Duration (months): 42.0
Total project cost (EUR): 6079642.5
EU funding (EUR): 5230698.75
Participants: 15
Project status: CLOSED

The data generated in the health domain is coming from heterogeneous, multi-modal, multi-lingual, dynamic and fast evolving medical technologies. Today we are found in a big health landscape characterized by large volume, versatility and velocity (3Vs) which has led to the evolution of the informatics in the big biodata domain. AEGLE project will build an innovative ICT solution addressing the whole data value chain for health based on: cloud computing enabling dynamic resource allocation, HPC infrastructures for computational acceleration and advanced visualization techniques. AEGLE will: - Realize a multiparametric platform using algorithms for analysing big biodata including features such as volume properties, communication metrics and bottlenecks, estimation of related computational resources needed, handling data versatility and managing velocity - Address the systemic health big bio-data in terms of the 3V multidimensional space, using analytics based on PCA techniques - Demonstrate AEGLE’s efficiency through the provision of aggregated services covering the 3V space of big bio-data. Specifically it will be evaluated in: a)big biostreams where the decision speed is critical and needs non-linear and multi-parametric estimators for clinical decision support within limited time, b)big-data from non-malignant diseases where the need for NGS and molecular data analytics requires the combination of cloud located resources, coupled with local demands for data and visualization, and finally c)big-data from chronic diseases including EHRs and medication, with needs for quantified estimates of important clinical parameters, semantics’ extraction and regulatory issues for integrated care - Bring together all related stakeholders, leading to integration with existing open databases, increasing the speed of AEGLE adaptation - Build a business ecosystem for the wider exploitation and targeting on cross-border production of custom multi-lingual solutions based on AEGLE.

Keywords: health bigdata,integrated care services,advanced visualization techniques,services acceleration,business innovation