Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Management of Real-time Energy Data (MORE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Ireland,Cyprus,Belgium,Greece,Denmark,Denmark
Call: Big Data technologies and extreme-scale analytics (H2020-ICT-2020-1, 2020)
Start date: 2020-10-01
End date: 2023-12-31
Duration (months): 39.0
Total project cost (EUR): 3720553.75
EU funding (EUR): 3720553.0
Participants: 7
Project status: SIGNED

The widespread use of sensor and IoT devices is generating huge volumes of time series data in various industries like finance, energy, factories, medicine, manufacturing and others. Industries use these data for monitoring, but their main potential is still untapped. Existing techniques and software for time series management do not provide tools sufficiently scalable and sophisticated for managing the huge volumes of data or adequate forecasting, prediction and diagnostics. MORE will create a platform that will address the technical challenges in time series and stream management, focusing on the RES industry. MORE’s platform will introduce an architecture that combines edge computing and cloud computing to be able to guarantee both responsiveness and provide sophisticated analytics simultaneously. This architecture will be combined with the usage of time series summarization techniques, or as we more accurately term them in MORE, modelling techniques for sensor data. Models are any compressed representations that allow the reconstruction of the original data points of a time series (e.g. a linear function) within a known error-bound (possibly zero). This approach has synergies with the edge computing approach, since summarization can be done at the edge, reducing the load in the whole data processing pipeline. MORE will introduce advanced analytics tools for prediction, forecasting and diagnostics based on two technological directions: machine learning and pattern extraction, with emphasis to motifs, which is the state-of-the-art for time series. MORE will adjust these techniques to work directly on models of data, thus enabling them to scale beyond state-of-the-art. The ability to ingest huge volumes of data will have an important impact to the accuracy of the prediction and diagnostics models.

Keywords: machine learning,energy,big data,renewable energy,pattern extraction,time series
From wrecks of ancient life to natural laboratories: Cave organisms as a testing ground for studying repeatability and predictability in evolution. (SPYCAVER)

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: Life Sciences
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-05-02
End date: 2024-05-01
Duration (months): 24.0
Total project cost (EUR): 184707.84
EU funding (EUR): 184707.84
Participants: 1
Project status: SIGNED

Predicting evolution is one of the major aims of evolutionary biologists. Convergent evolution—the independent outcome of similar traits in distinct lineages—occurs frequently in nature at every level of biological organization in distinct evolutionary lineages. In this context, convergence has been considered to play contrasting roles in shaping biodiversity patterns. The success of colonizing and thriving in a new environment strongly depends on the existence, or lack, of specialized traits that ensure survival in it, a phenomenon referred to as environmental filtering. Thus, organisms adapted to extreme environmental conditions provide an ideal framework to study repeatability in evolution and, ultimately, to test for predictability, the ability to match a priori specialized traits to specific environmental conditions. Subterranean extreme environmental conditions exert strong selective pressure on strict cave-dwelling organisms which, respond by evolving a similar suit of phenotypic and physiological traits. The main aim of this project is to investigate whether environmental selective pressures, determine patterns of genomic convergent evolution in obligate cave-dwelling organisms. I will use an interdisciplinary approach, integrating field research, available ecological and phenotypic data, and newly generated genomic information to investigate the genomic bases of convergent evolution in cave-dwelling organisms. For this, I propose to investigate i) the genomic basis of adaptation to different subterranean microhabitats, ii) the speciation mechanisms in subterranean species, and iii) the causes of phylogenetic constrain on microhabitat preference. This project will give an unprecedented understanding of repeated evolution. Additionally, the results obtained may have far-reaching implications for medicine and conservation biology, of great relevance to several H2020 Focus Areas.

Keywords: convergent evolution,cave evolution,phylogenomics,biodiversity
Ferroelectric Vertical Low energy Low latency low volume Modules fOr Neural network Transformers In 3D (FVLLMONTI)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Emerging themes and communities
Action type: Research and Innovation actions
Countries involved: Germany,Austria,Switzerland,France,France,France
Call: Neuromorphic computing technologies (H2020-FETPROACT-2020-01, 2020)
Start date: 2021-01-01
End date: 2025-08-31
Duration (months): 56.0
Total project cost (EUR): 4760060.0
EU funding (EUR): 4760060.0
Participants: 8
Project status: SIGNED

In the context of the fourth industrial revolution along with unprecedented growing global interdependencies, an innovative, inclusive and sustainable society is a sound European priority. For many people, the way towards inclusive and sustainable daily life goes through a lightweight in-ear device allowing speech-to-speech translation. Today, such IoT devices require internet connectivity which is proven to be energy inefficient. While machine translation has greatly improved, an embedded lightweight energy-efficient hardware remains elusive because existing solutions based on artificial neural networks (NNs) are computation-intensive and energy-hungry requiring server-based implementations, which also raises data protection and privacy concerns. Today, 2D electronic architectures suffer from "unscalable" interconnects, making it difficult for them to compete with biological neural systems in terms of real-time information-processing capabilities with comparable energy consumption. Recent advances in materials science, device technology and synaptic architectures have the potential to fill this gap with novel disruptive technologies that go beyond conventional CMOS technology. A promising solution comes from vertical nanowire field-effect transistors (VNWFETs) to unlock the full potential of truly 3D neuromorphic computing performance and density. Through actual VNWFETs fabrication setting up a design-technology co-optimization approach, the FVLLMONTI vision is to develop regular 3D stacked hardware layers of NNs empowering the most efficient machine translation thanks to a fine-grain hardware / software co-optimisation. FVLLMONTI consortium is a strong partnership with complementary expertise and extensive track-records in the fields of nanoelectronics, unconventional logic design, reliability, system‐level design, machine translation, cognition sciences. The consortium is composed of 50% of junior researchers and 90% of first-time participants to FETPROACT.

Keywords: cognitive science,3d integrated circuit,memory technology
Experimental Programme Investigating Cumulative Culture (EPICC)

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: Environment and Geosciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-09-01
End date: 2019-08-31
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

Humans exhibit a rich and complex material culture with no equivalent in other animals. The unique human capability to accumulate cultural innovations across time allows us to develop powerful technology and drives technological progress. Despite a growing literature investigating cumulative culture, the underlying processes at play in the accumulation of cultural knowledge remain puzzling. The overarching aims of this proposal are to identify the requirements of human cumulative culture both at the individual and population levels and improve our understanding of factors that affect the pace of cultural accumulation. During the course of this action, we will develop innovative experimental methods to investigate three important and timely lines of research and shed new light on the complex processes that underlie cultural accumulation: 1) Identify the cognitive requirements of innovation production and transmission, 2) Evaluate the interplay between population structure and cultural accumulation, 3) Evaluate the effects of ecological factors on the rate of innovation. This action will use lab experiments from psychology and economics and will bring knowledge from anthropology and biology to help explain why only humans are able to accumulate cultural information across time and why rates of cultural accumulation have varied in our evolutionary past.

Keywords: human cultural evolution,cumulative culture,innovation
African Governance and Space: Transport Corridors, Border Towns and Port Cities in Transition (AFRIGOS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: United Kingdom
Call: ERC Advanced Grant (ERC-2014-ADG, 2014)
Start date: 2016-01-01
End date: 2022-06-30
Duration (months): 78.0
Total project cost (EUR): 2491364.0
EU funding (EUR): 2491364.0
Participants: 1
Project status: SIGNED

AFRIGOS investigates the process of 'respacing' Africa, a political drive towards regional and continental integration, on the one hand, and the re-casting of Africa's engagement with the global economy, on the other. This is reflected in unprecedented levels of investment in physical and communications infrastructure, and the outsourcing of key functions of Customs, Immigration and security agencies. AFRIGOS poses the question of how far respacing is genuinely forging institutions that are facilitating or obstructing the movement of people and goods; that are enabling or preventing urban and border spaces from being more effectively and responsively governed; and that take into account the needs of African populations whose livelihoods are rooted in mobility and informality. The principal research questions are approached through a comparative study of port cities, border towns and other strategic nodes situated along the busiest transport corridors in East, Central, West and Southern Africa. These represent sites of remarkable dynamism and cosmopolitanism, which reflects their role in connecting African urban centres to each other and to other global cities. AFRIGOS considers how governance 'assemblages' are forged at different scales and is explicitly comparative. It works through 5 connected Streams that address specific questions: 1. AGENDA-SETTING is concerned with policy (re-)formulation. 2. PERIPHERAL URBANISM examines governance in border towns and port cities. 3. BORDER WORKERS addresses everyday governance emerging through the interaction of officials and others who make their livelihoods from the border. 4. CONNECTIVE INFRASTRUCTURE looks as the transformative effects of new technologies. 5. PEOPLE & GOODS IN MOTION traces the passage of people and goods and the regimes of regulation to which they are subjected. AFRIGOS contributes to interdisciplinary research on borderland studies, multi-level governance and the everyday state.

Keywords: border management,regional economic communities,informality,bureaucracy,customs,trade,migration,urbanism,everyday life,commodities,multi level governance,global assemblages,infrastructure
Epigenetic mechanisms underlying the influence of paternal drug experience on offspring behavior (EPOFFSPRING)

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: Life Sciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-03-01
End date: 2019-02-28
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The idea of transmitting paternal environmental impact across generations has been indicated and described in studies across species, but the mechanism is still unclear. The overall aim of the project is to test whether H3K27me3, a type of epigenetic modification on histone 3 [1], is involved in transmitting environmental impact across generation to influence the behavior of offspring. With a behavioral neuroscience background, the experienced research (ER) will apply his expertise in high throughput behavioral assay and combine techniques he will learn from the host lab, including epigenetic profiling, NGS, targeted epigenome editing and computational analysis to address specifically whether paternal drug experience influence offspring behavior via modifying H3K27me3 on dopamine-related genes that are involved in various behaviors [2]. Besides advancing our understanding of the importance and mechanism of paternal inheritance and the role of epigenetics in general, this project will also further extend zebrafish as a model in studying cross-generational transmission of environmental experience by combining multidisciplinary techniques. The trainings ER will be beneficial and essential for his future goal to study epigenetic mechanisms underlying physiology and pathology of brain.

Keywords: epigenomics,zebra fish,trans generational epigenetic inheritance
ICT-Supported Bath Robots (I-SUPPORT)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Active ageing and self-management of health
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Italy,Germany,Italy,Spain,Greece,Greece,France,France
Call: Advancing active and healthy ageing with ICT: service robotics within assisted living environments (H2020-PHC-2014-single-stage, 2014)
Start date: 2015-03-01
End date: 2018-02-28
Duration (months): 36.0
Total project cost (EUR): 3563198.75
EU funding (EUR): 3563198.0
Participants: 10
Project status: CLOSED

The I-SUPPORT project envisions the development and integration of an innovative, modular, ICT-supported service robotics system that supports and enhances older adults’ motion and force abilities and assists them in successfully, safely and independently completing the entire sequence of bathing tasks, such as properly washing their back, their upper parts, their lower limbs, their buttocks and groin, and to effectively use the towel for drying purposes. Advanced modules of cognition, sensing, context awareness and actuation will be developed and seamlessly integrated into the service robotics system to enable the robotic bathing system to adapt to the frail elderly population’ capabilities and the frail elderly to interact in a master-slave mode, thus, performing bathing activities in an intuitive and safe way. Adaptation and integration of state-of-the-art, cost-effective, soft-robotic manipulators will provide the hardware constituents, which, together with advanced human-robot force/compliance control that will be developed within the proposed project, will form the basis for a safe physical human-robot interaction that complies with the most up-to-date safety standards. Human behavioural, sociological, safety, ethical and acceptability aspects, as well as financial factors related to the proposed service robotic infrastructure will be thoroughly investigated and evaluated so that the I-SUPPORT end result is a close-to-market prototype, applicable to realistic living settings.

Keywords: soft robots,bathing,service robotics system,modularity,safe human robot interaction,shared control,force compliance control,cognition,context awareness,user acceptability,cost efficiency
SolarPredict: An advanced predictive tool and service of the Solar 11-yr Activity Cycle (SolarPredict)

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: France
Call: ERC Proof of Concept Grant (ERC-2014-PoC, 2014)
Start date: 2015-03-01
End date: 2016-08-31
Duration (months): 18.0
Total project cost (EUR): 149913.0
EU funding (EUR): 149913.0
Participants: 1
Project status: CLOSED

The main idea of the SolarPredict Proof of Concept project is to use physically based dynamo models to make solar 11-yr activity predictions, in particular of Earth impacting events, more robust/reliable and to develop the tools to make them accessible (with the appropriate licencing and IPR) to customers (such as private corporations or governmental agencies) as a service, software or paid/freemium applications. The key advantage of our tools/techniques over current ones is both our deep knowledge of the working of the solar dynamo and magnetism and the implementation in solar physics of state-of-the-art variational data assimilation (DA) techniques used daily in weather forecasting. These variational techniques are known to be more robust and versatile than for instance sequential methods or simple geomagnetic precursors thus allowing us to incorporate the highly complex solar magnetic activity and dynamics into our forecasting tools. Thanks to our advanced 2-D direct and adjoint mean field dynamo codes and modern DA technique, we will assimilate the most relevant solar observational data (sunspots numbers, polar cap magnetic field, surface flows...) into our prediction model hence allowing us to develop an operational prototype. Indeed major solar storms are strongly correlated to the intensity of solar cycle and 80% of them are directly due to the presence of complex active regions that are more frequent as the 11-yr cycle intensifies. Thus being able to anticipate the level and geometry of solar global magnetism give us a competitive edge in predicting major solar storms. We will thus bring with the SolarPredict project, our novel variational DA solar prediction algorithm to a more mature state such as to make it operational and useful to private companies and governmental agencies in order to help them evaluate the economic cost of solar activity and associated storms and protect their assets by anticipating such devastating solar activity.

Keywords: solar 11 yr activity and magnetism,societal impact,services,novel data assimilation techniques in solar physics,dynamo
COPERNICUS DATACUBE / AI DATACUBESERVICES FOR SOCIETY, INDUSTRY AND NEW MARKET GENERATION (CENTURION)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling exploitation of space data
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Ireland,Romania,Switzerland,Poland,Belgium,Netherlands,Netherlands
Call: Big data technologies and Artificial Intelligence for Copernicus (H2020-SPACE-2020, 2020)
Start date: 2021-05-01
End date: 2024-08-31
Duration (months): 40.0
Total project cost (EUR): 4120721.25
EU funding (EUR): 4120721.25
Participants: 10
Project status: TERMINATED

The CENTURION project will critically advance applications of AI methodology to the Big Earth Data challenge. Through mature, award-winning, Petascale-proven European datacube technology, all Copernicus data together with contributing missions and third party’s EO, climate, and thematic data sets will be homogenized into Analysis and Fusion Ready spatio-temporal data hypercubes offered through strictly standards-based interfaces. CENTURION will become a partner of the EarthServer Datacube federation thereby making its results seamlessly available for several DIASes as well as enabling free and open research and paving a road for commercial uses. Awards-winning AI platform operating throughout all cycles (ranging from data discovery to generation of actionable insights) will enable rapid use case development and will provide assured execution of analytical tasks at any scale in hybrid cloud environments. Reusable AI Knowledge Packs (novel approach to AI) will establish a method for creation of shrink-wrapped purpose-oriented analytics tools. The project will create several knowledge packs for at least 5 use cases. External contributions for future AI knowledge packs will be encouraged through outreach, trainings, and support. The CENTURION project success measures and KPIs will incorporate technical, economic, environmental, safety, security and social criteria, addressing the principal barriers that impede accelerated market uptake of Copernicus data and services and will demonstrate commercial value of the created innovations by establishing novel products and business models further described in the proposal that prioritise pertinent industry use cases in the scope of the project. By combining and advancing leading European tools in two critical fields, AI and Big Data Cubes, the project is key to European technology independence and monetisation of Copernicus Data.

Keywords: ai knowledge pack,rasdaman platform
Engineering Quantum Error Correction (EQEC)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Germany,Netherlands
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-04-01
End date: 2021-09-30
Duration (months): 66.0
Total project cost (EUR): 1786563.0
EU funding (EUR): 1440313.0
Participants: 2
Project status: CLOSED

This proposal will advance the theory of quantum error correction towards its application in real physical devices, in particular superconducting transmon qubit systems. The research will result in proposals for experiments: how to use physical qubits to redundantly represent logical quantum information and how error information can be obtained and classically processed. The research will consider novel ways of using transmon qubits to achieve a universal fault-tolerant surface code architecture. The research will produce a design of a universal fault-tolerant architecture in which qubits are encoded in the electromagnetic field of a (microwave) cavity. Research will also focus on mathematical and numerical studies in quantum error correction which are technology-independent, but shed light on coding overhead, decoding efficiency and logical universality.

Keywords: quantum error correction