Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Avionero – a new standard in flight search (Avionero)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: SME instrument
Countries involved: Sweden
Call: Small business innovation research for Transport and Smart Cities Mobility (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-12-01
End date: 2018-05-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Avionero is developing the next generation flight search service. This service is inspired by the vast unmet needs of modern travellers who are left frustrated and abandoned in their search for personalised flight travel options online. The existing flight search engines (e.g. Skyscanner, momondo) are based on the logic, technology and UX created back in the ‘90s. This means that they a) are built on the predetermined assumptions about the behaviour of the user (e.g. assuming that a user visiting the platform already has their travel destination and dates in mind) and b) drastically limit flight search personalisation opportunities through outdated technological frameworks. As a result, user trust in the search engines is low, while the frustration is high. Avionero is well positioned to break this paradigm. We have developed and pre-validated (TRL-6) the first prototype of the flight search service that truly puts the user in the driving seat while searching for their dream flight travel online. With the combination of powerful AI technology and an easy-to-use interface, we provide a much convenient flight search service. While leaving the user in control, our smart system gives them the freedom to efficiently explore and personalize. This project aims to develop the business plan for the market launch of Avionero. The feasibility assessment will be performed alongside an open beta testing in Sweden. User feedback from beta testing, combined with results of market feasibility investigations, will be used to optimise our strategy for international scaling and ultimate market launch of the platform. If successful, an overall innovation effort will take Avionero to a new level of competitiveness and growth. The project supports enhanced mobility of European travellers by proposing a new concept of flight search, providing higher degree of transparency in the flight conditions and enhanced opportunities to pick the right flight for individual needs.

Keywords: flight search service,ai technology,new flight search experience,flight search market,customer oriented air mobility
An enzyme-based self-oscillating gel (OSCILLOGEL)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Career Restart panel
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-02-01
End date: 2021-01-31
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

Self-oscillation is a periodic motion generated and maintained by a source of power that lacks the corresponding periodicity. In living systems several periodic motility processes or structural differentiation arise with no on-off stimuli, merely under the continual flow-in and flow-out of material and energy. The popular synthetic dynamic models use oscillatory chemical reactions to drive the system, though in most real cases no underlying biochemical oscillator is found. One clue is in the interdependence of chemistry and mechanics (stress, elasticity, or transport). Periodicity is counterintuitive because it cannot be attributed to any of the subsystems individually: this property emerges only through the collective behaviour of the components, as a systems-level property. To understand biological systems, we need to understand how these properties and functions are generated and controlled. Feedback-loops between chemical and mechanical processes are intrinsic in morphogenesis, though mechano-chemical feedback is generally still lacking in synthetic systems. I build coupled reaction-diffusion-mechanics systems, where a chemoresponsive hydrogel swells and shrinks (and, e.g., lifts and lowers a load) in a constant and uniform unreacted chemical environment, with no external stimuli. The chemistry is not oscillatory in itself, that is, if the gel is rigid or insufficiently responsive. Previous systems (mostly with inorganic reactions) operated under the continuous flow of fresh reactants. This inconvenience would be eliminated by making a big step forwards to biochemistry, where the reaction is linked to an enzyme immobilized in the gel. First we wish to demonstrate such a biocompatible system with the urease-urea reaction. After exploring the operating conditions, this autonomous system could fit to engineer regulatory functions by opening-closing a valve or to obtain biologically meaningful chemical responses by applying a force (pull, release) and vice versa.

Keywords: autonomous actuator,ph responsive hydrogel,mechano chemical feedback,nonlinear dynamics,reaction diffusion,systems chemistry,synergetics,self organisation,cooperativity,biomimetic system
Formulations and Computational Engineering (FORCE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Advanced materials
Action type: Research and Innovation actions
Countries involved: Italy,Germany,Switzerland,Greece,Greece,Netherlands,United Kingdom,United Kingdom
Call: Advancing the integration of Materials Modelling in Business Processes to enhance effective industrial decision making and increase competitiveness (H2020-NMBP-2016-two-stage, 2016)
Start date: 2017-01-01
End date: 2021-03-31
Duration (months): 51.0
Total project cost (EUR): 3957417.5
EU funding (EUR): 3957417.5
Participants: 10
Project status: CLOSED

The FORCE consortium is a 10 pan-European expert partnership with the objective to develop a integrated Business Decision Support System (BDSS) based on open standards for industries engaged in formulating chemical ingredients. The generic BDSS is an open framework that connects any existing or future materials models at various levels of complexity and discretion (electronic, atomistic, mesoscopic, continuum and empirical), experimental data sets, and structured and unstructured commercial information (e.g. on cost, forecasting, intellectual property (IP)). In combination with multi-criteria (objective) optimizers (MCO) for key performance indicators (KPI’s) the BDSS generates data driven formulation and product options for facilitating business decision making. The project has a generic focus but targets 3 specific important industrial sectors as main demonstrators, namely Personal Care (liquid detergents), Insulating Rigid PolyUrethane (PU) based Foams and Industrial Inks (PU-based) for the purpose of focus and generating a real ready to use BDSS available to large, medium and small enterprises alike. The proposed options are tailored for use into problem specific Apps. These provide an additional level of tailored user-friendliness and a data driven operational tool for product optimization, development and quality checks including faster and tailored customer services for the formulators and the providers of formulation components. Accordingly the project is positioning materials modeling as an integrated part of a business decision process. The consortium strives to change the modus operandi of mainly empiricism-based formulation industries into a science and technology and data driven industry by taking advantage of materials modelling and advanced computational learning methodologies for handling “big data”. The partners subscribe to the activities of the European Materials Modelling Council (EMMC).

Keywords: formulations,chemistry,foams,detergents,inks,multiscale modelling,pareto front
Understanding children's empathy: an ethnographic study among the indigenous Runa of the Ecuadorian Amazon (ChildEmp)

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: Social Sciences and Humanities
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-01-12
End date: 2021-01-11
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The phenomenon of empathy is receiving growing interest in the European public sphere and scientific community. In particular, the question of how one learns to feel empathy towards the environment and the beings which inhabit it has been identified as a key issue to address at this time of environmental crisis.The proposed project investigates how empathy is learnt by children from an Amazonian indigenous community in Ecuador. It explores how and under what circumstances indigenous children in the Ecuadorian Amazon learn to perceive nonhuman entities as human-like and develop empathy towards them. Grounded upon my extended ethnographic knowledge of the region, the project will contribute to broader contemporary debates of how empathy towards nonhumans is culturally acquired, manifested and actively learnt during childhood. This is a social anthropology project with a strong interdisciplinary approach which includes perspectives from developmental psychology, ecology, cognitive science and philosophy. The aims of this project are: 1. to explore how children learn to perceive others as human-like in a setting which is inductive to such learning; 2. to explore children’s perception and understanding of nonhuman personhood and intentionality; 3. to understand the nature of ‘empathy’ among indigenous Runa people of the Ecuadorian Amazon. These aims will be reached through 10 months of ethnographic fieldwork in an indigenous Runa village where I will deploy participant observation and other methodologies from psychology, medical and visual anthropology which will be designed during pre-fieldwork training at the University of Kent. Research results will be disseminated through an academic and public engagement plan which includes two academic publications, an ethnographic film, a secondment at the Centre for Subjectivity Research in Copenhagen, a workshop and a document to be used by community members for school policy-making.

Keywords: children,empathy,amazonia,indigenous people,ecuador
Smart Biopsy Tool for Real-Time Cancerous Cell Characterization at the Tip of the Needle (SmartGuide)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: SME instrument
Countries involved: Israel
Call: Supporting innovative SMEs in the healthcare biotechnology sector (H2020-SMEINST-2-2016-2017, 2016)
Start date: 2017-01-01
End date: 2018-12-31
Duration (months): 24.0
Total project cost (EUR): 3032500.0
EU funding (EUR): 3032500.0
Participants: 1
Project status: CLOSED

The project will clinically validate a smart biopsy solution that provides real-time direct tissue characterization at the tip of the needle, which can be displayed on the biopsy system screen as well as on the screen of the imaging system used to guide the biopsy, based on data directly related to the disease stage and tissue type. The real-time tissue characterization will improve the accuracy of the diagnosis, reduce the understaging risk by 95%, reduce the false negative rate by 80%, reduce the number of repeat biopsies by 80% and the number of excisional open breast biopsies by 50%, thus improving the standard of care for breast cancer diagnosis. The project also supports the development of personalized medicine by identifying novel biomarkers for cancer tissue characterization (conductivity and permittivity measurements based on dielectric spectroscopy), which will help clinicians predicting individual patient risk profiles and follow-up requirements. The project results will therefore lead to improved diagnosis, reduced clinical risks associated with un-necessary biopsies, and ultimately reduce costs for health providers, while improving standard of care and quality of life for the patients. Estimated cost savings can reach 275M Euros for each 1M biopsies. The project will implement an open label, single arm, multi-centre, prospective, cohort validation study, performed at 3 sites in Israel, supporting the adoption by the medical community and the filing of CE certification applications. The project duration is 24 months and the total budget 3M Euros.

Keywords: breast cancer,biopsy,cell characterization,dielectric spectroscopy,bio impedance
Recovering Europe´s PHotovoltaics LEadership through high Concentration Technology (REPHLECT)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Spain
Call: Stimulating the innovation potential of SMEs for a low carbon energy system (H2020-SMEINST-2-2015, 2015)
Start date: 2015-08-01
End date: 2018-04-30
Duration (months): 33.0
Total project cost (EUR): 2333716.25
EU funding (EUR): 1633601.38
Participants: 1
Project status: CLOSED

Focusing the Sun’s rays onto a piece of paper with a magnifying glass may sound as a children’s game, but it lies over the same principle that Photovoltaic (PV) technology, which can potentially lead Europe to obtain energy at a lower price and with the least environmental impact. In order to achieve it, PV’s efficiency and its associated costs need to be improved. REPHLECT project tackles both factors thanks to an innovative combination of advanced High Concentration PV (HCPV) technology and a close to the end market model. HCPV, due to its use of very high efficiency PV cells, is currently the solar technology with the highest cost reduction potential (85% in the last 5 years). REPHLECT’s HCPV builds up on the excellent results obtained in the FP7 project “NGCPV”, in which concentrator cells, module and system efficiency were improved. Now BSQ Solar, one of NGCPV’s partners, will take a step forward by designing a module that will reach a concentration of 1000X from the 820X developed by NGCPV, and at the same time including innovative features. To reduce the associated costs, REPHLECT will design components that allow local manufacturing and will migrate assembly lines to Satellite Production Centres (SPCs) located in highly irradiated areas to produce the panels close to the market. The only most IP sensitive part, the receivers, will be developed in BSQ headquarters in Madrid. In order words, REPHLECT intends to replicate the white box paradigm which introduced the ultimate commoditization of the computer hardware industry, by challenging the present industry model based in huge centralized upscaling in Asia. The project will be piloted in-house and the assembly satellite production will be demonstrated at the University of Al Akhawayn, in Morocco. REPHLECT counts already with letters of support of more than 15 prestigious companies which are very interested in its business model.

Keywords: photovoltaics,hcpv
Imaging and Addressing of Single Molecules in Optical Lattices (IASMOL)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-01-01
End date: 2021-12-31
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: CLOSED

Nobel Prize winner Richard Feynman first emphasized the complexity of simulating quantum systems. Using classical computers, the exponential scaling of the required computational power with the number of constituent particles of the quantum system makes full simulations impossible for high particle numbers. As a solution, Feynman suggested using a quantum computer that operates according to the laws of quantum mechanics. This notion of quantum simulation - to simulate one quantum system with another - therefore has the main goal of solving problems that are not accessible using a classical computer. A prominent example of quantum simulation, that is the topic of this proposal, is the study of interacting many-body quantum systems. Over the course of the “Imaging and Addressing of Single Molecules in Optical Lattices” (IASMOL) project I will develop techniques to combine the state-of-the-art imaging and addressing techniques currently employed in atomic quantum gas microscopes and apply them to molecule experiments. This will enable the quantum simulation of strongly interacting matter with precise single-particle control and in-situ imaging. I will use molecules created by the association of ultracold alkali-metal atoms. This approach benefits from the enormous advances in laser cooling of atoms and crucially allows the lattice to be loaded with atom-pairs from degenerate atomic gases. The host group (HG) within the physics department at Durham University is part of the Joint Quantum Centre which has a major research theme in ultracold atoms and molecules (both theory and experiment). The HG have successfully created RbCs molecules by the association of atoms for many years, allowing for studies of the properties of these molecules. The RbCs experiment in the HG is therefore the ideal environment to implement the IASMOL project.

Keywords: ultracold molecules,polar molecules,quantum simulation,optical lattices,quantum gas microscopes
Intra-tumoral heterogeneity in NRAS-driven metastatic melanoma (INHuMAN)

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: Belgium
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-04-01
End date: 2021-03-31
Duration (months): 24.0
Total project cost (EUR): 166320.0
EU funding (EUR): 166320.0
Participants: 1
Project status: CLOSED

Metastasis is largely refractory to therapy and, thereby, responsible for 90% of cancer-related deaths. An incomplete view of the mechanisms that drive metastasis has been a major barrier to rational development of effective therapeutics and prognostic diagnostics for metastatic patients. There is increasing evidence that this multi-step process involves reversible non-genetic reprogramming events allowing cancer cells to acquire diverse phenotypic features needed to migrate, invade, intra/extra-vasate and actively adapt to the varying environment (stress) they encounter. Understanding metastasis therefore requires methodologies that capture the magnitude and dynamics of non-genetic reprogramming in 4D (space and time) at the single-cell resolution. The advent of reliable single-cell multi-Omics analytical tools allows the simultaneous profiling of single cell’s genome, epigenome and transcriptome. Integrating single-cell profiling with lineage tracing provides a robust framework for defining cell fate transitions, intermediate states and trajectory inference. The host lab has recently used such a powerful combination of approaches to study the cellular origin of melanoma, the early molecular events associated with initiation of the disease and to portray cell state dynamics during therapy response. I propose to exploit this know-how to perform a longitudinal and exhaustive analysis of the diversity and trajectories of melanoma cell states during metastatic dissemination using a clinically-relevant mouse model of melanoma, a disease with a very high metastatic propensity. The gene regulatory networks underlying the identified metastatic cell states will be deciphered and the data exploited to develop therapeutic modalities targeting (amenable) drivers of state switching that contribute to early key steps of the metastatic process. The project is expected to lead to new avenues for early detection and interception of metastatic melanoma.

Keywords: intratumoral heterogeneity,mouse models,melanoma,metastasis,single cell sequencing approaches,plasticity,gene signatures
Approximate Computing for Power and Energy Optimisation (APROPOS)

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: Austria,Spain,Italy,Italy,Italy,Finland,Sweden,Switzerland,Finland,France,Netherlands,Netherlands,United Kingdom
Call: Innovative Training Networks (H2020-MSCA-ITN-2020, 2020)
Start date: 2020-11-01
End date: 2024-10-31
Duration (months): 48.0
Total project cost (EUR): 4095308.16
EU funding (EUR): 4095308.16
Participants: 14
Project status: SIGNED

The Approximate Computing for Power and Energy Optimisation ETN will train 15 ESRs to tackle the challenges of future embedded and high-performance computing energy efficiency by using disruptive methodologies. Following the current trend, by 2040 computers will need more electricity than the world energy resources can generate. On the communications side, energy consumption in mobile broadband networks is comparable to datacenters. To make things worse, Internet-of-Things will soon connect up to 50 billion devices through wireless networks to the cloud. APROPOS aims at decreasing energy consumption in both distributed computing and communications for cloud-based cyber-physical systems. We propose adaptive Approximate Computing to optimize energy-accuracy trade-offs. Luckily, in many parts of the global data acquisition, transfer, computation, and storage systems there exists the possibility to trade off accuracy to less power and less time consumed. As examples, numerous sensors are measuring noisy or inexact inputs; the algorithms processing the acquired signals can be stochastic; the applications using the data may be satisfied with an “acceptable” accuracy instead of exact and absolutely correct results; the system may be resilient against occasional errors; and a coarse classification may be enough for a data mining system. By introducing a new dimension, accuracy, to the design optimization, the energy efficiency can even be improved by a factor of 10x-50x. We will train the spearheads of the future generation to cope with the technologies, methodologies, and tools for successfully applying Approximate Computing to power and energy saving. The training, in this first ever ITN addressing approximate computing, is to a large extent done by researching energy-accuracy trade-offs on circuit, architecture, software, and system-level solutions, bringing together world leading experts from European organizations to train the ESR fellows.

Keywords: approximate computing,energy efficiency,wearables,edge computing,cloud computing,arithmetics,approximation,stochastic computing,hardware,software,computing system