Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Spreadsheets run the world. We run spreadsheets. (GRID)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Iceland
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-05-01
End date: 2019-08-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The spreadsheet is the most widely used data storage, manipulation and modelling software tool within the non-developers reach. Almost 750M people use it, while 60% of the business world underpins every critical business decision, planning and budgeting based on spreadsheets. Since a strong business comes with good data, analytic strategy and clear vision, organisations are extending current infrastructure with modern analytics tools, driving fast market expansion for Application Platforms as a Service, aPaaS (3.5Bn€ by 2020, 18.5%CAGR). Business intelligence based on spreadsheets is left behind though due to their shortcomings in handling high data volume, data integrity and flexibility. As successful entrepreneurs with 20 years of experience in software development for the data market, we have the means to challenge the shortcomings of spreadsheets. We introduce GRID, a high level web-based application transforming spreadsheets into user-friendly reports, dashboards and interactive applications. Through it, we enable not only the creation of new data collection, but also handling the existing ones within the online environment. Our technological innovation consists of a 3 steps mechanism capable to read spreadsheet files and automatically compile the data, logic and presentation layers to server-side. A 2018 start-up located in Iceland, GRID Inc, was founded as a response to a business opportunity resulting during our survey on spreadsheets as a self-service problem solving tools for non-IT individuals. GRID is an aPaaS that could improve the advantages of Business Intelligence (30.3Bn€ by 2023) or become an extension to Office Suites (27.7Bn€ by 2023). We follow a Software as a Service business model, a “Pay as you go” mechanism and 3 levels of monthly subscriptions offering full access and functionality of our product. By completing this project, we estimate 35.45M€ cumulated profit, ROI of 13.18 and additional 32 FTE.

Keywords: spreadsheet,modelling software tool,application platforms as a service
Next generation traffic management for empowering CAVs integration, cross-stakeholders collaboration and proactive multi-modal network optimization (FRONTIER)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Spain,Cyprus,Switzerland,Belgium,Greece,Belgium,Greece,Greece,Greece,Sweden,United Kingdom,United Kingdom,Luxembourg
Call: Network and traffic management for future mobility (H2020-MG-2020-TwoStages, 2020)
Start date: 2021-05-01
End date: 2024-04-30
Duration (months): 36.0
Total project cost (EUR): 4998963.75
EU funding (EUR): 4998963.5
Participants: 19
Project status: SIGNED

FRONTIER aims to provide the network and integrated traffic management strategies of the future, taking into account new types and modes of transport and automated vehicles (including their logical and physical requirements), the minimization of pollution and capacity bottlenecks (including congestion and traffic jams), the reduction of accidents, and the need to reduce the cost of mobility for all users (both citizens, public authorities and businesses). On the operational level FRONTIER facilitates the transition towards resilient multimodal autonomous mobility by establishing the processes of collaboration and arbitration among stakeholders while developing the business models that will address the commercial viability of the identified solutions. FRONTIER will develop, apply and test autonomous management systems, secured by design, that will constantly evolve using data generated from real-time monitoring of the transportation system, knowledge generated by operators and decision makers, and simulation models providing system optimal solutions accounting for new mobility services and technologies. These systems will support and enact proactive decisions, realising our vision to empower a seamless transition to an autonomous and integrated transport management for future mobility services. FRONTIER will be validated in three pilot sites (Oxfordshire UK, Athens GR and Antewerp BE) focusing on three main themes: Smart Infrastructures and CAVs integration; Multimodal mobility for passengers and freight cross-stakeholders collaboration; Network performance analysis for planning and policy making. To materialize this concept, FRONTIER follows an efficient multidisciplinary approach bringing together partners from 5 universities and research institutes, 7 companies, 5 transport authorities from three diverse European countries, one testbed for traffic management and one international road federation.

Keywords: automated and connected vehicles,multi stakeholders collaboration,organisational and business modelling,supply demand optimistation,transport simulation and performance analysis
Sex-Specific Interactions in Arbuscular Mycorrhizas in an Ecological Community Context (SIAM)

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: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-04-13
End date: 2017-04-12
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The importance of below-ground organisms for plant growth, plant community dynamics and ecosystem processes is widely recognised. Among them, arbuscular mycorrhizal symbioses are key elements as they mediate plant resource acquisition. The effects of arbuscular mycorrhizal fungi on plant fitness have been extensively studied in sexually monomorphic plants, but plant populations with separate sexes are relatively common in nature. Usually sexes differ in their resource needs and allocation patterns. Because arbuscular mycorrhizal symbioses mediate resource acquisition and allocation patterns through imposing both costs and benefits to the plants, it is not surprising that sex-specific interactions between arbuscular mycorrhizal fungi and sexually dimorphic plants occur. This is an extremely novel field of research. Most available studies on this topic have been exclusively focused on two trophic levels, neglecting the fact that plants live in complex multi-trophic scenarios, where both mutualistic and antagonistic relationships interact both above- and below-ground. The aim of this research project is to explore and understand plant – arbuscular mycorrhizal fungal interactions in a more realistic multi-trophic context. The essence of the project lies in the interdisciplinary and multidisciplinary approach as it will cover plant and insect ecology, fungal ecology and genetics, and chemical ecology. Implementation of this project has scientific importance for the improvement of our understanding of complex multi-trophic interactions in plants and has potentially enormous economic significance for agriculture as it includes pollination ecology and herbivory. Besides the scientific importance of the proposed project itself, this project will significantly enhance the applicant’s career by acquiring up-to-date techniques and other significant skills and provide expertise on mycorrhizal research for the host institution.

Keywords: arbuscular mycorrhizal fungi,above ground,below ground interactions,dioecy,gynodioecy,plant,fungal interactions,pollination,soil ecology,sexual dimorphism,multi trophic interactions
Life and death of a virtual copepod in turbulence (C0PEP0D)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: France
Call: ERC Advanced Grant (ERC-2018-ADG, 2018)
Start date: 2019-09-01
End date: 2024-08-31
Duration (months): 60.0
Total project cost (EUR): 2215794.0
EU funding (EUR): 2215794.0
Participants: 1
Project status: SIGNED

Life is tough for planktonic copepods, constantly washed by turbulent flows. Yet, these millimetric crustaceans dominate the oceans in numbers. What have made them so successful? Copepod antennae are covered with hydrodynamic and chemical sensing hairs that allow copepods to detect preys, predators and mates, although they are blind. How do copepods process this sensing information? How do they extract a meaningful signal from turbulence noise? Today, we do not know. C0PEP0D hypothesises that reinforcement learning tools can decipher how copepod process hydrodynamic and chemical sensing. Copepods face a problem similar to speech recognition or object detection, two common applications of reinforcement learning. However, copepods only have 1000 neurons, much less than in most artificial neural networks. To approach the simple brain of copepods, we will use Darwinian evolution together with reinforcement learning, with the goal of finding minimal neural networks able to learn. If we are to build a learning virtual copepod, challenging problems are ahead: we need fast methods to simulate turbulence and animal-flow interactions, new models of hydrodynamic signalling at finite Reynolds number, innovative reinforcement learning algorithms that embrace evolution and experiments with real copepods in turbulence. With these theoretical, numerical and experimental tools, we will address three questions: Q1: Mating. How do male copepods follow the pheromone trail left by females? Q2: Finding. How do copepods use hydrodynamic signals to ‘see’? Q3: Feeding. What are the best feeding strategies in turbulent flow? C0PEP0D will decipher how copepods process sensing information, but not only that. Because evolution is explicitly considered, it will offer a new perspective on marine ecology and evolution that could inspire artificial sensors. The evolutionary approach of reinforcement learning also offers a promising tool to tackle complex problems in biology and engineering.

Keywords: copepod,turbulence,reinforcement learning,hydrodynamic signalling
An Integrated Solution for Sustainable Care for Multimorbid Elderly Patients with Dementia (CAREPATH)

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,Spain,Spain,Germany,Switzerland,Türkiye,Romania,United Kingdom
Call: Healthcare interventions for the management of the elderly multimorbid patient (H2020-SC1-2020-Two-Stage-RTD, 2020)
Start date: 2021-07-01
End date: 2025-06-30
Duration (months): 48.0
Total project cost (EUR): 5091267.5
EU funding (EUR): 4965000.0
Participants: 10
Project status: SIGNED

CAREPATH proposes an ICT-based solution for the optimization of clinical practice in the treatment and management of multimorbid patients with Mild Cognitive Impairment or mild dementia. Such solution is targeting a more complex multimorbidity scenario and follows an integrated patient-centered approach, in order to develop a flexible and modular system to deliver a best care, adapted framework for increasing the independence and Quality of Life (QoL) of multimorbid patients with dementia. The proposed solution exploits the IONIS, C3-Cloud and imergo®-ICP healthcare platforms (whose three coordinators belong to the CAREPATH consortium) and provides a holistic environment for both healthcare providers and patients, efficiently addressing the joint multimorbidity and dementia challenges. To demonstrate and validate its results, CAREPATH will focus on combining multimorbid conditions, in different levels of complexity, and in combination with dementia. As such, CAREPATH will consider conditions such as Diabetes, Hypertension, Heart failure, Atrial Fibrillation, Chronic Obstructive Pulmonary Disease, Asthma, or Chronic Kidney Disease. The CAREPATH pilots will take place in four European countries (Spain, Romania, Germany and UK) with diverse health and social care systems, ICT landscape/digital maturity of healthcare provision and dementia national programs. The pilots will strengthen the evidence base on associated health outcomes and efficiency gains. CAREPATH will also elaborate on a methodology for computer interpretable clinical guidelines and computationally derived best clinical practice for the improved management of elderly multimorbid patients with dementia. It will develop Quality Key Performance Indicators for such a guideline-driven clinical practice and patient-centered integrated care delivery. In addition, the relevant health economic impacts of the solution, in terms of cost effectiveness and care provision inequalities will be assessed.

Keywords: interventions,multimorbid elderly patients,dementia,patient centred,integrated solution,sustainable health care,stratified care pathways,clinical guidelines,best practices,qkpis
Unified Framework for the Analysis of Co-evolutionary Systems (CoEvolFramework)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-02-01
End date: 2018-01-31
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

Today's challenges are marked by more frequent and wide-spread episodes of social, economic, political and environmental crisis. Co-evolutionary systems offer a natural perspective and powerful tools to help us understand conditions that affect populations of agents whose behavior changes in response to their interaction outcomes in situations of strategic decision-making. Studying these complex co-evolutionary systems remains an open challenge as rich structures in the models are not taken into account. The overarching aim of this project is to fill this major research gap with a unified, principled framework to analyze complex co-evolutionary systems. At the core of our approach is the graph representation of interacting agent behaviors where problem structures are fully captured by complete orientations in the graph and associated co-evolutionary dynamics by sampling processes on the graph. This project combines complementary expertise of the Experienced Researcher (Dr. Chong) in large co-evolutionary systems and the Supervisor (Professor Tino, University of Birmingham) in complex, adaptive and dynamical systems. Its vision is that the framework provides foundation for new modelling tools benefiting policy-makers, regulators, and academics through better understanding and predictive quality of real-world strategic decision-making systems.

Keywords: evolutionary computation,co evolution,complex and adaptive systems
Innovation in Tuberculosis (INNOVA4TB)

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: Life Sciences
Countries involved: Ukraine,Spain,Spain,Spain,Germany,Germany,Spain,Sweden,Moldova, Republic of,Sweden,Chile
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2018, 2018)
Start date: 2019-01-01
End date: 2024-06-30
Duration (months): 66.0
Total project cost (EUR): 1039600.0
EU funding (EUR): 1039600.0
Participants: 16
Project status: SIGNED

The objective of INNOVA4TB is to enhance and strengthen the collaborative research among sectors and to form a network aimed to perform high-quality and translational research in the field of diagnosis and management of tuberculosis (TB). The consortium is constituted by 12 institutions from 8 countries that combine complementary and synergic expertise: clinical management (hospitals), basic science and new technologies (academic institutions), and industrial development and entrepreneurship culture (SMEs). The exchanges between the institutions allow the participants to progress in their career perspectives. TB is one of the major infectious diseases worldwide, and the emergence and spread of drug resistant cases is a public health threat. However, the conventional methods used for diagnosis and drug-susceptibility testing are not enough for controlling the disease. In addition, all TB patients, independently of their age, gender, severity of the disease and type of responsible strain, follow the same treatment duration (up to 20 months in drug resistant cases), which often leads to high frequency of adverse events, suboptimal adherence to treatment, and poor outcome. A transition from programmatic to personalized management of TB is needed. Our proposal will develop innovative technologies and approaches in order to improve the individual risk assessment for TB development, to rapidly diagnose active TB, to detect the drug susceptibility of the strain, to design tailor-made therapies, and to use biomarkers to guide and individualize the duration of antimicrobial therapy. This is of great importance for improving the quality of life of patients and ensuring treatment success, as well as for economic reasons for the healthcare system.

Keywords: tuberculosis,diagnostics,latent tb,genotypic drug susceptibility
Aerial Situational Awareness for Every Firefighter (FOTOKITE-SME-P1)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Switzerland
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-02-01
End date: 2019-05-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Fotokite is a breakthrough situational awareness solution whose unique characteristics constitute it as a valuable public safety tool for firefighters. Fotokite aims to ensure operational safety, increase response efficiency, decrease associated workload and operational risks, and help in life-saving efforts.
Programmable polymer microarrays for tunable and flexible display (PPMTFD)

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: Chemistry
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-02-15
End date: 2023-03-28
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: SIGNED

The future is a world of screens. Not only TVs, computers, phones and open air screens, but also the surface of tables or walls, as well as the displays inside vehicles showing real-time information. Liquid crystal displays and organic light-emitting diode displays are now conventional displays that have been extensively used in smart phones, TVs, tablets and many other displays. However, their intrinsic limitations such as monotonous color, power needs and minimal deformations, significantly restrict future developments. In order to meet the increasing demand of portable electronic products and wearable devices, new display technologies including microscale and flexible displays with tunable properties are highly desired. In this proposal, I will design novel types of tunable and flexible displays based on programmable polymer microarrays (PPM). The core technology is that the displays response speed will be greatly enhanced by designing the structure of functional photochromic molecules. Photochromic spiropyrans (SP) and the fluorescent dye (perylene bisimide, PBI) will be introduced into PPM and used as energy acceptors and donors, respectively. The display process can be tunable through reversibly fluorescence resonance energy transfer between SP and PBI upon different light irradiation. This means that vivid color image displays will be able to be written, erased, and rewritten repeatedly. The new displays will possess advanced response speeds with new SP generated with a range of push-pull substituents. Importantly, the flexible polymeric matrix will expand the scope of display applications because of its stretchable, bending and crimp deformation ability. Moreover, the microscale feature of current designs will be beneficial for integrating displays onto the chip to meet the requirements of miniaturization of devices. The generated programmable and flexible optical microstructures would contribute to the next-generation platforms of smart displays.
Enabling Multilingual Conversational AI (MultiConvAI)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: United Kingdom
Call: Call for proposals for ERC Proof of Concept Grant (ERC-2020-PoC, 2020)
Start date: 2021-01-01
End date: 2022-06-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

In recent past, Conversational Artificial Intelligence (AI) has made major advances, thanks to the availability of big data and increasingly powerful deep learning. Task-based statistical dialogue systems (SDS) are now viable, embedded in popular commercial applications (e.g. the Apple’s Siri, Amazon’s Echo, Google’s Assistant) and cost-effective in many scenarios (e.g., customer support, call centre service, searching, booking). Yet current SDSs are only available for a handful of resource-rich languages, leaving the majority of the worlds languages and their speakers behind. Our project will develop the first prototype system for scaling conversational AI to multiple languages. This will be based on new methodology that learns multilingual word representations (i.e. embeddings, WEs) without the need for expensive training data, using a process called semantic specialisation that complements WEs with common-sense and linguistic knowledge in external knowledge graphs. Building on our promising pilot studies, we will develop Natural Language Understanding (NLU) modules for SDS via 1) more effective semantic specialisation based on joint multi-source multi-target training; and 2) focus on typologicallydiverse languages. We foresee a pioneering use of selective sharing and structural adaptation for obtaining WEs and optimisation for the target languages guided by typological knowledge. The best resulting technology will be integrated in a demo prototype system which users and industries can deploy to generate multilingual NLU input for more widely portable SDS. Since we also plan to explore the possibility to form a start-up company, we will use the system to demonstrate the potential to our network of industry contacts and potential customers. On a larger scale, extending the multilingual scope of SDSs can have major socioeconomic benefits: it can broaden the global reach of conversational AI and it can enhance its commercial viability.

Keywords: natural language processing,computational semantics,multilingual language technology,spoken,dialogue systems,conversational ai