Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Multi-layered biomimetics of lytic polysaccharide monooxygenases (MOMIMIC)

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: Belgium
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-01-08
End date: 2020-01-14
Duration (months): 24.0
Total project cost (EUR): 160800.0
EU funding (EUR): 160800.0
Participants: 1
Project status: CLOSED

The high stability of components like cellulose limit the efficiency and cost effectiveness of biofuel or chemical production from lignocellulosic biomass. Thus, the ability of the recently discovered class of metalloenzymes, lytic polysaccharide monooxygenases (LPMO), to enhance the efficiency of recalcitrant polysaccharide degradation makes understanding these enzymes invaluable for carbon friendly sustainable chemical and energy development as prioritized under the Horizon2020 program. The current project seeks to develop multi-layered biomimetics of the LPMO active site that can offer unprecedented replication first and second coordination sphere groups, in order to be able to rationally study the collection of interactions that contribute to enzyme activity. The research involves the design and chemical synthesis of aromatic oligoamide scaffolds that incorporate a specific copper binding site. Through synthetic modification of the scaffold to alter the second coordination sphere, and combined spectroscopic and electrochemical methods, changes in the properties and reactivity of the metal site will be studied with a goal of developing a structure- function relationship that can assist in guiding enzyme modification, as well as, new synthetic catalyst development. The applicant has a strong background in synthetic chemistry and mechanistic studies that will be crucial to the success of the project. Through joining the host lab in Belgium that specializes in coordination and supramolecular chemistry, she will greatly increase her own knowledge base, while transferring her knowledge of synthetic organic chemistry to the host. Additionally, during proposed secondments to work with a collaborator in Germany for the electrochemical studies, the applicant will further expand the gain and transfer of knowledge and strengthen international collaboration between the groups involved.

Keywords: second coordination sphere interactions,biomimetics
An Information-Theoretic Perspective on Massive Asynchronous Connectivity (MASCOT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Spain,United States
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-10-01
End date: 2024-09-30
Duration (months): 36.0
Total project cost (EUR): 263732.16
EU funding (EUR): 263732.16
Participants: 2
Project status: SIGNED

It is expected that in the coming decades the population living in urban areas will increase dramatically. Therefore, the sustainability of our planet depends critically on a smart and energy-efficient operation of cities. Wireless communication technologies arise as one of the main enablers to reach this goal. For example, services and applications such as intelligent transportation, industry automation, and mobile healthcare will require to accommodate a vast number of heterogeneous and battery-limited wireless devices connecting asynchronously and sporadically to the network. This is commonly known as the massive connectivity problem. Since traditional wireless communication technologies were not designed to support this kind of services and applications, there is a need for a profound theoretical study of this problem. The main objective of MASCOT is to characterize, from an information-theoretic perspective, the fundamental limits and tradeoffs of the asynchronous massive connectivity problem. To this end, I will derive in the outgoing phase at MIT nonasymptotic bounds and asymptotic expansions characterizing these limits. In the return phase at Universidad Carlos III de Madrid, I will then explore different strategies to efficiently and accurately compute the nonasymptotic bounds derived at MIT. During the course of the project, I will elaborate guidelines about how future wireless communication schemes must be designed, and I will adapt existing schemes according to these guidelines. The proposed training activities during the fellowship are fundamental for the correct achievements of MASCOT as well as to secure my future career goals. MASCOT guarantees a two-way transfer of knowledge since it combines my past expertise on elaborating and efficiently evaluating fundamental limits of low-latency wireless communications with the supervisors’ expertise on information theory applied to the massive connectivity problem and asynchronous communications.

Keywords: finite length information theory,wireless massive connectivity,asynchronous communications
Underpinning the vital role of the forest-based sector in the Circular Bio-Economy (WoodCircus)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Ensuring the sustainable supply of non-energy and non-agricultural raw materials
Action type: Coordination and support actions
Countries involved: Spain,Italy,Italy,Italy,Italy,Germany,Belgium,Finland,Slovenia,Slovenia,France,France
Call: Raw materials policy support actions for the circular economy (H2020-SC5-2018-1, 2018)
Start date: 2018-11-01
End date: 2021-12-31
Duration (months): 38.0
Total project cost (EUR): 2973953.75
EU funding (EUR): 2973953.75
Participants: 18
Project status: CLOSED

The main goal of the WoodCircus is to increase knowledge, raise awareness and improve conditions for an uptake of resource efficient processing and recycling in wood-based value chains, fostering increased competitiveness of the European woodworking sector. WoodCircus identifies, evaluates and disseminates the outstanding good practises in process efficiency, wood waste collection, management and recycling in the woodworking value chains in Europe with a focus on construction with wood. Achieving a thorough evaluation of the overall system’s performance and a validation of the most relevant transferable solutions, WoodCircus produces sound, critical evidence and tangible decision support information for market actors, stakeholders and policymakers. WoodCircus establishes a well-integrated network between wood processing industries and the waste management sector engaging excellence for future-oriented joint promotion of the wood sector in the Circular Bioeconomy. WoodCircus implements the EU Action Plan for the Circular Economy and the EU Bioeconomy Strategy targets ensuring intelligent utilisation of forest resources and sets up an interface to the EC Raw Materials Information System and the JRC Bioeconomy Knowledge Centre . WoodCircus major outcomes are: 1) Good practice database; 2) Open competition on individual good practice showcases and award to SMEs; 3) Performance and sustainability assessment; 4) Validated best performing supply chain typology for broad transfer; 5) RDTI plan wood industries towards the Circular Economy;(6) White Paper including policy recommendations and communication strategies; 7) WoodCircus Network, established on solid commitments from partners and stakeholders for follow-up beyond the project lifetime. WoodCircus is based on a balanced mix of leading RTO and companies with proven expertise all along the woodworking and construction value chains including waste valorisation and associations at local, national and international level.

Keywords: wood construction,process efficiency,cascade use of wood,recycling,waste management,good practices,stakeholders engagement,smes,construction and demolition,bioeconomy,trade offs
Startup Europe Partnership (SEP)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Future Internet: Software, hardware, Infrastructures, technologies and services
Action type: Coordination and support actions
Countries involved: Spain,Germany,Italy,United Kingdom
Call: Web Entrepreneurship (H2020-ICT-2014-1, 2014)
Start date: 2015-01-01
End date: 2016-12-31
Duration (months): 24.0
Total project cost (EUR): 599092.5
EU funding (EUR): 599092.5
Participants: 4
Project status: CLOSED

Established by the European Commission in January 2014, the Startup Europe Partnership (SEP) is the first pan-European open platform dedicated to supporting the growth and sustainability of European startups able to compete and raise funds at international and global level. SEP is thereby the first Startup Europe Initiative focused on scaling up new innovative ventures, by scouting the most promising European startups and connecting them with the large and medium corporations. The latter are committing capital, seniority (involvement of heads of innovation office or corporate development) and procurement channels to support startups in different ways. SEP was developed in partnership with key actors in the EU startup ecosystem, including leading corporates (Telefónica, BBVA, Orange), educational institutions (Cambridge University, IE Business School, Alexander von Humboldt Institute for Internet and Society), and investors (AngelList and the European Investment Bank Group/European Investment Fund). To reach the goal of helping the best European startups to scale-up, SEP will initially revolve around a unique, scalable format — the SEP Matching Events, which comprise of three activities: Matching, Mapping and Sharing. Matching- Through a series of international events where the best European startups have the opportunity to meet decision makers of corporates with a specific and concrete interest in procurement, investment and acquisition. Mapping- In parallel with the Matching Events, relevant information about startups will be collected. The goal is to map the most interesting European startups and to track their performance and evolution. Sharing- SEP will identify key forms of support that leading European companies provide to scale startups, including corporate acceleration, intrapreneurship, corporate venturing and acquisitions. SEP will produce and share an online repository of best practices to encourage more and stronger corporate-startup relationships.

Keywords: startups,growth,corporates,procurement,investment,acquisition,matching,mapping,sharing,best practices,accelerators,investors,on line repository,startup europe,startup manifesto
TUNABLE MODE RANDOM FIBER LASER FOR MODE DIVISION MULTIPLEXING LASER SOURCE (TUNEMODE)

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: 2015-12-01
End date: 2017-11-30
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The evolution of the bandwidth demand in optical fiber communication system in the Europe region keeps increasing year after year. As for now, most of these demands are supported by the WDM system of optical communication network. It is forecasted that this increasing bandwidth demand could not be supported any more data traffics in the future due to the consumption growth of new applications. In this regards, a new system for solving this issue is becoming all the necessary. An alternative which is forecasted to be able to fulfill this demand is Mode Division Multiplexing (MDM). MDM basically is based on a concept developed for increasing the optical data transmission capacity within the optical fiber itself. Thus, this project will be carried out to investigate the mode tuning of random fiber laser for the application in MDM system. The main objective of this project is to generate a laser with various modes which can be tuned by using few mode fiber and will be using random fiber laser. The purpose of using random fiber laser is because the conventional rare earth based fiber laser such as Erbium and Ytterbium are not optimized for lasing at higher order mode than the fundamental mode LP01. Investigation on mode tunability will be carried out using micro fiber technology and also fiber Bragg grating technology whereby the combination of these two technologies will be functioning as the tunable and filtering element. Also, in this project, new ideas and concepts will be developed whereby the generation of a laser with various modes will probably generate new concepts and findings, not only for MDM system, but also for the device to support this application in the future. In this regards, this research is very significant, in conjunction with the growth of the bandwidth demand in the Europe region as well as in the world.
Gender and Ethnic Integration in Science, Innovation, and Entrepreneurship (GEISIE)

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: Economic Sciences
Countries involved: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-06-01
End date: 2020-05-31
Duration (months): 24.0
Total project cost (EUR): 170121.6
EU funding (EUR): 170121.6
Participants: 1
Project status: CLOSED

While gender and ethnic diversity have increased in the workforce, the evidence is much less clear on whether there has been an increase in gender and ethnic integration, i.e., people actually working together across gender and ethnic lines. This project will analyse large databases (1) to assess trends in gender and ethnic integration in science, innovation, and entrepreneurship, (2) to understand the causes and consequences of gender and ethnic integration as well as potential barriers, and (3) to improve the methodology in the study of gender and ethnic integration and to develop indices that could be used to track changes. The project is specifically focused on European data and will consider issues related to differences in the level of integration within as well as between countries. Furthermore, the project will be able to analyze integration at multiple levels including team, organization, city, and field. The project will use large databases including PATSTAT, Microsoft Academic Graph, and government registry data, combined with name-matching algorithms to estimate the gender and ethnicity of the scientists, inventors, and entrepreneurs. The results of the project are highly relevant for scholars studying innovation, entrepreneurship, social inclusion, social structure, and inequality. The results will also be translated into insights for managers to help them understand and possibly integration in their organizations, yielding greater creativity and innovativeness. Furthermore, the results are of interest to policy makers as increasing gender and ethnic integration within Europe would help European competitiveness as well as the cohesion of European societies.

Keywords: ethnic integration,gender integration,diversity,science,research,innovation,inclusion,social structure
Mathematical Modelling and Optimization of Programmable 5G Networks (MAPNET)

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: France
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-01-01
End date: 2021-01-31
Duration (months): 24.0
Total project cost (EUR): 185076.0
EU funding (EUR): 185076.0
Participants: 1
Project status: CLOSED

The exponential increase in mobile data traffic warrants disruptive changes in the design and management of cellular networks. The next generation (5G) networks target to support a variety of applications having diverse requirements in data rates, latency, energy, etc. To address this surge in traffic demand and the associated heterogeneity in service requirements, several candidate technologies are being investigated under the 5G vision, naming a few: 1) Ultra-dense network deployment for high spatial capacity; 2) Network slicing to support heterogeneous service requirements; and 3) Cloud radio access networks (CRAN), etc. An important element of the 5G vision is to achieve a 50% reduction in the total network energy consumption. To ensure that the future networks meet both the service and the sustainability requirements, energy-efficient designs and integration of renewable-energy sources into the network infrastructure are needed. To address the sudden capacity demands, on-demand network deployment is desired, instead of maintaining a permanently over-engineered infrastructure. Inclusion of these approaches result in highly complex and stochastic network topologies. Modeling and optimizing such networks is a challenging problem. State-of-the-art approaches are not adequate to model these new scenarios, and different mathematical techniques are required. This proposal addresses the optimization and modelling challenges pertaining to the energy efficiency and service requirements of the future ultra-dense networks by: 1) The development of novel energy-efficiency models to ensure energy–neutral network operation considering renewable energy sources; 2) Innovative modeling framework for self-organized drone-assisted network infrastructure; 3) A unified programmable network interface for network slicing considering renewable energy and on-demand drone deployments; and 4) Validation of the developed approaches in a software-defined mobile network platform.

Keywords: programmable networks,network slicing,energy efficiency,drone aided cellular,system level modeling,optimization,renewable energy
Learning to Find Software Bugs (LearnBugs)

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: Germany
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-03-01
End date: 2025-08-31
Duration (months): 66.0
Total project cost (EUR): 1458375.0
EU funding (EUR): 1458375.0
Participants: 1
Project status: SIGNED

Learning to Find Software Bugs Software has become the cornerstone of modern society, economy, and life. Since software is created by humans, though, every non-trivial program contains various bugs, i.e., programming errors that may have disastrous consequences. Traditional approaches to find bugs include automated bug detection tools. Such tools search for instances of bug patterns that recur across projects and application domains. However, automated bug detection currently cannot unleash its full potential because each bug detector addresses one bug pattern and one programming language, while creating new bug detectors is feasible only for program analysis experts. The objective of this proposal is to radically change the way automated bug detection tools are created. The core idea is to replace manually written program analyses with trained machine learning models. To this end, developers will train a bug detector for a particular bug pattern with examples of buggy and non-buggy code, which the model learns to distinguish. The project will realize this vision by developing a reusable framework that addresses several fundamental challenges at the intersection of software engineering, programming languages, and machine learning, e.g.: (i) How to support developers in creating large amounts of training data of buggy and non-buggy code examples? (ii) How to represent programs in a way suitable for advanced machine learning techniques? The proposed project has the potential to revolutionize how software developers find bugs. To date, no other research has addressed the problem of automatically learning bug detection tools. If successful, the project will "democratize" bug detection by enabling all software developers, instead of a few program analysis experts, to create and share bug detection tools. Ultimately, the project will contribute to increasing the reliability, security, and efficiency of complex software systems used by millions of people.

Keywords: program analysis,bug detection
Evolution of herbivory in vertebrates: developing combined isotope (Ca, Sr) and dental surface texture analysis as deep time diet proxies (VERTEBRATE HERBIVORY)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Earth system science
Panel description: Physical geography, geology, geophysics, atmospheric sciences, oceanography, climatology, cryology, ecology, global environmental change, biogeochemical cycles, natural resources management
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-09-01
End date: 2022-12-31
Duration (months): 76.0
Total project cost (EUR): 1728065.0
EU funding (EUR): 1728065.0
Participants: 1
Project status: CLOSED

Diet is a key factor driving vertebrate evolution. Exploring dietary traits and trophic relationships in fossil food webs is fundamental for understanding radiation and extinction events. This project aims to constrain the evolution of herbivory (plant feeding) and trophic interaction of extinct vertebrates at different spatiotemporal scales by analysing their teeth with isotopic and dental wear techniques. A new approach of combined Ca and stable Sr isotope as well as 3D surface texture (3DST) analysis will be developed and applied to fossil teeth of mammal-ancestors and dinosaurs. Teeth record time-series of diet-related isotope compositions in their enamel while their surface tracks short-term food abrasion. These diet proxies will be calibrated on extant vertebrates with well-known diets from wild animals and controlled feeding experiments simulating diet and trophic level switches. Both Ca isotopes and enamel surface textures have a high preservation potential in fossil teeth and enable micro sampling of enamel for Ca isotope and non-destructive 3DST analysis. For the first time, I will combine Ca isotope and 3DST analysis to reconstruct the diet of extinct key vertebrate taxa and their trophic level in fossil food webs. This multi-proxy approach will provide a versatile toolset to test independently feeding hypotheses that mostly hinge on tooth and skeletal morphology, leading to fundamental new insights into the palaeoecology, dietary flexibility and niche partitioning of fossil vertebrates. The aim is to reconstruct the evolution of herbivory in vertebrates. Here, major objectives are: 1) to infer ontogenetic and evolutionary diet changes by combined Ca isotope and 3DST analysis of fossil teeth, 2) explore stable and radiogenic Sr isotopes as combined proxies for trophic level and habitat use, and 3) pioneer 3DST analysis for reptiles. Beyond the field of palaeontology these dietary proxies will be broadly applicable in archaeology, anthropology and ecology.