Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
An Integrative Framework for Modeling the Sense of Commitment (Sense of Commitment)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: Hungary,United Kingdom
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-07-01
End date: 2021-06-30
Duration (months): 60.0
Total project cost (EUR): 1483575.0
EU funding (EUR): 1290965.0
Participants: 2
Project status: CLOSED

The phenomenon of commitment is a cornerstone of human social life. Commitments make individuals’ behavior predictable in the face of fluctuations in their desires and interests, thereby facilitating the planning and coordination of joint actions involving multiple agents. Moreover, commitments make people willing to perform actions that they would not otherwise perform. For example, an investor may be willing to purchase government bonds because a central banker has made a commitment to maintaining that country’s currency. In general, social objects and institutions such as jobs, money, government and marriage depend for their origin and stability upon the credibility of commitments. Despite the crucial importance of commitment for characteristically human forms of sociality, it is not well understood how people identify and assess the level of their own and others’ commitments. The SENSE OF COMMITMENT will develop a theoretical framework for research on commitment, and create a suite of experimental paradigms for testing predictions generated by the theoretical framework. By focusing on joint actions involving pairs of agents, it will illuminate the fundamental mechanisms underlying large-scale human social phenomena. The SENSE OF COMMITMENT will generate basic scientific knowledge that will be relevant to many disciplines in the social sciences, cognitive sciences, and humanities. The insights gained will create a new perspective for: 1) social robotics, by specifying factors that will be useful in designing robots (e.g. for senior citizens’ homes and rescue operations) that participate in commitments with humans; 2) research on pathological conditions such as borderline personality disorder, in which individuals find it difficult to commit to or to rely upon others; 3) identifying factors relevant in sustaining people’s commitment to beneficial long-term programs (skills training for workers, exercise or rehabilitation programs for patients, etc.).

Keywords: joint action,trust,commitment,social interaction,embodied cognition,social robotics
Achieving sustainable agriculture in African cacao through DNA metabarcoding and food web models (CHOCOLATE4LIFE)

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-2017, 2017)
Start date: 2019-08-01
End date: 2021-10-31
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

Anthropocentric destruction of natural ecosystems, such as tropical rainforests, has created an urgent need to balance agricultural production with biodiversity. To achieve sustainability, we must manage ecosystems to prioritise both species that both maximise ecosystem support for crops (“ecosystem service species”) and those that maximise biodiversity (“keystone species”). The framework of community models offers an ideal platform for managing a balance between keystone and ecosystem service species, but two principle components remain: 1) a method for rapidly identifying key species and quantifying interactions between species, and 2) quantitative methods that can fit dynamic community models to such novel data. To overcome the first issue, I will characterize species interactions by implementing state-of-the-art diet metabarcoding, in which the prey of hundreds of animals as well as the plant taxa consumed by prey can be simultaneously identified through predator faeces. With my host at the University of Glasgow, these data will enable me to develop a step-change in food-web modelling. Using Bayesian statistical inference I will construct models in which the strength of connections among species will dynamically adapt to changes in their abundance. With species identifications from metabarcoding, I will build multi-trophic food web models of African shade cacao plantations to address three objectives: 1) identify keystone trees that maximize richness of birds and arthropods (i.e., biodiversity); 2) determine ecosystem service species that maximize predation of damaging pest arthropods and 3) identify “crossover species”: those with both ecosystem service and keystone properties. This cutting edge approach will provide an ecosystem-level understanding of factors affecting the relationship between biodiversity and agricultural production, allowing sustainable management and many further applications in agriculture, ecology, disease control and beyond.

Keywords: africa,arthropods,bayesian modelling,biodiversity,birds,ecosystem services,cacao,food web models,keystone species,sustainable agriculture,tropical rainforest
Semantics-Based Machine Translation (SEBAMAT)

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: Greece
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-04-01
End date: 2022-03-31
Duration (months): 24.0
Total project cost (EUR): 165085.44
EU funding (EUR): 165085.44
Participants: 1
Project status: CLOSED

Most current machine translation systems are either rule-based or corpus-based. They typically take the semantics of a text only in so far into account as they are implicit in the underlying text corpora or dictionaries. This is also true for the recent neural machine translation systems, which - in comparison to standard phrase-based systems, tend to have the focus even more on fluency rather than adequacy. However, it has been pointed out that it is unlikely to be able to bring machine translation quality to the next level as long as the systems do not make better use of semantic knowledge. For example, according to Kevin Knight future machine translation systems should use information of the type "who is doing what to whom and when", i.e. involving the identification of the semantic roles of the items occurring in a sentence. To move forward in this direction, we propose to implement and evaluate three different approaches: The first approach is based on state of the art machine translation but considers word senses rather than words. That is, a word sense disambiguation system is used to identify the word senses in large parallel text corpora. Then, in analogy to standard word alignment, the word senses are aligned across languages, and the resulting multilingual sense dictionaries are used in conjunction with the word sense disambiguation systems for translating new texts. Our second approach uses role labeling for identifying the semantic roles of the words in a sentence. The roles are aligned across languages, and this information is then used to improve the translation process. The third approach is based on an algorithm which computes the semantic similarity between phrases. It considers the translation task as finding semantically similar phrases across languages.

Keywords: machine translation,neural machine translation,semantics based machine translation,computational linguistics
Ice Age Genomic Tracking of Refugia and Postglacial Dispersal (IceAGenT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: Norway
Call: ERC Consolidator Grant (ERC-2018-COG, 2018)
Start date: 2019-10-01
End date: 2024-09-30
Duration (months): 60.0
Total project cost (EUR): 2189775.75
EU funding (EUR): 2189775.75
Participants: 1
Project status: SIGNED

Understanding rates of migration and resilience to climate change is important for explaining both the distribution of single species and anticipate how ecosystems may respond to climate change. There are two vigorously debated questions about the response of NW European biota to past climate changes: 1) glacial survival vs tabula rasa and 2) Reid´s paradox of rapid plant migration through seed dispersal vs. survival in cryptic refugia just south or east of the ice sheet. These are related as survival in any northern refugia would suggest local dispersal rather than the rapid dispersal rates that are needed from southern refugia. While we have learned a lot about dispersal routes from phylogeography and about glacial refugia from macrofossils, pollen and, more recently, ancient DNA (aDNA), we have never been able to trace plant migration routes back in time. Our lab is at a step-change in answering these questions as we now have a full genome reference library for the entire flora of Norway and adjacent regions (>2000 species), which will allow us to develop genomic markers identifying not only species, but genetic variation within species, in ancient sediment samples. In addition, we have >20 sediment cores already analysed for vascular plant aDNA using metabarcoding, and a further 20 are in the pipeline. Based on these and 12 new cores, we will select samples that contain key species representing different bioclimatic zones (boreal trees, dwarf shrubs, arctic herbs), and re-analyse them for within-species genetic variation. This will be complemented by analyses of contemporary phylogeography of the same species. This will allow us to identify refugia areas and trace migration routes back in time by different components of the ecosystems. The results of this study will open a new era in studies of species abilities to respond to climate changes (palaeo-phytogeography) and enable us to model the effects of current global warming more accurately than before.
AlchemyML, The “One-Click Data-In Model-Out” (AlchemyML)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-08-01
End date: 2018-11-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Skootik (https://skootik.com) is a start-up from San Sebastian (Spain) founded in 2012 developing more accessible (technically and regarding its cost) exploitation of information extracted from data with artificial intelligence. Skootik is in the final round of the BIND4.0 start-up accelerator programme sponsored by the Basque Country regional Government, where large companies test technologies developed by start-ups. Our product, AlchemyML, is a universal and fully automatic machine learning solution, initially conceived for predictive maintenance of industrial machines in the manufacturing sector. Currently AlchemyML is expanding its features to assist in supply chain management and resource management. AlchemyML does not require businesses of any size to have any knowledge of machine learning to get the advantages of information extracted from data. Using AlchemyML will help to reduce maintenance costs by 15-35% by prevention of machine failure, improve resource management with a 5-15% reduction in utility bills or increase stock rotation by 5-10%. AlchemyML is a disruptive solution in the very dynamic ML market, which will reach globally €7 billion (CAGR 44.1%) by 2022. We aim at a revenue of €56 million with a positive ROI of 4.94 in our first 5 years, reaching a leading position in the manufacturing SME ML solutions market, with over 20% of market share, 300 new customers in Europe, and our staff growing accordingly, with around 30 new employees expected.

Keywords: machine learning,predictive maintenance,supply chain management,resource management
SMAll RuminanTs breeding for Efficiency and Resilience (SMARTER)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Theme: Sustainable agriculture and forestry
Action type: Research and Innovation actions
Countries involved: Spain,Italy,Italy,Spain,Spain,Ireland,Spain,Uruguay,Norway,Greece,Hungary,Romania,New Zealand,Switzerland,China,Greece,France,France,France,France,France,France,France,France,Netherlands,United Kingdom,Canada,United Kingdom,United Kingdom,United Kingdom
Call: Breeding livestock for resilience and efficiency (H2020-SFS-2017-2, 2017)
Start date: 2018-11-01
End date: 2023-06-30
Duration (months): 56.0
Total project cost (EUR): 7643751.25
EU funding (EUR): 6998911.25
Participants: 37
Project status: SIGNED

SMARTER will develop and deploy innovative strategies to improve Resilience and Efficiency (R&E) related traits in sheep and goats. SMARTER will find these strategies by: i) generating and validating novel R&E related traits at a phenotypic and genetic level ii) improving and developing new genome-based solutions and tools relevant for the data structure and size of small ruminant populations, iii) establishing new breeding and selection strategies for various breeds and environments that consider R&E traits . SMARTER with help from stakeholders chose several key R&E traits including feed efficiency, health (resistance to disease, survival) and welfare. Experimental populations will be used to identify and dissect new predictors of these R&E traits and the trade-off between animal ability to overcome external challenges. SMARTER will estimate the underlying genetic and genomic variability governing these R&E related traits. This variability will be related to performance in different environments including genotype-by-environment interactions (conventional, agro-ecological and organic systems) in commercial populations. The outcome will be accurate genomic predictions for R&E traits in different environments across different breeds and populations. SMARTER will also create a new cooperative European and international initiative that will use genomic selection across countries. This initiative will make selection for R&E traits faster and more efficient. SMARTER will also characterize the phenotype and genome of traditional and underutilized breeds. Finally, SMARTER will propose new breeding strategies that utilise R&E traits and trade-offs and balance economic, social and environmental challenges. The overall impact of the multi-actor SMARTER project will be ready-to-use effective and efficient tools to make small ruminant production resilient through improved profitability and efficiency.

Keywords: feed efficiency,resilience,trade off,health,welfare,genomic selection,mathematic models,predictive biology
Tomographic 3D Ultrasound for Safe and More Cost Effective Vascular Diagnostics and Treatment Planning (PIUR tUS)

Framework: Horizon 2020 — Industrial Leadership
Action type: Innovation actions
Countries involved: Austria,Austria,Germany,United Kingdom,United Kingdom
Call: Fast Track to Innovation Pilot (H2020-FTIPilot-2016-1, 2016)
Start date: 2017-05-01
End date: 2019-10-31
Duration (months): 30.0
Total project cost (EUR): 2691746.25
EU funding (EUR): 2091204.78
Participants: 5
Project status: CLOSED

Annually, cardiovascular disease (CVD) causes over 4m deaths in Europe and 17.3m deaths globally, and is expected to grow to over 23.6m by 2030. It accounts for 40% of deaths in the EU and costs the EU economy almost €196bn each year. 2D ultrasound scans are currently the primary choice for vascular diagnostics. Due to low sensitivity, a limited field of action and the lack of volume information, patients are often referred for CTa, MRa and catheter angiography for the detailed imaging required for diagnosis and treatment planning. Referrals delay treatment, exposes the patient to risks associated with radiation and contrast mediums and increases costs. This presents a need to improve the speed and safety of the diagnosis of vascular conditions for rapid treatment, as well as to improve workflow efficiency and reduce costs. The project consortium will further develop the piur tUS system, a 3D freehand tomographic US system capable of rapid, safe and accurate reconstructive 3D quantifiable vascular imaging. It will provide a low cost and reproducible imaging solution that will reduce the need for referrals and be an effective preventative screening tool for CVD. We aim to complete and publish the results from 4 CVD clinical studies to generate the clinical evidence required for CE marking and clinical validation for market uptake. The 4 clinical applications studied will provide a solution for conditions most frequently referred for detailed 3D imaging to maximise the cost-benefit to clinics of purchasing the piur tUS system. The project consortium combines piur imaging’s expertise in medical device development and commercialisation with 3D imaging specialist ImFusion GmbH and medical device product development and manufacturing experts ACMIT. The clinical input for the product development and the clinical studies will be provided by our consortium partners, Independent Vascular Services Ltd and the Institute for Cardiovascular Science: University of Manchester

Keywords: ultrasound,diagnostic device,vascular surgery,imaging,cardiovascular disease
Servi Publici: Everybody's Slaves (SPES)

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: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-10-01
End date: 2018-09-30
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The researcher is moving from Italy to Newcastle University in the UK to embark on a full-scale study of the role of public slavery in the Roman world. The SPES project sets out to provide a full-scale reconsideration of the position of public slaves in the Roman economy and society through a multidisciplinary and comparative study. The preliminary step will be a full overview of the primary evidence, which will combine textual sources with iconographic and archaeological material. The second step will be engaging with two major interrelated questions: a) how a comparative and diachronic study may allow us to further our knowledge of public slavery in ancient Rome; b) how a stronger understanding of the social reality of public slavery in the Roman world may be achieved by the comparison with some modern manifestations of it. The importance of the project is twofold: a) for the first time, the researcher will build a versatile on-line database, which will collect all the sources concerning public slaves in the Roman world; b) it is also the first attempt ever made to cross-fertilize ancient and modern historians of slavery in order to deal with the problem of the slaves owned not by a private person, but by a whole community both in the ancient and modern history. The significance of the project goes thus beyond the remit of Ancient History. It is expected that the project will bring about dramatic changes in understanding how slavery became deep-rooted in all the slave-owning societies: public slaves were in fact essential for the State administration both in the ancient Roman world and in some modern Mediterranean and Transatlantic countries. Working on this project at Newcastle will enable the researcher to develop new sets of expertise and skills both in the IT area and in developing comparative approaches. The host organisation will in turn benefit from the researcher’s world-class expertise in the Latin epigraphy and the social history of the Roman world.

Keywords: roman history,latin epigraphy,roman slavery,modern slavery,database,epidoc use,encoding ancient documents,textual sources,iconographic sources,archaeological sources
Logistics for Manufacturing SMEs (L4MS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Spain,Italy,Italy,Germany,Spain,Estonia,Cyprus,Hungary,Lithuania,Romania,Croatia,Poland,Finland,Finland,Finland,Greece,Croatia,Denmark
Call: ICT Innovation for Manufacturing SMEs (I4MS) (H2020-FOF-2017, 2017)
Start date: 2017-10-01
End date: 2021-03-31
Duration (months): 42.0
Total project cost (EUR): 8764549.64
EU funding (EUR): 7996772.5
Participants: 21
Project status: CLOSED

L4MS (Logistics For Manufacturing SMEs) will spark incremental (productivity increase of new users by a factor of 4 and system setup time reduction by a factor of 10) and disruptive innovation (batch size one & consumerization) for over 100,000 European Manufacturing SMEs & Mid-Caps, building on their intra-factory logistics challenge (50% of the production cost of an item) unleashing their digitalization potential by powering new robot systems that are more cost effective at lower lot sizes. L4MS relies upon: • An open industrial IoT platform with enablers for rapid and efficient deployment of customized logistics solutions. • A suite of "Smartization services" including business modelling, technical support, mentoring, access to skills and to finance. • The L4MS Marketplace, a one-stop-shop, where European Manufacturing SMEs & Mid-Caps will access the L4MS services. • A portfolio of 23 cross-border Application Experiments by 50 SMEs selected through 2 competitive Open Calls, that will test more than 40 services & apps leveraging 10M€ of public funding across 12 established and emerging Digital Innovation Hubs. • A growing ecosystem that will foster Smart Specialization in each single region linked to L4MS. L4MS will transform a pan-European ecosystem into a self-sustainable start-up operating an Open Platform for Innovations in Logistics (OPIL) and L4MS marketplace consisting of 21 members. Comprising 6 Competence Centres, 5 technology providers, 4 industry associations, 3 end-users and 3 business developers -currently engaged in I4MS (XS2I4MS, HORSE and BEinCPPS) and FIWARE- plus 6 Satellites Nodes. L4MS covers 14 EU countries, 15 regions with 8 of them from East Europe. L4MS will help demonstrate that public funded research with a “Smartization” approach (accelerating Industry 4.0) can help manufacturing SMEs & Mid-Caps achieve digital excellence and global competitiveness through logistics automation become “entrepreneurial states and digital industries”.

Keywords: intra factory logistics,automation