Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
HARBOR. Humanitarianism and Refugees at the Border: A Transnational Feminist Analysis of Nonprofit Organizations (HARBOR)

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: Social Sciences and Humanities
Countries involved: Australia,Spain
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-01-15
End date: 2023-03-17
Duration (months): 36.0
Total project cost (EUR): 251939.52
EU funding (EUR): 251939.52
Participants: 2
Project status: CLOSED

HARBOR—Humanitarianism and Refugees at the Border—departs from the idea that humanitarianism is a neutral and timeless ideology, and instead turns a critical eye towards this sector to understand the ways in which nonprofit organizations become complicit with the neoliberal order—through reinforcing certain ideals of citizenship and sovereignty, occupying spaces that are destined for public institutions, and influencing refugees’ decision-making processes—and their possibilities for resistance. This feminist transnational comparison project expands my previous research in the refugee nonprofit sector at the US-Mexico border by including the two other most sought-after destinations in the world for refugees: Australia and Europe. Its aim is to make connections between nonprofit local practices and global dynamics to draw broader conclusions about the role nonprofit organizations play within refugee management. Through a combination of a transnational feminist lens and a Foucauldian framework, as well as ethnographic, participant observation and interview methods, HARBOR will reconstruct the role that humanitarian organizations play in the current refugee regime. In so doing, this project works at the connections between the academic, humanitarian, and policy-making sectors. In order to achieve my research objectives, I will be based at the University of Queensland (UQ) in Brisbane Australia where I will be trained in Global Governance and feminist political theory under the supervision of Dr. Hoffstaedter. Upon my return to my European host institution, CSIC, I will bring my new skills and engage in theory-building that challenges the idea of borders as protection with my mentor Professor Velasco at the Humanities Research Center.

Keywords: refugees,transnational feminism,humanitarianism,neoliberalism,gender,migration management,global governance
De- and reconstructing virulence strategies of fungal plant pathogens (conVIRgens)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Biotechnology and Biosystems Engineering
Panel description: Biotechnology using all organisms, biotechnology for environment and food applications, applied plant and animal sciences, bioengineering and synthetic biology, biomass and biofuels, biohazards
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2018-06-01
End date: 2024-05-31
Duration (months): 72.0
Total project cost (EUR): 1922000.0
EU funding (EUR): 1922000.0
Participants: 1
Project status: SIGNED

Fungal pathogens are enormous threats to plants, causing tremendous losses in worldwide crop production. Mechanistic understanding of fungal virulence is crucial to developing novel plant protection strategies in sustainable agriculture. Biotrophic pathogens colonize living plant tissue and reprogram their hosts to stimulate proliferation and development of infection structures. To promote infection, fungal pathogens secrete sets of virulence proteins termed “effectors” in a spatiotemporal program. Many economically relevant biotrophs like rusts and powdery mildew fungi are obligate pathogens. These organisms cannot be grown in culture and are not amenable to reverse genetics, which is a severe constraint for current research. In contrast, the biotrophic smut fungi have a haploid yeast stage, which allows simple cultivation and genetic modification. The causal agent of corn smut disease, Ustilago maydis, is one of the best-established model organisms for fungal genetics. This project aims to utilize the excellent genetic accessibility of U. maydis to approach a previously impossible, pioneering enterprise: the synthetic reconstruction of eukaryotic plant pathogens. In a first step, fungal virulence will be deconstructed by consecutive deletion of the U. maydis effector repertoire to generate disarmed mutants. These strains will serve as chassis for subsequent reconstruction of fungal pathogenicity from different sources. A combination of transcriptomics and comparative genomics will help to define synthetic effector modules to reconstruct virulence in the chassis strains. Deconstruction of U. maydis virulence will identify a complete arsenal of fungal virulence factors. Reconstruction of virulence will show how effector modules determine fungal virulence, including those of the previously not accessible obligate biotrophs. conVIRgens will thereby provide fundamentally new insights and novel functional tools towards the understanding of microbial virulence.

Keywords: fungal plant pathogens,effector biology,biotrophy,ustilago maydis
Human health and migration in prehistory (PALEoRIDER)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The study of the human past
Panel description: Archaeology, history and memory
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2018-04-01
End date: 2023-03-31
Duration (months): 60.0
Total project cost (EUR): 1997500.0
EU funding (EUR): 1997500.0
Participants: 1
Project status: CLOSED

Recent ancient DNA studies have discovered a basal form of Yersinia pestis, the causative agent of bubonic plague, in 5,000 year-old individuals from Eastern and Central Europe. Even though this strain is an early form that does likely not survive in fleas and might have been less transmissible, the timing intriguingly coincides with a period of substantial societal changes. The archaeological record of 3rd millennium BC Europe clearly demonstrates the demise of terminal Stone Age and the rise of Bronze Age societies across the continent. This turnover has so far been explained by factors such as climatic changes or the advent of new metal working technologies and associated trading networks, which led to a reorganization of past societies. However, contemporaneous genomic data from ancient Europeans have attested major genetic upheavals in Europe 5,000 years ago, with an introgression of 75% genetic ancestry from mobile groups from the eastern steppes appearing in Central Europe. This substantial contribution suggests that early outbreaks of infectious diseases, such as plague, are a vital alternative explanation for large-scale population replacements and thus an attractive hypothesis for investigation. With well-preserved ancient human samples from relevant time periods and key regions in Europe at our disposal, we have a unique and ideal test case to track evolutionary relationships between the human genome and pathogens through time. We will specifically target an extensive number of variants in human immune-related loci using state-of-the-art DNA capture assays alongside deep sequencing of microbial shotgun and pathogen data, which permits a direct characterization of human-pathogen co-evolution. This unique temporal framework will allow us to detect loci under selection in humans and pathogens, and explore the role of infectious diseases and human mobility in past societies via an innovative paleo-epidemiological database and explicit modeling approaches.

Keywords: ancient dna,human genome,disease,migration,pathogen,selection,prehistory
Spurring INnovations for Forest ECosystem SERvices in Europe (SINCERE)

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: Innovation actions
Countries involved: Italy,Germany,Italy,Spain,Spain,Spain,Indonesia,Belgium,Belgium,Finland,Croatia,Russian Federation,Finland,Switzerland,Finland,Denmark,Portugal,Peru
Call: Novel public policies, business models and mechanisms for the sustainable supply of and payment for forest ecosystem services (H2020-RUR-2017-1, 2017)
Start date: 2018-01-01
End date: 2022-03-31
Duration (months): 51.0
Total project cost (EUR): 4237214.13
EU funding (EUR): 3991234.38
Participants: 23
Project status: CLOSED

One of the major challenges relating to the management of Europe’s forests is to balance the provision of distinct forest ecosystem services with broad societal demands. If markets and existing governance arrangements fail, forest owners and managers struggle to meet societal needs. There is a necessity to explore new approaches to connect profitable forest management with changing societal demands. Against this background, innovative mechanisms (IM), including novel policies and business models, have the potential to align ecosystem services supply and demand. SINCERE will, first, systematically map the existing knowledge and practical experiences with IM at the European scale. Second, it will, in a joint effort of practice partners and researchers, design, implement and subsequently evaluate a complementary set of innovation actions that explore novel IM in different regional contexts. These actions encompass a broad spectrum of forest ecosystem services (e.g. biodiversity, climate change mitigation, water supply, recreation), governance mechanisms (e.g. new business models, ‘reverse auctions’ with forest owners, participatory governance) and regional settings (e.g. intensively managed commercial forests in Finland versus little-managed forest land in Spain). Third, a Learning Architecture will connect these innovation actions across countries to incentivize cross-case fertilization and learning between research and practice. Finally, practice partners, policy makers and researchers will jointly draw lessons learnt from the innovation actions, including the upscaling of successful IM to be replicated elsewhere. The project will also push for innovations at the interface between policies and on-the-ground IM, and will deliver concrete suggestions for a coordinated European policy framework that supports IM. Target group-specific communication and dissemination activities will ensure SINCERE’s impact throughout the entire project duration.

Keywords: forest policy,environmental governance,payments for ecosystem services,forest management,science policy interface,innovation
Maintenance and relapse in long-term desistance from crime and recovery from addiction (SLIPPED)

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-2018, 2018)
Start date: 2019-07-01
End date: 2021-06-30
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: CLOSED

The primary objective of this research is to investigate the dual processes of desistance from crime and recovery from addiction within the same population. The research therefore targets a thus far neglected area of scholarly study. Specifically, the aims of the Fellowship are twofold, i) to understand the personal, social, and structural factors that contribute towards ‘long-term’ desistance and recovery, and ii) to explore why individuals who had achieved more than three years success in both processes then experience relapse and recidivism. The research process will have three avenues of investigation, i) an interdisciplinary review of relevant literature and studies from the disciplines of Criminology and Addiction Studies, ii) an analysis of relevant legislature, and iii) sixty semi-structured qualitative interviews to uncover the nuances and complexities of maintenance and relapse in long-term desistance and recovery. Research data will be collected in Belfast, Northern Ireland, and Dublin, Republic of Ireland. The researcher will work out of the host institution, Queens University Belfast, under the supervision of a world leader in the field, Prof. Shadd Maruna. Participants will be recruited through a careful and determined process, overseen by the research supervisor, which will engage with statutory and non-statutory supervision and support services for former offenders and recovering substance misusers. The project will generate new knowledge relevant for the H2020 societal challenges 1 (Health, Demographic Change and Wellbeing) and 7 (Secure Societies). Further, the European Union Drugs Strategy 2013-20 identifies achieving a better understanding of addiction recovery and rehabilitation as central to the task of ‘Demand Reduction’.

Keywords: desistance,crime,recovery,addiction,resettlement,rehabilitation
Coordination and Support Action for Quantum Technology Education (QTEdu)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Tackling grand interdisciplinary science and technology challenges
Action type: Coordination and support actions
Countries involved: Germany,Italy,Netherlands,Denmark
Call: Training and Education on Quantum Technologies (H2020-FETFLAG-2020-01, 2020)
Start date: 2020-09-01
End date: 2022-08-31
Duration (months): 24.0
Total project cost (EUR): 340763.75
EU funding (EUR): 340763.75
Participants: 4
Project status: CLOSED

The QTEdu coordination and support action collaboration aims to meet the challenges posed in the call “Training and Education on Quantum Technologies”. QTEdu will assist QFlag in providing the EU quantum science and innovation community with the missing work force ready to bring quantum technologies into engineering applications without which the economic exploitation of Quantum Technologies won’t happen. It will coordinate a community effort needed for an immense scaling-up in training and education while increasing interdisciplinarity and drawing acute attention to current and future corporate and societal needs. It will advance the development of a European Quantum Technology Education community, including a network that connects QT Master students to industry. It will also initiate the development of quality-controlled QT education programs in the sectors corresponding to the three pillars addressed by the Flagship’s Strategic Research Agenda: secondary education, tertiary education and industry training.

Keywords: quantum tecnologies,education
An embryo transfer decision-support tool optimizes live-birth rates in IVF treatments (IVFMakeSense)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Biotechnology and Biosystems Engineering
Panel description: Biotechnology using all organisms, biotechnology for environment and food applications, applied plant and animal sciences, bioengineering and synthetic biology, biomass and biofuels, biohazards
Countries involved: Israel
Call: Call for proposals for ERC Proof of Concept Grant (ERC-2020-PoC, 2020)
Start date: 2021-05-01
End date: 2023-04-30
Duration (months): 24.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

In vitro fertilization (IVF) treatments are markedly inefficient since a significant fraction of embryos lacks the capacity to implant. Even for successfully implanted embryos, one out of nine clinical pregnancies is terminated due to first trimester miscarriage. In general, embryos that harbor certain chromosomal abnormalities leading to early pregnancy loss often permit “normal preimplantation development” that cannot be detectable via human visualization of time lapse images. Since current state-of-the-art algorithms fail to accurately assess the developmental potential of embryos to reach live birth, reasonable pregnancy rates are obtained by transferring more than one embryo to the uterus. However, multiple pregnancy (of more than one embryo), which account for 30-to-40% of all pregnancies (>95% are twins), are associated with a higher health risk to the mother and to the newborn. Here I propose to develop an embryo-transfer decision-support tool (ET-DST) that will analyze all possible embryo-transfer strategies that include multiple transfer cycles of embryos of the same patient. The ET-DST will identify the transfer strategy that optimizes the potential to reach live-birth and shorten time-to-pregnancy by combining multiple classifiers that evaluate the potential of embryos to implant, assess the risk of miscarriage, and predict the optimal day of transfer. The physician/embryologist will be able to set both embryo-specific parameters and maternal labels as follows: (1) a penalty of multiple pregnancies, (2) a cryopreservation factor that reflects the decrease in embryo quality due to verification and thawing compared with fresh transfer, (3) a maternal factor that reflects the clinical background of the patient, and (4) a penalty of multiple transfer cycles. The integration of patient specific parameters will minimize health risks while optimizing live-birth rates and shortening time-to-pregnancy.

Keywords: assisted reproductive technologies,in vitro fertilization,machine learning
Bayesian Monte Carlo for Global Illumination (BMC Rendering)

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: Spain
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-08-01
End date: 2018-07-31
Duration (months): 24.0
Total project cost (EUR): 158121.6
EU funding (EUR): 158121.6
Participants: 1
Project status: CLOSED

One of the most challenging problems in computer graphics (CG) is to synthesize physically-based realistic images given an accurate model of a virtual scene. Rendering a photo-realistic image requires solving the illumination integral which describes the light transport on a scene, and whose value is in general computed by resorting to numerical approximations such as those based on Monte Carlo (MC) methods. The quality of the approximation of those methods is strongly dependent on the samples placement and weighting. Therefore several works have focused on improving the purely random sampling used in classic MC techniques. In particular, a recent and innovative approach called Bayesian Monte Carlo (BMC) has been proven to greatly outperform classic MC methods due to its ability to incorporate prior knowledge which is then used for careful samples weighting and placement. This method was successfully applied in rendering by Brouillat et al. (2009) but only for diffuse materials. Recently, Marques et al. (2013) have generalized the application of BMC to non-diffuse materials. These works have confirmed the potential of BMC for efficiently solving the rendering integral, making it a new trend in computer graphics. Nevertheless, the use of BMC in CG is still in an incipient phase and its application to more evolved and widely used rendering algorithms remains cumbersome. We propose a research plan with a double objective: first, to develop an adaptive sampling strategy for BMC integration, where a new set of samples is used to further improve the approximation of the previous integral estimate. Second, to apply BMC to higher dimension problems such as path tracing, where the integration over all possible ray paths turns the approximation into a high-dimension integration problem, hence addressing the holy grail of the integration in light transport simulation: the curse of dimensionality.

Keywords: computer graphics,globarl illumination,ray tracing,bayesian monte carlo
INTEGRATED TIME TRACKING SYSTEM (IT-TRAS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Greece
Call: European SME innovation Associate - pilot (H2020-INNOSUP-2019-02, 2019)
Start date: 2019-12-09
End date: 2021-06-08
Duration (months): 18.0
Total project cost (EUR): 105275.0
EU funding (EUR): 105275.0
Participants: 1
Project status: CLOSED

Time tracking constitutes a key feature of efficiency evaluation. Nevertheless, the production of Global Time Sheets is a cumbersome task usually ignored or improperly produced by the workers leading to inability to evaluate efficiency or accurately calculate the billable hours of work. The main reason behind that is the need of constant user intervention to set, pause or stop a timer per task or project which is impossible for those working away from the business premises. Integrated Time Tracking system (IT-TRAS) will minimise the need for user intervention in accurately calculating the working hours by operating seamlessly regardless of the location of the worker, by automatically adjusting to operational features of different tasks and by making smart distribution of time per task. Artificial Intelligence and specifically Machine Learning will be employed to gradually minimise user intervention through supervised learning and classification algorithms applied in a defined pool of training data containing the actual working hours per task and project. To achieve this, an Innovation Associate will be hired by the Rhodes Centre for History and Social Research – Rhodes Project SCE. The successful candidate will have a PhD in informatics, background in AI and ML, specialisation in supervised learning and classification algorithms as well as working experience in programming and software development. The Innovation Associate will receive tailored and certified training in the methodology of social research adding to his/her transferrable skills. He/she will be working in the multinational and multidisciplinary environment of Rhodes Project SCE for one year, with competitive salary and actual prospects of career development within the SME.

Keywords: time tracking,global timesheets,artificial inteligence,machine learning,classification algorithms