Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Energy losses in nitride light-emitting diodes (NITRIDE-SRH)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Lithuania
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-05-01
End date: 2017-01-31
Duration (months): 21.0
Total project cost (EUR): 114432.15
EU funding (EUR): 114432.15
Participants: 1
Project status: CLOSED

Light-emitting diodes (LEDs) are the future of lighting for general-purpose and industrial applications because of their potentially superior efficiencies. Group-III nitrides are the principal materials used to manufacture blue and green LEDs. However, they are still rather inefficient, despite a lot of research efforts. Increasing the efficiency and reducing the cost of LEDs is currently the question of paramount importance. Nonradiative recombination at lattice defects is one of the main causes of reduced efficiencies. Direct experiments to determine the cause of nonradiative recombination are nearly impossible. This clearly calls for accurate theoretical modelling of nonradiative recombination in group-III nitride devices. A first-principles model will not only yield new knowledge about energy losses in nitride LEDs, but will also provide new insights into ways to improve device efficiencies. This is the main goal of the current Marie Skłodowska-Curie project. The researcher, dr. Audrius Alkauskas, will be returning to Europe after 3.5 years in the USA. He will be employed in the Centre for Physical Sciences and Technology (FTMC), under the supervision of prof. Gintaras Valušis. During the project the researcher will become an independent group leader, and grow as a specialist in semiconductor physics via a close collaboration with his colleagues in Lithuania and abroad.

Keywords: nitrides,first principles methods,nonradiative transitions,energy
How the human brain combines the certainty of prior expectations and the clarity of sensory input during speech perception (EXPECTBRAIN)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Germany
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-01-01
End date: 2019-11-17
Duration (months): 24.0
Total project cost (EUR): 171460.8
EU funding (EUR): 171460.8
Participants: 1
Project status: CLOSED

A fundamental question in the study of human perception concerns how we combine new sensory information with prior knowledge. Different underlying neural mechanisms have been proposed for how perceptual priors are combined with sensory input depending on their respective certainty to generate a subjective experience. Predictive Coding models suggest that neuronal populations compare (bottom-up) input from the sensory organs against (top-down) predictions so that only the unexpected part of the input is processed. Alternative models (e.g., Sharpening) propose that perceptual representations of the expected sensory input are enhanced while unexpected sensory input is suppressed. The objective of this proposal is to close this controversial research gap by testing 1) how top-down and bottom-up influences on perception depend on their respective certainty, i.e., the confidence in prior predictions and the clarity of sensory evidence, and 2) whether and how this mechanism is related to inter-individual differences during perception. To achieve this I will test multiple neuroimaging techniques (fMRI and EEG) against computational simulations of the two models. I will use state-of-the-art brain-activity pattern analysis to decode brain responses to individual words during perception of degraded speech. The innovative approach of combined pattern-information analysis techniques will allow unprecedented access to decode how prior information changes the representation of sensory information. The results of this project will have important implications for several clinical areas, e.g., the treatment of hearing impairments and neuropsychiatric conditions that are accompanied by aberrant perceptual experiences such as autism or schizophrenia. By strengthening my portfolio of research skills, the proposed project represents the perfect lead-in phase to put me in the position to start my independent research group at the host organisation and ultimately obtain a permanent post.

Keywords: brain imaging,computational modeling,representational similarity analysis,speech perception,predictive coding
Smart Sensor System for Food Safety, Quality Control and Resource Efficiency in the Food Processing Industry (S3FOOD)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Innovation actions
Countries involved: Spain,Germany,Spain,Spain,Greece,Hungary,Belgium,Belgium,Hungary,Belgium,France,France,France,Netherlands,Denmark
Call: Cluster facilitated projects for new industrial value chains (H2020-INNOSUP-2018-01-two-stage, 2018)
Start date: 2019-05-01
End date: 2022-09-30
Duration (months): 41.0
Total project cost (EUR): 5046050.09
EU funding (EUR): 4998322.5
Participants: 17
Project status: CLOSED

Smart Sensor Systems for Food safety, quality control and resource efficiency in the food processing industry (S3FOOD) will facilitate the modernisation and digitalisation of the food processing industry. S3FOOD will stimulate the integration of IoT and related technologies via the implementation of smart sensor systems in the food production processes in order to improve quality control, resource efficiency and the follow-up of food safety in the food production process. S3FOOD brings together clusters with a background in food processing industry, IoT, ICT and sensor technology. It will strengthen current and develop new cross-sectoral industrial value chains within the food production and processing industries through a combination of direct and indirect innovation actions, as well as support and capacity building measures. S3FOOD sets up a network of living labs, organize cross-sectoral, cross-border matchmaking/business/investment events, demonstrations and study visits for SMEs across geographical borders, sectors and with different innovation actors. An innovation voucher scheme will support the realisation of high-TRL, large scale, demonstration and commercialisation projects across Europe. Besides the consortium network, associated clusters from the S3 platform on Smart Sensor Systems 4 agri-food and other networks will support the outreach to SMEs across the EU. More than 2000 SMEs will be reached. More than 200 SME will participate in matchmaking events. A turnover growth rate of 30% is targeted in the SMEs having participated in support cases one year after the end of the project, preserving / creating more than 1000 jobs after the end of the project and by 2025. S3FOOD will operate for 3 years and has a total budget of € 5.046.050, €3.993.000 of which will directly benefit SMEs (79%). € 2.875.000 of the budget is targeted to provide innovation vouchers, and catalyse large-scale demonstration with commercialisation projects with 62 beneficiaries.

Keywords: foodtechnology
The Prison Narratives of Assad's Syria: Voices, Texts, Publics (SYRASP)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Cultures and cultural production
Panel description: Literary studies, cultural studies, study of the arts, philosophy
Countries involved: Germany
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-04-01
End date: 2025-03-31
Duration (months): 60.0
Total project cost (EUR): 1175239.0
EU funding (EUR): 1175239.0
Participants: 1
Project status: SIGNED

SYRASP combines textual analysis of Syrian prison literature with interviews on narrative and memory among former political prisoners. Between the late 1970s and early 2000s, the Assad regime imprisoned thousands of opponents from the secular left and Muslim Brotherhood, as well as their family members and associates. Political prisoners were held indefinitely in large group cells, often exclusively with members of their parties. By addressing their prison narratives as a diverse set of oral and print practices, the study traces the distinctive political cultures that took shape in and around prisons under the Assad regime, which remains in power under Bashar al-Assad (2000-present).The study’s interdisciplinary method will yield the first corpus of written and oral prison narrative. The primary literature under study consists of memoirs, poetry, stories, and essays by former political prisoners, as well as social media posts, unpublished manuscripts, and blogs. The interview population comprises male and female former prisoners who were held in group cells in Syria, accused of affiliation with the left or the Muslim Brotherhood, for a minimum of 1 year. Oral practices under study include formal techniques (e.g., recitation of poetry, scripture, folklore), memorisation of information on the cell population, and accounts of prison events. Interviews will use oral history methods. By treating prison narrative as a multi-modal system comprising print, orality, and sound, SYRASP traces networks of expression and contention that emerge from prisons, connecting lives on the inside to dissension and depictions of prison in Syrian letters. It uses the lens of publics to describe the forms of collective memory and belonging that Syrian prisoners created under harrowing conditions. It thus offers an actor-centred account of prisons at the centre, not the margins, of Syrian political culture.

Keywords: syrian literature,prison literature,oral narrative,oral history,publics,poetry,memorisation
Arrival infrastructures as sites of integration for recent newcomers (ReROOT)

Framework: Horizon 2020 — Societal Challenges
Programme: Europe in a changing world - inclusive, innovative and reflective societies
Theme: Inclusive societies
Action type: Research and Innovation actions
Countries involved: Germany,Hungary,Türkiye,Belgium,Greece,Sweden,Belgium,Belgium,France,Netherlands,United Kingdom
Call: Inclusive and innovative practices for the integration of recently arrived migrants in local communities (H2020-SC6-MIGRATION-2020, 2020)
Start date: 2021-04-01
End date: 2025-07-31
Duration (months): 52.0
Total project cost (EUR): 3016421.25
EU funding (EUR): 3016421.25
Participants: 13
Project status: SIGNED

Europe has been built and continues to be rebuilt at the convergence of innumerable migration trajectories. In the long run, the traces of migration processes are often effaced and sedimented into ‘native’ society. But many communities, civil society actors, public authorities, small businesses, religious institutions, leisure organisations, etc. have records and living memories of these migration processes, or indeed, are actively engaged in forging the integration of relatively newly arrived migrants. These actors, we submit, produce and co-constitute living ‘arrival infrastructures’ throughout urban, suburban and rural communities in nine different pilot sites in Turkey, Greece, Hungary, France, Germany, Belgium, the Netherlands, and the UK. Beyond the assumption that scaffolding and channelling of arrival and settlement processes comes through formal channels, agencies and programmes, ReROOT brings into view a wider constellation of actors, most notably previous generations of migrants who, together with ‘natives’ are co-creators of shops as information hubs, religious sites (churches or mosques), local labour offices, language classes, hairdressers, leisure clubs etc. ReROOT investigates the interactions, the transfers of knowledge and resources between first-comers and late-comers, the sedimented practices, organisations and provisions (whether private or public), as well as the transformations of all these through the recent, post-2015 arrival processes. ReROOT is dedicated to analyse, diagnose and learn lessons from past and recent transformations of arrival and integration processes, with the explicit goal of fostering sustainable, evidence-based integration practices, policies and public imaginaries. ReROOT is dedicated to unpack – with the help of migrants and a wide range of stakeholders – the nexus of migratory mobility and societal transformation in order to further inclusive and redistributive integration processes. Most importantly, ReROOT situates its impact in the transfer of knowledge, methods and analytical tools and reflexive methods to civil society and public service stakeholders. To that end, ReROOT develops and tests mapping toolkits and platform prototypes for policy makers and civil society – for them to continue the work ReROOT can only begin to do.

Keywords: arrival processes,belonging,social participation
A fully automated deep learning-based software for fast, robust and accurate detection and segmentation of tumours and metastasis (AUTO.DISTINCT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Prevention, Diagnosis and Treatment of Human Diseases
Panel description: Medical technologies and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions, pharmacology, preventative medicine, epidemiology and public health, digital medicine
Countries involved: Netherlands
Call: Call for proposals for ERC Proof of Concept Grant (ERC-2020-PoC, 2020)
Start date: 2020-10-01
End date: 2022-03-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

The inaccuracy and inconsistency of state-of-the-art tumour volume detection and segmentation has an adverse influence on patient outcomes. Accurately determining the exact location and volume of tumours is a prerequisite for the detection, segmentation, characterisation and therapy response monitoring for any type of cancer. Today, tumour segmentation is performed manually or semi-automatically in a laborious and time-consuming process that exhibits low accuracy and inconsistency. This compromises quality of care by limiting the certainty of lesion detection on medical images, hindering the effectivity of radiotherapy and restricting the accuracy of treatment response monitoring. In this ERC PoC project, we introduce fully automated software for fast, accurate, observer independent and reproducible detection and volumetric segmentation of (lung) tumours and metastases on CT images. Through a unique three-step approach, our software demonstrates superior speed, accuracy and robustness of tumour segmentation over both the state-of-the-art as well as published competing solutions for automated tumour segmentation. Hence, our software has the potential to drastically reduce the adverse impact that inaccurate tumour detection and segmentation currently has on (lung) cancer patient outcomes by: improving the detection of lesions on CT images, increasing the accuracy of radiotherapy treatment to reduce the occurrence of geometric misses, and advance the evaluation of tumour response to treatments through volumetric treatment monitoring. In AUTO.DISTINCT, we will provide technical and commercial proof-of-concept for our novel software. We will solve the remaining technical challenges and develop a user-friendly prototype that can be validated with end users. Moreover, we will develop a business strategy that incorporates all technical, commercial, IPR and regulatory aspects of our invention to ensure successful commercialisation.

Keywords: tumour detection,tumour segmentation,lung cancer,nsclc,hypoxia,radiology,radiotherapy,medical oncology,deep learning
Development and commercialization of kit for quantitative interrogation of a key RNA modification (M6AQuantKit)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Integrative Biology: from Genes and Genomes to Systems
Panel description: Genetics, epigenetics, genomics and other ‘omics studies, bioinformatics, systems biology, genetic diseases, gene editing, innovative methods and modelling, ‘omics for personalised medicine
Countries involved: Israel
Call: ERC Proof of Concept Grant (ERC-2019-PoC, 2019)
Start date: 2020-02-01
End date: 2021-07-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

N6-Methyladenosine (m6A) plays fundamental roles in regulation of metabolism, stem cell self-renewal, and metastasis. Consistently its dysregulation is implicated in a variety of human cancers including leukemia, glioblastoma and hepatocellular carcinoma. Consequently, the potential of m6A both as a novel cancer diagnostic and as a drug target has raised immense interest in scientific community and industry. For unravelling m6A functions, for the development of therapeutics and for prioritizing diseases and disease states most likely to benefit from therapeutic targeting of the methylation complex, it is thus of crucial importance to be able to measure the levels at which m6A is present. In our ERC project we addressed this challenge and developed MAZTER-seq, a methodology for quantifying m6A levels relying on a methylation-sensitive ribonuclease (RNase), representing the first systematic approach for quantitative interrogating of m6A levels. The goal of the project is to advance our approach as commercializable kit for quantitative profiling of m6A. In the PoC, we will develop multiplexed protocol of MAZTER-seq that allows the simultaneous processing and interrogation of multiple samples from low amounts of sample material. The kit, coupled with streamlined data analysis tool, addresses a major market need and exhibits significant added value for academic labs and the biotech & pharma industries targeting the methylation machinery, e.g. for creating novel RNA based therapeutics. Our readout from low-input material makes m6A monitoring amenable to patient samples, representing an unmet challenge across all our target market. Thus, our goal is to create a startup which harnesses the vast market potential. In the PoC, the commercialization considerations are advanced through actions such as, seeking market feedback, strengthening the IP position, defining the business strategy and planning business execution.

Keywords: rna modification,regulation of gene expression,rna based therapeutics and diagnostics,commercialization
Democracy Support Practice After the Third Wave: Adapting to Change? (DemSupPra)

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: Italy,United States
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2023-01-15
End date: 2026-06-16
Duration (months): 36.0
Total project cost (EUR): 269002.56
EU funding (EUR): 269002.56
Participants: 2
Project status: SIGNED

Democracy Support Practice After the Third Wave: Adapting to Change? (DemSupPra) aims to assess the significance and impact of three recent developments on the practices of international election observation and assistance: (1) rapid technological change (new voting technologies and communication revolution); (2) ‘social learning’ by autocrats, which made assaults against democratic institutions including elections less visible (‘fake compliance’); and (3) the use of the ballot box to ‘backslide’ or advance illiberal democracy (‘majoritarianism’). It asks how have these elements affected the two democracy support practices; and how have democracy supporters adapted to these developments? In doing so, the project also sets out to answers the policy relevant question, whether election observation and assistance are still fit for purpose. It seeks to suggest ways in which the effectiveness and credibility of the two practices may be strengthened, especially at a time when democracy and democratic institutions, including elections, are facing a fresh wave of contestation. The project’s objectives are to: (1) contribute to the conceptual, theoretical and methodological innovation in studies of democracy support, in particular election observation and assistance; (2) explain the impact of the three ‘crises of democracy’ developments on the two practices; (3) improve cross-fertilisation between policy practice and academic research. These objectives will be achieved through a mixed-methods approach that combines: mapping of election observation and assistance as practices and a quantitative assessment of their adaptation to change (WP1); with qualitative comparative case study design to investigate the impact of the ‘crisis of democracy’ developments (WP2); enriched by dissemination, communication and regular policy impact and public outreach endeavours (WP3); project and career management (WP4) teaching/training (WP5) and a secondment practice stage (S).

Keywords: election observation and assistance,democracy support,crises of democracy,technological change,fake norm compliance,democratic backsliding,illiberal democracy