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1,438 Projects, page 1 of 144

  • European Commission
  • 2020
  • 2022

10
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  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 898170
    Overall Budget: 224,934 EURFunder Contribution: 224,934 EUR
    Partners: University of Birmingham

    Abstract The Blood Brain Barrier (BBB) protects the brain from unwanted chemicals and provides a precisely regulated microenvironment to function normally. However, this defense barrier presents a challenge in shuttling therapeutic cargoes into the brain for the treatment of brain tumours and neurodegenerative diseases. To date, the known methods for BBB penetration poses inherent limitations which are often dangerous to the patients including the microbubble mediated ultrasound (US) driven BBB penetration. Herein we propose an innovative strategy to cross the BBB by introducing PiezoMagnetic Carbon Nanoneedles (PMCNNs) and evaluate its potential as an ideal brain drug delivery system (DDS). PMCNNs are made of functionalised carbon nanotubes (ƒ-CNT) decorated with PiezoMagnetic Nanoparticles. Due to the intrinsic piezoelectric property of PMCNNs, they convert short wave ultrasound (US) into electric pulses to electrically permeate the BBB noninvasively which is not possible by any of the known techniques so far. The main objectives of PiezoMagBBB are 1) to electrically permeate an in vitro BBB model with PMCNNs through nano-electroporation under short wave US and 2) to assess the efficacy of PMCNNs to deliver anticancer therapeutics in 3D tumour spheroids and brain tumour organoids. Thus PiezoMagBBB will design novel PMCNNs; assess their cytotoxicity in different brain cells; evaluate their BBB modulation under US and cellular uptake in BBB models; investigate their potential as a DDS for anticancer drugs in “in vivo tumour mimicking” glioblastoma spheroids and brain-tumour organoids. The fellow brings her extensive expertise in smart DDS design to the host lab, which in turn will offer world-class biological and nanotoxicological facilities and nanomedicine expertise. PiezoMagBBB also offers an industry secondment for high-throughput development of brain tumour organoids and a collaboration with an oncology consultant to enable validation of the model.

  • Open Access mandate for Publications
    Funder: EC Project Code: 846502
    Overall Budget: 207,312 EURFunder Contribution: 207,312 EUR
    Partners: UCPH

    The current obesity pandemic is a major threat to public health systems worldwide. The majority of obesity-related health care costs are due to cardiometabolic impairments such as insulin resistance, dyslipidemia, and hypertension, which increase the risk of type 2 diabetes and cardiovascular disease. However, many obese individuals seem resistant to cardiometabolic complications, the “metabolically healthy obese (MHO)”, while some normal weight individuals suffer from comorbidities similar to the obese. Genetic mechanisms may partly explain this paradox. Recent genome-wide studies have identified multiple genetic loci associated with increased overall body fat and subcutaneous fat deposition but lower cardiometabolic risk. Vice versa, the fat-decreasing alleles at these loci are associated with higher cardiometabolic risk. Some lifestyle factors, such as higher physical activity and smoking, are associated with lower body fat but show directionally opposite effects on cardiometabolic risk. At present, it remains unclear whether genetic predisposition to higher subcutaneous fat storage or healthy lifestyle behaviors may uncouple long-term weight gain from cardiometabolic risk during adulthood. Thus, the primary aim of the present project is to examine whether genetic and lifestyle factors abolish the impact of long-term weight gain on cardiometabolic risk by meta-analyses of five prospective cohorts with repeated measures of body weight and cardiometabolic traits. I will also examine whether these factors predict a MHO status in middle-age and the maintenance of such status over time. My results will provide new biological insights and may enable targeted lifestyle interventions against obesity-related cardiometabolic impairments. Moreover, the project will greatly advance my career by allowing me to learn highly valuable research skills in the area of genetic epidemiology, complementing my previous expertise in the field of cardiovascular epidemiology.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 893181
    Overall Budget: 162,806 EURFunder Contribution: 162,806 EUR
    Partners: LMU MUENCHEN

    The question of how an isolated quantum mechanical system thermalizes is not only significant in condensed matter physics, but it also invokes the intriguing problem of the apparent loss of information in a complex system as it thermalizes. A curious case is when a complex system fails to thermalize altogether -- a phenomenon known as many-body localization (MBL). Here, we propose to use interacting ultracold fermions in a lattice to experimentally study the distinctive properties of MBL using a novel set of observables. Among the questions in MBL debated intensely today are those concerning the existence of a many-body mobility edge, many-body intermediate phase and localization in higher dimensional lattice systems. Moreover, the striking relation between non-ergodicity and Hilbert space fragmentation is also not fully understood. In this view, our research objectives include: [1.] Stark many-body localization and Hilbert space fragmentation. We plan to study MBL in a tilted lattice, i.e., a Stark Hamiltonian and study non-ergodicity resulting from Hilbert space fragmentation. [2.] Bipartite fluctuations in an MBL system of >100 lattice sites: We propose to characterize the localization properties using bipartite fluctuations which is a proxy for the Entanglement entropy of a 1D lattice. [3.] Approximate theories for fermionic MBL systems: Due to the exponential Hilbert space dimension of an interacting many-body system, studying their properties numerically is also exponentially hard. We plan to use a quantum simulator with >100 lattice sites develop efficient approximate theories to describe these systems. The aforementioned projects are easily accessible to the current experimental capability and they will enhance our general understanding of MBL physics. Moreover, they also include a step towards developing ultracold atoms in a lattice into a quantum simulator, capable of solving hard problems.

  • Open Access mandate for Publications
    Funder: EC Project Code: 101016065
    Overall Budget: 7,911,320 EURFunder Contribution: 7,203,360 EUR
    Partners: VSI CIVITTA FOUNDATION, SERMAS, UPM, KI, BOSONIT SOCIEDAD LIMITADA, AUSTRALO INTERINNOV MARKETING LAB SL, EIGHT BELLS LTD, HUMANITAS MIRASOLE SPA, NETCOMPANY-INTRASOFT SA, F6S IE

    COVID-X will bridge the collaboration divide between eHealth solution providers -with emphasis on lean startups and small and medium-sized enterprises (SMEs)-, and the healthcare professional system to fight COVID-19. The purpose is to boost an end-to-end agile validation programme of cutting-edge technology in three real-world clinical scenarios, located in hotspots of the pandemic: Italy, Spain and Sweden. The project will fast-track value streams between the two poles under consideration: 1) attract, invest and empower a community of European eHealth SMEs –the beneficiaries of an acceleration program, selected by open calls- that will provide market-ready fast, cost-effective and easily deployable sampling, screening, diagnostic and prognostic systems and/or data-driven services and tools, already certified with -or close to receive- the CE marking (type 1 of the call); 2) actively involve some of the most relevant hospitals of Europe that have the resources, critical mass and ambition to scale-up their capabilities in the COVID-19 response; thanks to the support of an innovative data sandbox, released as an in-house asset of COVID-X, to facilitate access easily, uniformly and securely to various health data sources, and providing data services including Artificial Intelligence (AI)-based decision support systems, data security, visual analytics and intuitive dashboards capabilities. The project will invest dedicated efforts to enforce data privacy and security, ethical compliance and user acceptance. Besides a solid consortium to access world class startups/SMEs, deliver highly valuable technological & business services, provide an innovative data Sandbox with AI capabilities for COVID related services and access 3 piloting sites, COVID-X targets to attract +155 applications and select 31 to undertake through the COVID-X Programme, investing a total of €4.0mil in high impact solution providers.

  • Open Access mandate for Publications
    Funder: EC Project Code: 960667
    Overall Budget: 3,571,380 EURFunder Contribution: 2,499,960 EUR
    Partners: Provizio

    Provizio is radically transforming vehicle safety with our proprietary Accident Prevention Technology (APT) platform. Human error is the fault in 90% of car accidents. Over 1.35 million people are killed every year on the road (equivalent to 20 airplane crashes every single day) + 50 million injuries [World Health Organisation] = a cost USD $24 trillion (2%+ of worldwide GDP) [International Road Assessment Programme, iRAP] . More than $80 billion has been invested in ADAS over the last 5 years [Brookings Institute]…with zero impact on road deaths. Provizio was founded by a team of automotive and aerospace industry veterans with a mission to use advanced technology to reduce the devastation caused by road accidents. Our skill sets include entrepreneurship, scaling start-ups to exit, VC fund raising, building strong defensible IP portfolios as well as an enviable track record in developing the most advanced technology in automotive radar. This proposal outlines the further development of the APT Platform. APT combines proprietary vision sensors and machine learning to see further, wider and through obstacles, detecting danger in all-weather conditions and applying predictive analytics in real time to augment driver behaviour…and prevent accidents.

  • Open Access mandate for Publications
    Funder: EC Project Code: 899539
    Funder Contribution: 150,000 EUR
    Partners: University of Bordeaux

    Patients at risk of ventricular tachycardia (VT), the primary cause of sudden cardiac death, commonly undergo catheter ablation to cauterize the areas within myocardial scars responsible for arrythmias. However, the initial phase of the intervention devoted to identifying the ablation targets currently involves the intra-cardiac insertion of a mapping catheter characterized for being invasive, often inaccurate, and time-consuming. Pre-operative implementation of 3D cardiac imaging approaches to provide detailed structural information on ablation targets could overcome the shortcomings of standard catheter-based mapping. Still, state-of-the-art techniques have not lived up to their potential so far. During his ERC Starting Grant ECSTATIC (2017-2022), Prof. Hubert Cochet at University of Bordeaux developed a novel 3D image-processing technology (MAP-IN-HEART) which would allow cardiologists to locate VT ablation targets and guide ablation procedures in a non-invasive, highly precise and rapid manner using widely available cardiac CT images, without the need for a mapping catheter. In this ERC PoC project, we will investigate the technical feasibility of the innovative MAP-IN-HEART approach by assessing its efficiency and safety in a limited clinical study, and performing a cost-efficiency analysis. Moreover, we will ensure Freedom-To-Operate and explore all the potential paths for commercialization to finally develop a viable business strategy based on the technological aspects, the market needs and trends. Lastly, during this project we will gain technical and commercial proof-of-concept, providing the necessary information for potential commercialisation routes.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 892528
    Overall Budget: 183,473 EURFunder Contribution: 183,473 EUR
    Partners: Ca Foscari University of Venice

    This project will explore how educational culture from the Venetian Republic and Rome exported scientific knowledge to Britain in the 17th century. It has recently been discovered that an unpublished manuscript commentary on natural philosophy, astronomy, and mathematics written by the largely unknown writer and academic Adam King was the foundational text for instruction in those subjects from the early to mid 17th century at what would become the centre of Britain's Enlightenment culture, the University of Edinburgh. The text betrays an intimate familiarity with the ideas of key individuals (Patrizio, Telesio, Zabarella, Mirandola) and the formal teaching approaches of scholars (Galileo and Clavius) who operated within the Venetian Republic and the Collegio Romano. The project will present a detailed intellectual study that will trace the genealogy of the mechanical observational astronomy, Platonic and Aristotelian philosophy, and proto-empirical scientific methods contained in the Edinburgh manuscript (and the student dictates and Theses spread over 50 years that quote it verbatim) back to their Italian sources. It will offer a comprehensive textual comparison of the use educationalists in Edinburgh, Padua, and Rome made of Cristoph Clavius' educational texts as a hypertextual entry point for the new sciences in the academy in the wake of the collapse of Aristotelian cosmology. In addition to the formal text-based case study and philosophical survey, the project will provide a biographical (of key players) account that highlights how this process of knowledge exchange was enabled by the concerted actions of a network of scholars from across Europe.

  • Open Access mandate for Publications
    Funder: EC Project Code: 957008
    Funder Contribution: 102,225 EUR
    Partners: G2O ROBOTICS LTD FOR SERVICES

    The envisaged innovation idea of the H2O robotics is the full Internet of Underwater Things (IoUT) system created by lightweight, low-cost acoustic devices that link underwater network with terrestrial networks. IoUT system would provide positioning of underwater agents (e.g. sensors, vehicles, divers) and simultaneous communication between users on land and the underwater agents/things. Turning this innovative idea into an innovation project we will gradually expand our product portfolio with a new product, IoUT product, as well as expand the application portfolio of our existing products. Development of advanced technologies represents only one segment in a puzzle of turning innovation idea into commercially successful product. Insufficient in-house capacities in innovation management and business development and lack of appropriate candidates with these skills on the national labour market represent the problem and the barrier that this project will help us to overcome. Integration of the Innovation Associate into this venture will reinforce capacity of the team, multiply effect of the effort and help releasing full societal and commercial potential of the innovation idea. This project will be beneficial for both, Innovation Associate and the company. A solid scientific PhD-level background of the Associate will be deepened in the field related to innovation, his/her business-related skills will be developed and strengthen and a significant level of independence in work will be established. As a result, career stage of the Associate will be elevated to R3. H2O robotics will get an opportunity to launch new innovative products and/or services that will distinguish the SME from the competitors on the global market and get an employee (Innovation Associate) with capacities difficult to find and attract on the national labour market.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 897873
    Overall Budget: 147,815 EURFunder Contribution: 147,815 EUR
    Partners: NOVA

    Deductive software verification, a subject within the broader field of formal methods, proposes a very ambitious path: to turn the correctness of a computer program into a mathematical statement, and then prove it. This project aims to develop a deductive verification framework, with a clear focus on proof automation, that directly tackles the verification of OCaml-written programs. OCaml seems to be particularly good target for verification. On one hand, it is the language of choice for the implementation of sensible software such as proof assistants, automated solvers, and compilers. On the other hand, OCaml is a multi-paradigm language, supporting both the functional and imperative paradigm, one can write clean, concise, type-safe, and efficient code. Yet, a verification tool that can handle hand-written code and is mostly automated does not currently exist. OCaml programmers must chose between proof automation, with the price of learning and programming in a verification-aware language, and then perform code extraction, or tools that require manual proof assistance. The Cameleer project aims to remedy this situation by providing the tools and principles for the verification of OCaml programs. The main outcome of this project is a powerful, usable, and mostly automated verification framework for the OCaml-written code. This will be a major step towards making verification more accessible to OCaml programmers, even in case they are not verification experts. The Cameleer framework will feature a translation of OCaml programs annotated with specifications written in GOSPEL, a recently proposed specification language, to different intermediate verification languages, namely WhyML, Viper, and Coq. This coexistence of multiple intermediate verification infrastructures allows the devised framework to target the verification of a large subset of OCaml programs, while combining the strengths of each individual intermediate language to obtain better verification results.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 894799
    Overall Budget: 159,653 EURFunder Contribution: 159,653 EUR
    Partners: Universität Innsbruck

    Quantifying cyber risk is an important step in assigning resources to prevention. Yet data limitations mean that current estimates ignore certain incidents (e.g ransomware), rarely provide the financial cost, and cannot describe how risk varies based on the firm’s revenue or industry. Surprisingly insurers sell cyber insurance for the ignored incident types and vary the price based on firm-specific characteristics. Extracting insurers’ cyber loss models could help firms manage risk, regardless of whether they purchase insurance. The proposed action (QCYRISK) uses an iterative model fitting approach to infer loss distributions from insurance prices. The first research question develops the conceptual foundations by building an economic argument about how much information can be extracted from insurance markets. QCYRISK's second question seeks to infer full cyber loss distributions, including how they vary based on firm-specific characteristics. The final research question adopts an adversarial machine learning approach to probe the validity of the inferences, using both synthetic distributions and real cyber crime data. In terms of results and dissemination, QCYRISK will provide a set of loss distributions for multiple cyber incident types adjusted based on the firm’s revenue and industry. These will be made available as a spreadsheet for real-world risk managers. We will also run a continuing education seminar for insurance professionals to raise awareness about the method. The developed method represents a new computational insurance technique that could be applied to extract information from a global total of €4.7 trillion insurance premiums.

search
1,438 Projects, page 1 of 144
  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 898170
    Overall Budget: 224,934 EURFunder Contribution: 224,934 EUR
    Partners: University of Birmingham

    Abstract The Blood Brain Barrier (BBB) protects the brain from unwanted chemicals and provides a precisely regulated microenvironment to function normally. However, this defense barrier presents a challenge in shuttling therapeutic cargoes into the brain for the treatment of brain tumours and neurodegenerative diseases. To date, the known methods for BBB penetration poses inherent limitations which are often dangerous to the patients including the microbubble mediated ultrasound (US) driven BBB penetration. Herein we propose an innovative strategy to cross the BBB by introducing PiezoMagnetic Carbon Nanoneedles (PMCNNs) and evaluate its potential as an ideal brain drug delivery system (DDS). PMCNNs are made of functionalised carbon nanotubes (ƒ-CNT) decorated with PiezoMagnetic Nanoparticles. Due to the intrinsic piezoelectric property of PMCNNs, they convert short wave ultrasound (US) into electric pulses to electrically permeate the BBB noninvasively which is not possible by any of the known techniques so far. The main objectives of PiezoMagBBB are 1) to electrically permeate an in vitro BBB model with PMCNNs through nano-electroporation under short wave US and 2) to assess the efficacy of PMCNNs to deliver anticancer therapeutics in 3D tumour spheroids and brain tumour organoids. Thus PiezoMagBBB will design novel PMCNNs; assess their cytotoxicity in different brain cells; evaluate their BBB modulation under US and cellular uptake in BBB models; investigate their potential as a DDS for anticancer drugs in “in vivo tumour mimicking” glioblastoma spheroids and brain-tumour organoids. The fellow brings her extensive expertise in smart DDS design to the host lab, which in turn will offer world-class biological and nanotoxicological facilities and nanomedicine expertise. PiezoMagBBB also offers an industry secondment for high-throughput development of brain tumour organoids and a collaboration with an oncology consultant to enable validation of the model.

  • Open Access mandate for Publications
    Funder: EC Project Code: 846502
    Overall Budget: 207,312 EURFunder Contribution: 207,312 EUR
    Partners: UCPH

    The current obesity pandemic is a major threat to public health systems worldwide. The majority of obesity-related health care costs are due to cardiometabolic impairments such as insulin resistance, dyslipidemia, and hypertension, which increase the risk of type 2 diabetes and cardiovascular disease. However, many obese individuals seem resistant to cardiometabolic complications, the “metabolically healthy obese (MHO)”, while some normal weight individuals suffer from comorbidities similar to the obese. Genetic mechanisms may partly explain this paradox. Recent genome-wide studies have identified multiple genetic loci associated with increased overall body fat and subcutaneous fat deposition but lower cardiometabolic risk. Vice versa, the fat-decreasing alleles at these loci are associated with higher cardiometabolic risk. Some lifestyle factors, such as higher physical activity and smoking, are associated with lower body fat but show directionally opposite effects on cardiometabolic risk. At present, it remains unclear whether genetic predisposition to higher subcutaneous fat storage or healthy lifestyle behaviors may uncouple long-term weight gain from cardiometabolic risk during adulthood. Thus, the primary aim of the present project is to examine whether genetic and lifestyle factors abolish the impact of long-term weight gain on cardiometabolic risk by meta-analyses of five prospective cohorts with repeated measures of body weight and cardiometabolic traits. I will also examine whether these factors predict a MHO status in middle-age and the maintenance of such status over time. My results will provide new biological insights and may enable targeted lifestyle interventions against obesity-related cardiometabolic impairments. Moreover, the project will greatly advance my career by allowing me to learn highly valuable research skills in the area of genetic epidemiology, complementing my previous expertise in the field of cardiovascular epidemiology.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 893181
    Overall Budget: 162,806 EURFunder Contribution: 162,806 EUR
    Partners: LMU MUENCHEN

    The question of how an isolated quantum mechanical system thermalizes is not only significant in condensed matter physics, but it also invokes the intriguing problem of the apparent loss of information in a complex system as it thermalizes. A curious case is when a complex system fails to thermalize altogether -- a phenomenon known as many-body localization (MBL). Here, we propose to use interacting ultracold fermions in a lattice to experimentally study the distinctive properties of MBL using a novel set of observables. Among the questions in MBL debated intensely today are those concerning the existence of a many-body mobility edge, many-body intermediate phase and localization in higher dimensional lattice systems. Moreover, the striking relation between non-ergodicity and Hilbert space fragmentation is also not fully understood. In this view, our research objectives include: [1.] Stark many-body localization and Hilbert space fragmentation. We plan to study MBL in a tilted lattice, i.e., a Stark Hamiltonian and study non-ergodicity resulting from Hilbert space fragmentation. [2.] Bipartite fluctuations in an MBL system of >100 lattice sites: We propose to characterize the localization properties using bipartite fluctuations which is a proxy for the Entanglement entropy of a 1D lattice. [3.] Approximate theories for fermionic MBL systems: Due to the exponential Hilbert space dimension of an interacting many-body system, studying their properties numerically is also exponentially hard. We plan to use a quantum simulator with >100 lattice sites develop efficient approximate theories to describe these systems. The aforementioned projects are easily accessible to the current experimental capability and they will enhance our general understanding of MBL physics. Moreover, they also include a step towards developing ultracold atoms in a lattice into a quantum simulator, capable of solving hard problems.

  • Open Access mandate for Publications
    Funder: EC Project Code: 101016065
    Overall Budget: 7,911,320 EURFunder Contribution: 7,203,360 EUR
    Partners: VSI CIVITTA FOUNDATION, SERMAS, UPM, KI, BOSONIT SOCIEDAD LIMITADA, AUSTRALO INTERINNOV MARKETING LAB SL, EIGHT BELLS LTD, HUMANITAS MIRASOLE SPA, NETCOMPANY-INTRASOFT SA, F6S IE

    COVID-X will bridge the collaboration divide between eHealth solution providers -with emphasis on lean startups and small and medium-sized enterprises (SMEs)-, and the healthcare professional system to fight COVID-19. The purpose is to boost an end-to-end agile validation programme of cutting-edge technology in three real-world clinical scenarios, located in hotspots of the pandemic: Italy, Spain and Sweden. The project will fast-track value streams between the two poles under consideration: 1) attract, invest and empower a community of European eHealth SMEs –the beneficiaries of an acceleration program, selected by open calls- that will provide market-ready fast, cost-effective and easily deployable sampling, screening, diagnostic and prognostic systems and/or data-driven services and tools, already certified with -or close to receive- the CE marking (type 1 of the call); 2) actively involve some of the most relevant hospitals of Europe that have the resources, critical mass and ambition to scale-up their capabilities in the COVID-19 response; thanks to the support of an innovative data sandbox, released as an in-house asset of COVID-X, to facilitate access easily, uniformly and securely to various health data sources, and providing data services including Artificial Intelligence (AI)-based decision support systems, data security, visual analytics and intuitive dashboards capabilities. The project will invest dedicated efforts to enforce data privacy and security, ethical compliance and user acceptance. Besides a solid consortium to access world class startups/SMEs, deliver highly valuable technological & business services, provide an innovative data Sandbox with AI capabilities for COVID related services and access 3 piloting sites, COVID-X targets to attract +155 applications and select 31 to undertake through the COVID-X Programme, investing a total of €4.0mil in high impact solution providers.

  • Open Access mandate for Publications
    Funder: EC Project Code: 960667
    Overall Budget: 3,571,380 EURFunder Contribution: 2,499,960 EUR
    Partners: Provizio

    Provizio is radically transforming vehicle safety with our proprietary Accident Prevention Technology (APT) platform. Human error is the fault in 90% of car accidents. Over 1.35 million people are killed every year on the road (equivalent to 20 airplane crashes every single day) + 50 million injuries [World Health Organisation] = a cost USD $24 trillion (2%+ of worldwide GDP) [International Road Assessment Programme, iRAP] . More than $80 billion has been invested in ADAS over the last 5 years [Brookings Institute]…with zero impact on road deaths. Provizio was founded by a team of automotive and aerospace industry veterans with a mission to use advanced technology to reduce the devastation caused by road accidents. Our skill sets include entrepreneurship, scaling start-ups to exit, VC fund raising, building strong defensible IP portfolios as well as an enviable track record in developing the most advanced technology in automotive radar. This proposal outlines the further development of the APT Platform. APT combines proprietary vision sensors and machine learning to see further, wider and through obstacles, detecting danger in all-weather conditions and applying predictive analytics in real time to augment driver behaviour…and prevent accidents.

  • Open Access mandate for Publications
    Funder: EC Project Code: 899539
    Funder Contribution: 150,000 EUR
    Partners: University of Bordeaux

    Patients at risk of ventricular tachycardia (VT), the primary cause of sudden cardiac death, commonly undergo catheter ablation to cauterize the areas within myocardial scars responsible for arrythmias. However, the initial phase of the intervention devoted to identifying the ablation targets currently involves the intra-cardiac insertion of a mapping catheter characterized for being invasive, often inaccurate, and time-consuming. Pre-operative implementation of 3D cardiac imaging approaches to provide detailed structural information on ablation targets could overcome the shortcomings of standard catheter-based mapping. Still, state-of-the-art techniques have not lived up to their potential so far. During his ERC Starting Grant ECSTATIC (2017-2022), Prof. Hubert Cochet at University of Bordeaux developed a novel 3D image-processing technology (MAP-IN-HEART) which would allow cardiologists to locate VT ablation targets and guide ablation procedures in a non-invasive, highly precise and rapid manner using widely available cardiac CT images, without the need for a mapping catheter. In this ERC PoC project, we will investigate the technical feasibility of the innovative MAP-IN-HEART approach by assessing its efficiency and safety in a limited clinical study, and performing a cost-efficiency analysis. Moreover, we will ensure Freedom-To-Operate and explore all the potential paths for commercialization to finally develop a viable business strategy based on the technological aspects, the market needs and trends. Lastly, during this project we will gain technical and commercial proof-of-concept, providing the necessary information for potential commercialisation routes.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 892528
    Overall Budget: 183,473 EURFunder Contribution: 183,473 EUR
    Partners: Ca Foscari University of Venice

    This project will explore how educational culture from the Venetian Republic and Rome exported scientific knowledge to Britain in the 17th century. It has recently been discovered that an unpublished manuscript commentary on natural philosophy, astronomy, and mathematics written by the largely unknown writer and academic Adam King was the foundational text for instruction in those subjects from the early to mid 17th century at what would become the centre of Britain's Enlightenment culture, the University of Edinburgh. The text betrays an intimate familiarity with the ideas of key individuals (Patrizio, Telesio, Zabarella, Mirandola) and the formal teaching approaches of scholars (Galileo and Clavius) who operated within the Venetian Republic and the Collegio Romano. The project will present a detailed intellectual study that will trace the genealogy of the mechanical observational astronomy, Platonic and Aristotelian philosophy, and proto-empirical scientific methods contained in the Edinburgh manuscript (and the student dictates and Theses spread over 50 years that quote it verbatim) back to their Italian sources. It will offer a comprehensive textual comparison of the use educationalists in Edinburgh, Padua, and Rome made of Cristoph Clavius' educational texts as a hypertextual entry point for the new sciences in the academy in the wake of the collapse of Aristotelian cosmology. In addition to the formal text-based case study and philosophical survey, the project will provide a biographical (of key players) account that highlights how this process of knowledge exchange was enabled by the concerted actions of a network of scholars from across Europe.

  • Open Access mandate for Publications
    Funder: EC Project Code: 957008
    Funder Contribution: 102,225 EUR
    Partners: G2O ROBOTICS LTD FOR SERVICES

    The envisaged innovation idea of the H2O robotics is the full Internet of Underwater Things (IoUT) system created by lightweight, low-cost acoustic devices that link underwater network with terrestrial networks. IoUT system would provide positioning of underwater agents (e.g. sensors, vehicles, divers) and simultaneous communication between users on land and the underwater agents/things. Turning this innovative idea into an innovation project we will gradually expand our product portfolio with a new product, IoUT product, as well as expand the application portfolio of our existing products. Development of advanced technologies represents only one segment in a puzzle of turning innovation idea into commercially successful product. Insufficient in-house capacities in innovation management and business development and lack of appropriate candidates with these skills on the national labour market represent the problem and the barrier that this project will help us to overcome. Integration of the Innovation Associate into this venture will reinforce capacity of the team, multiply effect of the effort and help releasing full societal and commercial potential of the innovation idea. This project will be beneficial for both, Innovation Associate and the company. A solid scientific PhD-level background of the Associate will be deepened in the field related to innovation, his/her business-related skills will be developed and strengthen and a significant level of independence in work will be established. As a result, career stage of the Associate will be elevated to R3. H2O robotics will get an opportunity to launch new innovative products and/or services that will distinguish the SME from the competitors on the global market and get an employee (Innovation Associate) with capacities difficult to find and attract on the national labour market.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 897873
    Overall Budget: 147,815 EURFunder Contribution: 147,815 EUR
    Partners: NOVA

    Deductive software verification, a subject within the broader field of formal methods, proposes a very ambitious path: to turn the correctness of a computer program into a mathematical statement, and then prove it. This project aims to develop a deductive verification framework, with a clear focus on proof automation, that directly tackles the verification of OCaml-written programs. OCaml seems to be particularly good target for verification. On one hand, it is the language of choice for the implementation of sensible software such as proof assistants, automated solvers, and compilers. On the other hand, OCaml is a multi-paradigm language, supporting both the functional and imperative paradigm, one can write clean, concise, type-safe, and efficient code. Yet, a verification tool that can handle hand-written code and is mostly automated does not currently exist. OCaml programmers must chose between proof automation, with the price of learning and programming in a verification-aware language, and then perform code extraction, or tools that require manual proof assistance. The Cameleer project aims to remedy this situation by providing the tools and principles for the verification of OCaml programs. The main outcome of this project is a powerful, usable, and mostly automated verification framework for the OCaml-written code. This will be a major step towards making verification more accessible to OCaml programmers, even in case they are not verification experts. The Cameleer framework will feature a translation of OCaml programs annotated with specifications written in GOSPEL, a recently proposed specification language, to different intermediate verification languages, namely WhyML, Viper, and Coq. This coexistence of multiple intermediate verification infrastructures allows the devised framework to target the verification of a large subset of OCaml programs, while combining the strengths of each individual intermediate language to obtain better verification results.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 894799
    Overall Budget: 159,653 EURFunder Contribution: 159,653 EUR
    Partners: Universität Innsbruck

    Quantifying cyber risk is an important step in assigning resources to prevention. Yet data limitations mean that current estimates ignore certain incidents (e.g ransomware), rarely provide the financial cost, and cannot describe how risk varies based on the firm’s revenue or industry. Surprisingly insurers sell cyber insurance for the ignored incident types and vary the price based on firm-specific characteristics. Extracting insurers’ cyber loss models could help firms manage risk, regardless of whether they purchase insurance. The proposed action (QCYRISK) uses an iterative model fitting approach to infer loss distributions from insurance prices. The first research question develops the conceptual foundations by building an economic argument about how much information can be extracted from insurance markets. QCYRISK's second question seeks to infer full cyber loss distributions, including how they vary based on firm-specific characteristics. The final research question adopts an adversarial machine learning approach to probe the validity of the inferences, using both synthetic distributions and real cyber crime data. In terms of results and dissemination, QCYRISK will provide a set of loss distributions for multiple cyber incident types adjusted based on the firm’s revenue and industry. These will be made available as a spreadsheet for real-world risk managers. We will also run a continuing education seminar for insurance professionals to raise awareness about the method. The developed method represents a new computational insurance technique that could be applied to extract information from a global total of €4.7 trillion insurance premiums.

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