Dublin City University is a university situated between Glasnevin, Santry, Ballymun and Whitehall on the Northside of Dublin in Ireland. Created as the National Institute for Higher Education, Dublin in 1975, it enrolled its first students in 1980 and was elevated to university status in 1989 by statute. Wikipedia.
Dublin City University | Date: 2017-05-10
A microfluidic array supporting a lipid bilayer assembly on which membrane proteins can be assembled is described.
Dublin City University | Date: 2015-07-02
A microfluidic array supporting a lipid bilayer assembly on which membrane proteins can be assembled is described.
Agency: European Commission | Branch: H2020 | Program: IA | Phase: ICT-20-2015 | Award Amount: 6.43M | Year: 2016
Agency: European Commission | Branch: H2020 | Program: IA | Phase: WATER-1b-2015 | Award Amount: 9.80M | Year: 2016
The aim of the project is to implement and demonstrate at large scale the long-term technological and economic feasibility of an innovative, sustainable and efficient solution for the treatment of high salinity wastewater from the F&D industry. Conventional wastewater treatments have proven ineffective for this kind of wastewater, as the bacterial processes typically used for the elimination of organic matter and nutrients are inhibited under high salinity contents. Therefore, generally combinations of biological and physicochemical methods are used which greatly increase the costs of the treatment, making it unaffordable for SMEs, who voluntarily decide not to comply with EU directives and discharge without prior treatment, causing severe damage to the environment. The solution of SALTGAE to this issue consists in the implementation of innovative technologies for each step of the wastewater treatment that will promote energy and resource efficiency, and reduce costs. Amongst these, the use of halotolerant algae/bacteria consortiums in HRAPs for the elimination of organic matter and nutrients stands out for its high added value: not only will it provide an effective and ecological solution for wastewater treatment, but also it will represent an innovative way of producing algal biomass, that will subsequently be valorized into different by-products, reducing the economic and environmental impact of the treatment. Moreover, the project will also address cross-cutting barriers to innovation related to wastewater by developing a platform for the mobilization and networking of stakeholders from all the different sectors related to wastewater, and for the dissemination of results, enabling the development of a common roadmap for the alignment of legislation, regulation and pricing methodologies and promoting financial investment and paradigm shift in perception from wastewater treatment to resource valorisation.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: MG-3.6a-2015 | Award Amount: 6.23M | Year: 2016
Road accidents continue to be a major public safety concern. Human error is the main cause of accidents. Intelligent driver systems that can monitor the drivers state and behaviour show promise for our collective safety. VI-DAS will progress the design of next-gen 720 connected ADAS (scene analysis, driver status). Advances in sensors, data fusion, machine learning and user feedback provide the capability to better understand driver, vehicle and scene context, facilitating a significant step along the road towards truly semi-autonomous vehicles. On this path there is a need to design vehicle automation that can gracefully hand-over and back to the driver. VI-DAS advances in computer vision and machine learning will introduce non-invasive, vision-based sensing capabilities to vehicles and enable contextual driver behaviour modelling. The technologies will be based on inexpensive and ubiquitous sensors, primarily cameras. Predictions on outcomes in a scene will be created to determine the best reaction to feed to a personalised HMI component that proposes optimal behaviour for safety, efficiency and comfort. VI-DAS will employ a cloud platform to improve ADAS sensor and algorithm design and to store and analyse data at a large scale, thus enabling the exploitation of vehicle connectivity and cooperative systems. VI-DAS will address human error analysis by the study of real accidents in order to understand patterns and consequences as an input to the technologies. VI-DAS will also address legal, liability and emerging ethical aspects because with such technology comes new risks, and justifiable public concern. The insurance industry will be key in the adoption of next generation ADAS and Autonomous Vehicles and a stakeholder in reaching L3. VI-DAS is positioned ideally at the point in the automotive value chain where Europe is both dominant and in which value can be added. The project will contribute to reducing accidents, economic growth and continued innovation.
Agency: European Commission | Branch: H2020 | Program: MSCA-RISE | Phase: MSCA-RISE-2016 | Award Amount: 1.22M | Year: 2017
GETM3 Global Entrepreneurial Talent Management 3 - focuses on young talent as a key driver of future development, developed through co-operation of 3 stakeholders: employers (inc MNC & SMEs), universities and students/graduates. Despite a widely recognized importance of young talent (e.g. Europe 2020), its potential remains largely untapped. They are educated and entrepreneurial and yet experience instability in employment. At the same time, employers report skills mismatch and difficulties with attracting, managing and retaining young talent. To tackle this paradoxical situation, an innovative, multi-perspective approach is needed, reinforced by our 15 partner consortium; comprising of a transnational, inter-disciplinary, inter-generational, gender balanced and inter-sectorial research team. The main objective of GETM3 is to improve employability and future global talent management to support economic development by capitalizing on entrepreneurialism as a key characteristic of the young. To achieve this objective, the project is divided into six work packages. Three WPs focus on in-depth research of specific issues from each of the stakeholder perspectives. The Integration and Innovation WP, essential for impact, aims to integrate research outputs and develop GETM3 across dimensions: generations, genders, disciplines, countries, sectors and stakeholders. These are supported by a project management & administration WP and by the Researcher development, knowledge transfer & dissemination WP. In total, 292 mobility months are planned, 232 of those are for EU partners. Matched funding specially dedicated to H2020 will be claimed from the Korean Research Foundation. The overall design of the project builds impact through researcher mobility in two ways: researchers will gain first hand and in-depth insights on specific issues from various perspectives, and will develop their skills through networking and training incorporated into mobility with sandpit events.
Agency: European Commission | Branch: H2020 | Program: COFUND-EJP | Phase: EURATOM | Award Amount: 856.96M | Year: 2014
A Roadmap to the realization of fusion energy was adopted by the EFDA system at the end of 2012. The roadmap aims at achieving all the necessary know-how to start the construction of a demonstration power plant (DEMO) by 2030, in order to reach the goal of fusion electricity in the grid by 2050. The roadmap has been articulated in eight different Missions. The present proposal has the goal of implementing the activities described in the Roadmap during Horizon 2020 through a joint programme of the members of the EUROfusion Consortium. ITER is the key facility in the roadmap. Thus, ITER success remains the most important overarching objective of the programme and, in the present proposal the vast majority of resources in Horizon 2020 are devoted to ensure that ITER is built within scope, time and budget; its operation is properly prepared; and a new generation of scientists and engineers is properly educated (at undergraduate and PhD level) and trained (at postdoctoral level) for its exploitation. DEMO is the only step between ITER and a commercial fusion power plant. To achieve the goal of fusion electricity demonstration by 2050, DEMO construction has to begin in the early 2030s at the latest, to allow the start of operation in the early 2040s. DEMO cannot be defined and designed by research laboratories alone, but requires the full involvement of industry in all technological and systems aspects of the design. Specific provisions for the involvement of industry in the Consortium activities are envisaged.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: FCT-01-2015 | Award Amount: 11.99M | Year: 2016
ASGARD has a singular goal, contribute to Law Enforcement Agencies Technological Autonomy and effective use of technology. Technologies will be transferred to end users under an open source scheme focusing on Forensics, Intelligence and Foresight (Intelligence led prevention and anticipation). ASGARD will drive progress in the processing of seized data, availability of massive amounts of data and big data solutions in an ever more connected world. New areas of research will also be addressed. The consortium is configured with LEA end users and practitioners pulling from the Research and Development community who will push transfer of knowledge and innovation. A Community of LEA users is the end point of ASGARD with the technology as a focal point for cooperation (a restricted open source community). In addition to traditional Use Cases and trials, in keeping with open source concepts and continuous integration approaches, ASGARD will use Hackathons to demonstrate its results. Vendor lock-in is addressed whilst also recognising their role and existing investment by LEAs. The project will follow a cyclical approach for early results. Data Set, Data Analytics (multimodal/ multimedia), Data Mining and Visual Analytics are included in the work plan. Technologies will be built under the maxim of It works over Its the best. Rapid adoption/flexible deployment strategies are included. The project includes a licensing and IPR approach coherent with LEA realities and Ethical needs. ASGARD includes a comprehensive approach to Privacy, Ethics, Societal Impact respecting fundamental rights. ASGARD leverages existing trust relationship between LEAs and the research and development industry, and experiential knowledge in FCT research. ASGARD will allow its community of users leverage the benefits of agile methodologies, technology trends and open source approaches that are currently exploited by the general ICT sector and Organised Crime and Terrorist organisations.
Agency: European Commission | Branch: H2020 | Program: MSCA-RISE | Phase: MSCA-RISE-2016 | Award Amount: 900.00K | Year: 2017
The challenges facing society in urban wastewater management cannot be solved by any one sector alone. ALICE (AcceLerate Innovation in urban wastewater management for Climate changE) will accelerate innovation by bringing together and exchanging knowledge between the key players who can, together, address the future techno-economic, governance and societal challenges arising from climate change. It will boost international and interdisciplinary skills, as well as careers perspective of Experienced Researchers, Early Stage Researchers, and the workforce of industry, water utilities and public organizations. The results will 1) benefit water utilities, 2) support political and managerial decisions in wastewater, 3) benefit wastewater equipment manufacturers, identifying new market opportunities in the EU, 4) benefit EU citizens from the improved wastewater infrastructure, the environment and job creations. Higher precipitation and more frequent storms will require change in sewer water management. Moreover, higher risks of water scarcity and droughts require increased wastewater reuse, currently at 20% of its potential in the EU. These changes will lead to increased energy demand in a sector that is already a major contributor of carbon emissions. ALICE will promote effective solutions based on innovative technologies, green infrastructures, climate vulnerability assessments, governance and economic models, embracing stakeholders and citizens views to overcome barriers to the acceptance and uptake of new technologies. The excellence of the project lies in the joined-up thinking of different perspectives and disciplines. Academic and non-academic partners along the wastewater value-chain will exchange knowledge, develop training, research and innovation activities. ALICE will build lasting knowledge and cooperation networks and will provide the non-academic sector with practical solutions to respond in innovative ways to the challenges posed by climate change.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-06-2016 | Award Amount: 4.61M | Year: 2017
Large-scale computing systems are today built as distributed systems (for reasons of scale, heterogeneity, cost and energy efficiency) where components and services are distributed and accessed remotely through clients and devices. In some systems, in particular latency-sensitive or high availability systems, components are also placed closer to end-users (in, e.g., radio base stations and other systems on the edge of access networks) in order to increase reliability and reduce latency - a style of computing often referred to as edge or fog computing. However, while recent years have seen significant advances in system instrumentation as well as data centre energy efficiency and automation, computational resources and network capacity are often provisioned using best effort provisioning models and coarse-grained quality of service (QoS) mechanisms, even in state-of-the-art data centres. These limitations are seen as a major hindrance in the face of the coming evolution of(IoT and the networked society, and have even today manifested in, e.g., a limited cloud adoption of systems with high reliability requirements such as telecommunications infrastructure and emergency services systems. RECAP goes beyond the current state of the art and develop the next generation of cloud/edge/fog computing capacity provisioning via targeted research advances in cloud infrastructure optimization, simulation and automation. Building on advanced machine learning, optimization and simulation techniques. The overarching result of RECAP is the next generation of agile and optimized cloud computing systems. The outcomes of the project will pave the way for a radically novel concept in the provision of cloud services, where services are instantiated and provisioned close to the users that actually need them by self-configurable cloud computing systems.