Ulm, Germany
Ulm, Germany

Ulm University is a public university in the city of Ulm, in the South German state of Baden-Württemberg. The university was founded in 1967 and focuses on natural science, medicine, engineering science, mathematics, economics and computer science. With 9,188 students , it is one of the newest public universities in Germany. Times Higher Education ranks it at no. 16 position among world's top 100 universities under the age of 50 years in 2014, thus making it the best young university in Germany. It ranks among the top five universities in Germany for Electrical Engineering and Computer Science. It also frequently ranks as one of the top schools in natural science in domestic rankings.In 2007, University of Ulm was appreciated by German Universities Excellence Initiative and altogether financially endowed for International Graduate School in Molecular Medicine. In 2012, University of Ulm has been selected for 27th position by Academic Ranking of World Universities according to ratio of Academic staff to students indicator. The campus of the university is located north of the city on a hill called Oberer Eselsberg, while the university hospital has additional sites across the city. Wikipedia.


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A sensor (1, 2, 3, 4, 5, 6, 7, 8) comprising a first diamond substrate (9) with at least one colour centre (15), the sensor (1, 2, 3, 4, 5, 6, 7, 8) further comprising a first piezomagnetic (10) or piezoelectric primary element (11), which primary element (10, 11) is arranged to interact with the colour centre(s) (15) of the first diamond substrate (9).


Grant
Agency: European Commission | Branch: H2020 | Program: SGA-RIA | Phase: FETFLAGSHIP | Award Amount: 89.00M | Year: 2016

This project is the second in the series of EC-financed parts of the Graphene Flagship. The Graphene Flagship is a 10 year research and innovation endeavour with a total project cost of 1,000,000,000 euros, funded jointly by the European Commission and member states and associated countries. The first part of the Flagship was a 30-month Collaborative Project, Coordination and Support Action (CP-CSA) under the 7th framework program (2013-2016), while this and the following parts are implemented as Core Projects under the Horizon 2020 framework. The mission of the Graphene Flagship is to take graphene and related layered materials from a state of raw potential to a point where they can revolutionise multiple industries. This will bring a new dimension to future technology a faster, thinner, stronger, flexible, and broadband revolution. Our program will put Europe firmly at the heart of the process, with a manifold return on the EU investment, both in terms of technological innovation and economic growth. To realise this vision, we have brought together a larger European consortium with about 150 partners in 23 countries. The partners represent academia, research institutes and industries, which work closely together in 15 technical work packages and five supporting work packages covering the entire value chain from materials to components and systems. As time progresses, the centre of gravity of the Flagship moves towards applications, which is reflected in the increasing importance of the higher - system - levels of the value chain. In this first core project the main focus is on components and initial system level tasks. The first core project is divided into 4 divisions, which in turn comprise 3 to 5 work packages on related topics. A fifth, external division acts as a link to the parts of the Flagship that are funded by the member states and associated countries, or by other funding sources. This creates a collaborative framework for the entire Flagship.


Grant
Agency: European Commission | Branch: H2020 | Program: ECSEL-RIA | Phase: ECSEL-01-2015 | Award Amount: 14.53M | Year: 2016

Current driver assistance systems are not all-weather capable. They offer comfort and safety in sound environmental conditions. However, in adverse weather conditions where the accident risks are highest they malfunction or even fail. Now that we are progressing towards automated cars and work machines, the requirements of fully reliable environment perception are only accentuated. The project is focusing on automated driving and its key enabling technology, environment perception. Consequently, projects main objective is to develop and validate an all-weather sensor suit for traffic services, driver assistance and automated driving. Extended driving environment perception capability with smart, reliable and cost-efficient sensing system is necessary to meet the targets of all future driver assistance system applications. These targets need to be met regardless of location, weather or time of the day. Only by means of reliable and robust sensing system upcoming automated driving will be possible. The new sensor suit is based on a smart integration of three different technologies: (i) Radio radar, 77 GHz-81 GHz, (MIMO Radar); (ii) Gated short wave infrared camera with pulsed laser illumination (SWIR camera)and (iii) Short-wave infrared LIDAR (SWIR Lidar). Such a full fusion approach has never been investigated before, so that the outcome will advance the state-of-the-art significantly and demonstrate the potential of all-weather environment perception. DENSE innovation lies in the provision of a brilliant restored enriched colour image from a degraded infrared image and consequently, this is followed by a variety of application fields for low cost solutions. An important aim is also to close the gap to US developments in the field and avoid their restrictions for selling components overseas for strategic reasons and strengthen the position of European industry in worldwide competition.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: SC1-PM-11-2016-2017 | Award Amount: 6.00M | Year: 2017

Current orthopaedic treatments permit spontaneous bone regeneration to unite and heal 90% bone injuries. Non-union associates pain and disability, often requiring biological enhancement. Regenerative medicine research suggests to the general public that alternative treatments based on advanced therapy medicinal products (ATMP) are already available. However, early clinical trials only explore its potential benefit. Underreported results and absence of early trial confirmation in adequately powered prospective randomized clinical trials (RCT) indicate that evidence is not available to transfer any technique into routine clinical application. This ORTHOUNION Project was developed from FP7-Project (REBORNE). Its results confirmed 92% bone healing rate (Gmez-Barrena et al, 2016 submitted manuscript) with an autologous ATMP of GMP expanded bone marrow derived human MSC in non-unions, where the reported bone healing rate after surgery with standard bone autograft is 74%. Any further development requires adequately powered prospective RCTs. This will be the main aim of ORTHOUNION: to assess clinically relevant efficacy of an autologous ATMP with GMP multicentric production in a well-designed, randomized, controlled, three-arm clinical trial under GCP, versus bone autograft, gold-standard in fracture non-unions. A non-inferiority analysis will evaluate if cell dose can be lowered. ATMP has been authorized by the National Competent Authorities of the participating countries in 3 previous trials (REBORNE) and will be monitored by ECRIN-ERIC to ensure quality and credibility of RCT results. Secondary aims include innovative strategies to increase manufacturing capacity and lower costs to pave translation into routine clinical treatments, biomaterial refinement to facilitate surgery, personalized medicine supportive instruments for patient selection and monitoring, and health economic evaluation. Results in this project may help define the future of bone regenerative medicine


Grant
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.

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