Jacobs University Bremen is an international, private residential university in Bremen, Germany.Jacobs University is an English-speaking higher education institution and combines aspects from the American and German academic systems. Wikipedia.
Jacobs University Bremen | Date: 2016-12-28
The invention relates to a method for arranging an encrypted NFC connection. Two NFC devices (A, B) each exchange a signal of the same frequency having a random phase (A, B), this signal being registered at the other of the devices (B, A) as a reception signal with a frequency-specific and distance-dependent phase rotation (C), the phase of the devices own transmission signal being added to said reception signal in order to obtain a phase total ( A=A+B+C, B= A +B+C). The phase total produced in this manner is quantised in the signal space, in L of the same type levels, and the signal is coded in symbols represented by bit sequences. The suggested method does not require channel entropy and is secured from eavesdropping in a spatial section determined by the frequencies used.
Jacobs University Bremen | Date: 2017-05-24
The invention relates to a genetically modified yeast with improved glycerol catabolism. The problem addressed by the present invention is the improvement of the capability of yeast to utilize glycerol as a carbon source. The problem is solved by a genetically modified yeast cell of the genus Saccharomyces with improved glycerol catabolism, wherein the yeast cell is genetically modified in such a way that a) the breakdown of glycerol to dihydroxyacetone phosphate via the glycerol-3-phosphate pathway is blocked, b) a heterologous glycerol uptake facilitator protein is expressed, and c1) a heterologous glycerol dehydrogenase that catalyzes the oxidation of glycerol to dihdroxyacetone is expressed, or a heterologous glycerol dehydrogenase that catalyzes the oxidation of glycerol to dihdroxyacetone is over-expressed, or c2) at least one enzyme that is involved in the breakdown of glycerol to glyceraldehyde 3-phosphate via the glyceraldehyde pathway is over-expressed, or at least one enzyme that is involved in the breakdown of glycerol to glyceraldehyde 3-phosphate via the glyceraldehyde pathway is replaced by a heterologous enzyme with the same enzyme activity.
Jacobs University Bremen | Date: 2017-08-02
The invention relates to a method for antigen-specific immunostaining of T cells and to a staining kit for this purpose. The object of the present invention is to enable a simple and reliable antigen-specific detection of T cells. In order to solve the problem, the present invention provides a method for antigen-specific immunostaining of T cells, wherein a polyelectrolyte microcapsule having an antigen-presenting MHC class I molecule on the outside is contacted with a T cell bearing a T cell receptor under conditions that allow an interaction between the T cell receptor and the antigen-presenting MHC class I molecule so that a complex consisting of T cell, antigen-presenting MHC class I molecule and polyelectrolyte microcapsule can be formed. The invention further provides a staining kit for carrying out the method.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: INFRAIA-1-2014-2015 | Award Amount: 10.23M | Year: 2015
The Europlanet 2020 Research Infrastructure (EPN2020-RI) will address key scientific and technological challenges facing modern planetary science by providing open access to state-of-the-art research data, models and facilities across the European Research Area. Its Transnational Access activities will provide access to world-leading laboratory facilities that simulate conditions found on planetary bodies as well as specific analogue field sites for Mars, Europa and Titan. Its Virtual Access activities will make available the diverse datasets and visualisation tools needed for comparing and understanding planetary environments in the Solar System and beyond. By providing the underpinning facilities that European planetary scientists need to conduct their research, EPN2020-RI will create cooperation and effective synergies between its different components: space exploration, ground-based observations, laboratory and field experiments, numerical modelling, and technology. EPN2020-RI builds on the foundations of successful FP6 and FP7 Europlanet programmes that established the Europlanet brand and built structures that will be used in the Networking Activities of EPN2020-RI to coordinate the European planetary science communitys research. It will disseminate its results to a wide range of stakeholders including industry, policy makers and, crucially, both the wider public and the next generation of researchers and opinion formers, now in education. As an Advanced Infrastructure we place particular emphasis on widening the participation of previously under-represented research communities and stakeholders. We will include new countries and Inclusiveness Member States, via workshops, team meetings, and personnel exchanges, to broaden/widen/expand and improve the scientific and innovation impact of the infrastructure. EPN2020-RI will therefore build a truly pan-European community that shares common goals, facilities, personnel, data and IP across national boundaries
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: INFRADEV-4-2014-2015 | Award Amount: 14.84M | Year: 2015
The social and economic challenges of ageing populations and chronic disease can only be met by translation of biomedical discoveries to new, innovative and cost effective treatments. The ESFRI Biological and Medical Research Infrastructures (BMS RI) underpin every step in this process; effectively joining scientific capabilities and shared services will transform the understanding of biological mechanisms and accelerate its translation into medical care. Biological and medical research that addresses the grand challenges of health and ageing span a broad range of scientific disciplines and user communities. The BMS RIs play a central, facilitating role in this groundbreaking research: inter-disciplinary biomedical and translational research requires resources from multiple research infrastructures such as biobank samples, and resources from multiple research infrastructures such as biobank samples, imaging facilities, molecular screening centres or animal models. Through a user-led approach CORBEL will develop the tools, services and data management required by cutting-edge European research projects: collectively the BMS RIs will establish a sustained foundation of collaborative scientific services for biomedical research in Europe and embed the combined infrastructure capabilities into the scientific workflow of advanced users. Furthermore CORBEL will enable the BMS RIs to support users throughout the execution of a scientific project: from planning and grant applications through to the long-term sustainable management and exploitation of research data. By harmonising user access, unifying data management, creating common ethical and legal services, and offering joint innovation support CORBEL will establish and support a new model for biological and medical research in Europe. The BMS RI joint platform will visibly reduce redundancy and simplify project management and transform the ability of users to deliver advanced, cross-disciplinary research.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EINFRA-9-2015 | Award Amount: 7.64M | Year: 2015
OpenDreamKit will deliver a flexible toolkit enabling research groups to set up Virtual Research Environments, customised to meet the varied needs of research projects in pure mathematics and applications and supporting the full research life-cycle from exploration, through proof and publication, to archival and sharing of data and code. OpenDreamKit will be built out of a sustainable ecosystem of community-developed open software, databases, and services, including popular tools such as LinBox, MPIR, Sage(sagemath.org), GAP, PariGP, LMFDB, and Singular. We will extend the Jupyter Notebook environment to provide a flexible UI. By improving and unifying existing building blocks, OpenDreamKit will maximise both sustainability and impact, with beneficiaries extending to scientific computing, physics, chemistry, biology and more and including researchers, teachers, and industrial practitioners. We will define a novel component-based VRE architecture and the adapt existing mathematical software, databases, and UI components to work well within it on varied platforms. Interfaces to standard HPC and grid services will be built in. Our architecture will be informed by recent research into the sociology of mathematical collaboration, so as to properly support actual research practice. The ease of set up, adaptability and global impact will be demonstrated in a variety of demonstrator VREs. We will ourselves study the social challenges associated with large-scale open source code development and of publications based on executable documents, to ensure sustainability. OpenDreamKit will be conducted by a Europe-wide demand-steered collaboration, including leading mathematicians, computational researchers, and software developers long track record of delivering innovative open source software solutions for their respective communities. All produced code and tools will be open source.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-25-2015 | Award Amount: 4.18M | Year: 2016
We propose to fabricate a chip implementing a neuromorphic architecture that supports state-of-the-art machine learning algorithms and spike-based learning mechanisms. With respect to its physical architecture this chip will feature an ultra low power, scalable and highly configurable neural architecture that will deliver a gain of a factor 50x in power consumption on selected applications compared to conventional digital solutions; and a monolithically integrated 3D technology in Fully-Depleted Silicon on Insulator (FDSOI) at 28nm design rules with integrated Resistive Random Access Memory (RRAM) synaptic elements; We will complete this vision and develop complementary technologies that will allow to address the full spectrum of applications from mobile/autonomous objects to high performance computing coprocessing, by realising (1) a technology to implement on-chip learning, using native adaptive characteristics of electronic synaptic elements; and (2) a scalable platform to interconnect multiple neuromorphic processor chips to build large neural processing systems. The neuromorphic computing system will be developed jointly with advanced neural algorithms and computational architectures for online adaptation, learning, and high-throughput on-line signal processing, delivering 1. an ultra-low power massively parallel non von Neumann computing platform with non-volatile nano-scale devices that support on-line learning mechanisms 2. a programming toolbox of algorithms and data structures tailored to the specific constraints and opportunities of the physical architecture; 3. an array of fundamental application demonstrations instantiating the basic classes of signal processing tasks. The neural chip will validate the concept and be a first step to develop a European technology platform addressing from ultra-low power data processing in autonomous systems (Internet of Things) to energy efficient large data processing in servers and networks.