Agency: European Commission | Branch: FP7 | Program: MC-IRSES | Phase: FP7-PEOPLE-2010-IRSES | Award Amount: 779.10K | Year: 2011
The focus in cosmology is shifting from the determination of the basic cosmological parameters to developing an understanding of how galaxies formed. Progress in this field has been driven by a combination of computer simulation and observational breakthroughs. Over the next few years, groundbreaking new facilities will come online and will provide data of unprecedented quality with which to test theoretical models. The key objective of our proposal is to allow European scientists to play a leading role in advancing our understanding of galaxy formation, by forging new links and research collaborations with scientists in Latin America and China, which host some of these new experiments. Our research programme covers all aspects of numerical galaxy formation. In addition to building new research capacity, we will organise a series of events to avoid fragmentation of research expertise and to help train a new generation of galaxy formation modellers.
Agency: European Commission | Branch: H2020 | Program: SGA-RIA | Phase: FETFLAGSHIP | Award Amount: 89.00M | Year: 2016
Understanding the human brain is one of the greatest scientific challenges of our time. Such an understanding can provide profound insights into our humanity, leading to fundamentally new computing technologies, and transforming the diagnosis and treatment of brain disorders. Modern ICT brings this prospect within reach. The HBP Flagship Initiative (HBP) thus proposes a unique strategy that uses ICT to integrate neuroscience data from around the world, to develop a unified multi-level understanding of the brain and diseases, and ultimately to emulate its computational capabilities. The goal is to catalyze a global collaborative effort. During the HBPs first Specific Grant Agreement (SGA1), the HBP Core Project will outline the basis for building and operating a tightly integrated Research Infrastructure, providing HBP researchers and the scientific Community with unique resources and capabilities. Partnering Projects will enable independent research groups to expand the capabilities of the HBP Platforms, in order to use them to address otherwise intractable problems in neuroscience, computing and medicine in the future. In addition, collaborations with other national, European and international initiatives will create synergies, maximizing returns on research investment. SGA1 covers the detailed steps that will be taken to move the HBP closer to achieving its ambitious Flagship Objectives.
Agency: European Commission | Branch: FP7 | Program: CPCSA | Phase: ICT-2013.9.9 | Award Amount: 72.73M | Year: 2013
Understanding the human brain is one of the greatest challenges facing 21st century science. If we can rise to the challenge, we can gain profound insights into what makes us human, develop new treatments for brain diseases and build revolutionary new computing technologies. Today, for the first time, modern ICT has brought these goals within sight. The goal of the Human Brain Project, part of the FET Flagship Programme, is to translate this vision into reality, using ICT as a catalyst for a global collaborative effort to understand the human brain and its diseases and ultimately to emulate its computational capabilities. The Human Brain Project will last ten years and will consist of a ramp-up phase (from month 1 to month 36) and subsequent operational phases.\nThis Grant Agreement covers the ramp-up phase. During this phase the strategic goals of the project will be to design, develop and deploy the first versions of six ICT platforms dedicated to Neuroinformatics, Brain Simulation, High Performance Computing, Medical Informatics, Neuromorphic Computing and Neurorobotics, and create a user community of research groups from within and outside the HBP, set up a European Institute for Theoretical Neuroscience, complete a set of pilot projects providing a first demonstration of the scientific value of the platforms and the Institute, develop the scientific and technological capabilities required by future versions of the platforms, implement a policy of Responsible Innovation, and a programme of transdisciplinary education, and develop a framework for collaboration that links the partners under strong scientific leadership and professional project management, providing a coherent European approach and ensuring effective alignment of regional, national and European research and programmes. The project work plan is organized in the form of thirteen subprojects, each dedicated to a specific area of activity.\nA significant part of the budget will be used for competitive calls to complement the collective skills of the Consortium with additional expertise.
Agency: European Commission | Branch: FP7 | Program: CP-FP | Phase: HEALTH.2013.2.3.4-2 | Award Amount: 7.61M | Year: 2014
The infectious diseases burden imposed by the parasites of Trypanosomatidae family represents a huge problem on peoples lives in countries where these diseases are endemic. Problems associated with existing drugs include inefficient delivery, insufficient efficacy, excessive toxicity and increasing resistance. New drugs are urgently needed now and in the foreseeable future. The New Medicine for Trypanosomatid Infections (NMTrypI) consortium uses a highly interdisciplinary approach to optimize pteridine, benzothiazole and miltefosine derivatives, as well as natural products against Trypanosomatids. The lead compounds target mechanisms that are associated with protozoa virulence and pathogenicity. The major objectives of this 3-year project are: i) development of drug leads which may be used in combination with a known or an investigational drugs, by using a common drug discovery platform established by experts in their respective fields, ii) development of pharmacodynamic biomarkers enabling the proteomic profiling of compound efficacy and early identification of drug resistance. NMTrypI addresses sleeping sickness, leishmaniasis, and Chagas disease. The partners are SMEs (5) and academics (8) in Europe and in disease-endemic countries (Italy, Greece, Portugal, Sudan, and Brazil). The new platform enables high throughput screening of compound libraries, lead development, testing in relevant animal models, as well as toxicology and safety testing. NMTrypI will translate drug leads into drug candidacy through 6 scientific work packages (WPs1-6) supported by two transversal WPs dedicated to project dissemination and management. The major strength of the consortium lies in the complementary partnersexpertise and the integrated platform that will provide: - at least 1-2 innovative, less toxic and safer drug candidates for Trypanosomatid infections compared to existing ones, - early phase biomarkers for efficacy prediction (overall improved efficacy and safety)
Agency: European Commission | Branch: FP7 | Program: CP-CSA-Infra | Phase: INFRA-2012-2.2.4. | Award Amount: 6.56M | Year: 2012
The Infrastructure for Systems Biology in Europe (ISBE) programme comprises an infrastructure that is designed to meet the needs of European systems biology, in terms of development, applications and training. In order to address this requirement, we are proposing a distributed, interconnected infrastructure which primarily comprises three types of centres: Data Integration Centres (DICs), and systems biology dedicated Data Generation Centres (DGCs), and Data Stewardship Centres (DSCs). DICs are research centres that apply and develop expertise in model-driven data integration and make this expertise available to the community. DGCs are technology-based centres that make available a wide range of high, medium and low throughput technologies that are essential for the acquisition of quantitative datasets under standardised conditions. DSCs are centres that are responsible for data processing, curation and analysis they store data, models and simulations. Each type of centre will be functionally different, but organisationally similar. Within participating universities and other organisations across Europe there will be foci of expertise and facilities which fit the requirements for a DIC, DGC or DSC. Such foci will be evaluated and then designated as local centres of a particular type. Each focus will then form a component of a particular type of DIC, DGC or DSC centre. ISBE centres may be single institutions or can be distributed. Large institutions, such as leading universities, may well contribute facilities and expertise across different types of centres. A particular distributed centre may focus on an area of Systems Biology; for example, a model organism, a disease, or, alternatively an area such as biotechnology, ecology or green biology. Importantly, the ISBE will include technological expertise; for example, stochastic computation, algorithmic modelling, multi-scale modelling integration of diverse high-and low-throughput datasets.
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2009.2.2 | Award Amount: 3.12M | Year: 2010
The combination of dynamic user-generated content and multi-lingual aspects is particularly prominent in Wiki sites. Wikis have gained increased popularity over the last few years as a means of collaborative content creation as they allow users to set up and edit web pages directly. A growing number of organizations use Wikis as an efficient means to provide and maintain information across several sites.\nCurrently, multi-lingual Wikis rely on users to manually translate different Wiki pages on the same subject. This is not only a time-consuming procedure but also the source of many inconsistencies, as users update the different language versions separately, and every update would require translators to compare the different language versions and synchronize the updates.\n\nThe overall aim of the CoSyne project is to automate the dynamic multi-lingual synchronization process of Wikis.\n\nCoSyne will:\n- achieve robust translation of noisier user-generated content between 6 core languages (consisting of 4 core languages and 2 languages with limited resources to demonstrate adaptability of the system),\n- improve machine translation quality by segment-specific adaptive modeling,\n- identify textual content overlap between segments of Wiki pages across languages to avoid redundant machine translation,\n- identify the optimal insertion points for translated content to preserve coherence,\n- analyze user edits to distinguish between factual content changes and corrections of machine translation output, and exploit the latter to improve machine translation performance in a self-learning manner.\n\nThe components of CoSyne will be integrated through web services with the open-source MediaWiki platform, which is the most commonly used Wiki platform.\n\nThe three end-user partners of the consortium will deploy, integrate into their daily workflow, and evaluate the CoSyne system, which will give a clear direction towards the exploitability of the projects outcomes.
Nastase V.,HITS GGmbH |
Strube M.,HITS GGmbH
Artificial Intelligence | Year: 2013
A knowledge base for real-world language processing applications should consist of a large base of facts and reasoning mechanisms that combine them to induce novel and more complex information. This paper describes an approach to deriving such a large scale and multilingual resource by exploiting several facets of the on-line encyclopedia Wikipedia. We show how we can build upon Wikipedia's existing network of categories and articles to automatically discover new relations and their instances. Working on top of this network allows for added information to influence the network and be propagated throughout it using inference mechanisms that connect different pieces of existing knowledge. We then exploit this gained information to discover new relations that refine some of those found in the previous step. The result is a network containing approximately 3.7 million concepts with lexicalizations in numerous languages and 49+ million relation instances. Intrinsic and extrinsic evaluations show that this is a high quality resource and beneficial to various NLP tasks. © 2012 Elsevier B.V. All rights reserved.
Agency: European Commission | Branch: FP7 | Program: ERC-AG | Phase: ERC-AG-ID1 | Award Amount: 1.73M | Year: 2012
The future being uncertain, forecasts ought to be probabilistic in nature, taking the form of probability distributions over future quantities or events. Accordingly, a transdisciplinary transition from point forecasts to probabilistic forecasts is well under way. The ScienceFore project seeks to provide guidance and leadership in this transition, by developing the theoretical foundations of the science of forecasting, as well as cutting-edge statistical methodology, along with applications in meteorology and economics. Theoretically, we will focus on the study of aggregation methods for the combination of multiple probabilistic forecasts for the same quantity or event, and on the design and structure of performance measures that encourage truthful predictions, including but not limited to proper scoring rules. In applications, we will develop statistical postprocessing techniques for the THORPEX Interactive Grand Global Ensemble (TIGGE), which comprises the worlds leading global numerical weather prediction models. The key challenge is to retain physically realistic and coherent joint dependence structures across meteorological variables, continents and oceans, and look-ahead times. Furthermore, we will investigate the use of statistical postprocessing techniques in macroeconomic surveys, and aim to resolve a long-standing puzzle in the evaluation of economic and financial forecasts. Theory and applications will intertwine closely, to result in a project that constitutes much more than the sum of its parts. For example, the study of the properties of aggregation methods will inform the development of postprocessing methods for ensemble weather forecasts, and decision theoretically principled approaches to the design of performance measures call for a change of paradigms in the practice of the generation and evaluation of point forecasts, to be demonstrated in case studies.
Agency: European Commission | Branch: H2020 | Program: ERC-COG | Phase: ERC-CoG-2014 | Award Amount: 2.00M | Year: 2016
Understanding the physics of galaxy formation is arguably among the greatest problems in modern astrophysics. Recent cosmological simulations have demonstrated that feedback by star formation, supernovae and active galactic nuclei appears to be critical in obtaining realistic disk galaxies, to slow down star formation to the small observed rates, to move gas and metals out of galaxies into the intergalactic medium, and to balance radiative cooling of the low-entropy gas at the centers of galaxy clusters. This progress still has the caveat that feedback was modeled empirically and involved tuning to observed global relations, substantially weakening the predictive power of hydrodynamic simulations. More problematic, these simulations neglected cosmic rays and magnetic fields, which provide a comparable pressure support in comparison to turbulence in our Galaxy, and are known to couple dynamically and thermally to the gas. Building on our previous successes in investigating these high-energy processes, we propose a comprehensive research program for studying the impact of cosmic rays on the formation of galaxies and clusters. To this end, we will study cosmic-ray propagation in magneto-hydrodynamic turbulence and improve the modeling of the plasma physics. This will enable us to perform the first consistent magneto-hydrodynamical and cosmic-ray simulations in a cosmological framework, something that has just now become technically feasible. Through the use of an advanced numerical technique that employs a moving mesh for calculating hydrodynamics, we will achieve an unprecedented combination of accuracy, resolution and physical completeness. We complement our theoretical efforts with a focused observational program on the non-thermal emission of galaxies and clusters, taking advantage of new capabilities at radio to gamma-ray wavelengths and neutrinos. This promises important and potentially transformative changes of our understanding of galaxy formation.
Agency: European Commission | Branch: FP7 | Program: ERC-SG | Phase: ERC-SG-PE9 | Award Amount: 1.49M | Year: 2013
Numerical simulations of galaxy formation provide a powerful technique for calculating the non-linear evolution of cosmic structure formation. In fact, they have played an instrumental role in establishing the current standard cosmological model known as LCDM. However, unlocking the predictive power of current petaflop and future exaflop computing platforms requires a targeted effort in developing new numerical methods that excel in accuracy, parallel scalability, and in physical fidelity to the processes relevant in galaxy formation. A new moving-mesh technique for hydrodynamics recently developed by us provides a significant opportunity for a paradigm shift in cosmological simulations of structure formation, replacing the established smoothed particle hydrodynamics technique with a much more accurate and flexible approach. Building on the first successes with this method, we here propose a comprehensive research program to apply this novel numerical framework in a new generation of hydrodynamical simulations of galaxy formation that aim to greatly expand the physical complexity and dynamic range of theoretical galaxy formation models. We will perform the first simulations of individual galaxies with several tens of billion hydrodynamical resolution elements and full adaptivity, allowing us to resolve the interstellar medium in global models of galaxies with an unprecedented combination of spatial resolution and volume. We will simultaneously and self-consistently follow the radiation field in galaxies down to very small scales, something that has never been attempted before. Through cosmological simulations of galaxy formation in representative regions of the Universe, we will shed light on the connection between galaxy formation and the large-scale distribution of gas in the Universe, and on the many facets of feedback processes that regulate galactic star formation, such as energy input from evolving and dying stars or from accreting supermassive black holes.