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TUM

Technical University of Munich
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868 Projects, page 1 of 174
  • Funder: European Commission Project Code: 657682
    Overall Budget: 171,461 EURFunder Contribution: 171,461 EUR

    This project aims at changing the impact of optimal control methodology on solid state nuclear magnetic resonance (NMR). This way, routine structure determination of biological solids like amyloid fibrils and membrane proteins will be facilitated. Multi-dimensional experiments of these samples often suffer from low resolution and sensitivity. Optimal control theory provides efficient means for automated design of pulse experiments with improved efficiency, lower deposited radiofrequency power, and robustness with respect to experimental imperfections. The methodology has already been successfully applied to liquid state as well as solid state NMR. However, and especially for solids, the optimized pulse sequences are not used within the NMR community, probably due to barriers imposed by individual RF hardware characteristics of the employed probes and consoles. In order to change this we propose, in cooperation with the market leading manufacturer of NMR spectrometers, to study the interplay of the hardware with numerically predicted “optimal” experiments, including relaxation and reformulation of the optimization problem in a new theoretical framework. Such comprehensive optimizations should provide us with easy-to-use building blocks of multidimensional solid state NMR experiments with superior performance, boosting thus the sensitivity and the accessibility of structural information from the acquired spectra. To promote dissemination of the developed protocols a workshop on implementation of optimal control methods in magnetic resonance will be organized. The potential impact of the project is enormous, revolutionizing hardware development with new quality measures that combine its properties with fundamental laws of spin dynamics.

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  • Funder: European Commission Project Code: 306274
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  • Funder: European Commission Project Code: 884679
    Overall Budget: 3,500,000 EURFunder Contribution: 3,500,000 EUR

    Despite their amazing success, we believe that computer vision algorithms have only scratched the surface in terms of understanding our world from images. While most research on 3D reconstruction has been concerned with recovering the surface geometry and reflectance, SIMULACRON is focused on inferring the underlying physics (masses, elasticity, momenta, forces, etc.) and a simulation of the observed action directly from videos. This not only provides a more profound understanding of the observed phenomena, but it also allows us to interpolate and extrapolate complex actions far beyond the observation: The inferred physical simulation can be employed for space-time super-resolution and for predictions into the future. SIMULACRON covers three lines of research: A) We will develop algorithms for deformable shape modeling. We will explore suitable representations of 3D shape and its evolution that enable the efficient computation of shape deformation, correspondence, interpolation and extrapolation. These techniques will form the basis for inferring physical simulations in parts B and C. B) We will develop variational methods for inferring physical simulations from videos. We will compute a reference shape and simulation parameters that generate the shape deformation that is most consistent with the observations. C) We will develop learning-based approaches for inferring physical simulations from videos. We will pursue two alternative approaches: First, we will generate synthetic training data by simulating deformable shapes and the associated camera observations. Second, we will devise self-supervised techniques for learning from real data without requiring labeled training data. By shifting from inference of 3D geometry to inference of physical simulations, SIMULACRON will give rise to a more profound notion of dynamic scene understanding in computer vision, robotics and beyond. We believe that we have the necessary competence to pursue this project.

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  • Funder: European Commission Project Code: 101115963
    Overall Budget: 1,499,490 EURFunder Contribution: 1,499,490 EUR

    Violence against women is a violation of fundamental human rights and substantially compromises women’s health, wellbeing, and empowerment. Globally, more than one in four women experience physical and/or sexual violence by a partner in their lives. This risk is considerably higher among women in low- and middle-income countries and in cultures with pronounced patriarchal gender norms. However, existing research has so far neglected an important dimension of intimate partner violence (IPV): economic abuse. This form of abuse includes denying women the right to participate in financial decisions, taking away their income or preventing them from seeking employment. The consequences are profound – economic IPV compromises women’s economic welfare and independence, traps them in abusive relationships, and adversely affects their mental health. To tackle this major global health concern, ECOVI has three objectives: first, to establish the prevalence of different forms of economic IPV; second, to develop a theory of economic abuse by investigating drivers of economic IPV and linkages with other forms of IPV; and third, to design and test a community-based prevention approach. To this end, I will focus on India, which is home to 670 million women and girls and exhibits high levels of gender discrimination that exacerbate women’s vulnerability to economic IPV. I will capitalise on a mixed-methods approach, including (i) systematic reviews and meta-analyses, (ii) conducting qualitative in-depth interviews and focus groups, and (iii) implementing a cluster randomised controlled trial and innovative survey experiments with husbands and wives in 150 Indian communities. ECOVI will generate the largest existing database on economic IPV and establish an evidence-informed prevention approach. This has the potential to yield ground-breaking scientific and programmatic evidence on how to alleviate the economic violence and associated economic hardship that women worldwide are facing.

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  • Funder: European Commission Project Code: 101106893
    Funder Contribution: 189,687 EUR

    Thermal barrier coatings (TBCs) have been widely used to protect the substrate of hot components against the hot and corrosive environment, which have extensive applications in power sectors, aerospace engineering and chemical industrials. They are, however, facing the paradox of conflicting competition between the strength and toughness, especially under high temperature. Aiming to develop high temperature TBCs with simultaneously improved strength and toughness, this project proposes an innovative strategy of engineering nano-twinned ceramics and examines their mechanical properties under high temperature with improved mechanistic understanding, which include: i) developing novel nano-twinned TYaO4 ceramic materials via hierarchical structures; ii) examining the mechanical properties of formed TBC materials via a unique high temperature nano-indentation system up to 2000 K; 3) establishing a multi-scale simulation framework to predict the macroscopic mechanical properties; and iv) developing a twin boundary affected hardening and crack growth model to reveal the influence of nanoscale structures. Four work programs are proposed ranging from experiments, simulations to theories to realize such an ambitious plan, intervened with a careful balanced training program, dissemination and management skill development. Properly implemented, the project shall reveal for the first time the effect of hierarchical nanoscale structures on the improved mechanical properties of TYaO4 ceramics up to 2000 K, which are much needed for the development of next generations of TBCs. The project exhibits strong interdisciplinary coupling among materials science and engineering, solid mechanics, and multiscale computation engineering. Not only bearing with significant scientific potentials, the mutual benefits from this program will booster the career of the researcher significantly and promote long term knowledge exchange and collaboration between Europe and China.

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