Unitarity in three-dimensional flat space higher spin theories

We investigate generic flat-space higher spin theories in three dimensions and find a no-go result, given certain assumptions that we spell out. Namely, it is only possible to have at most two out of the following three properties: unitarity, flat space, non-trivial higher spin states. Interestingly, unitarity provides an (algebra-dependent) upper bound on the central charge, like c=42 for the Galilean $W_4^{(2-1-1)}$ algebra. We extend this no-go result to rule out unitary "multi-graviton" theories in flat space. We also provide an example circumventing the no-go result: Vasiliev-type flat space higher spin theory based on hs(1) can be unitary and simultaneously allow for non-trivial higher-spin states in the dual field theory.Comment: 34 pp, v2: added two paragraphs in section 5.3 + minor change

Targeted delivery and MRI tracking of magnetically labelled cells

The realisation of the therapeutic potential of cellular therapies will depend on our ability to deliver these cells to selected positions in the body where they can find a suitable micro-environment to flourish. Additionally our scientific understanding would befit from studies which can assess the behaviour of cells at specific locations inside the body. Magnetic cell delivery is a potential technology which might allow realising these premises. The major advantage of magnetic delivery compared to other delivery strategies is the ability to spatially localise entities in the body via externally applied magnetic fields. However, the fast decline of these fields with increasing distances is posing a major challenge for its in vivo application. The aim of this thesis was to investigate potential magnetic delivery approaches which can circumvent some of the typical limitations of this technique. Two different approaches were explored to this end. The first approach was evaluating the feasibility of a magnetic resonance imaging (MRI) system to steer labelled cells in arteries. Such an approach could take advantage of the imaging capabilities of magnetic resonance systems and combine these with steering to interactively guide cells or other entities of interest to a target area. The second approach was addressing the feasibility of theoretical optimisations and the scalability of experimental results. For that, human MRI data was used to derive geometrical models of the blood vessels to which cells were to be delivered in this scenario. Finite element modelling was then used to explore potential magnet arrangements with the aim to maximise the force acting on cells over all target vessels. The best performing arrangement was then used for computational fluid dynamics simulations to test the possibility of cell capture from the flowing blood stream. Finally the possibility to scale-down such an arrangement to the dimensions of an animal model without changing the forces acting on cells was investigated. Cells have to be labelled with magnetic materials in order to allow their magnetic actuation. This magnetic materials cause a distinctive contrast on MRI images. The potential of this imaging modality for cell tracking has been illustrated with an in vivo example for cell tracking in a rat heart and an in vitro example for a tissue engineering application. Experiments with a preclinical MRI system illustrated the feasibility of cell steering with MRI indicating that such an approach could be useful for magnetic cell delivery. Computational models for the evaluation of magnet arrangements allowed the in-silico assessment of their potential and could be used to improve the experimental design of pre-clinical studies

Performance of single photon-counting X-ray charge coupled devices

Results of intial performance tests on X-ray sensing properties of charge-coupled devices (CCDs) are presented. CCDs have demonstrated excellent spatial resolution and good spectral resolution, superior to that of non-imaging proportional counters

APPLYING TERRAIN AND HYDROLOGICAL EDITING TO TANDEM-X DATA TO CREATE A CONSUMER-READY WORLDDEM PRODUCT

The Geo-intelligence division of Airbus Defence and Space and the German Aerospace Center (DLR) have partnered to produce the first fully global, high-accuracy Digital Surface Model (DSM) using SAR data from the twin satellite constellation: TerraSAR-X and TanDEM-X. The DLR is responsible for the processing and distribution of the TanDEM-X elevation model for the world's scientific community, while Airbus DS is responsible for the commercial production and distribution of the data, under the brand name WorldDEM™. For the provision of a consumer-ready product, Airbus DS undertakes several steps to reduce the effect of radar-specific artifacts in the WorldDEM data. These artifacts can be divided into two categories: terrain and hydrological. Airbus DS has developed proprietary software and processes to detect and correct these artifacts in the most efficient manner. Some processes are fullyautomatic, while others require manual or semi-automatic control by operators

Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network

Depth estimation from a single image is a fundamental problem in computer vision. In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for depth prediction. Specifically, we adopt an efficient linear propagation model, where the propagation is performed with a manner of recurrent convolutional operation, and the affinity among neighboring pixels is learned through a deep convolutional neural network (CNN). We apply the designed CSPN to two depth estimation tasks given a single image: (1) To refine the depth output from state-of-the-art (SOTA) existing methods; and (2) to convert sparse depth samples to a dense depth map by embedding the depth samples within the propagation procedure. The second task is inspired by the availability of LIDARs that provides sparse but accurate depth measurements. We experimented the proposed CSPN over two popular benchmarks for depth estimation, i.e. NYU v2 and KITTI, where we show that our proposed approach improves in not only quality (e.g., 30% more reduction in depth error), but also speed (e.g., 2 to 5 times faster) than prior SOTA methods.Comment: 14 pages, 8 figures, ECCV 201