A Topological Reconstruction Theorem for D∞D^{\infty}-Modules

In this paper, we prove that any perfect complex of $D^{\infty}$-modules may be reconstructed from its holomorphic solution complex provided that we keep track of the natural topology of this last complex. This is to be compared with the reconstruction theorem for regular holonomic $D$-modules which follows from the well-known Riemann-Hilbert correspondence. To obtain our result, we consider sheaves of holomorphic functions as sheaves with values in the category of ind-Banach spaces and study some of their homological properties. In particular, we prove that a K\"{u}nneth formula holds for them and we compute their Poincar\'{e}-Verdier duals. As a corollary, we obtain the form of the kernels of ``continuous'' cohomological correspondences between sheaves of holomorphic forms. This allows us to prove a kind of holomorphic Schwartz' kernel theorem and to show that $D^{\infty}=RHomtop(O,O)$. Our reconstruction theorem is a direct consequence of this last isomorphism. Note that the main problem is the vanishing of the topological Ext's and that this vanishing is a consequence of the acyclicity theorems for DFN spaces which are established in the paper.Comment: 36 pages, LaTeX + AMS and Xy-pic macros. To appear in Duke Math. Journa

Parent form for higher spin fields on anti-de Sitter space

We construct a first order parent field theory for free higher spin gauge fields on constant curvature spaces. As in the previously considered flat case, both Fronsdal's and Vasiliev's unfolded formulations can be reached by two different straightforward reductions. The parent theory itself is formulated using a higher dimensional embedding space and turns out to be geometrically extremely transparent and free of the intricacies of both of its reductions.Comment: 39 pages, LaTeX; misprints corrected, references adde

Moregrasp: Restoration of Upper Limb Function in Individuals with High Spinal Cord Injury by Multimodal Neuroprostheses for Interaction in Daily Activities

The aim of the MoreGrasp project is to develop a noninvasive, multimodal user interface including a brain-computer interface (BCI) for intuitive control of a grasp neuroprosthesis to support individuals with high spinal cord injury (SCI) in everyday activities. We describe the current state of the project, including the EEG system, preliminary results of natural movements decoding in people with SCI, the new electrode concept for the grasp neuroprosthesis, the shared control architecture behind the system and the implementation of a user-centered design

Patch-Based Experiments with Object Classification in Video Surveillance

We present a patch-based algorithm for the purpose of object classification in video surveillance. Within detected regions-of-interest (ROIs) of moving objects in the scene, a feature vector is calculated based on template matching of a large set of image patches. Instead of matching direct image pixels, we use Gabor-filtered versions of the input image at several scales. This approach has been adopted from recent experiments in generic object-recognition tasks. We present results for a new typical video surveillance dataset containing over 9,000 object images. Furthermore, we compare our system performance with another existing smaller surveillance dataset. We have found that with 50 training samples or higher, our detection rate is on the average above 95%. Because of the inherent scalability of the algorithm, an embedded system implementation is well within reach

Identification of a novel prophage regulator in Escherichia coli controlling the expression of type III secretion

This study has identified horizontally acquired genomic regions of enterohaemorrhagic Escherichia coli O157:H7 that regulate expression of the type III secretion (T3S) system encoded by the locus of enterocyte effacement (LEE). Deletion of O-island 51, a 14.93 kb cryptic prophage (CP-933C), resulted in a reduction in LEE expression and T3S. The deletion also had a reduced capacity to attach to epithelial cells and significantly reduced E. coli O157 excretion levels from sheep. Further characterization of O-island 51 identified a novel positive regulator of the LEE, encoded by ecs1581 in the E. coli O157:H7 strain Sakai genome and present but not annotated in the E. coli strain EDL933 sequence. Functionally important residues of ECs1581 were identified based on phenotypic variants present in sequenced E. coli strains and the regulator was termed RgdR based on a motif demonstrated to be important for stimulation of gene expression. While RgdR activated expression from the LEE1 promoter in the presence or absence of the LEE-encoded regulator (Ler), RgdR stimulation of T3S required ler and Ler autoregulation. RgdR also controlled the expression of other phenotypes, including motility, indicating that this new family of regulators may have a more global role in E. coli gene expression

3D Fluid Flow Estimation with Integrated Particle Reconstruction

The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view video in two separate steps, utilizing either a pure Eulerian or pure Lagrangian approach. Eulerian methods perform a voxel-based reconstruction of particles per time step, followed by 3D motion estimation, with some form of dense matching between the precomputed voxel grids from different time steps. In this sequential procedure, the first step cannot use temporal consistency considerations to support the reconstruction, while the second step has no access to the original, high-resolution image data. Alternatively, Lagrangian methods reconstruct an explicit, sparse set of particles and track the individual particles over time. Physical constraints can only be incorporated in a post-processing step when interpolating the particle tracks to a dense motion field. We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian model reconstructs individual particles, and at the same time recovers a dense 3D motion field in the entire domain. Making particles explicit greatly reduces the memory consumption and allows one to use the high-res input images for matching. Whereas the dense motion field makes it possible to include physical a-priori constraints and account for the incompressibility and viscosity of the fluid. The method exhibits greatly (~70%) improved results over our recently published baseline with two separate steps for 3D reconstruction and motion estimation. Our results with only two time steps are comparable to those of sota tracking-based methods that require much longer sequences.Comment: To appear in International Journal of Computer Vision (IJCV

INTEGRATED DESIGN OF A LIGHTWEIGHT POSITIONING SYSTEM

Abstract In this paper a new approach to the design of positioning systems is introduced. The approach aims at the design of fast and accurate systems that are lightweight compared to classical designs. The new design reduces peak power requirements and thermal effects that deteriorate performance of the whole system