28 research outputs found

    Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

    Get PDF
    Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes

    Multi-view Active Appearance Models for the X-Ray Based Analysis of Avian Bipedal Locomotion

    No full text
    Abstract. Many fields of research in biology, motion science and robotics depend on the understanding of animal locomotion. Therefore, numerous experiments are performed using high-speed biplanar x-ray acquisition systems which record sequences of walking animals. Until now, the evalu-ation of these sequences is a very time-consuming task, as human experts have to manually annotate anatomical landmarks in the images. There-fore, an automation of this task at a minimum level of user interaction is worthwhile. However, many difficulties in the data—such as x-ray occlu-sions or anatomical ambiguities—drastically complicate this problem and require the use of global models. Active Appearance Models (AAMs) are known to be capable of dealing with occlusions, but have problems with ambiguities. We therefore analyze the application of multi-view AAMs in the scenario stated above and show that they can effectively han-dle uncertainties which can not be dealt with using single-view models. Furthermore, preliminary studies on the tracking performance of huma

    Iterative Solvers for Discretized Stationary Euler Equations

    No full text
    Abstract In this paper we treat subjects which are relevant in the context of iterative methods in implicit time integration for compressible flow simulations. We present a novel renumbering technique, some strategies for choosing the time step in the implicit time integration, and a novel implementation of a matrix-free evaluation for matrix-vector products. For the linearized compressible Euler equations, we present various comparative studies within the QUADFLOW package concerning preconditioning techniques, ordering methods, time stepping strategies, and different implementations of the matrix-vector product. The main goal is to improve efficiency and robustness of the iterative method used in the flow solver.
    corecore