Gamma oscillations and stimulus selection

More coherent excitatory stimuli are known to have a competitive advantage over less coherent ones. We show here that this advantage is amplified greatly when the target includes inhibitory interneurons acting via GABA(A)-receptor-mediated synapses and the coherent input oscillates at gamma frequency. We hypothesize that therein lies, at least in part, the functional significance of the experimentally observed link between attentional biasing of stimulus competition and gamma frequency rhythmicity.     

Interactive multiscale tensor reconstruction for multiresolution volume visualization

Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes.     

A framework for regional association rule mining and scoping in spatial datasets

The motivation for regional association rule mining and scoping is driven by the facts that global statistics seldom provide useful insight and that most relationships in spatial datasets are geographically regional, rather than global. Furthermore, when using traditional association rule mining, regional patterns frequently fail to be discovered due to insufficient global confidence and/or support. In this paper, we systematically study this problem and address the unique challenges of regional association mining and scoping: (1) region discovery: how to identify interesting regions from which novel and useful regional association rules can be extracted; (2) regional association rule scoping: how to determine the scope of regional association rules. We investigate the duality between regional association rules and regions where the associations are valid: interesting regions are identified to seek novel regional patterns, and a regional pattern has a scope of a set of regions in which the pattern is valid. In particular, we present a reward-based region discovery framework that employs a divisive grid-based supervised clustering for region discovery. We evaluate our approach in a real-world case study to identify spatial risk patterns from arsenic in the Texas water supply. Our experimental results confirm and validate research results in the study of arsenic contamination, and our work leads to the discovery of novel findings to be further explored by domain scientists.     

Visual optimality and stability analysis of 3DCT scan positions

Industrial cone-beam X-Ray computed tomography (CT) systems often face problems due to artifacts caused by a bad placement of the specimen on the rotary plate. This paper presents a visual-analysis tool for CT systems, which provides a simulation-based preview and estimates artifacts and deviations of a specimen's placement using the corresponding 3D geometrical surface model as input. The presented tool identifies potentially good or bad placements of a specimen and regions of a specimen, which cause the major portion of artefacts. The tool can be used for a preliminary analysis of the specimen before CT scanning, in order to determine the optimal way of placing the object. The analysis includes: penetration lengths, placement stability and an investigation in Radon space. Novel visualization techniques are applied to the simulation data. A stability widget is presented for determining the placement parameters' robustness. The performance and the comparison of results provided by the tool compared with real world data is demonstrated using two specimens.     

Ranking kinematics for revising by contextual information

Annals of Mathematics and Artificial Intelligence - Probability kinematics is a leading paradigm in probabilistic belief change. It is based on the idea that conditional beliefs should be...     

Tactile–optical probes for three-dimensional microparts

The dimensional measurement of microsystem components is a field of application that is gaining more and more importance. While optical probing systems offer a number of advantages, their performance is strongly affected by the varying optical properties of the measured surfaces. For this reason, tactile probing systems are essential to many fields of micrometrology. Since conventional tactile probing systems are not suitable for the measurement of microparts, there is a demand for new tactile probing systems that are specifically adapted to the requirements of micrometrology. The tactile–optical Werth Fiber Probe is an established solution within this scope of application. In the present paper, two recent approaches to adding full 3D capabilities to the fiber probe principle are proposed. First prototypes of these sensors are shown and the obtained results are discussed.     

HiL simulation in biomechanics: a new approach for testing total joint replacements

Instability of artificial joints is still one of the most prevalent reasons for revision surgery caused by various influencing factors. In order to investigate instability mechanisms such as dislocation under reproducible, physiologically realistic boundary conditions, a novel test approach is introduced by means of a hardware-in-the-loop (HiL) simulation involving a highly flexible mechatronic test system. In this work, the underlying concept and implementation of all required units is presented enabling comparable investigations of different total hip and knee replacements, respectively. The HiL joint simulator consists of two units: a physical setup composed of a six-axes industrial robot and a numerical multibody model running in real-time. Within the multibody model, the anatomical environment of the considered joint is represented such that the soft tissue response is accounted for during an instability event. Hence, the robot loads and moves the real implant components according to the information provided by the multibody model while transferring back the position and resisting moment recorded. Functionality of the simulator is proved by testing the underlying control principles, and verified by reproducing the dislocation process of a standard total hip replacement. HiL simulations provide a new biomechanical testing tool for analyzing different joint replacement systems with respect to their instability behavior under realistic movements and physiological load conditions.     

Tile-Packing Tomography Is \mathbb{NP}-hard

Discrete tomography deals with reconstructing finite spatial objects from their projections. The objects we study in this paper are called tilings or tile-packings, and they consist of a number of disjoint copies of a fixed tile, where a tile is defined as a connected set of grid points. A row projection specifies how many grid points are covered by tiles in a given row; column projections are defined analogously. For a fixed tile, is it possible to reconstruct its tilings from their projections in polynomial time? It is known that the answer to this question is affirmative if the tile is a bar (its width or height is 1), while for some other types of tiles $\mathbb {NP}$ -hardness results have been shown in the literature. In this paper we present a complete solution to this question by showing that the problem remains $\mathbb {NP}$ -hard for all tiles other than bars.