Active data structures on GPGPUs

Active data structures support operations that may affect a large number of elements of an aggregate data structure. They are well suited for extremely fine grain parallel systems, including circuit parallelism. General purpose GPUs were designed to support regular graphics algorithms, but their intermediate level of granularity makes them potentially viable also for active data structures. We consider the characteristics of active data structures and discuss the feasibility of implementing them on GPGPUs. We describe the GPU implementations of two such data structures (ESF arrays and index intervals), assess their performance, and discuss the potential of active data structures as an unconventional programming model that can exploit the capabilities of emerging fine grain architectures such as GPUs

System data communication structures for active-control transport aircraft, volume 1

Candidate data communication techniques are identified, including dedicated links, local buses, broadcast buses, multiplex buses, and mesh networks. The design methodology for mesh networks is then discussed, including network topology and node architecture. Several concepts of power distribution are reviewed, including current limiting and mesh networks for power. The technology issues of packaging, transmission media, and lightning are addressed, and, finally, the analysis tools developed to aid in the communication design process are described. There are special tools to analyze the reliability and connectivity of networks and more general reliability analysis tools for all types of systems

System data communication structures for active-control transport aircraft, volume 2

The application of communication structures to advanced transport aircraft are addressed. First, a set of avionic functional requirements is established, and a baseline set of avionics equipment is defined that will meet the requirements. Three alternative configurations for this equipment are then identified that represent the evolution toward more dispersed systems. Candidate communication structures are proposed for each system configuration, and these are compared using trade off analyses; these analyses emphasize reliability but also address complexity. Multiplex buses are recognized as the likely near term choice with mesh networks being desirable for advanced, highly dispersed systems

Validation of the magnetic energy vs. helicity scaling in solar magnetic structures

We assess the validity of the free magnetic energy - relative magnetic helicity diagram for solar magnetic structures. We used two different methods of calculating the free magnetic energy and the relative magnetic helicity budgets: a classical, volume-calculation nonlinear force-free (NLFF) method applied to finite coronal magnetic structures and a surface-calculation NLFF derivation that relies on a single photospheric or chromospheric vector magnetogram. Both methods were applied to two different data sets, namely synthetic active-region cases obtained by three-dimensional magneto-hydrodynamic (MHD) simulations and observed active-region cases, which include both eruptive and noneruptive magnetic structures. The derived energy--helicity diagram shows a consistent monotonic scaling between relative helicity and free energy with a scaling index 0.84$\pm$0.05 for both data sets and calculation methods. It also confirms the segregation between noneruptive and eruptive active regions and the existence of thresholds in both free energy and relative helicity for active regions to enter eruptive territory. We consider the previously reported energy-helicity diagram of solar magnetic structures as adequately validated and envision a significant role of the uncovered scaling in future studies of solar magnetism

Improving the Knowledge on Seismogenic Sources in the Lower Tagus Valley for Seismic Hazard Purposes

The Lower Tagus Valley, that includes the metropolitan area of Lisbon, has been struck by several earthquakes which produced significant material damage and loss of lives. Their exact location remains unknown. Our goal is to shed some light into the seismogenic sources in the area using seismic reflection and geological data. In areas with no seismic coverage, potential-field data interpretation was carried out. Seismicity was overlaid to the potential seismogenic structures and high-resolution data was acquired in order to confirm which structures have been active into the Quaternary. Three major fault-zones affecting the Neogene were identified: V. F. Xira, Samora-Alcochete and Pinhal Novo. For the first fault, strong evidences suggest it is active. The other two fault-zones and other structures previously unknown can be correlated with several epicentres. Empirical relationships between maximum moment magnitude and fault area indicate that MW > 6.5 earthquakes can be expected for the larger structures

Volumetric segmentation of multiple basal ganglia structures

We present a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. Neighboring anatomical structures in the human brain exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and inter-shape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities based on training data, we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework, and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance (MR) images. We compare our technique with existing methods and demonstrate the improvements it provides in terms of segmentation accuracy

Insights into antibody catalysis: Structure of an oxygenation catalyst at 1.9-Å resolution

The x-ray crystal structures of the sulfide oxidase antibody 28B4 and of antibody 28B4 complexed with hapten have been solved at 2.2-Å and 1.9-Å resolution, respectively. To our knowledge, these structures are the highest resolution catalytic antibody structures to date and provide insight into the molecular mechanism of this antibody-catalyzed monooxygenation reaction. Specifically, the data suggest that entropic restriction plays a fundamental role in catalysis through the precise alignment of the thioether substrate and oxidant. The antibody active site also stabilizes developing charge on both sulfur and periodate in the transition state via cation-pi and electrostatic interactions, respectively. In addition to demonstrating that the active site of antibody 28B4 does indeed reflect the mechanistic information programmed in the aminophosphonic acid hapten, these high-resolution structures provide a basis for enhancing turnover rates through mutagenesis and improved hapten design

Coupled non-parametric shape and moment-based inter-shape pose priors for multiple basal ganglia structure segmentation

This paper presents a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. In biological tissues, such as the human brain, neighboring structures exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and inter-shape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance (MR) images. We present a set of 2D and 3D experiments as well as a quantitative performance analysis. In addition, we perform a comparison to several existent segmentation methods and demonstrate the improvements provided by our approach in terms of segmentation accuracy

On the Active Compensation of Operational Amplifier Based VCVS

A unified treatment of the active compensation for VCVS realized by operational amplifiers is presented. It is a summary of low-sensitivity circuit structures which can be either magnitude or phase compensated. The performance of such a circuits is discussed in detail. Experimental data for some of them are also included