1,312 research outputs found

    Analysis techniques for multivariate root loci

    Get PDF
    Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus

    Airloads on bluff bodies, with application to the rotor-induced downloads on tilt-rotor aircraft

    Get PDF
    The aerodynamic characteristics of airfoils with several flap configurations were studied theoretically and experimentally in environments that simulate a wing immersed in the downwash of a hovering rotor. Special techniques were developed for correcting and validating the wind tunnel data for large blockage effects, and the test results were used to evaluate two modern blockage effects, and the test results were used to evaluate two modern computational aerodynamics codes. The combined computed and measured results show that improved flap and leading-edge configurations can be designed which will achieve large reductions in the downloads of tilt-rotor aircraft, and thereby improve their hover efficiency

    On the efficiency of estimating penetrating rank on large graphs

    Get PDF
    P-Rank (Penetrating Rank) has been suggested as a useful measure of structural similarity that takes account of both incoming and outgoing edges in ubiquitous networks. Existing work often utilizes memoization to compute P-Rank similarity in an iterative fashion, which requires cubic time in the worst case. Besides, previous methods mainly focus on the deterministic computation of P-Rank, but lack the probabilistic framework that scales well for large graphs. In this paper, we propose two efficient algorithms for computing P-Rank on large graphs. The first observation is that a large body of objects in a real graph usually share similar neighborhood structures. By merging such objects with an explicit low-rank factorization, we devise a deterministic algorithm to compute P-Rank in quadratic time. The second observation is that by converting the iterative form of P-Rank into a matrix power series form, we can leverage the random sampling approach to probabilistically compute P-Rank in linear time with provable accuracy guarantees. The empirical results on both real and synthetic datasets show that our approaches achieve high time efficiency with controlled error and outperform the baseline algorithms by at least one order of magnitude

    The Energetic Costs of Cellular Computation

    Full text link
    Cells often perform computations in response to environmental cues. A simple example is the classic problem, first considered by Berg and Purcell, of determining the concentration of a chemical ligand in the surrounding media. On general theoretical grounds (Landuer's Principle), it is expected that such computations require cells to consume energy. Here, we explicitly calculate the energetic costs of computing ligand concentration for a simple two-component cellular network that implements a noisy version of the Berg-Purcell strategy. We show that learning about external concentrations necessitates the breaking of detailed balance and consumption of energy, with greater learning requiring more energy. Our calculations suggest that the energetic costs of cellular computation may be an important constraint on networks designed to function in resource poor environments such as the spore germination networks of bacteria.Comment: 9 Pages (including Appendix); 4 Figures; v3 corrects even more typo

    Phantom Validation of Tc-99m Absolute Quantification in a SPECT/CT Commercial Device.

    Get PDF
    Aim. Similar to PET, absolute quantitative imaging is becoming available in commercial SPECT/CT devices. This study's goal was to assess quantitative accuracy of activity recovery as a function of image reconstruction parameters and count statistics in a variety of phantoms. Materials and Methods. We performed quantitative (99m)Tc-SPECT/CT acquisitions (Siemens Symbia Intevo, Erlangen, Germany) of a uniform cylindrical, NEMA/IEC, and an anthropomorphic abdominal phantom. Background activity concentrations tested ranged: 2-80 kBq/mL. SPECT acquisitions used 120 projections (20 s/projection). Reconstructions were performed with the proprietary iterative conjugate gradient algorithm. NEMA phantom reconstructions were obtained as a function of the iteration number (range: 4-48). Recovery coefficients, hot contrast, relative lung error (NEMA phantom), and image noise were assessed. Results. In all cases, absolute activity and activity concentration were measured within 10% of the expected value. Recovery coefficients and hot contrast in hot inserts did not vary appreciably with count statistics. RC converged at 16 iterations for insert size > 22 mm. Relative lung errors were comparable to PET levels indicating the efficient integration of attenuation and scatter corrections with adequate detector modeling. Conclusions. The tested device provided accurate activity recovery within 10% of correct values; these performances are comparable to current generation PET/CT systems

    Tail asymptotics of light-tailed Weibull-like sums

    Get PDF
    Abstract: We consider sums of n i.i.d. random variables with tails close to exp{−x^β} for some β > 1. Asymptotics developed by Rootzén (1987) and Balkema, Klüppelberg, and Resnick (1993) are discussed from the point of view of tails rather than of densities, using a somewhat different angle, and supplemented with bounds, results on a random number N of terms, and simulation algorithms

    The statistical mechanics of complex signaling networks : nerve growth factor signaling

    Full text link
    It is becoming increasingly appreciated that the signal transduction systems used by eukaryotic cells to achieve a variety of essential responses represent highly complex networks rather than simple linear pathways. While significant effort is being made to experimentally measure the rate constants for individual steps in these signaling networks, many of the parameters required to describe the behavior of these systems remain unknown, or at best, estimates. With these goals and caveats in mind, we use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. To establish the usefulness of our approach, we have applied our methods towards modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. Using our approach, we are able to extract predictions that are highly specific and accurate, thereby enabling us to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. We show that extracting biologically relevant predictions from complex signaling models appears to be possible even in the absence of measurements of all the individual rate constants. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems wherein particular ''soft'' combinations of parameters can be varied over wide ranges without impacting the final output and demonstrating that a few ''stiff'' parameter combinations center around the paramount regulatory steps of the network. We refer to this property -- which is distinct from robustness -- as ''sloppiness.''Comment: 24 pages, 10 EPS figures, 1 GIF (makes 5 multi-panel figs + caption for GIF), IOP style; supp. info/figs. included as brown_supp.pd

    The bridge between social identity and community capital on the path to recovery and desistance

    Get PDF
    It has long been recognised that changes in social networks (and the underpinning changes in personal and social identity) are strong predictors of both desistance from crime and recovery from substance use. Building on existing work attempting to measure and shift social networks and transitions to prosocial groups, the current study provides pilot data from prisoners and family members about a visualisation technique widely used in specialist addiction treatment (node-link mapping) to map opportunities for linkage to prosocial groups and networks. The data presented in the paper are from a small-scale feasibility pilot. This suggests both bonding and bridging capital in prisoner populations due for release and the diversity of community capital opportunities that exists in this population. The implications of this work are significant for substance users and offenders pending return to the community, and has implications around resettlement and reintegration support for probation staff in prisons and in the community. The paper emphasises the importance of mapping connectedness as a key component of planning for reintegration back into the community for those working with offenders who are aspiring to achieve desistance and recovery

    Microstructural enrichment functions based on stochastic Wang tilings

    Full text link
    This paper presents an approach to constructing microstructural enrichment functions to local fields in non-periodic heterogeneous materials with applications in Partition of Unity and Hybrid Finite Element schemes. It is based on a concept of aperiodic tilings by the Wang tiles, designed to produce microstructures morphologically similar to original media and enrichment functions that satisfy the underlying governing equations. An appealing feature of this approach is that the enrichment functions are defined only on a small set of square tiles and extended to larger domains by an inexpensive stochastic tiling algorithm in a non-periodic manner. Feasibility of the proposed methodology is demonstrated on constructions of stress enrichment functions for two-dimensional mono-disperse particulate media.Comment: 27 pages, 12 figures; v2: completely re-written after the first revie
    corecore