High Resolution Measurements of the Temperature Dependence of the Roton Energy of Superfluid 4He

New measurements of the roton excitations in superfluid ⁴He have been made using the IRIS spectrometer (energy resolution 20 eV at the roton energy) at the ISIS spallation neutron source. The roton energy was determined over a temperature range of 0.56 to 1.61 K. High resolution (energy resolution <1 eV) neutron inelastic scattering measurements by Andersen et al.² of the dependence of the ⁴He roton energy on temperature have shown significant deviations from the expected behaviour; the temperature variation was found to be discontinuous and slower than predicted by the established roton-roton interaction theory due to Bedell, Pines and Zawadowski (BPZ). ³ We find that our results can be described well by the BPZ theory over this temperature range and we do not observe the anomalous behaviour reported by Andersen et al. We offer some explanations as to the origin of this apparent disagreement.     

Bearing parameter identification of rotor–bearing system using clustering-based hybrid evolutionary algorithm

A new bearing parameter identification methodology based on global optimization scheme using measured unbalance response of rotor–bearing system is proposed. A new hybrid evolutionary algorithm which is a clustering-based hybrid evolutionary algorithm (CHEA), is proposed for global optimization scheme to improve the convergence speed and global search ability. Clustering of individuals by using a neural network is introduced to evaluate the degree of mature of genetic evolution. After clustering-based genetic algorithm (GA), local search is carried out for each cluster to judge the convexity of each cluster. Finally, random search is adapted for extrasearching to find a potential global candidate, which could be missed in GA and local search. The proposed methodology can identify not only unknown bearing parameters but also unbalance information of disk by simply setting them as unknown parameters. Numerical example and experimental results were used to verify the effectiveness of the proposed methodology.     

Numerical Modeling of Cemented Mine Backfill Deposition

In current underground mining practice, it is common to use tailings, without added cement, to fill mined-out voids (“stopes”). If fine-grained tailings are used, the high placement rates and low permeability can often result in undrained loading conditions and, hence, lower effective stress, when assessed in the conventional manner. Where cement is added, the cement modifies the consolidation characteristics in a number of ways, including increasing the strength and stiffness, reducing the permeability, and inducing volumetric changes associated with the hydration reactions leading to “self-desiccation.” As a result, conventional consolidation-analysis techniques are unsuitable for assessing the behavior. The one-dimensional mine-tailings-consolidation program (MinTaCo) has been modified, and renamed CeMinTaCo, to couple cement hydration with conventional consolidation analysis. The fundamental theory behind the modifications is presented. The model is used to undertake a sensitivity study, which highlights some of the important features of the behavior of cemented backfill, and shows how complex interactions between the various properties produce some outcomes that are counterintuitive.     

Impaired processing of local geometric features during navigation in a water maze following hippocampal lesions in rats.

Hippocampal damage impairs navigation with respect to information provided by the shape of an arena. Recent evidence has suggested that normal rats use local geometric information, as opposed to a global geometric representation, to navigate to a correct corner. One implication of this pattern of results is that hippocampal lesions may impair processing of 1 or more of the local geometric features of an environment. The authors therefore investigated the effects of hippocampal cell loss in rats on navigation to a hidden goal with respect to a variety of local cues in an environment with a distinctive shape. Rats with lesions of the hippocampus were impaired in discriminating a right-angled corner from its mirror image. However, they were able to use cues provided by an acute-angled corner (Experiment 1) or a local polarizing cue (Experiment 2). In contrast, lesioned rats were impaired in discriminating long versus short walls (Experiment 3). Results indicate that the hippocampus plays a role in disambiguating locations by processing (metric) information related to the distance between corners. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"Task control and cognitive abilities of self and spouse in collaboration in middle-aged and older couples": Erratum.

Reports an error in "Task control and cognitive abilities of self and spouse in collaboration in middle-aged and older couples" by Cynthia A. Berg, Timothy W. Smith, Kelly J. Ko, Nancy J. M. Henry, Paul Florsheim, Gale Pearce, Bert N. Uchino, Michelle A. Skinner, Ryan M. Beveridge, Nathan Story and Kelly Glazer (Psychology and Aging, 2007[Sep], Vol 22[3], 420-427). Due to an editing mistake, the order of authorship was incorrect. The correct order is as follows: Berg, Smith, Ko, Beveridge, Story, Henry, Florsheim, Pearce, Uchino, Skinner, & Glazer. (The following abstract of the original article appeared in record 2007-13103-002.) Collaborative problem solving may be used by older couples to optimize cognitive functioning, with some suggestion that older couples exhibit greater collaborative expertise. The study explored age differences in 2 aspects of collaborative expertise: spouses' knowledge of their own and their spouse's cognitive abilities and the ability to fit task control to these cognitive abilities. The participants were 300 middle-aged and older couples who completed a hypothetical errand task. The interactions were coded for control asserted by husbands and wives. Fluid intelligence was assessed, and spouses rated their own and their spouse's cognitive abilities. The results revealed no age differences in couple expertise, either in the ability to predict their own and their spouse's cognitive abilities or in the ability to fit task control to abilities. However, gender differences were found. Women fit task control to their own and their spouse's cognitive abilities; men only fit task control to their spouse's cognitive abilities. For women only, the fit between control and abilities was associated with better performance. The results indicate no age differences in couple expertise but point to gender as a factor in optimal collaboration. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An efficient algorithm for superresolution in medium field imaging

In this paper, we study the problem of reconstruction of a high-resolution (HR) image from several blurred low-resolution (LR) image frames in medium field. The image frames consist of blurred, decimated, and noisy versions of a HR image. The HR image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a HR image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore HR images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach. This research was conducted with support from the Army Research Office Grant DAAD 19-03-1-0261 and the National Science Foundation Grant CCF-0429481. Research supported in part by RGC Grant Nos. 7130/02P, 7046/03P, 7035/04P and 7035/04P and FRG/04-05/II-51.     

Profiling with AspectJ

This paper investigates whether AspectJ can be used for efficient profiling of Java programs. Profiling differs from other applications of AOP (e.g. tracing), since it necessitates efficient and often complex interactions with the target program. As such, it was uncertain whether AspectJ could achieve this goal. Therefore, we investigate four common profiling problems (heap usage, object lifetime, wasted time and time‐spent) and report on how well AspectJ handles them. For each, we provide an efficient implementation, discuss any trade‐offs or limitations and present the results of an experimental evaluation into the costs of using it. Our conclusions are mixed. On the one hand, we find that AspectJ is sufficiently expressive to describe the four profiling problems and reasonably efficient in most cases. On the other hand, we find several limitations with the current AspectJ implementation that severely hamper its suitability for profiling. Copyright © 2006 John Wiley & Sons, Ltd.     

MINING SURPRISING PATTERNS AND THEIR EXPLANATIONS IN CLINICAL DATA

□ We present a new technique for interactively mining patterns and generating explanations by harnessing the expertise of domain experts. Key to the approach is the distinction between what is unexpected from the perspective of the computational data mining process and what is surprising to the domain experts and interesting relative to their needs. We demonstrate the potential of the approach for discovering patterns and generating rich explanations in a clinical domain. Discovering interesting facts in clinical data is a grand challenge, because medical practitioners and clinicians generally have exceptional knowledge in the problem domain in which they work, however, this knowledge is typically difficult to isolate computationally. To identify the desired surprising patterns, we formally record user knowledge and use that knowledge to filter and constrain the output from an objective data mining technique, with the user making the final judgement about whether a rule is surprising. Specifically, we introduce an unexpectedness algorithm based on association rule mining and Bayesian Networks and a ?-explanations technique for explanation generation to identify unexpected patterns. An implemented prototype is successfully demonstrated using a large clinical database recording incidence, prevalance, and outcome of dialysis and kidney transplant patients.     

Hybridization of stochastic reduced basis methods with polynomial chaos expansions

We propose a hybrid formulation combining stochastic reduced basis methods with polynomial chaos expansions for solving linear random algebraic equations arising from discretization of stochastic partial differential equations. Our objective is to generalize stochastic reduced basis projection schemes to non-Gaussian uncertainty models and simplify the implementation of higher-order approximations. We employ basis vectors spanning the preconditioned stochastic Krylov subspace to represent the solution process. In the present formulation, the polynomial chaos decomposition technique is used to represent the stochastic basis vectors in terms of multidimensional Hermite polynomials. The Galerkin projection scheme is then employed to compute the undetermined coefficients in the reduced basis approximation. We present numerical studies on a linear structural problem where the Youngs modulus is represented using Gaussian as well as lognormal models to illustrate the performance of the hybrid stochastic reduced basis projection scheme. Comparison studies with the spectral stochastic finite element method suggest that the proposed hybrid formulation gives results of comparable accuracy at a lower computational cost.