Application of single-level,pointwise algebraic,and smoothed aggregation multigrid methods to direct numerical simulations of incompressible turbulent flows

Single- and multi-level iterative methods for sparse linear systems are applied to unsteady flow simulations via implementation into a direct numerical simulation solver for incompressible turbulent flows on unstructured meshes. The performance of these solution methods, implemented in the well-established SAMG and ML packages, are quantified in terms of computational speed and memory consumption, with a direct sparse LU solver (SuperLU) used as a reference. The classical test case of unsteady flow over a circular cylinder at low Reynolds numbers is considered, employing a series of increasingly fine anisotropic meshes. As expected, the memory consumption increases dramatically with the considered problem size for the direct solver. Surprisingly, however, the computation times remain reasonable. The speed and memory usage of pointwise algebraic and smoothed aggregation multigrid solvers are found to exhibit near-linear scaling. As an alternative to multi-level solvers, a single-level ILUT-preconditioned GMRES solver with low drop tolerance is also considered. This solver is found to perform sufficiently well only on small meshes. Even then, it is outperformed by pointwise algebraic multigrid on all counts. Finally, the effectiveness of pointwise algebraic multigrid is illustrated by considering a large three-dimensional direct numerical simulation case using a novel parallelization approach on a large distributed memory computing cluster.     

Learning to Be Thoughtless: Social Norms and Individual Computation

This paper extends the literature on the evolution of norms with anagent-based modelcapturing a phenomenon that has been essentially ignored, namely thatindividual thought – orcomputing – is often inversely related to the strength of a social norm.Once a norm isentrenched, we conform thoughtlessly. In this model, agents learn how tobehave (what normto adopt), but – under a strategy I term Best Reply to Adaptive SampleEvidence – they also learnhow much to think about how to behave. How much they are thinking affects howthey behave,which – given how others behave – affects how much they think. Inshort, there is feedbackbetween the social (inter-agent) and internal (intra-agent) dynamics. Inaddition, we generate thestylized facts regarding the spatio-temporal evolution of norms: localconformity, global diversity,and punctuated equilibria.     

Parametric embedding for class visualization

We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.     

Bovine muscle shortening and protein degradation after electrical stimulation, excision and chilling

Electrical stimulation-dependent improvement in beef tenderness resulted from mechanisms other than avoidance of cold shortening in excised muscle chilled at a normal rate (10°C at 10h post-stimulation). At normal chilling rate, electrical stimulation enhanced degradation of the myofibrillar proteins, alpha actinin and troponin-T, and increased the amount of a 30 000 dalton protein, as assessed by gel electrophoresis, whereas sarcomere lengths were not different from unstimulated muscle. Under slightly accelerated chilling conditions (10°C at 5 h post stimulation), electrical stimulation prevented cold shortening but the meat was more tender than, and had the same sarcomere length as, unstimulated muscle chilled to 10°C in 10 h. Electrical stimulation did not improve the tenderness of beef chilled at a rapid rate (10°C at 2 h post stimulation), nor did it prevent cold shortening when muscles were chilled rapidly.     

Apparatus for the high temperature measurement of the Seebeck coefficient in thermoelectric materials

The Seebeck coefficient is a physical parameter routinely measured to identify the potential thermoelectric performance of a material. However, researchers employ a variety of techniques, conditions, and probe arrangements to measure the Seebeck coefficient, resulting in conflicting materials data. To compare and evaluate these methodologies, and to identify optimal Seebeck coefficient measurement protocols, we have developed an improved experimental apparatus to measure the Seebeck coefficient under multiple conditions and probe arrangements (300 K-1200 K). This paper will describe in detail the apparatus design and instrumentation, including a discussion of its capabilities and accuracy as measured through representative diagnostics. In addition, this paper will emphasize the techniques required to effectively manage uncertainty in high temperature Seebeck coefficient measurements.     

Examining cognitive function across the lifespan using a mobile application

Many studies conducted in a laboratory or university setting are limited by funding, personnel, space, and time constraints. In the present study, we introduce a method of data collection using a mobile application that circumvents these typical experiment administration issues. Using the application, we examined cross-sectional age differences in cognitive function. We obtained data from more than 15,000 participants and replicated specific patterns of age-related differences in cognition. Using a subset of these participants, we also examined the processing speed account of age-related cognitive differences, and the association of exercise and leisure activity with cognitive function across the lifespan. We discuss the relative advantages and disadvantages of data collection with a mobile application, and provide recommendations for the use of this method in research.     

A state-of the-art survey of TOPSIS applications

Multi-Criteria Decision Aid (MCDA) or Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives across diverse industries. Among numerous MCDA/MCDM methods developed to solve real-world decision problems, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily across different application areas. In this paper, we conduct a state-of-the-art literature survey to taxonomize the research on TOPSIS applications and methodologies. The classification scheme for this review contains 266 scholarly papers from 103 journals since the year 2000, separated into nine application areas: (1) Supply Chain Management and Logistics, (2) Design, Engineering and Manufacturing Systems, (3) Business and Marketing Management, (4) Health, Safety and Environment Management, (5) Human Resources Management, (6) Energy Management, (7) Chemical Engineering, (8) Water Resources Management and (9) Other topics. Scholarly papers in the TOPSIS discipline are further interpreted based on (1) publication year, (2) publication journal, (3) authors’ nationality and (4) other methods combined or compared with TOPSIS. We end our review paper with recommendations for future research in TOPSIS decision-making that is both forward-looking and practically oriented. This paper provides useful insights into the TOPSIS method and suggests a framework for future attempts in this area for academic researchers and practitioners.     

Prosocial Emotions and Helping: The Moderating Role of Group Membership.

In this article, the authors introduce and test a group-level perspective on the role of empathy and interpersonal attraction in helping. In line with our predictions, Study 1, a longitudinal field study of 166 AIDS volunteers, confirmed that empathy was a stronger predictor of helping when the recipient of assistance was an in-group member than when that person was an out-group member. Also as hypothesized, attraction was a stronger predictor of helping when the recipient was an out-group member than when that person was an in-group member. Study 2 replicated and further extended these results in a laboratory experiment on spontaneous helping of a person with hepatitis. Strengthening the validity of the findings, in both studies the effects of empathy and attraction held up even when the authors statistically controlled for potential alternative predictors of helping. The theoretical and practical implications of these findings for helping in intergroup contexts are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)