Automatic Generation of Redundant Models for Permutation Constraint Satisfaction Problems

If we have two representations of a problem as constraint satisfaction problem (CSP) models, it has been shown that combining the models using channeling constraints can increase constraint propagation in tree search CSP solvers. Handcrafting two CSP models for a problem, however, is often time-consuming. In this paper, we propose model induction, a process which generates a second CSP model from an existing model using channeling constraints, and study its theoretical properties. The generated induced model is in a different viewpoint, i.e., set of variables. It is mutually redundant to and can be combined with the input model, so that the combined model contains more redundant information, which is useful to increase constraint propagation. We also propose two methods of combining CSP models, namely model intersection and model channeling. The two methods allow combining two mutually redundant models in the same and different viewpoints respectively. We exploit the applications of model induction, intersection, and channeling and identify three new classes of combined models, which contain different amounts of redundant information. We construct combined models of permutation CSPs and show in extensive benchmark results that the combined models are more robust and efficient to solve than the single models.     

Approximate analysis of M/G/c/c state-dependent queueing networks

Congestion is ever present in most practical situations. We describe a methodology for approximate analysis of open state-dependent M/G/c/c queueing networks in which the service rate is subject to congestion, that is, it is a function of the number of customers in the system. Important performance measurements are easily computed with high accuracy, such as the blocking probability, throughput, expected number of customers in the system (known also as work-in-process), and expected waiting time. The methodology forms a basic building block useful in many practical applications and contexts. Computational results demonstrate that the methodology provides accurate results in many topological configurations as well as in the analysis of network evacuation problems in high-rise buildings.     

Conflicting social motives in negotiating groups.

Negotiators' social motives (cooperative vs. individualistic) influence their strategic behaviors. In this study, the authors used multilevel modeling and analyses of strategy sequences to test hypotheses regarding how negotiators' social motives and the composition of the group influence group members' negotiation strategies. Four-person groups negotiating a 5-issue mixed-motive decision-making task were videotaped, and the tapes were transcribed and coded. Group composition included 2 homogeneous conditions (all cooperators and all individualists) and 3 heterogeneous conditions (3 cooperators and 1 individualist, 2 cooperators and 2 individualists, 1 cooperator and 3 individualists). Results showed that cooperative negotiators adjusted their use of integrative and distributive strategies in response to the social-motive composition of the group, but individualistic negotiators did not. Results from analyses of strategy sequences showed that cooperators responded more systematically to others' behaviors than did individualists. They also redirected the negotiation depending on group composition. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Romantic attachment in individuals with physical disabilities.

Objective: To examine the relationship between adult attachment style and physical disability in intimate romantic relationships. Method: Participants were 50 individuals with adult-onset spinal cord injuries (SCI) and 50 individuals with congenital disabilities (CON) living in the community. The main outcome measures were adult attachment style and dyadic relationship adjustment. Results: Participants with SCI and CON did not differ in rates of secure versus insecure attachment, and the rates of neither group differed significantly from rates reported for persons without disability. Dyadic adjustment was clearly predicted by attachment variables and differed between the participants with SCI and those with CON; individuals with SCI reported greater total dyadic adjustment. Avoidance showed a strong negative association with dyadic satisfaction, but no association was found with dyadic cohesion. Social participation variables were associated with dyadic adjustment. For instance, mobility was positively associated with dyadic satisfaction. Conclusions: Dyadic adjustment in people with disabilities, as in other groups, is affected by attachment style, but disability and social participation variables may also affect dyadic adjustment. Clinicians should consider differences in attachment styles among persons with disabilities and their implications for intimate close relationships. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The factor structure of situational and dispositional versions of the Smith Irrational Beliefs Inventory in a Spanish student population.

This study attempted to identify and replicate the factor structure of English and Spanish versions of the Smith Irrational Beliefs Inventory (SIBI). Factor analyses of irrational beliefs have yielded conflicting results. In contrast to the results of studies on clinical populations, studies on college students have mostly resulted in unifactorial solutions. Factor analyses of situational and dispositional Spanish versions of the SIBI on 960 Spanish college students resulted in 7 factors: Negativity, Distorted Egocentrism, Perfectionism, Catastrophizing-Task Exaggeration, Minimizing-Avoiding, Needless Other- Blaming, and Distorted Isolation. The results suggest that the SIBI displays a consistent factor structure across cultures and situational/dispositional formats. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Particle Characterization and Settling Velocities for a Water Supply Reservoir during a Turbidity Event

Characterization of the particle population for a location in a water supply reservoir, Kensico Reservoir, N.Y., is documented for a high turbidity event, from its onset, through alum treatment and its waning. Supporting in situ measurements included the beam attenuation coefficient at 670?nm (c670) and 660?nm (c660) [surrogates of turbidity (Tn)], particle concentrations (N) and size distributions (PSDs), and size class specific settling velocities (SVs). Laboratory measurements included chemical and morphometric analyses of individual particles, and routine measurements of Tn. The turbidity is shown to be primarily derived from clay minerals, mostly in the size range of 1.5–6?μm. An initial high c670 level (40?m?1;Tn ～ 100?NTU) decreased sevenfold in less than 1?week in response to alum treatment that largely eliminated the particle size classes responsible for the elevated turbidity. Successful SV experiments, made using a laser in situ scattering and transmissometry (LISST) instrument, for seven particle size classes in the range of 1.25–129?μm yielded SV values of 0.17–69.4?m?day?1. Size classes larger than ～ 5?μm settled much slower than Stokes law predictions, before alum treatment, indicating that these classes existed as porous flocs or aggregates. Decreases in SVs following treatment suggest changes in floc character consistent with increased porosity. In situ measurements of c670, N, PSDs, and SVs can contribute to the development and testing of a multiple particle size class model to simulate fate, transport, and impacts of suspended particles.     

Algorithms for discrete and continuous multicommodity flow network interdiction problems

We consider a network interdiction problem on a multicommodity flow network, in which an attacker disables a set of network arcs in order to minimize the maximum profit that can be obtained from shipping commodities across the network. The attacker is assumed to have some budget for destroying (or “interdicting”) arcs, and each arc is associated with a positive interdiction expense. In this paper, we examine problems in which interdiction must be discrete (i.e., each arc must either be left alone or completely destroyed), and in which interdiction can be continuous (the capacities of arcs may be partially reduced). For the discrete problem, we describe a linearized model for optimizing network interdiction that is similar to previous studies in the field, and compare it to a penalty model that does not require linearization constraints. For the continuous case, we prescribe an optimal partitioning algorithm along with a heuristic procedure for estimating the optimal objective function value. We demonstrate on a set of randomly generated test data that our penalty model for the discrete interdiction problem significantly reduces computational time when compared to that consumed by the linearization model.     

Categorization of novel animals by patients with Alzheimer's disease and corticobasal degeneration.

We taught a novel animal category by rule-based and similarity-based processes to participants with Alzheimer's disease (AD), corticobasal degeneration (CBD), and healthy age-matched participants. Healthy participants successfully categorized by either process. AD patients' rule-based categorization was impaired, while their similarity-based categorization resembled that of healthy participants. Correlations of AD patients' performance with measures of executive functioning suggested a deficit in the cognitive resources necessary for engaging rule-based categorization. The contribution of limited executive resources to categorization difficulty in AD was further demonstrated in a second experiment in which features determining category membership were of lower salience. CBD patients were relatively impaired at similarity-based processing, suggesting that qualitatively distinct categorization processes can be selectively compromised in patients with focal neurodegenerative diseases. Moreover, AD patients' impaired categorization correlated with performance on a measure of semantic memory, implicating this categorization deficit in AD patients' semantic memory difficulty. (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)     

Can emotions be truly group level? Evidence regarding four conceptual criteria.

Recent advances in understanding prejudice and intergroup behavior have made clear that emotions help explain people's reactions to social groups and their members. Intergroup emotions theory (D. M. Mackie, T. Devos, & E. R. Smith, 2000; E. R. Smith, 1993) holds that intergroup emotions are experienced by individuals when they identify with a social group, making the group part of the psychological self. What differentiates such group-level emotions from emotions that occur purely at the individual level? The authors argue that 4 key criteria define group-level emotions: Group emotions are distinct from the same person's individual-level emotions, depend on the person's degree of group identification, are socially shared within a group, and contribute to regulating intragroup and intergroup attitudes and behavior. Evidence from 2 studies supports all 4 of these predictions and thus points to the meaningfulness, coherence, and functionality of group-level emotions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)