Cinderella and the wicked stepmother: How do we perceive step and biological families?

Undergraduate psycholog)' students from stepfamilies (always one step and one biological parent) and biologically intact families (always both biological parents) participated in this study. The goal was to assess perceptions of stepfamilies (N = 106, Nstepfamilies = 44, Nbiological = 62, age range = 17.17 to 28.92 years, M = 19.46 years). One theoretical perspective, the social stigma h)'pothesis, argues that there is a stigma attached to stepfamilies, or that stepfamilies are consistentiy associated with negative stereotypes. In the current study, participants were assessed on a number of variables, including a semantic differential scale, a perceived conflict scale and a perceived general satisfaction scale. It was found that a consistently negative view of stepfamilies was prevalent. Furthermore, the negative stereotypes existed, irrespective of participant family type. Results support the theoretical view that stepfamilies are stereotypically viewed as negative, when compared to biological families.

Genetic algorithm optimization of adaptive multi-scale GLCM features

We introduce a new second-order method of texture analysis called Adaptive Multi-Scale Grey Level Co-occurrence Matrix (AMSGLCM), based on the well-known Grey Level Co-occurrence Matrix (GLCM) method. The method deviates significantly from GLCM in that features are extracted, not via a fixed 2D weighting function of co-occurrence matrix elements, but by a variable summation of matrix elements in 3D localized neighborhoods. We subsequently present a new methodology for extracting optimized, highly discriminant features from these localized areas using adaptive Gaussian weighting functions. Genetic Algorithm (GA) optimization is used to produce a set of features whose classification worth is evaluated by discriminatory power and feature correlation considerations. We critically appraised the performance of our method and GLCM in pairwise classification of images from visually similar texture classes, captured from Markov Random Field (MRF) synthesized, natural, and biological origins. In these cross-validated classification trials, our method demonstrated significant benefits over GLCM, including increased feature discriminatory power, automatic feature adaptability, and significantly improved classification performance.

HPGR model verification and scale-up

This paper summarises test results that were used to validate a model and scale-up procedure of the high pressure grinding roll (HPGR) which was developed at the JKMRC by Morrell et al. [Morrell, Lim, Tondo, David,1996. Modelling the high pressure grinding rolls. In: Mining Technology Conference, pp. 169-176.]. Verification of the model is based on results from four data sets that describe the performance of three industrial scale units fitted with both studded and smooth roll surfaces. The industrial units are currently in operation within the diamond mining industry and are represented by De Beers, BHP Billiton and Rio Tinto. Ore samples from the De Beers and BHP Billiton operations were sent to the JKMRC for ore characterisation and HPGR laboratory-scale tests. Rio Tinto contributed an historical data set of tests completed during a previous research project. The results conclude that the modelling of the HPGR process has matured to a point where the model may be used to evaluate new and to optimise existing comminution circuits. The model prediction of product size distribution is good and has been found to be strongly dependent of the characteristics of the material being tested. The prediction of throughput and corresponding power draw (based on throughput) is sensitive to inconsistent gap/diameter ratios observed between laboratory-scale tests and full-scale operations. (C) 2004 Elsevier Ltd. All rights reserved.

The gambling related cognitions scale (GRCS): development, confirmatory factor validation and psychometric properties

Aims The aims of this study are to develop and validate a measure to screen for a range of gambling-related cognitions (GRC) in gamblers. Design and participants A total of 968 volunteers were recruited from a community-based population. They were divided randomly into two groups. Principal axis factoring with varimax rotation was performed on group one and confirmatory factor analysis (CFA) was used on group two to confirm the best-fitted solution. Measurements The Gambling Related Cognition Scale (GRCS) was developed for this study and the South Oaks Gambling Screen (SOGS), the Motivation Towards Gambling Scale (MTGS) and the Depression Anxiety Stress Scale (DASS-2 1) were used for validation. Findings Exploratory factor analysis performed using half the sample indicated five factors, which included interpretative control/bias (GRCS-IB), illusion of control (GRCS-IC), predictive control (GRCS-PC), gambling-related expectancies (GRCS-GE) and a perceived inability to stop gambling (GRCS-IS). These accounted for 70% of the total variance. Using the other half of the sample, CFA confirmed that the five-factor solution fitted the data most effectively. Cronbach's alpha coefficients for the factors ranged from 0.77 to 0.91, and 0.93 for the overall scale. Conclusions This paper demonstrated that the 23-item GRCS has good psychometric properties and thus is a useful instrument for identifying GRC among non-clinical gamblers. It provides the first step towards devising/adapting similar tools for problem gamblers as well as developing more specialized instruments to assess particular domains of GRC.

A cognitive genetic algorithm for power distribution system planning

Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.

Establishing representative no-take areas in the Great Barrier Reef : Large scale implementation of theory on marine protected areas

The Great Barrier Reef Marine Park, an area almost the size , of Japan, has a new network of no-take areas that significantly improves the protection of biodiversity. The new marine park zoning implements, in a quantitative manner, many of the theoretical design principles discussed in the literature. For example, the new network of no-take areas has at least 20% protection per bioregion, minimum levels of protection for all known habitats and special or unique features, and minimum sizes for no-take areas of at least 10 or 20 kat across at the smallest diameter Overall, more than 33% of the Great Barrier Reef Marine Park is now in no-take areas (previously 4.5%). The steps taken leading to this outcome were to clarify to the interested public why the existing level of protection wets inadequate; detail the conservation objectives of establishing new no-take areas; work with relevant and independent experts to define, and contribute to, the best scientific process to deliver on the objectives; describe the biodiversity (e.g., map bioregions); define operational principles needed to achieve the objectives; invite community input on all of The above; gather and layer the data gathered in round-table discussions; report the degree of achievement of principles for various options of no-take areas; and determine how to address negative impacts. Some of the key success factors in this case have global relevance and include focusing initial communication on the problem to be addressed; applying the precautionary principle; using independent experts; facilitating input to decision making; conducting extensive and participatory consultation; having an existing marine park that encompassed much of the ecosystem; having legislative power under federal law; developing high-level support; ensuring agency Priority and ownership; and being able to address the issue of displaced fishers.

Differential distribution of ammonia- and nitrite-oxidising bacteria in flocs and granules from a nitrifying/denitrifying sequencing batch reactor

A lab-scale sequencing batch reactor was operated with alternating anoxic/aerobic conditions for nitrogen removal. Flocs and granules co-existed in the same reactor, with distinct aggregate structure and size, for over 180 days of reactor operation' Process data showed complete nitrogen removal, with temporary nitrite accumulation before full depletion of ammonia in the aerobic phase. Microbial quantification of the biomass by fluorescence in situ hybridisation showed that granules contained most of the nitrite-oxidising bacteria (NOB) whereas the ammonium-oxidising bacteria (AOB) seemed to be more abundant in the flocs. This was supported by microsensor measurements, which showed a higher potential of NO2- uptake than NH4 uptake in the granules. The segregation is possibly linked to the different growth rates of the two types of nitrifiers and the reactor operational conditions, which produced different sludge retention time for flocs and granules. The apparent physical separation of AOB and NOB in two growth forms could potentially affect mass transfer of NO2- from AOB to NOB, but the data presented here shows that it did not impact negatively on the overall nitrogen removal. (c) 2006 Elsevier Inc. All rights reserved.

Applying network analysis to the conservation of habitat trees in urban environments: a case study from Brisbane, Australia

In Australia more than 300 vertebrates, including 43 insectivorous bat species, depend on hollows in habitat trees for shelter, with many species using a network of multiple trees as roosts, We used roost-switching data on white-striped freetail bats (Tadarida australis; Microchiroptera: Molossidae) to construct a network representation of day roosts in suburban Brisbane, Australia. Bats were caught from a communal roost tree with a roosting group of several hundred individuals and released with transmitters. Each roost used by the bats represented a node in the network, and the movements of bats between roosts formed the links between nodes. Despite differences in gender and reproductive stages, the bats exhibited the same behavior throughout three radiotelemetry periods and over 500 bat days of radio tracking: each roosted in separate roosts, switched roosts very infrequently, and associated with other bats only at the communal roost This network resembled a scale-free network in which the distribution of the number of links from each roost followed a power law. Despite being spread over a large geographic area (> 200 km(2)), each roost was connected to others by less than three links. One roost (the hub or communal roost) defined the architecture of the network because it had the most links. That the network showed scale-free properties has profound implications for the management of the habitat trees of this roosting group. Scale-free networks provide high tolerance against stochastic events such as random roost removals but are susceptible to the selective removal of hub nodes. Network analysis is a useful tool for understanding the structural organization of habitat tree usage and allows the informed judgment of the relative importance of individual trees and hence the derivation of appropriate management decisions, Conservation planners and managers should emphasize the differential importance of habitat trees and think of them as being analogous to vital service centers in human societies.

Small-scale randomized controlled trials need more powerful methods of mediational analysis than the Baron-Kenny method

Objective: To devise more-effective physical activity interventions, the mediating mechanisms yielding behavioral change need to be identified. The Baron-Kenny method is most commonly used. but has low statistical power and May not identify mechanisms of behavioral change in small-to-medium size Studies. More powerful statistical tests are available, Study Design and Setting: Inactive adults (N = 52) were randomized to either a print or a print-plus-telephone intervention. Walking and exercise-related social support Were assessed at baseline, after file intervention, and 4 weeks later. The Baron-Kenny and three alternative methods of mediational analysis (Freedman-Schatzkin; MacKinnon et al.: bootstrap method) were used to examine the effects of social support on initial behavior change and maintenance. Results: A significant mediational effect of social support on initial behavior change was indicated by the MacKinnon et al., bootstrap. and. marginally. Freedman-Schatzkin methods, but not by the Baron-Kenny method. No significant mediational effecl of social support on maintenance of walking was found. Conclusions: Methodologically rigorous intervention studies to identify mediators of change in physical activity are costly and labor intensive, and may not be feasible with large samples. The Use of statistically powerful tests of mediational effects in small-scale studies can inform the development of more effective interventions. (C) 2006 Elsevier Inc. All rights reserved.

Differential diffusion: Often a finite-mising length effect

Many instances of differential diffusion, i e, different species having different turbulent diffusion coefficients in the same flow, can be explained as a finite mixing length effect. That is, in a simple mixing length scenario, the turbulent diffusion coefficient has the form 1 ( m )2 m m c l K w l OL   =  +    where, wm is the mixing velocity, lm the mixing length and Lc the overall distribution scale for a particular species. The first term represents the familiar gradient diffusion while the second term becomes important when lm/Lc is finite. This second term shows that different species will have different diffusion coefficients if they have different overall distribution scales. Such different Lcs may come about due to different boundary conditions and different intrinsic properties (molecular diffusivity, settling velocity etc) for different species. For momentum transfer in turbulent oscillatory boundary layers the second term is imaginary and explains observed phase leads of shear stresses ahead of velocity gradients.

Differential evolution based total transfer capability assessment with optimal dispatch

In this paper, a new differential evolution (DE) based power system optimal available transfer capability (ATC) assessment is presented. Power system total transfer capability (TTC) is traditionally solved by the repeated power flow (RPF) method and the continuation power flow (CPF) method. These methods are based on the assumption that the productions of the source area generators are increased in identical proportion to balance the load increment in the sink area. A new approach based on DE algorithm to generate optimal dispatch both in source area generators and sink area loads is proposed in this paper. This new method can compute ATC between two areas with significant improvement in accuracy compared with the traditional RPF and CPF based methods. A case study using a 30 bus system is given to verify the efficiency and effectiveness of this new DE based ATC optimization approach.