Workplace conflict, bullying, and counterproductive behaviors

Using a multi-method approach, this paper presents both a qualitative and quantitative examination of workplace conflict, the emotional reactions to bullying and counterproductive behaviors. Three studies were undertaken for the present research. Data for Study 1 emerged from semi-structured interviews conducted with 50 group leaders and members from six workgroups in two large organizations. Interviews were transcribed and analyzed using systematic interpretative techniques. Findings from Study 1 showed that conflict induced a variety of emotional and behavioral responses. Data from Study 2 were collected from 660 employees from 7 public sector organizations using a structured open-ended survey. Results from Study 2 revealed that the majority of respondents perceived their managers as bullies. Study 3 surveyed 510 staff in 122 workgroups from five organizations. Regression analysis revealed that differing conflict events were associated with bullying, emotional reactions and counterproductive behaviors. In particular, prolonged conflict increased incidents of bullying. Higher levels of bullying were predictive of workplace counterproductive behaviors such as purposely wasting company material and supplies, purposely doing one's work incorrectly and purposely damaging a valuable piece of property belonging to the employer.

Physical activity as a dimension of family life for lower primary school children

While questions of children's engagement in physical activity are being widely debated, little is known about how physical activity is valued and managed within families. This paper reports on qualitative data from a multi-method study on lower primary aged children. The focus of the broader study was to determine the relationships between young children's physical activity patterns, skills, and recreational interests, and their families' location, income, commitment to physical activity, and other responsibilities. Drawing on interviews with 12 purposively selected families, it was found that physical activity was highly valued across different family contexts, that children's engagement was shaped by their interests, friendships, and safety, and that issues such as income, family configuration, parental work commitments, and transport were potential barriers to further engagement.

'I could do with a pair of wings': Perspectives on physical activity, bodies and health from young Australian children

There is little research that reports children's perspectives on physical activity, bodies and health. This paper, drawn from a larger multi-method study on physical activity in the lives of seven- and eight-year-old Australian children, attempts to 'give a voice' to 13 children's views. Interviews focused on children's activity preferences and related decision making and motivations pertaining to these activities, as well as how they thought about the relationships between physical activity, health and their bodies. Data suggest some tensions surrounding the importance of fun for children alongside their awareness of 'healthist' discourses that require self-monitoring and improvement.

Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

Cluster measurement and benchmarking - A recent Welsh approach

Drawing on extensive academic research and theory on clusters and their analysis, the methodology employed in this pilot study (sponsored by the Welsh Assembly Government’s Economic Research Grants Assessment Board) seeks to create a framework for reviewing and monitoring clusters in Wales on an ongoing basis, and generate the information necessary for successful cluster development policy to occur. The multi-method framework developed and tested in the pilot study is designed to map existing Welsh sectors with cluster characteristics, uncover existing linkages, and better understand areas of strength and weakness. The approach adopted relies on synthesising both quantitative and qualitative evidence. Statistical measures, including the size of potential clusters, are united with other evidence on input-output derived inter-linkages within clusters and to other sectors in Wales and the UK, as well as the export and import intensity of the cluster. Multi Sector Qualitative Analysis is then designed for competencies/capacity, risk factors, markets, types and crucially, the perceived strengths of cluster structures and relationships. The approach outlined above can, with the refinements recommended through the review process, provide policy-makers with a valuable tool for reviewing and monitoring individual sectors and ameliorating problems in sectors likely to decline further.

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.

Field evaluation of a novel colorimetric method - Double-site enzyme-linked lactate dehydrogenase immunodetection assay - To determine drug susceptibilities of Plasmodium falciparum clinical isolates from northwestern Thailand

A double-site enzyme-linked lactate dehydrogenase enzyme inummodetection assay was tested against field isolates of Plasmodium falciparum for assessing in vitro drug susceptibilities to a wide range of antimalarial drugs. Its sensitivity allowed the use of parasite densities as low as 200 parasites/mul of blood. Being a nonisotopic, colorimetric assay, it lies within the capabilities of a modest laboratory at the district level.

The cross-entropy method for continuous multi-extremal optimization

In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with non-linear constraints.

Evaluation of parameters effective in FRP shear strengthening of RC beams using FE method

Shear strengthening is required when an RC beam is found deficient in shear, or when its shear capacity falls below its flexural capacity after flexural strengthening. A recent technique for the shear strengthening of RC beams is to provide additional FRP web reinforcement, commonly in the form of bonded external FRP strips/sheets. Over the last few years, several experimental studies have been conducted on this new strengthening technique, which has established its effectiveness. While experimental methods of investigation are extremely useful in obtaining information about the composite behaviour of FRP and reinforced concrete, the use of numerical models such as the one presented in this paper helps in developing a good understanding of the behaviour at lower costs. In the study presented in this paper, ANSYS finite element program is used to examine the response of beams strengthened in shear by FRPs. The FE model is calibrated against test results performed at the University of Kentucky. Once validated, the model is used to examine the influence of fibre orientation, compressive strength of concrete, area of tensile and compressive reinforcements, and amount and distance between stirrups on the strength and ductility of FRP strengthened beam.