Assessing the strain experienced by managers and professional Australian footballers using an augmented job strain model

Generic models of job stress, such as the Job Strain Model (JSM), have recently been criticised for focusing on a small number of general work characteristics while ignoring those that are occupation-specific (Sparks & Cooper, 1999). However this criticism is based on limited research that has not examined the relative influence of all three dimensions of the JSM - job demand, job control and social support - and job-specific stressors. The JSM is the most commonly used model underpinning large-scale occupational stress research (Fox, Dwyer, & Ganster, 1993) and is regarded as the most influential model in the research on the psycho-social work environment, stress and disease in recent times (Kristensen, 1995). This thesis addresses the lack of information on the relative influence of the JSM and job-specific stressors by assessing the capacity of an augmented JSM to predict the strain experienced by managers and professional Australian footballers. The augmented JSM consisted of job-specific stressors in addition to the generic components of the model. Managers and professional Australian footballers represent two very different occupational groups. While the day-today roles of a manager include planning, organising, monitoring and controlling (Carroll & Gillen, 1987), the working life of a professional Australian footballer revolves around preparing for and playing football (Shanahan, 1998). It was expected that the large differences in the work undertaken by managers and professional Australian footballers would maximise the opportunities for identifying job-specific stressors and measuring the extent that these vary from one group to the next. The large disparity between managers and professional footballers was also used to assess the cross-occupational versatility of the JSM when it had been augmented by job-specific stressors. This thesis consisted of three major studies. Study One involved a survey of Australian managers, while studies Two and Three focused on professional Australian footballers. The latter group was under-represented in the literature, and as a result of the lack of information on the stressors commonly experienced by this group, an in-depth qualitative study was undertaken in Study Two. The results from Study Two then informed the survey of professional footballers that was conducted in Study Three. Contrary to previous research examining the relative influence of generic and job-specific stressors, the results only provided moderate support for augmenting the JSM with job-specific stressors. Instead of supporting the versatility of the augmented JSM, the overall findings reinforced the broad relevance of the original JSM. Of the four health outcomes measured in Studies One and Three, there was only one - the psychological health of professional Australian footballers - where the proportion of total variance explained by job-specific stressors exceeded 13%. Despite the generally strong performance of the JSM across the two occupational groups, the importance of demand, control and support diminished when examining the less conventional occupation of professional football. The generic model was too narrow to capture the highly specific work characteristics that are important for this occupational group and, as a result, the job-specific stressors explained significantly more of the strain over and above that already provided by the generic model. These findings indicate that when investigating the stressors experienced by conventional occupational groups such as managers, the large amount resources required to identify job-specific stressors are unlikely to be cost-effective. In contrast, the influence of the more situation specific stressors is significantly greater in unconventional occupations and thus the benefits of identifying these non-generic stressors are more likely to outweigh the costs. Studies One and Three identified strong connections between job-specific stressors and important characteristics of the occupation being studied. These connections were consistent with previous research and suggest that before attempting to identify job-specific stressors, researchers need to first become familiar with the nature and context of the occupation. The final issue addressed in this thesis was the role of work and non-work support. The findings indicate that the support provided by supervisors and colleagues was a significant predictor of wellbeing for both managers and professional footballers. In contrast, the level of explained strain accounted for by non-work support was not significant. These results indicate that when developing strategies to protect and enhance employee well-being, particular attention should be given to monitoring and, where necessary, boosting the effectiveness of work-based support. The findings from this thesis have been fed back to the management and sporting communities via conference presentations and peer-reviewed journals (refer pp 220-221). All three studies have been presented at national and international conferences and, overall, were well received by participants. Similarly, the methods, results and major findings arising from Studies One and Two have been critiqued by anonymous reviewers from two international journals. These papers have been accepted for publication in 2001 and 2002 and feedback from the reviewers indicates that the findings represent a significant and unique contribution to the literature. The results of Study Three are currently under review by a sports psychology journal.

Bivariate variance-component analysis, with application to systolic blood pressure and total cholesterol levels in the Framingham Heart Study

Background :
The correlations between systolic blood pressure (SBP) and total cholesterol levels (CHOL) might result from genetic or environmental factors that determine variation in the phenotypes and are shared by family members. Based on 330 nuclear families in the Framingham Heart Study, we used a multivariate normal model, implemented in the software FISHER, to estimate genetic and shared environmental components of variation and genetic and shared environmental correlation between the phenotypes. The natural logarithm of the phenotypes measured at the last visit in both Cohort 1 and 2 was used in the analyses. The antihypertensive treatment effect was corrected before adjustment of the systolic blood pressure for age, sex, and cohort.
Results :
The univariate correlation coefficient was statistically significant for sibling pairs and parent-offspring pairs, but not significant for spouse pairs. In the bivariate analysis, the cross-trait correlation coefficients were not statistically significant for all relative pairs. The shared environmental correlation was statistically significant, but the genetic correlation was not significant.
Conclusion :
There is no significant evidence for a close genetic correlation between systolic blood pressure and total cholesterol levels. However, some shared environmental factors may determine the variation of both phenotypes.

An interdependence analysis of Australian house prices using variance decomposition

Purpose - The purpose of this paper is to analyse the interdependencies of the house price growth rates in Australian capital cities.
Design/methodology/approach - A vector autoregression model and variance decomposition are introduced to estimate and interpret the interdependences among the growth rates of regional house prices in Australia.
Findings - The results suggest the eight capital cities can be divided into three groups: Sydney and Melbourne; Canberra, Adelaide and Brisbane; and Hobart, Perth and Darwin.
Originality/value - Based on the structural vector autoregression model, this research develops an innovative interdependence analysis approach of regional house prices based on a variance decomposition method.

Optimal management of a goose flyway : migrant management at minimum cost

1. We adopt a ‘whole flyway’ approach to modelling scenarios for protecting migratory birds, aiming at efficient and cost-effective conservation of flyway habitat.

2. We developed a model to minimize flyway management costs while safeguarding a migrating bird population. The model assumes that the intensity of the birds’ use of sites can be manipulated by varying management regimes (with concomitant costs) and that the birds make optimal use of the conditions created along their flyway.

3. We used dynamic programming to find the sequence of migratory decisions that maximizes the fitness of the migrants given a range of management scenarios, followed by a management cost estimate of all these scenarios and selection of those scenarios yielding an optimal solution from both an economic and the migrants’ perspective.

4. Using the population of pink-footed geese Anser brachyrhynchus that breed in Svalbard as an example, we calculated that the cheapest management scenario given current compensation payment rates at the various goose stopover sites yielded a 35% cost saving over current management. This cheapest scenario provides a migration itinerary that is very similar to the current itinerary used by the geese. This is fortuitous since changing environmental conditions may put the migrants at risk.

5. Synthesis and application. Given the global threats to migratory birds, developing a framework for efficient and effective conservation of flyway habitat is an urgent need. Such a framework may likewise be used to assist in controlling migrants causing conflict with agriculture, such as several goose species, in an economic and responsible fashion. Our suggested exemplified framework identified large unexplainable differences in management costs between regions. Differences in management costs between staging sites for birds make big differences to the optimal management of a flyway. Hence, to achieve efficient and effective management of migratory birds, we firstly need an objective assessment of the cost of management in different locations, followed by a modelling approach as here advocated, and followed up by a collaborative action of managers along the entire flyway.

The influence of parents, siblings and peers on pre- and early-teen smoking : a multilevel model

Introduction and Aims. Despite considerable success in tobacco control, many teenagers in Australia and other industrialised countries still smoke tobacco. There is mixed evidence on the relative influence of proximal social networks (parents/siblings/peers) on pre- and early-teen smoking, and no research has examined how these influences compare after accounting for school- and community-level effects.The aim of this study was to compare the relative influences of parents, siblings and peers, after accounting for school- and community-level variation in smoking.

Design and Methods. A cross-sectional fixed and random effects model of smoking prevalence was used, with individuals (n = 7314) nested within schools (n = 231) nested within communities (n = 30). Grade 6 and 8 students (modal ages 11 and 13 years) completed an on-line survey. Key variables included parent/sibling/peer use. Controls included alcohol involvement, sensation seeking, pro-social beliefs, laws/norms about substance use and school commitment.

Results.There was significant variation in smoking at both the school and community levels, supporting the need for a multilevel model. Individual-level predictors accounted for much of the variance at higher levels. The strongest effects were for number of friends who smoke, sibling smoking and alcohol involvement. Smaller significant effects were found for parent smoking. At the community level, socioeconomic disadvantage was significant, but community-level variance in pro-social and drug-related laws/norms was not related to smoking.

Discussion and Conclusions. Cross-level interactions were generally non-significant. Early teenage smoking was best explained by sibling and peer smoking, and individual risks largely accounted for the substantial variation observed across schools and communities. In terms of future tobacco control, findings point to the utility of targeting families in disadvantaged communities.[Kelly AB, O'Flaherty M, Connor JP, Homel R, Toumbourou JW, Patton GC, Williams J. The influence of parents, siblings and peers on pre- and early-teen smoking: A multilevel model.

A novel romance : the technology acceptance model with emotional attachment

E-readers, or devices designed primarily for reading e-books, are taking the world by storm. Several papers in library studies and education have examined e-book consumption for academic reading. However, no previous marketing study has investigated consumers’ adoption of e-readers for pleasure reading. We address this gap by testing an extended version of the Technology Acceptance Model (TAM) with emotional attachment (TAME) in this context. Consumers’ attachment to paper books is proposed as a barrier to their adoption of e-readers. This speaks to a key deficiency of the TAM, being its focus on cognition at the expense of consumer emotion. A three-phase study finds support for the TAME, with 64% of the variance explained in consumers’ intentions to adopt e-readers. Emotional attachment to paper books is found to be weakly and negatively associated with consumers’ attitude toward using e-readers. The qualitative findings suggest that e-reader adoption may not involve a binary choice between paper and e-formats.

Multiple actuator fault tolerance for static nonlinear systems based on minimum velocity jump

Static nonlinear systems are common when the model of the kinematics of mechanical or civil structures is analyzed for instance kinematics of robotic manipulators. This paper addresses the maximum effort toward fault tolerance for any number of the locked actuators failures in static nonlinear systems. It optimally reconfigures the inputs via a mapping that maximally accommodates the failures. The mapping maps the failures to an extra action of healthy actuators that results to a minimum jump for the velocity of the output variables. Then from this mapping, the minimum jump of the velocity of the output is calculated. The conditions for a zero velocity jump of the output variables are discussed. This shows that, when the conditions of fault tolerance are maintained, the proposed framework is capable of fault recovery not only at fault instances but also at the whole output trajectory. The proposed mapping is validated by three case studies.

Multifaceted role of nitric oxide in an in vitro mouse neuronal injury model: transcriptomic profiling defines the temporal recruitment of death signalling cascades

Nitric oxide is implicated in the pathogenesis of various neuropathologies characterized by oxidative stress. Although nitric oxide has been reported to be involved in the exacerbation of oxidative stress observed in several neuropathologies, existent data fail to provide a holistic description of how nitrergic pathobiology elicits neuronal injury. Here we provide a comprehensive description of mechanisms contributing to nitric oxide induced neuronal injury by global transcriptomic profiling. Microarray analyses were undertaken on RNA from murine primary cortical neurons treated with the nitric oxide generator DETA-NONOate (NOC-18, 0.5 mM) for 8–24 hrs. Biological pathway analysis focused upon 3672 gene probes which demonstrated at least a ±1.5-fold expression in a minimum of one out of three time-points and passed statistical analysis (one-way anova, P < 0.05). Numerous enriched processes potentially determining nitric oxide mediated neuronal injury were identified from the transcriptomic profile: cell death, developmental growth and survival, cell cycle, calcium ion homeostasis, endoplasmic reticulum stress, oxidative stress, mitochondrial homeostasis, ubiquitin-mediated proteolysis, and GSH and nitric oxide metabolism. Our detailed time-course study of nitric oxide induced neuronal injury allowed us to provide the first time a holistic description of the temporal sequence of cellular events contributing to nitrergic injury. These data form a foundation for the development of screening platforms and define targets for intervention in nitric oxide neuropathologies where nitric oxide mediated injury is causative.

Power penalty assessment of OXADM device model - analytical analysis

This OXADM are located in the nodes, which have more than two switching directions in ring networks. The function of OXADM is to flexibility switch the wavelengths among the different input and output ports. Because of the OXADM's imperfect performance, the insertion loss and crosstalk are induced in the system. Analytical modeling method is using to analyze the OXADM structure in crosstalk or power leakage that lead to the power penalty. To overcome this problem, power penalty is needed to be supplied. The insertion of this power penalty depends on few parameters. The parameters that we going to investigate here will be in term of number of operating wavelengths and number of input/output ports as well as the Q factor. The variation of this parameters will affects the amount of the desired power penalty. Simulation results in higher crosstalk or higher power penalty needed as the number of OXADM increases. As the sum of the wavelength and the number of input/output for each OXADM increases, the power penalty will increased as well. Investigation on the maximum Q factors is 6 to get the minimum power penalty at the lowest BER for most of the combination of the sum of the wavelength and the number of input/output for each OXADM.

The influence of job, team and organizational level resources on employee well-being, engagement, commitment and extra-role performance : test of a model

Purpose – Worker well-being continues to be fundamental to the study of work and a primary consideration for how organizations can achieve competitive advantage and sustainable and ethical work practices (Cartwright and Holmes; Harter, Schmidt and Keyes; Wright and Cropanzano). The science and practice of employee engagement, a key indicator of employee well-being, continues to evolve with ongoing incremental refinements to existing models and measures. This study aims to elaborate the Job Demands-Resources model of work engagement (Bakker and Demerouti) by examining how organizational, team and job level factors interrelate to influence engagement and well-being and downstream outcome variables such as affective commitment and extra-role behaviour.

Design/methodology/approach – Structural equations modelling of survey data obtained from 3,437 employees of a large multi-national mining company was used to test the important direct and indirect influence of organizational focused resources (a culture of fairness and support), team focused resources (team climate) and job level resources (career development, autonomy, supervisor support, and role clarity) on employee well-being, engagement, extra-role behaviour and organizational commitment.

Findings – The fit of the proposed measurement and structural models met criterion levels and the structural model accounted for sizable proportions of the variance in engagement/wellbeing (66 percent), extra-role-behaviour (52 percent) and commitment (69 percent).

Research limitations/implications – Study limitations (e.g. cross-sectional research design) and future opportunities are outlined.

Originality/value – The study demonstrates important extensions to the Job Demands-Resources model and provides researchers and practitioners with a simple but powerful motivational framework, a suite of measures, and a map of their inter-relationships which can be used to help understand, develop and manage employee well-being and engagement and their outcomes.

Investigation of process dynamics and control of polystyrene batch reactor using hybrid model

The effects of operating conditions such as initiator and monomer concentration as well as reactor temperature of polymerization reactors are studied in this work. A recently developed hybrid model for polystyrene batch reactor is utilized in simulation study. The simulation results reveal the sensitivity of polymer properties and monomer conversion to variation of process operating conditions. In the second phase of this study, the optimization problem involving minimum time optimal temperature policy is considered for control study. An advanced neural network-based model predictive controller (NN-MPC) is designed and tested online. The experimental studies reveal that the developed controller is able to track the optimal setpoint with a minor oscillation and overshoot.

Understanding the link between body image and binge eating: a model comparison approach

Purpose
The present study tests several competing, explanatory models—dual pathways, escape from awareness, and objectification theory—for the established link between body dissatisfaction and binge eating.

Methods
408 women aged between 18 and 40 years completed a survey designed to assess contributions of proposed mediators (dietary restraint and negative affect from the dual pathway model, self-distraction from the escape from awareness model, and interoceptive deficits from objectification theory) for the body dissatisfaction–binge eating relationship.

Results
Although mediation analyses supported the dual pathway model and objectification theory when tested separately, the dual pathway model most strongly predicted the body dissatisfaction–binge eating relationship. Both model-implied mediators (dietary restraint and negative affect) made significant unique contributions, accounting for roughly one-quarter of the shared variance between body dissatisfaction and binge eating when tested separately from other mediators. Improvements in variance explained were negligible once other proposed mediators were included in a test of models combined.

Conclusions
Collectively, these findings suggest the superiority of the dual pathway model over objectification theory and the escape model, but the remaining unaccounted for covariance suggests need to consider alternative mechanisms that may also account for the relationship between body dissatisfaction and binge eating.

Reasoned versus reactive prediction of behaviour: a meta-analysis of the prototype willingness model

The prototype willingness model (PWM) was designed to extend expectancy-value models of health behaviour by also including a heuristic, or social reactive pathway, to better explain health-risk behaviours in adolescents and young adults. The pathway includes prototype, i.e., images of a typical person who engages in a behaviour, and willingness to engage in behaviour. The current study describes a meta-analysis of predictive research using the PWM and explores the role of the heuristic pathway and intentions in predicting behaviour. Eighty-one studies met inclusion criteria. Overall, the PWM was supported and explained 20.5% of the variance in behaviour. Willingness explained 4.9% of the variance in behaviour over and above intention, although intention tended to be more strongly related to behaviour than was willingness. The strength of the PWM relationships tended to vary according to the behaviour being tested, with alcohol consumption being the behaviour best explained. Age was also an important moderator, and, as expected, PWM behaviour was best accounted for within adolescent samples. Results were heterogeneous even after moderators were taken into consideration. This meta-analysis provides support for the PWM and may be used to inform future interventions that can be tailored for at-risk populations.

Type D personality and the Five-Factor Model : a facet-level analysis

Objective: This study assessed the degree to which NEO-PI-R facets contribute to understanding of Type D personality over and above the Big 5. Method: Healthy participants (n = 268) completed the DS14 and the NEO-PI-R. In addition to analyzing the Type D subscales of social inhibition and negative affectivity, we computed a continuous measure of Type D scored as the sum of the two subscales. Results: Facets provided moderate incremental prediction of Type D subscales. The facets of assertiveness, self- consciousness, and positive emotion provided incremental prediction of negative affectivity, and warmth, activity, and gregariousness provided incremental prediction of social inhibition. Facets provided minimal incremental prediction of continuous Type D. The Big 5 explained substantially more variance in continuous Type D (71%) than negative affectivity (59%) or social inhibition (61%). Conclusions: Overall, the facet-level analysis provided additional insights into the nature of Type D. The incremental prediction of the Type D subscales by facets supported the idea that Type D scales are narrower constructs than the Big 5. However, the strong prediction of continuous Type D by the Big 5 and the lack of incremental prediction by facets points to the overall Type D construct being well represented by the Big 5.

Intelligent facial emotion recognition using a layered encoding cascade optimization model

In this research, we propose a facial expression recognition system with a layered encoding cascade optimization model. Since generating an effective facial representation is a vital step to the success of facial emotion recognition, a modified Local Gabor Binary Pattern operator is first employed to derive a refined initial face representation and we then propose two evolutionary algorithms for feature optimization including (i) direct similarity and (ii) Pareto-based feature selection, under the layered cascade model. The direct similarity feature selection considers characteristics within the same emotion category that give the minimum within-class variation while the Pareto-based feature optimization focuses on features that best represent each expression category and at the same time provide the most distinctions to other expressions. Both a neural network and an ensemble classifier with weighted majority vote are implemented for the recognition of seven expressions based on the selected optimized features. The ensemble model also automatically updates itself with the most recent concepts in the data. Evaluated with the Cohn-Kanade database, our system achieves the best accuracies when the ensemble classifier is applied, and outperforms other research reported in the literature with 96.8% for direct similarity based optimization and 97.4% for the Pareto-based feature selection. Cross-database evaluation with frontal images from the MMI database has also been conducted to further prove system efficiency where it achieves 97.5% for Pareto-based approach and 90.7% for direct similarity-based feature selection and outperforms related research for MMI. When evaluated with 90° side-view images extracted from the videos of the MMI database, the system achieves superior performances with >80% accuracies for both optimization algorithms. Experiments with other weighting and meta-learning combination methods for the construction of ensembles are also explored with our proposed ensemble showing great adpativity to new test data stream for cross-database evaluation. In future work, we aim to incorporate other filtering techniques and evolutionary algorithms into the optimization models to further enhance the recognition performance.