Website physical activity interventions : preferences of potential users

Information and communication technologies (particularly websites and e-mail) have the potential to deliver health behavior change programs to large numbers of adults at low cost. Controlled trials using these new media to promote physical activity have produced mixed results. User-centered development methods can assist in understanding the preferences of potential participants for website functions and content, and may lead to more effective programs. Eight focus group discussions were conducted with 40 adults after they had accessed a previously trialed physical activity website. The discussions were audio taped, transcribed and interpreted using a themed analysis method. Four key themes emerged: structure, interactivity, environmental context and content. Preferences were expressed for websites that include simple interactive features, together with information on local community activity opportunities. Particular suggestions included online community notice boards, personalized progress charts, e-mail access to expert advice and access to information on specific local physical activity facilities and services. Website physical activity interventions could usefully include personally relevant interactive and environmentally focused features and services identified through a user-centered development process.

Latent variable models in statistical genetics

Understanding the complexities that are involved in the genetics of multifactorial diseases is still a monumental task. In addition to environmental factors that can influence the risk of disease, there is also a number of other complicating factors. Genetic variants associated with age of disease onset may be different from those variants associated with overall risk of disease, and variants may be located in positions that are not consistent with the traditional protein coding genetic paradigm. Latent Variable Models are well suited for the analysis of genetic data. A latent variable is one that we do not directly observe, but which is believed to exist or is included for computational or analytic convenience in a model. This thesis presents a mixture of methodological developments utilising latent variables, and results from case studies in genetic epidemiology and comparative genomics. Epidemiological studies have identified a number of environmental risk factors for appendicitis, but the disease aetiology of this oft thought useless vestige remains largely a mystery. The effects of smoking on other gastrointestinal disorders are well documented, and in light of this, the thesis investigates the association between smoking and appendicitis through the use of latent variables. By utilising data from a large Australian twin study questionnaire as both cohort and case-control, evidence is found for the association between tobacco smoking and appendicitis. Twin and family studies have also found evidence for the role of heredity in the risk of appendicitis. Results from previous studies are extended here to estimate the heritability of age-at-onset and account for the eect of smoking. This thesis presents a novel approach for performing a genome-wide variance components linkage analysis on transformed residuals from a Cox regression. This method finds evidence for a dierent subset of genes responsible for variation in age at onset than those associated with overall risk of appendicitis. Motivated by increasing evidence of functional activity in regions of the genome once thought of as evolutionary graveyards, this thesis develops a generalisation to the Bayesian multiple changepoint model on aligned DNA sequences for more than two species. This sensitive technique is applied to evaluating the distributions of evolutionary rates, with the finding that they are much more complex than previously apparent. We show strong evidence for at least 9 well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least 7 classes in an alignment of four mammals, including human. A pattern of enrichment and depletion of genic regions in the profiled segments suggests they are functionally significant, and most likely consist of various functional classes. Furthermore, a method of incorporating alignment characteristics representative of function such as GC content and type of mutation into the segmentation model is developed within this thesis. Evidence of fine-structured segmental variation is presented.

Efficient and accurate retrieval of business process models through indexing

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective than developing them from scratch. As process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. Experiments are conducted to demonstrate that our proposal achieves a significant reduction in query evaluation time.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

Brain-derived neurotrophic factor (BDNF) gene : no major impact on antidepressant treatment response

The brain-derived neurotrophic factor (BDNF) has been suggested to play a pivotal role in the aetiology of affective disorders. In order to further clarify the impact of BDNF gene variation on major depression as well as antidepressant treatment response, association of three BDNF polymorphisms [rs7103411, Val66Met (rs6265) and rs7124442] with major depression and antidepressant treatment response was investigated in an overall sample of 268 German patients with major depression and 424 healthy controls. False discovery rate (FDR) was applied to control for multiple testing. Additionally, ten markers in BDNF were tested for association with citalopram outcome in the STAR*D sample. While BDNF was not associated with major depression as a categorical diagnosis, the BDNF rs7124442 TT genotype was significantly related to worse treatment outcome over 6 wk in major depression (p=0.01) particularly in anxious depression (p=0.003) in the German sample. However, BDNF rs7103411 and rs6265 similarly predicted worse treatment response over 6 wk in clinical subtypes of depression such as melancholic depression only (rs7103411: TTmodels when the remaining SNPs were considered as covariates. The STAR*D analyses did not yield significant results at any of the ten BDNF markers. Our results do not support an association between genetic variation in BDNF and antidepressant treatment response or remission. Post-hoc analyses provide some preliminary support for a potential minor role of genetic variation in BDNF and antidepressant treatment outcome in the context of melancholic depression.

Destination brand equity among the host community : a potential source of comparative advantage for DMO's

Since the emergence of the destination branding literature in 1998, there have been few studies related to performance measurement of destination brand campaigns. There has also been little interest to date in researching the extent to which a destination brand represents the host community’s sense of place. Given that local residents represent a key stakeholder group for the destination marketing organisation (DMO), research is required to examine the extent to which marketing communications have been effective in enhancing engagement with the brand, and inducing a brand image that is congruent with the brand identity. Motivated by conceptual and practical aims, this paper reports the trial of a hierarchy of consumer-based brand equity (CBBE) for a destination, from the perspective of residents as active participants of local tourism. It is proposed that strong levels of CBBE among the host community representsa strong level of CBBE among the host community represents a source of comparative advantage for a destination, for which the DMO could proactively develop into a competitive advantage.

The growth-profitability relationship : strategic orientations as moderator

Principal Topic: In this study we investigate how strategic orientation moderates the impact of growth on profitability for a sample of Danish high growth (Gazelle) firms. ---------- Firm growth has been an essential part of both management research and entrepreneurship research for decades (e.g. Penrose 1959, Birch 1987, Storey 1994). From a societal point of view, firm growth has been perceived as economic generator and job creator. In entrepreneurship research, growth has been an important part of the field (Davidsson, Delmar and Wiklund 2006), and many have used growth as a measure of success. In strategic management, growth has been seen as an approach to achieve competitive advantages and a way of becoming increasing profitable (e.g. Russo and Fouts 1997, Cho and Pucic 2005). However, although firm growth used to be perceived as a natural pathway to profitability recently more skepticism has emerged due to both new theoretical development and new empirical insights. Empirically, studies show inconsistent and inconclusive empirical evidence regarding the impact of growth on profitability. Our review reveals that some studies find a substantial positive relationship, some find a weak positive relationship, some find no relationship and further some find a negative relationship. Overall, two dominant yet divergent theoretical positions can be identified. The first position, mainly focusing on the environmental fit, argues that firms are likely to become more profitable if they enter a market quickly and on a larger scale due to first mover advantages and economic of scale. The second position, mainly focusing the internal fit, argues that growth may lead to a range of internal challenges and difficulties, including rapid change in structure, reward systems, decision making, communication and management style. The inconsistent empirical results together with two divergent theoretical positions call for further investigations into the circumstances by which growth generate profitability and into the circumstances by which growth do not generate profitability. In this project, we investigate how strategic orientations influence the impact of growth on profitability by asking the following research question: How is the impact of growth on profitability moderated by strategic orientation? Based on a literature review of how growth impacts profitability in areas such as entrepreneurship, strategic management and strategic entrepreneurship we develop three hypotheses regarding the growth-profitability relationship and strategic orientation as a potential moderator. ---------- Methodology/Key Propositions: The three hypotheses are tested on data collected in 2008. All firms in Denmark, including all listed and non-listed (VAT-registered) firms who experienced a 100 % growth and had a positive sales or gross profit over a four years period (2004-2007) were surveyed. In total 2,475 fulfilled the requirements. Among those 1,107 firms returned usable questionnaires satisfactory giving us a response rate on 45 %. The financial data together with data on number of employees were obtained from D&B (previously Dun & Bradstreet). The remaining data were obtained through the survey. Hierarchical regression models with ROA (return on assets) as the dependent variable were used to test the hypotheses. In the first model control variables including region, industry, firm age, CEO age, CEO gender, CEO education and number of employees were entered. In the second model, growth measured as growth in employees was entered. Then strategic orientation (differentiation, cost leadership, focus differentiation and focus cost leadership) and then interaction effects of strategic orientation and growth were entered in the model. ---------- Results and Implications: The results show a positive impact of firm growth on profitability and further that this impact is moderated by strategic orientation. Specifically, it was found that growth has a larger impact on profitability when firms do not pursue a focus strategy including both focus differentiation and focus cost leadership. Our preliminary interpretation of the results suggests that the value of growth depends on the circumstances and more specifically 'how much is left to fight for'. It seems like those firms who target towards a narrow segment are less likely to gain value of growth. The remaining market shares to fight for to these firms are not large enough to compensate for the cost of growing. Based on our findings, it therefore seems like growth has a more positive relationship with profitability for those who approach a broad market segment. Furthermore we argue that firms pursuing af Focus strategy will have more specialized assets that decreases the possibilities of further profitable expansion. For firms, CEOs, board of directors etc., the study shows that high growth is not necessarily something worth aiming for. It is a trade-off between the cost of growing and the value of growing. For many firms, there might be better ways of generating profitability in the long run. It depends on the strategic orientation of the firm. For advisors and consultants, the conditional value of growth implies that in-depth knowledge on their clients' situation is necessary before any advice can be given. And finally, for policy makers, it means they have to be careful when initiating new policies to promote firm growth. They need to take into consideration firm strategy and industry conditions.

Using virtual reality modelling in cultural management, archiving and research

This paper outlines how the Ortelia project’s 3D virtual reality models have the capacity to assist our understanding of sites of cultural heritage. The VR investigation of such spaces can be a valuable tool in 'real world' empirical research in theatre and spatiality. Through a demonstration of two of Ortelia's VR models (an art gallery and a theatre), we suggest how we might consider interpreting cultural space and sites as contributing significantly to cultural capital. We also introduce the potential for human interaction in such venues through motion-capture to discuss the potential for assessing how humans interact in such contexts.

Alternative film production

Typically a film producer expects the director and actors to 'do their job' within a scheduled timeframe. Rather than expecting the creative principals to just deliver, a production model can be tailored to help this creative team produce successful outcomes. This research paper contrasts alternative production models with a traditional (or standard) production and presents possibilities for producers to emphasise the collaborative potential for their production.

Virtual Environment Visualisation of Executable Business Process Models

Business Process Modelling is a fast growing field in business and information technology, which uses visual grammars to model and execute the processes within an organisation. However, many analysts present such models in a 2D static and iconic manner that is difficult to understand by many stakeholders. Difficulties in understanding such grammars can impede the improvement of processes within an enterprise due to communication problems. In this chapter we present a novel framework for intuitively visualising animated business process models in interactive Virtual Environments. We also show that virtual environment visualisations can be performed with present 2D business process modelling technology, thus providing a low barrier to entry for business process practitioners. Two case studies are presented from film production and healthcare domains that illustrate the ease with which these visualisations can be created. This approach can be generalised to other executable workflow systems, for any application domain being modelled.

An Integrative framework of the factors affecting process model understanding : a learning perspective

Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies.

Estimating short and long-term residential demand for electricity : new evidence from Sri Lanka

This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand - per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas - using annual data for Sri Lanka for the period, 1960-2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, - 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 032, - 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and(4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages ill the country.

The contribution of different androgen receptor domains to receptor dimerization and signaling

The androgen receptor (AR) is a ligand-activated transcription factor of the nuclear receptor superfamily that plays a critical role in male physiology and pathology. Activated by binding of the native androgens testosterone and 5-dihydrotestosterone, the AR regulates transcription of genes involved in the development and maintenance of male phenotype and male reproductive function as well as other tissues such as bone and muscle. Deregulation of AR signaling can cause a diverse range of clinical conditions, including the X-linked androgen insensitivity syndrome, a form of motor neuron disease known as Kennedy’s disease, and male infertility. In addition, there is now compelling evidence that the AR is involved in all stages of prostate tumorigenesis including initiation, progression, and treatment resistance. To better understand the role of AR signaling in the pathogenesis of these conditions, it is important to have a comprehensive understanding of the key determinants of AR structure and function. Binding of androgens to the AR induces receptor dimerization, facilitating DNA binding and the recruitment of cofactors and transcriptional machinery to regulate expression of target genes. Various models of dimerization have been described for the AR, the most well characterized interaction being DNA-binding domain- mediated dimerization, which is essential for the AR to bind DNA and regulate transcription. Additional AR interactions with potential to contribute to receptor dimerization include the intermolecular interaction between the AR amino terminal domain and ligand-binding domain known as the N-terminal/C-terminal interaction, and ligand-binding domain dimerization. In this review, we discuss each form of dimerization utilized by the AR to achieve transcriptional competence and highlight that dimerization through multiple domains is necessary for optimal AR signaling.

Sustained release and osteogenic potential of heparan sulfate-doped fibrin glue scaffolds within a rat cranial model

This paper explores the potential therapeutic role of the naturally occurring sugar heparan sulfate (HS) for the augmentation of bone repair. Scaffolds comprising fibrin glue loaded with 5 lg of embryonically derived HS were assessed, firstly as a release-reservoir, and secondly as a scaffold to stimulate bone regeneration in a critical size rat cranial defect. We show HS-loaded scaffolds have a uniform distribution of HS, which was readily released with a typical burst phase, quickly followed by a prolonged delivery lasting several days. Importantly, the released HS contributed to improved wound healing over a 3-month period as determined by microcomputed tomography (lCT) scanning, histology, histomorphometry, and PCR for osteogenic markers. In all cases, only minimal healing was observed after 1 and 3 months in the absence of HS. In contrast, marked healing was observed by 3 months following HS treatment, with nearly full closure of the defect site. PCR analysis showed significant increases in the gene expression of the osteogenic markers Runx2, alkaline phosphatase, and osteopontin in the heparin sulfate group compared with controls. These results further emphasize the important role HS plays in augmenting wound healing, and its successful delivery in a hydrogel provides a novel alternative to autologous bone graft and growth factorbased therapies.