Towards a model of the institutional logics of climate change

The proliferation of innovative schemes to address climate change at international, national and local levels signals a fundamental shift in the priority and role of the natural environment to society, organizations and individuals. This shift in shared priorities invites academics and practitioners to consider the role of institutions in shaping and constraining responses to climate change at multiple levels of organisations and society. Institutional theory provides an approach to conceptualising and addressing climate change challenges by focusing on the central logics that guide society, organizations and individuals and their material and symbolic relationship to the environment. For example, framing a response to climate change in the form of an emission trading scheme evidences a practice informed by a capitalist market logic (Friedland and Alford 1991). However, not all responses need necessarily align with a market logic. Indeed, Thornton (2004) identifies six broad societal sectors each with its own logic (markets, corporations, professions, states, families, religions). Hence, understanding the logics that underpin successful –and unsuccessful– climate change initiatives contributes to revealing how institutions shape and constrain practices, and provides valuable insights for policy makers and organizations. This paper develops models and propositions to consider the construction of, and challenges to, climate change initiatives based on institutional logics (Thornton and Ocasio 2008). We propose that the challenge of understanding and explaining how climate change initiatives are successfully adopted be examined in terms of their institutional logics, and how these logics evolve over time. To achieve this, a multi-level framework of analysis that encompasses society, organizations and individuals is necessary (Friedland and Alford 1991). However, to date most extant studies of institutional logics have tended to emphasize one level over the others (Thornton and Ocasio 2008: 104). In addition, existing studies related to climate change initiatives have largely been descriptive (e.g. Braun 2008) or prescriptive (e.g. Boiral 2006) in terms of the suitability of particular practices. This paper contributes to the literature on logics by examining multiple levels: the proliferation of the climate change agenda provides a site in which to study how institutional logics are played out across multiple, yet embedded levels within society through institutional forums in which change takes place. Secondly, the paper specifically examines how institutional logics provide society with organising principles –material practices and symbolic constructions– which enable and constrain their actions and help define their motives and identity. Based on this model, we develop a series of propositions of the conditions required for the successful introduction of climate change initiatives. The paper proceeds as follows. We present a review of literature related to institutional logics and develop a generic model of the process of the operation of institutional logics. We then consider how this is applied to key initiatives related to climate change. Finally, we develop a series of propositions which might guide insights into the successful implementation of climate change practices.

Competence in Intelligence Testing : A Training Model for Postgraduate Psychology Students

The assessment of intellectual ability is a core competency in psychology. The results of intelligence tests have many potential implications and are used frequently as the basis for decisions about educational placements, eligibility for various services, and admission to specific groups. Given the importance of intelligence test scores, accurate test administration and scoring are essential; yet there is evidence of unacceptably high rates of examiner error. This paper discusses competency and postgraduate training in intelligence testing and presents a training model for postgraduate psychology students. The model aims to achieve high levels of competency in intelligence testing through a structured method of training, practice and feedback that incorporates peer support, self-reflection and multiple methods for evaluating competency.

CTCombine : rotating and combining CT data with an accurate detector model, to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc. The geometric and dosimetric accuracy of CTCombine’s output has been assessed by simulating simple and complex treatments applied to a rotated planar phantom and a rotated humanoid phantom and comparing the resulting virtual EPID images with the images acquired using experimental measurements and independent simulations of equivalent phantoms. It is expected that CTCombine will be useful for Monte Carlo studies of EPID dosimetry as well as other EPID imaging applications.

Statistical analysis and reduction of multiple access interference in MC-CDMA systems

Multicarrier code division multiple access (MC-CDMA) is a very promising candidate for the multiple access scheme in fourth generation wireless communi- cation systems. During asynchronous transmission, multiple access interference (MAI) is a major challenge for MC-CDMA systems and significantly affects their performance. The main objectives of this thesis are to analyze the MAI in asyn- chronous MC-CDMA, and to develop robust techniques to reduce the MAI effect. Focus is first on the statistical analysis of MAI in asynchronous MC-CDMA. A new statistical model of MAI is developed. In the new model, the derivation of MAI can be applied to different distributions of timing offset, and the MAI power is modelled as a Gamma distributed random variable. By applying the new statistical model of MAI, a new computer simulation model is proposed. This model is based on the modelling of a multiuser system as a single user system followed by an additive noise component representing the MAI, which enables the new simulation model to significantly reduce the computation load during computer simulations. MAI reduction using slow frequency hopping (SFH) technique is the topic of the second part of the thesis. Two subsystems are considered. The first sub- system involves subcarrier frequency hopping as a group, which is referred to as GSFH/MC-CDMA. In the second subsystem, the condition of group hopping is dropped, resulting in a more general system, namely individual subcarrier frequency hopping MC-CDMA (ISFH/MC-CDMA). This research found that with the introduction of SFH, both of GSFH/MC-CDMA and ISFH/MC-CDMA sys- tems generate less MAI power than the basic MC-CDMA system during asyn- chronous transmission. Because of this, both SFH systems are shown to outper- form MC-CDMA in terms of BER. This improvement, however, is at the expense of spectral widening. In the third part of this thesis, base station polarization diversity, as another MAI reduction technique, is introduced to asynchronous MC-CDMA. The com- bined system is referred to as Pol/MC-CDMA. In this part a new optimum com- bining technique namely maximal signal-to-MAI ratio combining (MSMAIRC) is proposed to combine the signals in two base station antennas. With the applica- tion of MSMAIRC and in the absents of additive white Gaussian noise (AWGN), the resulting signal-to-MAI ratio (SMAIR) is not only maximized but also in- dependent of cross polarization discrimination (XPD) and antenna angle. In the case when AWGN is present, the performance of MSMAIRC is still affected by the XPD and antenna angle, but to a much lesser degree than the traditional maximal ratio combining (MRC). Furthermore, this research found that the BER performance for Pol/MC-CDMA can be further improved by changing the angle between the two receiving antennas. Hence the optimum antenna angles for both MSMAIRC and MRC are derived and their effects on the BER performance are compared. With the derived optimum antenna angle, the Pol/MC-CDMA system is able to obtain the lowest BER for a given XPD.

Towards a model of understanding strategic decision-making in micro-firms : exploring the Australian information technology sector

This study explores strategic decision-making (SDM) in micro-firms, an economically significant business subsector. As extant large- and small-firm literature currently proffers an incomplete characterization of SDM in very small enterprises, a multiple-case methodology was used to investigate how these firms make strategic decisions. Eleven Australian Information Technology service micro-firms participated in the study. Using an information-processing lens, the study uncovered patterns of SDM in micro-firms and derived a theoretical micro-firm SDM model. This research also identifies several implications for micro-firm management and directions for future research, contributing to the understanding of micro-firm SDM in both theory and practice.

Comparison of multiple and novel measures of dietary glycemic carbohydrate with insulin resistant status in older women

BACKGROUND:Previous epidemiological investigations of associations between dietary glycemic intake and insulin resistance have used average daily measures of glycemic index (GI) and glycemic load (GL). We explored multiple and novel measures of dietary glycemic intake to determine which was most predictive of an association with insulin resistance.METHODS:Usual dietary intakes were assessed by diet history interview in women aged 42-81 years participating in the Longitudinal Assessment of Ageing in Women. Daily measures of dietary glycemic intake (n = 329) were carbohydrate, GI, GL, and GL per megacalorie (GL/Mcal), while meal based measures (n = 200) were breakfast, lunch and dinner GL; and a new measure, GL peak score, to represent meal peaks. Insulin resistant status was defined as a homeostasis model assessment (HOMA) value of >3.99; HOMA as a continuous variable was also investigated.RESULTS:GL, GL/Mcal, carbohydrate (all P < 0.01), GL peak score (P = 0.04) and lunch GL (P = 0.04) were positively and independently associated with insulin resistant status. Daily measures were more predictive than meal-based measures, with minimal difference between GL/Mcal, GL and carbohydrate. No significant associations were observed with HOMA as a continuous variable.CONCLUSION:A dietary pattern with high peaks of GL above the individual's average intake was a significant independent predictor of insulin resistance in this population, however the contribution was less than daily GL and carbohydrate variables. Accounting for energy intake slightly increased the predictive ability of GL, which is potentially important when examining disease risk in more diverse populations with wider variations in energy requirements.

Elucidating the links between UV radiation and vitamin D synthesis : using an in vitro model

Ultraviolet radiation (UV) is the carcinogen that causes the most common malignancy in humans – skin cancer. However, moderate UV exposure is essential for producing vitaminDin our skin. VitaminDincreases the absorption of calcium from the diet, and adequate calcium is necessary for the building and maintenance of bones. Thus, low levels of vitamin D can cause osteomalacia and rickets and contribute to osteoporosis. Emerging evidence also suggests vitamin D may protect against falls, internal cancers, psychiatric conditions, autoimmune diseases and cardiovascular diseases. Since the dominant source of vitamin D is sunlight exposure, there is a need to understand what is a “balanced” level of sun exposure to maintain an adequate level of vitamin D but minimise the risks of eye damage, skin damage and skin cancer resulting from excessive UV exposure. There are many steps in the pathway from incoming solar UV to the eventual vitamin D status of humans (measured as 25-hydroxyvitamin D in the blood), and our knowledge about many of these steps is currently incomplete. This project begins by investigating the levels of UV available for synthesising vitamin D, and how these levels vary across seasons, latitudes and times of the day. The thesis then covers experiments conducted with an in vitro model, which was developed to study several aspects of vitamin D synthesis. Results from the model suggest the relationship between UV dose and vitamin D is not linear. This is an important input into public health messages regarding ‘safe’ UV exposure: larger doses of UV, beyond a certain limit, may not continue to produce vitamin D; however, they will increase the risk of skin cancers and eye damage. The model also showed that, when given identical doses of UV, the amount of vitamin D produced was impacted by temperature. In humans, a temperature-dependent reaction must occur in the top layers of human skin, prior to vitamin D entering the bloodstream. The hypothesis will be raised that cooler temperatures (occurring in winter and at high latitudes) may reduce vitamin D production in humans. Finally, the model has also been used to study the wavelengths of UV thought to be responsible for producing vitamin D. It appears that vitamin D production is limited to a small range of UV wavelengths, which may be narrower than previously thought. Together, these results suggest that further research is needed into the ability of humans to synthesise vitamin D from sunlight. In particular, more information is needed about the dose-response relationship in humans and to investigate the proposed impact of temperature. Having an accurate action spectrum will also be essential for measuring the available levels of vitamin D-effective UV. As this research continues, it will contribute to the scientific evidence-base needed for devising a public health message that will balance the risks of excessive UV exposure with maintaining adequate vitamin D.

Are organ donation communication decisions reasoned or reactive? A test of the utility of an augmented Theory of Planned Behaviour with the Prototype/Willingness Model

Objectives: To explore whether people's organ donation consent decisions occur via a reasoned and/or social reaction pathway. --------- Design: We examined prospectively students' and community members' decisions to register consent on a donor register and discuss organ donation wishes with family. --------- Method: Participants completed items assessing theory of planned behaviour (TPB; attitude, subjective norm, perceived behavioural control (PBC)), prototype/willingness model (PWM; donor prototype favourability/similarity, past behaviour), and proposed additional influences (moral norm, self-identity, recipient prototypes) for registering (N=339) and discussing (N=315) intentions/willingness. Participants self-reported their registering (N=177) and discussing (N=166) behaviour 1 month later. The utility of the (1) TPB, (2) PWM, (3) augmented TPB with PWM, and (4) augmented TPB with PWM and extensions was tested using structural equation modelling for registering and discussing intentions/willingness, and logistic regression for behaviour. --------- Results: While the TPB proved a more parsimonious model, fit indices suggested that the other proposed models offered viable options, explaining greater variance in communication intentions/willingness. The TPB, augmented TPB with PWM, and extended augmented TPB with PWM best explained registering and discussing decisions. The proposed and revised PWM also proved an adequate fit for discussing decisions. Respondents with stronger intentions (and PBC for registering) had a higher likelihood of registering and discussing. --------- Conclusions: People's decisions to communicate donation wishes may be better explained via a reasoned pathway (especially for registering); however, discussing involves more reactive elements. The role of moral norm, self-identity, and prototypes as influences predicting communication decisions were highlighted also.

A modified cementing technique using BoneSource to augment fixation of the acetabulum in a sheep model

Background and purpose Our aim was to prove in an animal model that the use of HA paste at the cement-bone interface in the acetabulum would improve fixation. We examined, in sheep, the effect of interposing a layer of hydroxyapatite cement around the periphery of a polyethylene socket prior to fixing it using polymethylemethacrylate (PMMA). Methods We made a randomized study involving 22 sheep to test whether the application of BoneSource hydroxyapatite material to the surface of the ovine acetabulum prior to cementing a polyethylene cup at hip arthroplasty improved the fixation and the nature of the interface. We studied the gross radiographical appearance of the implant-bone interface and the histological appearance at the interface. Results There were more radiolucencies evident in the control group. Histologically, only sheep randomized into the BoneSource group exhibited a fully osseointegrated interface. Use of the hydroxyapatite material did not confer any detrimental effects. In some cases the material appeared to have been fully resorbed. When the material was evident on histological section, it was incorporated into an osseointegrated interface. There was no giant cell reaction present in any case. There was no evidence of migration of BoneSource to the articulation. Interpretation The application of HA material prior to cementation of a socket produced an improved interface. The technique may be useful in man with to extend the longevity of the cemented implant by protecting the socket interface from the effect of hydrodynamic fluid flow and particulate debris.

A connective model for the practice-led research exegesis : an analysis of content and structure

Since the formal recognition of practice-led research in the 1990s, many higher research degree candidates in art, design and media have submitted creative works along with an accompanying written document or ‘exegesis’ for examination. Various models for the exegesis have been proposed in university guidelines and academic texts during the past decade, and students and supervisors have experimented with its contents and structure. With a substantial number of exegeses submitted and archived, it has now become possible to move beyond proposition to empirical analysis. In this article we present the findings of a content analysis of a large, local sample of submitted exegeses. We identify the emergence of a persistent pattern in the types of content included as well as overall structure. Besides an introduction and conclusion, this pattern includes three main parts, which can be summarized as situating concepts (conceptual definitions and theories); precedents of practice (traditions and exemplars in the field); and researcher’s creative practice (the creative process, the artifacts produced and their value as research). We argue that this model combines earlier approaches to the exegesis, which oscillated between academic objectivity, by providing a contextual framework for the practice, and personal reflexivity, by providing commentary on the creative practice. But this model is more than simply a hybrid: it provides a dual orientation, which allows the researcher to both situate their creative practice within a trajectory of research and do justice to its personally invested poetics. By performing the important function of connecting the practice and creative work to a wider emergent field, the model helps to support claims for a research contribution to the field. We call it a connective model of exegesis.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Implementation and evaluation of a new model of nursing practice in radiation oncology

Patients undergoing radiation therapy for cancer face a series of challenges that require support from a multidisciplinary team which includes radiation oncology nurses. However, the specific contribution of nursing, and the models of care that best support the delivery of nursing interventions in the radiotherapy setting, is not well described. In this case study, the Interaction Model of Client Health Behaviour and the associated principles of person-centred care were incorporated into a new model of care that was implemented in one radiation oncology setting in Brisbane, Australia. The new model of care was operationalised through a Primary Nursing/Collaborative Practice framework. To evaluate the impact of the new model for patients and health professionals, multiple sources of data were collected from patients and clinical staff prior to, during, and 18 months following introduction of the practice redesign. One cohort of patients and clinical staff completed surveys incorporating measures of key outcomes immediately prior to implementation of the model, while a second cohort of patients and clinical staff completed these same surveys 18 months following introduction of the model. In-depth interviews were also conducted with nursing, medical and allied health staff throughout the implementation phase to obtain a more comprehensive account of the processes and outcomes associated with implementing such a model. From the patients’ perspectives, this study demonstrated that, although adverse effects of radiotherapy continue to affect patient well-being, patients continue to be satisfied with nursing care in this specialty, and that they generally reported high levels of functioning despite undergoing a curative course of radiotherapy. From the health professionals’ perspective, there was evidence of attitudinal change by nursing staff within the radiotherapy department which reflected a greater understanding and appreciation of a more person-centred approach to care. Importantly, this case study has also confirmed that a range of factors need to be considered when redesigning nursing practice in the radiotherapy setting, as the challenges associated with changing traditional practices, ensuring multidisciplinary approaches to care, and resourcing a new model were experienced. The findings from this study suggest that the move from a relatively functional approach to a person-centred approach in the radiotherapy setting has contributed to some improvements in the provision of individualised and coordinated patient care. However, this study has also highlighted that primary nursing may be limited in its approach as a framework for patient care unless it is supported by a whole team approach, an appropriate supportive governance model, and sufficient resourcing. Introducing such a model thus requires effective education, preparation and ongoing support for the whole team. The challenges of providing care in the context of complex interdisciplinary relationships have been highlighted by this study. Aspects of this study may assist in planning further nursing interventions for patients undergoing radiotherapy for cancer, and continue to enhance the contribution of the radiation oncology nurse to improved patient outcomes.

Business Process Model Merging : An Approach to Business Process Consolidation

This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.