Structural Equation Modeling (SEM) is a framework of statistical methods that allows us to represent complex relationships between variables. SEM is widely used in economics, genetics and the behavioral sciences (e.g. psychology, psychobiology, sociology and medicine). Model complexity is defined as a model’s ability to fit different data patterns and it plays an important role in model selection when applying SEM. As in linear regression, the number of free model parameters is typically used in traditional SEM model fit indices as a measure of the model complexity. However, only using number of free model parameters to indicate SEM model complexity is crude since other contributing factors, such as the type of constraint or functional form are ignored. To solve this problem, a special technique, Confirmatory Tetrad Analysis (CTA) is examined. A tetrad refers to the difference in the products of certain covariances (or correlations) among four random variables. A structural equation model often implies that some tetrads should be zero. These model implied zero tetrads are called vanishing tetrads. In CTA, the goodness of fit can be determined by testing the null hypothesis that the model implied vanishing tetrads are equal to zero. CTA can be helpful to improve model selection because different functional forms may affect the model implied vanishing tetrad number (t), and models not nested according to the traditional likelihood ratio test may be nested in terms of tetrads. In this dissertation, an R package was created to perform CTA, a two-step method was developed to determine SEM model complexity using simulated data, and it is demonstrated how the number of vanishing tetrads can be helpful to indicate SEM model complexity in some situations.

The study investigated the effects of a motivational and cognitive pre-tasks on oral task production by intermediate and low advanced college learners of French at a large public university in the United States. The motivation and cognitive groups engaged in an information-gap group discussion task in French following brief motivationally and strategically oriented pre-tasks conducted in the participants' native language, while the control group completed the discussion task without a pre-task. In addition, all groups completed a dictation as a measure of proficiency and a post-task motivation survey. The results of the study did not show any significant differences between the motivation, cognitive and control treatments in terms of accuracy, fluency or complexity of their speech. Possible reasons contributing to the findings are discussed and interpretations are proposed. Particularly, it is suggested that strategies for motivating students and providing cognitive support for a language task need to be coupled with focus on the task content and/or form, addressed in the target language, in order to differentially affect the fluency, accuracy, and complexity aspects of the second language speech. At the same time, the motivation group participants reported significantly higher interest in the task, higher perception of its value, and higher perception of their own autonomy, which indicates that the motivation pre-task did positively affect their motivation in relation to the task. Interest and value subcategories of the motivation survey were particularly sensitive to differences between the groups. It is suggested that regular support and promotion of positive motivational dispositions in a language class may, in the long run, result in an observable positive effect on certain aspects of the learners' speech.

The potential failure in through-silicon vias (TSVs) still poses a challenge in trying to extend the useful life of a 3D integrated circuit (IC). A model is proposed to mitigate the communication problem in 3D integrated circuits caused by the breaks at the TSVs. We provide the details of a low-complexity network that takes advantages of redundant TSVs to make it possible to re-route around breaks and maintain effective communication between layers. Different configurations for the micronetwork are analyzed and discussed. We also present an evaluation of the micronetwork's performance, which turns out to be quite promising, based on several Monte Carlo simulations. Finally, we provide some directions for future research on the subject.

According to cognitive reserve theory, challenging and/or stimulating cognitive activities can build a theoretical reserve, which may lead to a delay in the clinical expression of dementia and/or Alzheimer's Disease. These cognitively stimulating activities are thought to build cognitive strategies and neural pathways that are more efficient, enabling the individual to live symptom-free for a longer period of time. One mechanism through which cognitive reserve can be built is by participating in an occupation high in cognitive complexity. When individuals hold an occupation that is high in complexity, they may build their cognitive reserve in such a manner as to reduce their risk for dementia in late life. Using extant data from an existing longitudinal, population-based study, we examined the effect of various subdomains of cognitive complexity of the longest-held job on dementia risk. In cox regression models, individuals holding agricultural occupations and occupations high in complexity of interaction with machinery, equipment, tools and inanimate objects ("Things") had an increased risk for both AD and dementia. Socioeconomic status was found to partially mediate the relationship between high Things complexity and dementia/AD risk, as well as the relationship between agricultural occupations and dementia/AD risk. While there has been some debate regarding whether results reflect a true effect of occupational complexity or simply an effect of education, results from this study indicate that both occupational complexity and education contribute unique effects to dementia/AD risk. Gender, job duration, and APOE genotype were not found to moderate any of the above associations. An understanding of how occupational complexity impacts cognitive reserve and risk for dementia/AD will enable individuals as well as clinicians to implement activities that enhance cognitive reserve and lead to a greater number of years lived symptom-free from dementia/AD.

This research addressed the design and implementation of a polynomial-complexity deadlock avoidance controller for a flexible manufacturing cell modeled using Colored Petri Nets. The cell model is robust to changes in the part types to be manufactured in the system and is automatically generated using the interaction of the resources in the cell and the technological capabilities of the machines. The model also captures dynamic routing flexibility options. The framework introduced separates the cell model from the control logic allowing the system designer to implement and test various control algorithms using the same cell model. The controller adopts the neighborhood deadlock avoidance policy to resolve deadlocks and control the resource allocation decisions within the system. The evaluation of the performance of systems controlled by not maximally permissive algorithms is important in determining the applicability of the control algorithms. There are many polynomial time deadlock avoidance algorithms proposed for the control of general resource allocation systems. However, the permissiveness of these algorithms is not quantified and the applicability of these algorithms in terms of effective resource utilization remains unanswered. The performance of automated manufacturing cells controlled using the neighborhood deadlock avoidance policy is benchmarked by comparing its performance with other control policies.

This study investigates the constructs of Derivation and Complexity and how they relate to latency. Derivation and Complexity are theoretical constructs that have been posited as two of the main factors in differences in latency to responding in implicit measures such as the Implicit Relational Assessment Procedure (IRAP) and the Implicit Association Task (IAT). This study trained participants to relate two groups of novel stimuli in a linear fashion and then tested their latency to responding to derived relations (relations based on previously trained relations, but not directly trained themselves). The study then analyzed participant's latency to responding after dividing the responses based on derivation, complexity, and phase. The study found a significant relationship between phase and latency (p=.01), derivation and latency (p=.01), and complexity and latency (p=.04). This indicates that brief, immediate relational responses are influenced by both derivation and complexity as well as practice responding and these variables should be considered in future investigations into implicit attitudes.

A simple stochastic game (SSG) is a game defined on a directed multigraph and played between players MAX and MIN. Both players have control over disjoint subsets of vertices: player MAX controls a subset VMAX and player MIN controls a subset VMIN of vertices. The remaining vertices fall into either VAVE, a subset of vertices that support stochastic transitions, or SINK, a subset of vertices that have zero outdegree and are associated with a payoff in the range [0, 1]. The game starts by placing a token on a designated start vertex. The token is moved from its current vertex position to a neighboring one according to certain rules. A fixed strategy σ of player MAX determines where to place the token when the token is at a vertex of VMAX. Likewise, a strategy τ of player MIN determines where to place the token when the token is at a vertex of VMIN. When the token is at a vertex of VAVE, the token is moved to a uniformly at random chosen neighbor. The game stops when the token arrives on a SINK vertex; at this point, player MAX gets the payoff associated with the SINK vertex. A fundamental question related to SSGs is the SSG value problem: Given a SSG G, is there a strategy of player MAX that gives him an expected payoff at least 1/2 regardless of the strategy of player MIN? This problem is among the rare natural combinatorial problems that belong to the class NP ∩ coNP but for which there is no known polynomial-time algorithm. In this thesis, we survey known algorithms for the SSG value problem and characterize them into four groups of algorithms: iterative approximation, strategy improvement, mathematical programming, and randomized algorithms. We obtain two new algorithmic results: Our first result is an improved worst-case, upper bound on the number of iterations required by the Homan-Karp strategy improvement algorithm. Our second result is a randomized Las Vegas strategy improvement algorithm whose expected running time is O(20:78n).

Research into the polyculture of finfish and crayfish has been conducted in Western Australia for over a decade now. This research was instigated out of a need to increase revenues from freshwater crayfish farmers wishing to diversify their income base with a view to increasing profitability and reducing risk. It has become clear that several key variables dictate how the polyculture system (i.e. polysystem) will perform. These include biological factors like: size of participating species, relative densities, gender, planktonic turbidity, natural feeds; and abiotic factors like: light intensity, clay turbidity, floating cages for segregation, water quality, and habitat/shelter complexity. Many of these factors can be controlled / adjusted by the manager of the polysystem to maximise performance, production and profitability.While much of the research to date has focussed on the marron (Cherax tenuimanus) industry, it is also important to realise that an understanding of these factors can also assist other crayfish polysystems, like integrated agri-aquaculture systems containing yabbies (Cherax albidus). Some of the factors that influence how the system will perform may become more prevalent, like suspended clay turbidity and the associated role of light intensity in species interactions, or shelter complexity and the resulting choice of shelter material. But overall, they are the same basic variables and we must understand how they affect the particular multi-species system that we are dealing with. There is a lot to be learned from the literature on how these variables affect multi-species aquatic environments in the wild. Perhaps aquaculturists have not considered this enough in the past. Some farmers seem to believe that these variables are different JUST because it is a culture system. This is not true. / The variables will take on different levels in a culture system (i.e. a manager will stimulate turbidity, provide artificial feeds, stock different sizes, and supply particular types of shelter) BUT the actual variables themselves (e.g. food, density, light, shelter) are basic to ALL aquatic ecosystems. Other researchers have looked at important factors like density, gender, and light intensity / turbidity in crayfish polysystems - but the issue of habitat complexity and the role of shelter has not been adequately addressed. This thesis will investigate some basic questions about shelter and endeavour to apply them to crayfish polysystems, with the emphasis on marron (C. tenuimanus) and yabbies (C. albidus) because these are the two most commercially important species of crayfish in Western Australia. Importantly, it should be noted that due to the invasive nature of yabbies, and their apparent ability to displace native marron in the wild, findings will be related to yabby-marron competition / displacement where relevant. We need to know many things about shelter: what type is best in a multi-species system? Should the shelter size match the crayfish size? Do marron have different requirements for shelter than yabbies? Does it matter who gets first use of a shelter (i.e. prior residence effect)? Can we learn about crayfish shelter requirements by examining the behaviour / plasticity of crayfish species? If crayfish are stocked with finfish and they retreat into shelter as a predator-avoidance measure, is the complexity important given that their densities will be higher? If densities of crayfish inside shelters are higher in polysystems, will cannibalism be a concern, particularly when conditions are right for moulting? Does visual recognition and / or chemo-detection of a predator affect the shelter usage by marron or yabbies? / Does temperature affect shelter usage behaviour for a burrowing species like yabbies? Shelter is an important factor in the life history of a freshwater crayfish and an understanding of its influence on different species is important for maximising system performance. Crayfish are categorised depending on their ability to construct shelters (i.e. burrows). Yabbies have evolved in systems with fluctuating water quality and many predators and, as such, have learned to burrow (to escape drought and also to escape predators). Marron, on the other hand, are a non-burrowing native crayfish species that have existed with relatively few predators in the South-West. As a result, marron are less capable of modifying their behaviour when confronted with a predator (i.e. low behavioural plasticity). Species with high plasticity, like yabbies, are more capable of adapting to new environments, because they can change their behaviour to increase their chance of survival. Therefore we can expect yabbies and marron to utilize habitats differently and we should compare these behaviours as a basis to developing management strategies. This type of knowledge may also assist with managing the translocation and spread of yabbies in the wild and their displacement of native marron.Within multi-species systems, the physical structure of shelter plays an important role inprotecting crayfish and the perfect shelter would not only provide safety from co-stocked finfish, but also from conspecific cannibalism. Given the different life histories and behaviours, it is probable that both species of crayfish will have different refuge requirements.Over the course of this four-year investigation, trials were conducted in four culture systems (72L aquariums, 300L circular tanks, 80t mesocosm tank, and 720m2 earthen ponds) using marron and yabbies as the species of interest. / Silver perch and Murray cod were chosen as the finfish species of interest as they appear to have the highest aquaculture potential for native freshwater finfish in Australia at the present time. Further, both of these fish have been documented as potential predators of crayfish, resulting in a challenge to understand the role of shelter in minimising the negative effects of fish-crayfish interactions within a polysystem. This study has confirmed that shelter plays a critical role in multi-species system dynamics. In the case of polysystems, it will affect both interspecific and intra-specific interactions, ultimately governing production and profitability, along with the other, previously defined factors. This means that the manager of a polysystem can influenceproductivity by understanding: a) the behavioural characteristics and biology of the crayfish; b) the feeding biology of the finfish; and c) the system variables (both biotic and abiotic) that will affect the overall well being of the fish and crayfish. In the case ofshelter, the manager should understand the available shelter types, the appropriatedensities, the importance of matching complexity to the crayfish size, and the prior residence effect when choosing a timing strategy for stocking and harvesting. Prior residence increased resource holding potential for both marron and yabbies in the short term. In fact, prior residence was a stronger determinant of successful sheltering than crayfish gender or species. However, in longer-term trials the physical size of the crayfish (larger animals evicted smaller animals) and reproductive status (berried females were successful at evicting all other crayfish) were more important factors in determining successful shelter acquisition, although the temporal variations (i.e. growth and release of young) complicate the issue. / When stocking crayfish of different sizes, and in polysystems, the correct size of shelter becomes critical, as smaller individuals will be forced to leave over-sized shelter and locate a shelter commensurate with their own body size to avoid predators. This is relevant to crayfish nurseries where complex habitat is paramount for juvenile cohorts that display variation in sizes and gender. The expansion of crayfish polyculture holds considerable promise; however, furtherinvestigations are required into shelter complexity within floating fish cages, shelter types and arrangement of shelters within ponds (for increased production and ease-of-harvesting), potential of yabbies in polyculture (comparison of monosex and hybrid strains), and the impact of shelter on escape behaviour of marron in a polysystem.

Doctor of Philosophy (PhD) / The aim of this thesis is to understand what drives the evolution of industrial networks and how such understanding can be used to stimulate sustainable development. A complex adaptive systems perspective has been adopted to analyse the complex interaction between organisational behaviour and industrial network evolution. This analysis has formed the basis for the development of a modelling approach that allows for quantitative exploration of how different organisational perceptions about current and future uncertainty affect their behaviour and therefore the network evolution. This analysis results in a set of potential evolutionary pathways for an industrial network and their associated performance in terms of sustainable development. Subsequently, this modelling approach has been used to explore the consequences of interventions in the network evolution and to identify robust interventions for stimulating sustainable development of industrial networks. The analysis, modelling approach and development of interventions has been developed in the context of a bioenergy network in the region of KwaZulu-Natal in South Africa. Industrial networks are an important aspect of today’s life and provide many goods and services to households and individuals all over the world. They consist of a large number of autonomous organisations, where some organisations contribute by transforming or transacting natural resources, such as oil, agricultural products or water, while other organisations contribute to networks by providing information or setting regulation or subsidies (local or national governments) or by influencing decision making processes of other organisations in networks (advocacy groups). Throughout the process from natural resource to product or service, industrial networks have important economic, environmental and social impacts on the socio-economic and biophysical systems in which they operate. The sum of complex interactions between organisations affects the rate in which natural resources are used, environmental impacts associated with transformation and transaction of resources and social impacts on local communities, regions or countries as a whole. The aim of this thesis is to understand how industrial networks evolve and how they can be stimulated towards sustainable development. The first question that has been addressed in this thesis is how to understand the complex interaction between organisational behaviour and industrial network evolution. Organisational behaviour is affected by many functional and implicit characteristics within the environment in which the organisation operates, while simultaneously the environment is a function of non-linear relationships between individual organisational actions and their consequences for both the function and structure of the network. This thesis has identified four different characteristics of industrial networks that affect organisational behaviour: 1) Functional characteristics 2) Implicit behavioural characteristics 3) Implicit relational characteristics 4) Implicit network characteristics. Functional characteristics are those characteristics that are formally recognised by all organisations within an industrial network and which affect their position within the network. Examples of functional characteristics are the price and quantity of resources available, the location and distance of organisations within a network, infrastructure availability or regulation. Implicit characteristics, on the other hand, are those characteristics that impact the decision making process of organisations, but which are not formally part of the network. From an organisational perspective, implicit characteristics are the rules, heuristics, norms and values that an organisation uses to determine its objectives, position and potential actions. Implicit relational characteristics, most importantly trust and loyalty, affect an organisations choice between potential partners and implicit network characteristics are those social norms and values that emerge through social embeddedness. Collectively, these functional and implicit characteristics and their interactions determine the outcome of organisational decisions and therefore the direction of the industrial network evolution. The complex interaction between these large numbers of characteristics requires quantitative models to explore how different network characteristics and different interactions result in different network evolutions. This thesis has developed an agent-based simulation model to explore industrial network evolutions. To represent the multi-scale complexity of industrial networks, the model consists of four scales. Each scale represents different processes that connect the functional and implicit characteristics of an industrial network to each other. The two basic scales represent the strategic actions of the organisations on the one hand and the industrial network function and structure on the other. The third scale represents the processes that take place within the mental models of organisations describing how they make sense of their environment and inform their strategic decision making process. The fourth scale represents the social embeddedness of organisations and how social processes create and destroy social institutions. The model has been developed such that it allows for exploring how changes in different network characteristics or processes affect the evolution of the network as a whole. The second question that has been addressed in this thesis is how to evaluate sustainable development of different evolutionary pathways of industrial networks. First of all, a systems approach has been adopted to explore the consequences of an industrial network to the larger socio-economic and biophysical system in which the network operates. Subsequently, a set of structural indicators has been proposed to evaluate the dynamic performance of industrial networks. These four structural indicators reflect the efficiency, effectiveness, resilience and adaptiveness of industrial networks. Efficiency and effectiveness relate to the operational features by which industrial networks provides a particular contribution to society. Resilience and adaptiveness relate to the system’s capacity to maintain or adapt its contribution to society while under stress of temporary shocks or permanent shifts, respectively. Finally, different multi-criteria decision analysis (MCDA) tools have been applied to provide a holistic evaluation of sustainable development of industrial networks. The third important question that is addressed in this thesis is how to systematically explore the potential evolutionary pathways of an industrial network, which has led to the development of agent-based scenario analysis. Agent-based scenario analysis systematically explores how industrial network evolutions might evolve depending on the perceptions of organisations towards the inherent uncertainty associated with strategic decision making in networks. The agent-based scenario analysis consists of two steps. Firstly, analysts develop a set of coherent context scenarios, which represents their view on the context in which an industrial network will operate within the future. For a bioenergy network, for example, this step results in a set of scenarios that each represent a coherent future of the socio-economic system in which the network might evolve. The second step is the development of a set of ‘agent scenarios’. Each agent-based scenario is based on a different ‘mental model’ employed by organisations within the network about how to deal with the inherent ambiguity of the future. The organisational perspective towards uncertainty is of major importance for the evolution of industrial networks, because it determines the innovative behaviour of organisations, the structure of the network and the direction in which the network evolves. One the one hand, organisations can ignore future ambiguity and base their actions on the environment that they can observe in their present state. On the other extreme, organisations can adopt a view that the future is inherently uncertain and in which they view social norms and values more important than functional characteristics to make sense of their environment. The mental models are differentiated according to two dimensions: 1) different mental representation of the world and 2) different cognitive processes that can be employed to inform strategic actions. Along these dimensions, different processes can be employed to make sense of the environment and to inform decision making. The thesis has shown that by systematically exploring the different perceptions possible, an adequate understanding of the different evolutionary pathways can be gained to inform the evaluation and development of interventions to stimulate sustainable development. The final part of this thesis has applied the analysis and methodology developed throughout this thesis to a bioenergy network in the province of Kwazulu-Natal in South Africa. The bioenergy network consists of a set of existing sugar mills with large quantities of bagasse, a biomass waste product, available. Bagasse is currently burned inefficiently to produce steam for the sugar mills, but can potentially be used for the production of green electricity, biodiesel, bioethanol or gelfuel. All of these products have important consequences for the region in terms of associated reductions in CO2 emissions, electrification of and/or energy provision for rural households and local economic development of the region. This thesis has modelled strategic decisions of the sugar mills, the existing electricity generator, potential independent energy producers, local and national governments and how their actions and interactions can lead to different evolutionary pathways of the bioenergy network. The agent-based scenario analysis has been used to explore how different perceptions of organisations can lead to different network evolutions. Finally, the model has been used to explore the consequences of two categories of interventions on stimulating sustainable development. The conclusions are that both categories of interventions, financial interventions by national government and the introduction of multi-criteria decision analysis (MCDA) tools to aid strategic decision making, can have both positive and negative effects on the network evolutions, depending on what ‘mental models’ are employed by organisations. Furthermore, there is no single intervention that outperforms the others in terms of stimulating both functional and structural features of sustainable development. The final conclusion is that instead of focusing on individual or collective targets, emphasis should be placed on the development of interventions that focus on evolutionary aspects of industrial networks rather than functional performance criteria. This thesis has also highlighted interesting research questions for future investigation. The methodology developed in this thesis is applied to a single case study, but there are still many questions concerning how different industrial networks might benefit from different organisational perceptions towards uncertainty. Furthermore, the role between the mental models and sustainable development requires further investigation, especially in the light of globalisation and the interconnectiveness of industrial networks in different countries and continents. Finally, this methodology has provided a platform for investigating how new technologies might be developed that anticipate needs of future generations. This thesis has provided a first and important step in developing a methodology that addresses the complex issues associated with sustainable development, benefiting both academics and practitioners that aim to stimulate sustainable development.

Abstract not available